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 UNITED STATES DEPARTMENT OF AGRICULTURE

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 FRUIT AND VEGETABLE INDUSTRY

 ADVISORY COMMITTEE

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 MEETING

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 WEDNESDAY, AUGUST 14, 2019

 The Advisory Committee met in the

Fairfax Room of the Hyatt Regency Crystal City

Hotel, 2799 Richmond Highway, Arlington,

Virginia, at 8:30 a.m., Chalmers R. Carr, III,

Chair, presiding. 

PRESENT 

CHALMERS R. CARR, III, Chair

KILEY HARPER-LARSEN, Vice Chair

RICHARD E. BOWMAN 

JOHN CHANDLER 

TINA ELLOR 

K.C. ELY 

BRET ERICKSON 

MOLLY GLEASON 

JULIE L. GORDON 

JEFF HUCKABY 

BRIAN KIRSCHENMANN 

TOM LIPETZKY 

KELLY POWELL-MCIVER 

READE SIEVERT 

STEVE SMITH 

BRUCE TALBOTT 

GREG TISON 

DERRIN WHEELER 

TOMMY WILKINS 

CHARLES A. WINGARD 

DONN ZEA 

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MEMBERS NOT IN ATTENDANCE 

DAVID K. BELL 

MICHAEL JANIS 

PAUL PALMBY 

STAFF PRESENT 

DARRELL HUGHES, Designated Federal Official

SONIA JIMENEZ, Deputy Administrator, AMS 

ALSO PRESENT 

C.B. ALONSO, USDA Rural Housing Service

ROBERT GUENTHER, United Fresh Produce

 Association 

BRENDA FOOS, USDA Pesticide Data Program

JASON HAFEMEISTER, USDA Trade and Foreign

 Agricultural Affairs

DAVID HILES, U.S. Department of Labor

AMELIA JACKSON-GHEISSARI, Bayer AG

JOHN JONES, U.S. Department of Labor

LEWIS KOSKI, Metrc

BRUCE LAMMERS, Administrator, USDA Rural

 Housing Service

JODI McDANIEL, USDA National Agricultural

 Statistics Service 

JENNIFER McENTIRE, United Fresh Produce

 Association 

ALLISON MOORE, Fresh Produce Association of the

 Americas 

BRIAN PASTERNAK, U.S. Department of Labor 

ED ROBISON, U.S. Department of Labor 

DAVID TALAN, U.S. Department of Labor 

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 CONTENTS 

Call to Order. . . . . . . . . . . . . . . . . . . 4 

Public Comments. . . . . . . . . . . . . . . . . .11 

Status Report to Full Committee (Trade). . . . . .93 

Presentation - Agricultural Trade. . . . . . . . .99 

 (Production) 

Presentation - Overview of Pesticide

 Data Program . . . . . . . . . . . . . . . 164 

Status Report to Full Committee

Status Report to Full Committee (Labor). . . . . 201 

Presentation - Farm Labor. . . . . . . . . . . . 205 

Presentation - Overview of Farm Labor Housing

 Direct Loans & Grants Program. . . . . . . 315 

Status Report to Full Committee

 (Food Safety). . . . . . . . . . . . . . . 341 

Presentation - Agricultural Water

 Regulation . . . . . . . . . . . . . . . . 359 

Adjourn. . . . . . . . . . . . . . . . . . . . . 396 

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 P-R-O-C-E-E-D-I-N-G-S 

 (8:30 a.m.) 

 CHAIR CARR: Well, good morning, 

everybody. I will call our meeting to order. I 

appreciate everybody traveling in and more 

importantly, I appreciate all the hard work that 

everybody's done over the summer in putting 

together a very good list of recommendations and 

discussion points for later on. 

 A little point of order so just so we 

understand how this is going to flow a little 

bit. Each one of the working groups is going to 

make a presentation on what has already been 

submitted in your packet. Hopefully you all had 

the time to read them. 

 So we're basically going to just read 

those statements, not go into discussion on those 

today but read those, have guest speakers who 

have been invited to speak on those topics. 

 Obviously want you to ask questions to 

those speakers while they're here so we're going 

to allow ample time for that. 

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 The intention tomorrow is we will go 

back in the working groups so we'll start 

tomorrow morning with about an hour for each 

working group to break up to see if there's 

anything they want to modify or add to their 

recommendations. 

 Then we'll bring it back to the full 

Committee starting hopefully about 9 o'clock and 

be able to discuss each one of them. 

 The goal is hopefully to approve those 

as a Committee. If we don't reach a consensus or 

if there's still work to be done, we still have 

about 45 days roughly to go back and do those 

over the telephone and get those done later on. 

We can either do it by a conference call or 

submit them around in writing. 

 So again, it would be great if we 

could wrap things up today, or today and tomorrow 

but it's not a requirement. We do have time 

remaining. 

 And again and it's hopefully that 

these speakers will be able to bring some clarity 

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to some of the topics we're talking about. So 

again, as you look through it and you hear these 

speakers speak, please be ready to ask them 

questions and everything. 

 So at this point in time, I'm going to 

turn it over to the Deputy Administrator. Sonia? 

 MS. JIMENEZ: Hi, good morning. I'm 

very happy to see you all again. You've been 

very busy since the last time we met. In fact, I 

don't remember a committee that has been so busy 

and since I, you know, since I started a long 

time ago. I'm not going to say how many years. 

 But as you know, the purpose of this 

Committee is to examine the full spectrum of 

specialty crop issues and make recommendations to 

the Secretary of Agriculture about how we better 

tailor our programs to better meet the produce 

industry's needs. 

 We fully understand all the details 

involved in doing that and we welcome 

recommendations that are applicable to all sizes 

and all types of industry businesses. 

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 So I appreciate all the work you've 

done. I know that you've been very busy over the 

phone and different long-distance meetings. 

 Just to recap a couple of the things 

that we, that you've been doing since May, you 

established four working groups. One for Food 

Safety, one for Labor, one for Trade, and one for 

Production. 

 I remember when we met in May, you had 

back and forth discussions of what the committees 

and what the more important pieces were and those 

were the four committees that you decided to 

establish. 

 On the Food Safety, you held three 

conference calls, one of which included 

coordination with about half a dozen FDA subject 

matter experts engaged in committee issues. 

 And some of the issues that you talked 

about ranged from the FSMA topics concerns 

surrounding the Foreign Supplier Verification 

Program and other Ag Water regulations. So we 

look forward to that committee's recommendations. 

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 Later we also have a stakeholder from 

United Fresh that will provide industry 

perspective on Ag Water later today. 

 On the Labor Committee, you members of 

that committee explored a range of topics 

associated with the H2-A Program which as you 

know, allows the U.S. employers to bring foreign 

nationals to work on our fields. 

 The work group is also very interested 

in farm labor statistics and labor survey 

methodologies. And we have today a person from 

Labor to talk to you about some of those issues. 

 Trade, you put together three types of 

recommendations to be considered. One on Buy 

America, one on trade promotion, and one on 

protecting U.S. growers. 

 We have someone from the U.S. Trade 

and Foreign Agriculture Affairs expert to talk to 

you about some of those issues today. 

 Production, last but not least. You 

developed recommendations for consideration to, 

pertaining to research, crop insurance, over 

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spraying and also targets chemical applications 

and inconsistent agriculture pesticide levels. 

 We also have a speaker. Every 

committee has a speaker, at least one today, so 

that's great, that is going to talk to you about 

Pesticide Data Program. 

 The last thing I wanted to mention was 

at the May meeting, I was very surprised that 

some of you mentioned that people were not as 

familiar with our inspection and auditing 

programs and that really hit hard on me because 

I'm like, how could we not have shared that 

information with the industry? 

 So I want to tell you that Jack Davis 

which works for us, unfortunately he's not here 

today, has prepared some materials and a plan on 

how we can better communicate with the industry 

about our services. 

 He's going to be contacting you after 

this meeting, shortly after this meeting, so you 

can take a look at what we've put together to get 

your feedback about what you think, where we're 

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going, if it's the right way to go, or any 

another recommendation you may have on that 

because we want to make sure that people do know 

all the services that are available. 

 I think you mentioned, Carl, that you 

called a service and it was faster and cheaper 

and great service. So we want to make sure that 

people have access to our services. 

 So thank you very much. You have a 

full agenda. I'm very excited to hear about all 

the things that you've been working on and all 

the recommendations you're going make. 

 I'm going to be sitting in the back 

because that's the only plug I could find so I 

can take notes. I couldn't find a plug from 

here. 

 But thank you for being here and I 

look forward to all of your recommendations 

today. 

 CHAIR CARR: Thank you. Darrell? Has 

he left? 

 MS. JIMENEZ: I think he walked 

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outside. What do you need? 

 CHAIR CARR: Well, I was going to say, 

are we ready for public comment? 

 MS. JIMENEZ: Yes, I think so. Let me 

find Darrell real quick. 

 CHAIR CARR: So now we're going to 

move into the public comment section on -- I know 

there are some speakers here that are going to 

talk to us on some topics but there's also some 

that have submitted some in writing that you're 

going to read, is that correct? 

 MR. HUGHES: Yes, yes. All right. So 

on, what day is this, Monday, July 22nd, we 

received a written public comment from Jean 

Public. Jean Public's comments were emailed 

responses. 

 There are too many toxic chemicals 

being used to grow these products. Growers are 

poisoning the air, water, soil and their own 

workers and owners. 

 The American people are dying earlier 

than ever and at lower ages. Cancer is rampant. 

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We need cleaner organic food to go back to what 

our ancestors ate. 

 I am against all the chemical growing 

practices for plants and vegetables. I assume 

that meant, that's supposed to be, I am against 

all the chemical growing practices for plants and 

vegetables, totally opposed to it. 

 We need organic. Also, the peaches 

you buy at the store are totally rotten in two 

days, totally rotten. That didn't used to 

happen. This comment is for the public record. 

Please receive, Jean Public. 

 And the second written comment is 

going to be from Lance Jungmeyer from the Fresh 

Produce Association of the Americas. However, 

Lance has a delegate here who's going to give 

oral remarks in person. 

 But before we have his delegate come 

up, we're going to invite the next oral speaker 

and it will be a representative from a company 

called METRC to give oral remarks. And I think 

it's METRC, right? METRC. 

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 MR. KOSKI: Yeah. 

 MR. HUGHES: Yes. Go ahead and 

introduce yourself. 

 MR. KOSKI: Thank you so much for 

giving me the opportunity to be here with you 

today. My name is Lewis Koski. I'm a former law 

enforcement executive from the state of Colorado. 

I saw that we had someone there from the state. 

 I am currently the chief operating 

officer for a company called METRC, M-E-T-R-C. 

You can find out website at metrc.com. 

 We are essentially an inventory 

tracking system and we have most notably been 

involved in the cannabis industry and we work for 

13 state governments around the country. 

 We track inventory that is regulated 

by, comprehensively regulated by each state 

agency that tracks cannabis plants from the time 

they're little baby plants to the time that 

they're harvested and transported to other 

licensed facilities like the store fronts for 

smokable cannabis or to processors for conversion 

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into edible products and oils and tinctures and 

things like that. 

 So the reason why I'm here today is 

I'm definitely not here today to ask you guys to 

start having some considerations about the 

cannabis industry and those types of things, but 

what I did want to do is just take an opportunity 

to kind of introduce ourselves, kind of let you 

know some of what we've been involved with and 

how the public-private partnerships that we've 

been involved with around the country can help to 

inform other industry outside of the cannabis 

sector. 

 Along those lines I'd just like to 

take a few minutes to just kind of describe a 

little bit more, in a little more detail what 

we've built and kind of what we've learned from 

the process of doing this 13 times across the 

country. 

 So our system is somewhat unique in 

that it's a government system. And what, but 

it's a government system that's visible from the 

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licensee side of the equation, but it's also 

visible from the government side of the equation. 

 And so we contact with government 

agencies around the country and licensees report 

into our system their inventory based on 

regulatory requirements that each state has. 

 And so it's, sometimes those are very 

comprehensive and sometimes they're a little less 

so. But we collect key data points from the time 

a cannabis plant is very small to the time it's 

harvested until the time it's transported to 

other licensed premises. 

 And we use that, we use radio 

frequency ID tagging as a way to really make that 

process efficient. 

 And one of the cornerstones to our 

system is that we pay very close attention and 

customize our solution based on the regulatory 

requirement so as licensed and regulated, it's 

the regulated community is reporting into the 

system, their inventories, they're also meeting a 

lot of those reporting requirements that they 

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have for the regulator as is. 

 I've been a police officer and a 

regulator for my entire adult life and one of the 

biggest challenges we have as a regulator is to 

be able to efficiently get the information that 

we need so that we're not disrupting those 

business operations of the regulated community. 

 And what we've done is we've created 

a system that allows the regulating community to 

seamlessly continue on with their business 

operations while also at the same time being able 

to input data into our system that meets a lot of 

the reporting requirements that a regulated 

community faces. 

 And so we really believe strongly in 

that public-private partnership between the 

regulator, the regulated community and the 

technologies that can make those processes much 

more efficient. 

 And kind of for the sake of time 

because I know you guys have a very packed 

agenda, but I'd just share a little bit of what 

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we've learned in that process that might be able 

to help you all in some of the work that you do. 

 One is that we really feel, this is 

kind of also, kind of close to my heart because 

it's the topic of my doctoral dissertation that 

I'm working on in my free time, and that is that 

the regulator is really critical at facilitating 

what's in the public interest. 

 Not that they're really -- it's really 

important for the, or the regulator to bring in 

and collaborate with members of the regulated 

community, special interest groups and those 

types of things, to really arrive at balanced 

public policy. 

 As I've been traveling around the 

world talking about cannabis policy, one thing 

that I've noticed is that it's not always how 

comprehensive the regulating framework, that it's 

tough for the regulated community, it's really 

how hard it is to report in and show compliance 

and be able to demonstrate compliance. 

 And what we've learned is that the 

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more the regulator is involved in facilitating 

those processes that you can strike that right 

balance. 

 The other thing too that's kind of 

different, that was different for me because I've 

been on the law enforcement and regulator side: 

to a hammer, everything is a nail. 

 But I realized that the regulating 

community, regardless of what the industry, their 

will to comply is very strong but the tools to be 

able to report on compliance are sometimes 

lacking and that's why we're really focused on 

having a system that makes it efficient for the 

regulated community to keep stride with their 

business practices while at the same time being 

able to meet reporting requirements that the 

regulator has. 

 The other thing too is we found that 

this can be scalable. So depending upon the size 

of the business, the actual process of tracking 

inventory can be scalable for small companies to 

make it really affordable while at the same time, 

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not being so cumbersome for a large organization 

so that it ends of costing millions of dollars to 

be able to afford. 

 And then kind of lastly, we found that 

our system doesn't have to be, you can have a 

centralized system that the government can look 

into to efficiently monitor essentially from 

their desktops in their office space, to be able 

to take enforcement action and if necessary, have 

evidentiary data that they can get real 

efficiently while still making it real efficient 

for the licensees and the regulating community, 

input that information. 

 They can either do it manually 

entering information or they can utilize 

proprietary or legacy systems that they have in 

place for ERP to be able to just seamlessly 

transition that data over to the government 

system for monitoring. 

 So we feel really strongly that there 

is a lot to be learned from the cannabis use 

case, not because we advocate one way or the 

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other for legalization of cannabis or hemp, but 

we really believe that there's been some real 

progress in creating efficient systems for 

regulators, the regulated community, and 

technologies to work together to have a 

comprehensive regulated framework while also 

still being able to do so without disrupting 

commerce. 

 So with that I'm happy to take some 

comments or some questions from the Committee. 

 CHAIR CARR: I have one. When you 

talked about your software there at the end when 

you have legacy systems that companies have and 

then new technology that go in into your data 

base and then you can, that to be able to meet 

the U.S. requirements or the regulatory 

requirements, do you have software that actually 

will take their information in the company's way 

if it's say a legacy system and will be able to 

extract that data and put it where it's supposed 

to? Is that what you're doing basically or? 

 MR. KOSKI: Yes, so if you have a 

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system that you use, like an ERP system, that you 

report all of your inventory into anyway, that 

system can integrate in with our system to throw 

data over the wall to populate the system that 

the government's going to look at. 

 And the government in our system also 

has the ability to throw information over the 

wall into that ERP. 

 So for example, if you had product 

that was moving from a farm to a processor or a 

farm to a distributor, when that data from our 

system could get thrown over the wall and 

received by another system without the -- either 

the farm or the distributor having to actually 

log into our system. 

 MS. HARPER LARSEN: Couple of 

questions bouncing off of him, based on FN 

statements --

 MR. KOSKI: I'm sorry? 

 MS. HARPER LARSEN: So when you talk 

about ERP transition from a legacy system into a 

software system --

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 MR. KOSKI: Yes? 

 MS. HARPER LARSEN: Most of them are 

based on FN statements which are highly human 

error-prone. So does your software read it or 

does it read and then come back? How -- because 

we're trying to look at this as it relates to all 

of our subgroup committee discussions. 

 MR. KOSKI: Yes. Sure, sure. So what 

I would say and I hope if I missed the mark on 

this just throw something at me, but so the way, 

what we've found is double entry is the most 

error-prone methodology of being able to report 

to a government on. 

 So if you have to enter something into 

your current systems and then you have to reenter 

that into a government system, that is the most 

likely avenue of creating errors. 

 So what we've done is we've created an 

interface that allows those software programs to 

take the data that is entered into an ERP system, 

and let's say it's just like, like a manifest or 

data that is input into a system. That manifest 

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data comes from that system and automatically 

populates on a field by field basis. 

 So the third party integrators which 

would be your system that integrate into our 

system, we work together with the third party 

integrators to make sure that the fields that 

they use are the fields that land and are 

important to the regulator for their monitoring 

activities. 

 MS. HARPER LARSEN: Okay. All right. 

You mentioned RFID technology and many of us in 

the produce industry have been down that route 

before. How does that relate to blockchain and 

transparency? 

 MR. KOSKI: Well, so RFID technology 

has proven to be very successful in the cannabis 

industry. And the system that we've created can 

be as granular as tagging every plant and then 

tracking batches that are derived from that 

plant. 

 Also, we have the ability then to 

trace back, talk about transparency, once a 

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product makes it all the way to the end point to 

where the consumer purchases it, if it were to be 

a public health or is a safety concern, we can 

actually trace back through the data that we had, 

that we collected at key points during the stream 

of commerce to be able to trace back to that 

product all the way to its originations. 

 So I don't know exactly what your 

experience has been with RFID technology, but 

there's a little bit, my experience has shown 

that there's a lot of conversation about how 

granular you trace things. 

 Do you trace every potato that comes 

out of the ground? We would say absolutely not. 

Do you track every strawberry plant? Absolutely 

not. There's ways for you to be able to scale 

the tracking using RFID technology based on the 

comprehensive nature of the regulations. 

 So if the regulations allow for it to 

be done by an acre, we can track it by an acre. 

But we'd still be able to trace things back to 

the origins. 

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 And one of the concerns that we, or 

one of the problems that we see is a lot of times 

in fruits and vegetables and in the agricultural 

community, you'll have an outbreak. 

 And a lot of times the entire industry 

pays the price for that outbreak because there's 

not a system in place that allows the regulator 

or the regulated community to go back and really 

identify the origins of the outbreak. 

 So our system, even using like minimal 

points throughout the stream of commerce would be 

able to track back, well, a lot more surgically 

than just a region of California or a region in 

the southeast part of the country. 

 We'd be able to really narrow it down 

to the actual farm that the products came from 

and probably, depending upon how many RFID tags 

you'd use, and we recommend, you know, the less 

the better as long as you can collect the data 

that you need, you'd be able to narrow it down to 

that acre or two acres that produced the product 

that was creating an outbreak. 

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 So when it comes to blockchain and 

transparency, I think what this does is the 

system itself creates a spirit of transparency in 

that the regulated community is like, we 

understand these points are the ones that are 

important to you as a regulator, we're going to 

feed those into a system where you can monitor 

efficiently and potentially even do inspections 

and risk mitigation work from the desktop and 

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 And so the transparency is really 

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regulator community. 

 MS. HARPER LARSEN: Thank you. 

 MR. KOSKI: And then just sort of 

blockchain, just one quick thing on blockchain, I 

would say that our, in the same way the 

blockchain really helps with the transparency 

piece, II think the way we have our system set up 

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and at the point that we collect data for tracing 

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commerce, that we cover a lot of what blockchain 

technology is capable of doing. 

 CHAIR CARR: Any other questions? 

 MR. KOSKI: Thank you, again. I'm 

going to be around all day today if you have any 

more interest. I have business cards and some of 

our material for you guys to have so if you want 

to get back in touch at a later time, I'd love to 

be able to able to talk with you more. Thanks 

again for your time. 

 CHAIR CARR: Thank you. 

 MR. HUGHES: Now we invite Lance 

Jungmeyer's delegate to speak. As that speaker 

approaches the podium, just in transparency, I 

received written comments from a member of public 

at 8:40 this morning. I won't be able to provide 

that to you all until after the meeting but I did 

receive some written comments and I'll probably, 

I'll try to forward that email to the group just 

so that you can read them before you go into your 

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work groups tomorrow. 

 MS. MOORE: All right. Hi, everybody. 

I'm Allison Moore with the Fresh Produce 

Association of the Americas in Nogales. 

 A lot of you look familiar. Hi, Fred. 

I'm going to have to report back to Lance. 

You'll be happy to know that I am his delegate. 

He works in an office of all females and we tell 

him that he works for us. So he will be happy to 

know today that I am representing him, finally. 

You know, he doesn't get all the kudos he 

deserves, so kudos. 

 So I'm here because we're one of the 

many faces of the specialty crop industry. Our 

members are U.S. importers of fresh produce from 

Mexico. 

 A lot of them are also integrated with 

growing operations here in the U.S. or in Canada. 

So we are sort of the example of the integrated 

North America in terms of supply of fresh 

produce. And I think when you look at the last 

20 years, we've done a good job as a produce 

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industry of increasing consumption of a lot of 

major commodities with consumers. 

 You look at blueberries, they've 

increased 600 percent according to ERS data. 

Tomatoes since the 90s have increased close to 80 

percent. You know, going from 12 pounds to 20 

pounds is a pretty big deal and then we see that 

across the board for a lot of commodities. 

 You know, I think that's a huge, 

important thing we have to remember and something 

that we need to focus on, how do we keep people 

eating the foods that we're growing and bringing 

to the marketplace. 

 Ag obviously accounts for a huge 

amount of our economy. U.S. Ag actually exported 

$138 billion in 2017. I'm taking all this from 

USDA, so if there's a problem you have to yell at 

the USDA folks. 

 And that's a $178 billion generated 

just from that $138 billion. So and that's a 

huge economic gain. I mean, that's $317 million 

worth of exports in a year. 

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 If you look at imports, we also impact 

the U.S. economy positively. We, just looking at 

tomatoes we had a study done by the U of A. 

That's 33,000 U.S. jobs across the country. In 

my county that accounts for over 20 percent of 

total employment in a rural county that's very 

poor and that's a huge deal. 

 We account for overall produce, 24 

percent of total wages in our county, in our 

little rural county. 

 So looking at our Ag industry in a 

whole, I think you see a lot of good things that 

are happening and also a lot of potential. 

 I think we have to keep looking at 

programs that are going to do more to bring food 

to consumers and to get consumers to eat the 

foods that we grow and that we bring to the 

marketplace instead of eating the Snickers bar or 

the what have you. You know, that's our 

competition, in our opinion anyway. 

 And there have been a lot of 

successful programs with USDA. I know for 

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domestic agriculture and MAP funding for exports, 

again, those, the $300 billion in economic 

activity for U.S. exports. 

 In looking at how do you leverage MAP 

funding, how do you improve it, how do you 

amplify that with potential state programs. 

 And we've seen a lot of really great, 

positive movement come out of the promotion 

programs, watermelons, avocados and mangos, that 

not only leverages U.S. dollars but it leverages 

all the imported produce dollars as well coming 

into those programs. 

 And then obviously school lunches and 

how do we work better with global partners and 

state partners in addition to federal money to 

improve kids wanting to eat fresh produce. 

 And I know our members support the 

United Fresh Salad Bars in Schools Program and we 

do that in our local community and we see that's 

a huge positive benefit just in our area, 

especially for kids, that a lot of their families 

work in the produce industry and now they're 

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going to, you know, eat salads at schools. 

 So that's for us, the, we would 

encourage the Committee to focus on programs that 

look at how do you increase access for consumers 

to fresh fruits and vegetables. 

 We are encouraging you all to avoid 

programs that seek to limit supplies to consumers 

that are going to make consumer choice 

diminished. Measures to restrict supply harms 

everybody. If you put protectionist measures in 

for products coming in from other countries, 

you're harming the companies that import, but you 

are also harming U.S. Ag that exports because 

what's good for the goose is going to be good for 

the gander. 

 So if you're going to limit imports 

into the U.S. then we're going to have 

retaliatory measures from our trading partners as 

well. 

 We're seeing that play out now in a 

number of arenas in trade. I know China's the big 

one that you can think of but, you know, also 

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looking at what's happening right now with 

tomatoes in Mexico and, you know, the 

negotiations are ongoing for that. 

 And it's just not, it's 

counterproductive to increasing consumption of 

the foods that we're all growing and that's 

really the reason you grow it, right, to have 

people buy and eat it. 

 Another concern that restricts 

movement is the proposed seasonality trade 

provisions. I know those were talked about in 

the USMCA and they were rejected in that process 

and we encourage this Committee to also reject 

measures such as seasonality trade restrictions. 

 So let's focus on how do you get 

people to eat more, how do you, when you put more 

food in front of people, consumption increases 

and so I would just ask that we focus on ways to 

do that instead of ways the industry and energies 

fighting for our little small piece of the pie, 

let's make our pie bigger together. So that's my 

comment. 

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 CHAIR CARR: Questions? 

 MR. BOWMAN: I have a comment or a 

question. You know, I do believe we need 

sustainable market access but we also need fair 

trade and House Bill 101 addresses that with a 

seasonality deal and I think that's a very 

important topic that we need to discuss, and, you 

know, I think you're missing the point a little 

bit on your comment. Thank you. 

 MS. MOORE: All right. We will have 

to agree to disagree. I think the seasonality 

bill takes us a step back and is going to create 

a patchwork quilt of tit-for-tat trade fights 

and, you know, people that look to export 

markets, then they're going to have the seasonal 

regional groups and those export markets putting 

similar cases against U.S. product. 

 And it just becomes a continuous 

battle back and forth instead of a continuous 

movement forward for everybody. 

 MR. BOWMAN: But if you have 

sustainable market access but you can't have 

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dumping and at times and the only way we can 

combat that is with a seasonal clause, then 

there'll still be seasonal business. 

 And if you have times during the year 

where there's excess supply coming into our 

market, you know, we need to be able to enforce 

that and then and protect ourselves also. 

 MS. MOORE: I think seasonal change to 

anti-dumping law is the wrong way to go. 

 MR. BOWMAN: Okay. 

 MS. MOORE: That's my opinion. 

 MR. WILKINS: You've stated that the 

USMCA rejected the first negotiation on 

seasonality. Do you have where that is today? 

 MS. MOORE: As far as I know, 

seasonality is not in the implementing language 

for USMCA. Mexico and Canada both were strongly 

opposed to seasonality language. So in the final 

implementing language that was passed by Mexico 

and Canada already, it's not in the language. 

 MR. WILKINS: Is that the time frame 

we're hearing of October '19 that that is, are 

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you aware of that date? Do you know? 

 MR. WILKINS: I believe it's come up 

very quickly. I don't have the exact date. 

 MS. MOORE: Yes, I don't know what the 

timeline is for when the USTR will even get the 

final package back to Congress but I think that's 

the next step. 

 MS. HARPER LARSEN: First of all, 

thank you very much for coming to present to us 

knowing the makeup of the Committee, 

predominately, and having done business in both 

domestic and foreign markets, I understand where 

your commentary is at. 

 One thing that I would like to ask 

about is we're dealing with trading partners who 

don't have seasonality issues predominately in 

their production patterns. 

 Mexico in particular, according to a 

University of Florida Study, invested since 2005 

52 times more capital in developing its grower 

infrastructure to develop greenhouse structures. 

 We already know that Canada has the 

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capacity especially in the four eastern provinces 

that supply in a lot of the dry veg so we're 

dealing with two trading partners here who don't 

have seasonality and we have the lower hand at 

that. 

 What would the Fresh Produce of the 

Americas Association offer to assist since you do 

also receive domestic product into those 

repacking operations in Nogales, to assist this 

Committee in making a well-rounded statement? 

 MS. MOORE: So we don't really see a 

lot of domestic product come into Nogales, into 

repacking facilities. 

 A lot of the repacking of any kind of 

product happens closer to the buying end. So a 

lot of that is actually, I know just in tomatoes 

is specifically a lot of U.S. integrated-owned 

repacking facilities that are repacking both 

domestic and foreign product. 

 A lot of our members for example might 

be growers in Canada, as well as growers here in 

the U.S., as well as growers in Mexico. We're 

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working with all of them. 

 They looked and said, what can I do to 

bring product to consumers. What can I do to 

access retail clients and does that involve me 

expanding my supply chain, expanding my growing 

window in other areas to be able to do that? 

 So a lot of people have looked at 

different innovation like Greenhouse in Canada. 

Greenhouse in Mexico. 

 Greenhouses here in the U.S., you're 

seeing that pop up in around metropolitan areas. 

You see greenhouses in Virginia. You see 

greenhouses going in in Kentucky. 

 You know, people are finding ways to 

adopt new technologies. I'm not a grower here in 

the U.S. I can't say, hey, go and adopt this 

technology. 

 What I can say is, we need to have 

consumer access to the foods that they want to 

eat year-round and flavors that they want, you 

know, to enjoy. Flavorful, good, high quality 

product. And, you know, you need to look to what 

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are the programs that can help growers across the 

U.S. innovate and meet those demands. 

 MS. HARPER LARSEN: Thank you. 

 MR. WILKINS: I guess this is more of 

a comment than anything but, you know, my father 

was in this business for over 50 years in retail 

and I've followed the past 44 and we both have 

spent our lifetime trying to supply consumer, 

okay. 

 You know, when I look at why I came 

here, we all represent obviously certain entities 

in the world. But you know, I, Bret and I happen 

to live in an area that has the highest diabetes 

rate in the world and one of the ways we can do 

is increase consumption. And I think that we've 

identified an issue here and I worry that we 

haven't provided the solution. 

 When we walk around Texas, which is 

where I'm from, there's a tremendous amount of 

second- and third-generation farmers that are 

struggling. 

 They're fighting water, they're 

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fighting urban encroachment, they're fighting 

labor. They're also fighting global encroachment 

as far as what they're doing. 

 You know, I challenge our Committee to 

come up more with a solution than a statement and 

I worry that we're just doing a statement and not 

offering a solution. 

 You mentioned House Bill 101 and 

dumping. You know, I worry that the vocabulary 

that we've stated in our recommendation has been 

left out of the conversation at this point, and 

if I was Secretary Perdue, I'd want more of a 

solution than just a statement and I worry that 

we're making a statement. 

 And I've got to look growers in Texas 

in the eye that I'm asking to grow and, you know, 

I believe in the American farmer but I don't see 

that we've offered a solution. Maybe some, and 

we are all in this business and, you know, I 

challenge us tomorrow to be a little bit more 

definitive in a solution. 

 We need all the fresh produce 

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consumption we can muster but it can't be at the 

sacrifice of the American farmer. I believe in 

that. I truly do. 

 But I just, I feel like we're 

reiterating a problem without offering a solution 

and I challenge us to work on that solution. 

 CHAIR CARR: Any other questions or 

comments for Allison? Allison, I have one. 

First of all again, I appreciate your comments 

and everything and I do think we could all agree 

on the fact that we want to increase consumption. 

 We, you know, and you mentioned the 

school lunch programs and the best way to start 

people off eating healthy is to start them off 

when they're young. And so we've all agreed and 

bought into that. 

 But one of our big concerns in this 

and it's something we're going to discuss 

tomorrow, is the Buy American provisions in our 

school lunch programs where we're using federal 

dollars that are getting spent on foreign 

products that are putting our producers at a 

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disadvantage here. 

 So these are concerns that we have 

when you're taking federal dollars and going and 

buying foreign product when there's U.S. product 

available. 

 And as Richard said, the big thing is 

fair trade. So if you're competing, if 

everything is level, that's great but when you're 

competing when it gets to subsidized industry in 

Mexico right now that's getting federal dollars 

from their own government to grow their 

infrastructure, defer their cost, we're not 

competing on a level playing field. 

 So that's where some of these 

challenges will come in. If you put us on a 

level playing field, we'll compete. But with all 

the regulations, our labor costs, and the fact 

that you got subsidized production coming in, not 

just from Mexico, but other countries as well, it 

is very difficult and we could see this industry 

change and continue to change in a negative way 

because of that. 

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 Anything else? Thank you, Allison, 

for your comments. 

 MS. MOORE: Thank you. 

 MR. HUGHES: Okay. So that's the last 

public speaker that was registered. We are 

turning ahead on time. 

 We do have a few members here with the 

public. There's a representative from Bayer 

here. It's totally up to you if you would like. 

If you're interested in giving some quick 

comments to the Committee, feel free to do so. 

Pass or? 

 MS. JACKSON-GHEISSARI: Yes, I mean, 

I haven't been trying to do this at all. This is 

the first time I've heard about --

 MR. HUGHES: Okay. 

 MS. JACKSON-GHEISSARI: -- this 

meeting and really very happy to be here. One of 

the areas that --

 MR. HUGHES: Would you, do you mind 

coming up here? 

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you. 

 MR. HUGHES: Sorry. 

 MS. JACKSON-GHEISSARI: That's okay. 

 MR. HUGHES: I figured I'd just give 

you the opportunity. 

 (Simultaneous speaking.) 

 MS. JACKSON-GHEISSARI: Put me on the 

spot. So good morning. My name is Amelia 

Jackson-Gheissari. My title is International 

Regulatory Affairs for Bayer Crop Science in the 

Washington D.C. office. 

 And for the last almost 30 years I've 

been in the highly regulation industry of 

agrochemicals, whether they're for the 

conventional farming industry or for the organic 

industry. 

 In the last four years, I would say 

I've spent a lot of time working on import 

tolerances and MRLs and I heard the Chairman say 

that later on today I think we're going to hear 

from the USTR or USDA FAS and I'd be happy to 

engage in that conversation. 

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 I would say that the countries that 

we're very concerned about at the moment are 

those countries that have their own positive list 

system and they're moving away from Codex MRLs. 

 So for example, China, Taiwan and 

Korea, and I know all those countries are 

important, especially Taiwan and Korea, to our 

fruit and vegetable exporters. 

 The EU also with its special 

precautionary regulations and the cut-off 

criteria that they apply to the approval system 

for pesticides in the European Union. And that 

is something that we are looking at, you know, 

very closely for our products and U.S. export. 

 So I'm happy to answer questions. I 

hadn't intended to make any statements but it's a 

fabulous organization here and I'm glad I got to 

know about you. 

 I'll be going out to California in 

January to speak to some growers about this 

issue, about particularly China, Taiwan and Korea 

and I can maybe tell you a little bit about that 

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a little later. Thank you. 

 MR. HUGHES: Okay. And also we have 

Robert Guenther from the United Fresh and then 

we'll be hearing from United Fresh later on this 

afternoon. But I'd like Robert to come up and 

give us a little more. 

 MR. TISON: Darrell, excuse me, will 

we be getting a printout of all these speakers 

with their names and who they're with? 

 MR. HUGHES: Yes. 

 MR. TISON: Okay. 

 MR. GUENTHER: Well, good morning 

again or good morning. Robert Guenther with 

United Fresh Produce. I wasn't going to speak 

but Darrell twisted my arm a little bit to say a 

few words. But again, to echo other speakers, 

welcome back for your second meeting. 

 For this session, as you know, United 

Fresh, this is a Committee that's very near and 

dear to our heart. 

 We worked very closely back in the 

early 2000s with Secretary Veneman to get this 

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Fruit and Vegetable Industry Advisory Committee 

chartered and it's, we think it's been a very 

successful committee over the last 18-plus years. 

 I really didn't have any formal 

comments but to welcome you. You know, I would 

say, based on what I've heard already, I mean, 

you're talking about issues we're talking about 

every day. 

 Tommy, to your point about solutions 

versus finger-pointing is very important to us 

especially in this trade environment we're in at 

this time. 

 You know, we need solutions and that's 

a combination of things. Part of it is increased 

consumption, part of it is better infrastructure 

investment. The government can help that. 

 Certainly we work very closely in the 

Farm Bill to kind of bring back hopefully to some 

efforts through the Farm Bill efforts that we 

spend a lot of time on and other industry 

associations spend a lot of time on say block 

grants, on research, pest/disease. But that's 

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not enough, obviously. 

 So we need to continue to think 

outside the box there beyond the traditional ways 

that USDA and other parts of the government can 

help us. We're looking at that. There's a lot 

of pressure on a lot of you, you know, in this, 

you know, current trade environment. 

 But we also see positive stuff and, 

you know, you mentioned the access to more fruits 

and vegetables for children and for, in federal 

nutrition programs. 

 We've seen a lot of positive movement 

in that policy space, certainly immigration. I 

know you have a committee working on that and 

continues to be on the top line for everybody. 

 You know, hopefully it's something 

that we can continue to move in the right 

direction. Certainly when we put these --

administrations put together a set of proposals 

on H-2A reforms, I think we move us in the right 

direction, but it's not enough. There still need 

to be Congress to act on those issues. 

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 So again, a lot of things you guys can 

help us with. A lot of things that, you know, 

your recommendation's going to be very important 

to the Secretary to listen to and to review, so 

appreciate your time to volunteer for this 

Committee. Happy to answer any questions as 

well. 

 MR. WILKINS: Do you all have any 

information on the USMCA Bill that you could 

share with us as to --

 MR. GUENTHER: Tommy, I mean it's 

really kind of waiting for the administration and 

the Democrats in the House to kind of come up 

with some agreement that they can fine-tune, some 

of the issues that the Democrats want in the 

House. I mean, that's the key thing. 

 Senate's ready to move on it. They've 

got bipartisan support, but there's a portion 

which you may have read that the Speaker has put 

together that is working with the USTR, 

Ambassador Lighthizer, to come up with some 

changes that they would be acceptable to them. 

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 And once that's done and they're 

working right now on this to, it could be as 

early as September. The administration brings 

the legislative leverage up to the Hill which 

then triggers that time period where they have to 

vote up or down on the bill, Congress does. It's 

90 days. 

 MR. WILKINS: So Mr. Trump backed off 

a little bit on the Apple and China issue 

yesterday and curious from your input on your 

history and work daily on some of the Hill. 

 Where do you see the collateral damage 

to some of the things we're talking about in the 

United States, say from the corn, the pork, the 

beef, potatoes? Is there any insight you can 

give us on what the collateral damage to some of 

this conversation we're having here? 

 MR. GUENTHER: I think it's 

significant. I think, number one, I think we're 

in this for the long haul with China. That's my, 

a lot of that I think is my personal, but I think 

that's a lot of you know how to, you know, we've 

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got an ongoing fight. I think the Chinese are 

ready to wait it out and see what happens next 

year. This shouldn't be political so I apologize 

to USDA for this. 

 But let's kind of see how the 

elections work out. You know, and see where this 

goes if -- but I think a lot of folks who are 

very reliant on exports to China for a lot of 

commodity groups and that's the Midwest, and some 

of our commodity groups are very concerned that, 

you know, these markets may, it'll be hard to get 

them back if, when and if there's an agreement 

for this trade war back and forth. 

 So I think we have a lot of folks in 

the grain industry. My wife's in the grain 

industry. I think we talk about, a lot of people 

talk about that in that world about will they, 

will China continue to keep them as markets or 

reestablish those markets once this trade 

agreement opens so there's a lot of concern and 

where does that product go. 

 There's already a lot of movement, you 

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know, in that world to shift production to other 

areas outside of the U.S. 

 MR. WILKINS: So how would you 

recommend that we as a Committee look at that for 

the word fair trade? 

 MR. GUENTHER: Well, continue to open 

markets. We got to get away from trade aid. 

Certainly we appreciate the administration's 

efforts to send two amounts, two buckets of 

funding for trade aid. 

 Some of that has gone to fruit and 

vegetable specialty crops community in the form 

of payments, in the form of commodity purchases. 

But we've got to get away from that. That's just 

not a long-standing or, you know, a sustaining 

type of way to deal with trade battles. 

 So we've got to find and continue to 

open up new markets best we can. You know, but I 

think the problem is not just China. We've got a 

lot of other battles that the administration is 

fighting right now related to tariffs and 

challenges. India is a good example. 

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 You know, we need to get some of these 

bilateral agreements done with Asia, like Korea 

and Japan, for instance. I know Jason 

Hafemeister's going to talk to you guys later and 

shortly, I guess. 

 And I mean, I think he can fill you in 

on kind of that view of the administration but I 

think that we've got to look for alternative 

markets. 

 You can't just settle on one market. 

I think that a lot of folks in the grain industry 

have gotten it. Once that dries up it becomes a 

challenge. 

 CHAIR CARR: Charles? 

 MR. WINGARD: Robert, you mentioned 

about we need solutions, not finger-pointing, I 

think is the word you used. Does United have a 

proposed solution for these trade issues? 

 MR. GUENTHER: You know, we're still 

-- we don't. I think it's a challenge right now 

to understand when the next shoe's going to drop 

with the next fight. 

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 This is a very unpredictable 

environment, we are in trade, that we've never 

been in in my 20-plus years here that I can 

remember over the last two to three years. 

 So it's hard to kind of create a longterm strategy when you're not sure kind of the 

changes in negotiation strategy that are going on 

with some of our partners. 

 So I continue to believe that, you 

know, we've got to continue to try to open up 

markets through trade agreements, through, I 

mean, somebody mentioned a market access program. 

Allison mentioned the Market Access Program, 

expanding these programs that allow for increased 

opportunities in trade. And I think that's our 

best tool right now, is a new solution to that, 

Charles. 

 But that's nothing novel that I, it's 

hard to create a long-term strategy when you're 

not sure how, just what the real strategy endgame 

is for the current, you know, environment we're 

in. We're just not sure. And I'm just not sure 

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it's by me but a lot of body groups of trade 

agreements. 

 CHAIR CARR: Okay. Go. 

 MR. ZEA: Donn Zea with California 

Prune Board. Robert, what was, in your opinion, 

I mean, there's a lot of discussion about the 

challenges we're now facing in this chaotic time 

and we're all looking for solutions. 

 But how were we doing before this 

chaotic time, in your opinion? I mean, how were 

things going, what were the solutions then as 

compared to now? 

 MR. GUENTHER: I think that things 

were going, were doing well. I think we were 

focusing on how do we reduce the non-tariff, 

trade barriers. Tariffs were not an issue for 

us. It was for the sight-unseen sanitary issues 

that we were trying to bring down and once 

tariffs were at a good space across the world, 

and I think those were the areas we were focusing 

most of our time on, was how do you bring down 

these fundamental trade barriers, as we call 

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them? 

 And they were areas related to pest 

and disease sometimes. Sometimes they were 

quote-unquote, made up to try to block product 

kind of going out from the U.S. to other 

countries. Some of it was safety-related and you 

had challenges there from other countries. 

 And these were things with more 

technical challenges that we were fighting 

basically by commodity, by commodity. The tariff 

stuff then when it started kind of going back and 

forth, you know, changed that dynamic that we 

just got to get back to where we were and then 

have those fights. 

 And a lot of that could have been 

addressed in some of the trade agreements or new 

trade agreements. We could be pushing for the 

Trans-Pacific Partnership. The TPP was one area 

that we thought was moving in the right direction 

and then of course we pulled, the United States 

pulled out of that agreement in 2017. 

 So but they had some really good 

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strong sanitary and phytosanitary provisions that 

were transparent that required you to really 

justify it scientifically why you were reducing, 

people were blocking product coming into your 

country and that was like around 65 different 

countries were part of that. 

 MR. ZEA: Okay. 

 MR. GUENTHER: And it was going to, 

you know, and we unfortunately pulled out of 

that, so. But that, before it was really the 

technical areas that we were facing on all trade. 

Hopefully that answers a little bit. 

 MR. ZEA: Okay. 

 MS. HARPER LARSEN: Good morning, sir. 

 MR. GUENTHER: Good morning. Good to 

see you. 

 MS. HARPER LARSEN: I think we can all 

say that NAFTA has failed us as the American 

producer and we haven't been able to actively 

police it. 

 And with the fact that we all do need 

to come up with solutions but we have a shortened 

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timeline. We're talking about September time 

frame, maybe October time frame, to be able to 

give the American producer a leg to stand on 

because he's on his knees right now. 

 With that in play, if we allow a 

seasonality provision in law, H.R. 101, S.B. 16, 

we could not enter into an agreement, correct, 

that would not have that provision, is that 

correct? 

 MR. GUENTHER: It would be our 

understanding that, well, during the negotiations 

before the agreement was signed in last year, the 

Canada and U.S., or excuse me, Canada and Mexico 

refused to accept a seasonality provision in the 

USMCA agreement. 

 So if that was reintroduced, it's 

unclear, probably most likely they would push 

hard back at that being part of it because the 

agreements have to be pretty much simultaneously 

agreed to or, let me back up. They must be, you 

know, consistent between the --

 MS. HARPER LARSEN: But currently when 

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those negotiations, when our folks went into 

those agreements in Mexico City, they didn't have 

any legal teeth. They said, this is what we want 

but they didn't have any legal teeth to say this 

is what regulation says. 

 MR. GUENTHER: Yes, I think I 

understand that question. I think that's right. 

 MS. HARPER LARSEN: Can you give the 

Committee a little bit, because I know United was 

at the table and at those meetings, that was an 

11th-hour discussion. You know, seasonality was 

in the USMCA provision. 

 MR. GUENTHER: Mm-hmm. 

 MS. HARPER LARSEN: Can you detail to 

them what we were exchanged for? 

 MR. GUENTHER: Well, I don't think we 

were really at the table. I think we were 

certainly, I mean, I certainly, so you got, some 

of you may know, Bret and I serve on the fruit 

and vegetable industry, excuse me, the USDA Fruit 

and Vegetable Trade Advisory Committee. 

 So there's a different advisory 

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committee where trade is based on different 

commodity groups. So there is a Fruit and 

Vegetable Advisory Committee on Trade to the 

Secretary. 

 And so as part of that group we as a 

committee did not support; we encouraged the 

USTR, the trade rep, the trade negotiators to not 

include a seasonality provision but to find other 

solutions, to Tommy's point, to address the needs 

of the current domestic workforce, or domestic, 

excuse me, domestic industry. 

 So that then, the negotiators for the 

U.S. then, right, were kind of put in a position 

where they couldn't push as hard as they were 

initially. 

 So is that, I mean, so basically they 

put in a new proposal --

 MS. HARPER LARSEN: Is there a new 

committee makeup now though? 

 MR. GUENTHER: -- Canada, U.S., Canada 

and Mexico disagreed or said hell, no, we're not 

going to do that. 

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 MS. HARPER LARSEN: Right. 

 MR. GUENTHER: And then they pulled it 

out of the agreement. 

 MS. HARPER LARSEN: But we were 

exchanged for auto, correct? Automobiles? 

 MR. GUENTHER: I don't know that. 

 MS. HARPER LARSEN: Can you talk to 

them, because a lot of people might not be --

 MR. GUENTHER: I can, yes. 

 MS. HARPER LARSEN: -- familiar with 

USDA's trade committee? 

 MR. GUENTHER: Mm-hmm. 

 MS. HARPER LARSEN: And what its 

current makeup is? 

 MR. GUENTHER: Sure. So I don't know 

how much you're aware of this, but for a long 

time USDA and USTR had a series of technical 

trade committees as well as a, what's called the 

Agriculture Policy Advisory Committee on Trade, 

which again advises both USDA and USTR on trade 

issues. 

 And there's an overall committee and 

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then there's several groups driven by commodity 

groups. So there's a fruit and vegetable one, 

there's a grains, there's a dairy one, there's 

several others, Chemical Ag retail farm inputs. 

 And those groups then break up into 

meet two or three times a year and we're also 

have weekly or monthly discussions with U.S., 

with USDA-USTR about some of the language that is 

in the different agreements or proposed 

agreements and we're allowed to comment on those 

before the public does. 

 But those are all kind of private 

conversations or secret. We're not allowed to 

publicly share that information. So it's quite a 

process compared to what you guys probably have 

to go through for the Committee. You'd get on 

the committee. 

 So anyway, that's kind of, Jason again 

is part of that group who helps guide us. So it 

could be, if you want to, you know, understand 

the structure of that he might be a good person 

to talk to about that as well, kind of tell you 

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about how that process works. 

 But it, yes, I mean it's, they're, again, 

it's focused on trade. Some in this committee 

are very focused on just trade and all the trade 

things going on with the U.S. and other 

countries. 

 MR. ERICKSON: I have a question for 

you. This is a tough topic, the trade issue. 

One of the things that, you know, there is a lot 

of us that, like our company, you know, we're 

primarily a domestic producer, a gross shipper. 

 We probably grow, pack and ship 85 

percent of our product in the U.S. We do import 

some product out of Mexico to sustain ourselves 

when, you know, we move from Texas to New Mexico 

or Georgia and then up to New Jersey. 

 And then we use Mexico as a bridge to 

help us kind of, and then we do some work in Peru 

to kind of complete a cycle so that we can be a 

year round supplier to our customers. 

 We're also not, you know, our owner 

and our company, you know, it's not to say that, 

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you know, we're not too excited when Mexican 

product is coming in at the same time that we're 

producing product because it, you know, it's more 

expensive, frankly, for us to grow. 

 But my point is, you know, maybe as a 

group and an industry I really believe we should 

be putting more pressure on the buyers and the 

retailers to support first domestic production 

when possible. You know, we sell a lot of 

product. We export a lot of product to Canada. 

 And the Canadians do a tremendous job 

of protecting their own seasons. When stuff is, 

when Canada is in season you can't get in. They 

support Canada. 

 It's not by law or regulation. They 

support Canadian. And it would be nice for us to 

find a way to, you know, be united. It's tough 

to, you know, you don't want to tell your buyers 

hey, you wag your finger at your customers. 

 But, you know, as an industry it would 

be nice if we could find a way to collectively 

say, you know, the cost of labor is going up. A 

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lot of us are having to go into H-2A. 

 We're competing with, you know, we 

talk about fair trade. Our buyers should be 

recognizing that and they can say well we support 

local. You know, we believe we support domestic. 

 But at the end of the day, you know, 

it's about the cost and a lot of them, you know, 

are sourcing the lowest cost option. And 

considering the circumstances that U.S. producers 

are in for a lot of reasons, a number of which 

we're discussing here, it makes it really tough 

for us to compete on those items that we're 

growing here in the U.S. and that are coming from 

somewhere else at the same time. 

 MR. GUENTHER: Yes, Bret. I think 

you're spot on. This is the way we've got to as 

an industry try to work in partnership with our 

customers to figure out better ways of supporting 

the domestic industry but also making sure 

obviously that consumer demand is met. 

 Market access is important. You know, 

the U.S. consumes I think, Allison mentioned kind 

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of the increase of consumption in certain 

commodities. How do we address that from a 

domestic standpoint but also make sure that 

consumer demand is met? 

 You know, I think, you know, we do 

have some very progressive market access in our 

world, fruit and vegetables in terms of product 

coming into this country. You look at the 

increase. 

 But that also means a lot of demand is 

put on there, in terms of demand from the 

consumers. You know, we've got companies now in 

the U.S. who are investing in other, as you 

mentioned, other countries as well because of the 

demand. 

 And a lot of that's coming from the 

customer side, the customer base. And in terms 

of being a one stop shop supplier of product, 

peaches, collards, whatever you want to call it, 

you know, and how do we meet that customer, I 

mean consumer demand but also that customer 

demand. 

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 And you're right, that's an industry 

discussion that we need to try and figure out 

what's the best way to approach that because we 

have not necessarily addressed that directly as 

much as we've let the marketplace work it out. 

 MR. ERICKSON: Like school, you know, 

school lunch programs it's easy to find ways to 

incentivize them for school lunches to buy 

American first. And believe me, I'm a fan of 

having, my wife wants strawberries all year 

round. 

 She wants blueberries all year round. 

She wants tomatoes all year round. To Allison's 

point, we are eating a lot more tomatoes than we 

did five years ago in our household. 

 Avocados, you know, there are a lot of 

examples. And I want options at the grocery 

store. I want everything available to us 365 

days a year. 

 But if we can find ways to incentivize 

school lunch programs maybe there's ways we could 

look at to incentivize regional and national 

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retail chains to source local or domestic 

leaders. 

 MR. GUENTHER: I agree. And, you 

know, one of the tools we have as far as I'm 

concerned that we need to probably have a more 

strategic plan on is the Specialty Crop Block 

Grant Program. 

 That is supposed to be incentivizing, 

supposed to be marketing, promoting fruit and 

vegetables across the country. I know let's take 

my state we've included a multi-state that you 

can do more regional national approaches to it. 

 But I think it's something this 

committee ought to spend a little bit of time on 

with AMS as they run the Block Grant Program to 

understand how the states are using that funding 

to promote, to help the domestic industry because 

that is one of our best tools in terms of 

domestic support. 

 And, yes, I mean there are some good 

projects going on the state by state level. 

Colorado Department of AG is here somewhere. 

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 But I think that, you know, it's 

something I think we ought to think about, 

especially this committee ought to think about is 

how can we encourage states to continue to have 

this, you know, because it is a federally funded 

program, $85 million a year now. 

 And it's been, you know, it's a good 

vessel. But that really was focused on 

increasing domestic and supporting and marketing 

domestic product. 

 MR. WILKINS: This leads a little bit 

into what I challenged us to work on tomorrow is 

that, you know, 21 years I was director of 

produce procurement for United Supermarkets in 

Lubbock, Texas. 

 And if it was grown in the United 

States I bought it. I didn't buy nowhere else. 

So I'm not saying about what anybody else does. 

But, by God, I did that, okay. 

 And I agree with it 100 percent. But 

we are in a time where we're seeing investment 

firms sucking up companies, all these companies 

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that are buying into what we're doing. 

 And I challenge us, you know, I did 

what you asked, okay. But I think the solution 

to this is prohibiting the dumping or anything 

that is a barrier to fair trade, okay. 

 And I just, I question that 

seasonality goes far enough or there's not a 

solution in that. It's been balked at already. 

We have to do something to give the American 

farmer every chance he can. 

 You guys need to and you can do it 

right now. But I believe that a lot of domestic 

produce people in my position in the past 

understand that and do that. 

 But I think from our tier we've got to 

look at helping with more of the things that we 

do to hurt, you know, the dumping issue is one 

that, when the market is $5 on anything nobody 

makes money, nobody. 

 And the consumer, quite honestly, 

don't even get the benefit of the deal. You 

know, the question and I don't have all the 

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answers and I certainly have got more questions 

and I am way too passionate about this. 

 But you put a tariff on something 

where does that tariff money go? I know it comes 

out of my pocket paying more for product coming 

in on the tariff issue. 

 I don't think that's a solution. We 

are smart enough in here to come up with more 

solutions. But I really feel like we owe the 

solution to be more than just agreeing that we 

have a problem. 

 We've got a problem. How can the 

intelligence on this committee come up with a 

solution? 

 MR. BOWMAN: And I'm under the 

impression that there's tax incentives to 

retailers in Canada to buy Canadian product when 

it's in season there. And that's one of the 

things that promotes them and our trade 

representative might be able to confirm that. 

 I mean, Canada protects its growers, 

I mean, the dairy industry, the wheat industry. 

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I mean, I was visiting growers in Canada a couple 

months ago and I don't know if everybody in this 

room knows. 

 But the U.S. dairy industry is in 

horrible condition right now. And to see new 

dairy farms being built in Canada was just mind 

boggling. 

 I do believe they have support 

programs to get the retailers to buy Canadian 

through tax incentives. But I'm not 100 percent 

sure. 

 CHAIR CARR: I have a few comments. 

There are many of us here that are members of 

your group. And I don't know if a national 

organization has done more to actually try to 

expand the consumption of fresh fruits and 

vegetables than the United States, very 

commendable there. 

 But looking at this and the couple of 

the issues that we obviously disagree on. So we 

have provisions where we give federal dollars to, 

you know, support school lunch programs and 

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everything like that. 

 And we've obviously got importers 

being product in here. These are being used to 

provide those. Where does United stand on the 

Buy America provision? 

 MR. GUENTHER: We support the Buy 

American provision. We always have. And it 

mushroomed at some point. Certainly, you know, 

the Child Nutrition Reauthorization policy, but 

that bill is now up for consideration in like 

September. 

 That's going to be another area where 

they can strengthen the Buy American provision. 

So your recommendations will be helpful to not 

just the USDA but even Congress to figure out how 

that can be strengthened in the way that makes 

sure that schools and school districts, in 

particular are applying that provision. 

 I know we've had a lot of challenges 

in California. That's kind of the tip of the 

iceberg with the Chinese peaches that were bought 

by the Sacramento School District. 

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 We can't have that happen, period. I 

mean, you know, Steve knows this, being part of 

the industry, you know, we just can't have that. 

We're not going to support that. 

 But, you know, I think that's another 

opportunity. But anyway, but that's kind of, 

that's what we want. 

 CHAIR CARR: So we already discussed, 

I mean we all know what NAFTA has in place in 

certain parts of this country in particular the 

southeast, Florida would probably be number one 

where tomatoes, same think like the peaches. 

 Like before NAFTA there was other 

commodities as well. But we all knew there was a 

problem with that and so we came up with this 

regional language. 

 And then that got removed through 

negotiations. But United has not taken a 

position, your position is not to support 

regional because it could change the agreement 

that's in place. 

 How do we then understand that, work 

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around that or work for another solution going 

forward? 

 MR. GUENTHER: Well it goes to a 

little bit of Tony and Richard brought this up 

too. I think we feel and I think Allison even 

touched on this, I think we feel, well we do feel 

that the USMCA in its current state is a good 

thing. 

 You mentioned the dairy industry. 

They didn't get what they wanted in the USMCA. 

They gave more access to Canada yet they are 

supporting USMCA as well. 

 But in terms of the national bearing 

organizations, there is, negotiations at that 

point. But I think that we have got to find 

different ways to help invest in our domestic 

industry to help them continue to thrive. 

 And again, that's part of what we do 

in the Farm Bill. It may not be enough. We may 

need to think differently. We may need to 

redirect some of the programs that we thought 

were going to be useful. 

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 You know, ten or 15 years ago when we 

started this Farm Bill effort to help enhance the 

Farm Bill, you know, the Farm Bill in our world 

was there for 60, 70 years. I'm very interested 

in, I mean obviously, you know, we have a test 

case going on right now with tomatoes. 

 And it is going through now the 

process of whether or not, you know, there is 

funding. And the primary decision by IDC is 

there was. 

 So there is a process that is going on 

as we speak. It may not be the best process. It 

may not be the most direct process. It took a 

while. 

 So if this case continues and there's 

no agreement, you know, we're going to find out 

real quick what our customers are going to react 

to that in terms of supply. 

 You know, how is industry going to 

change if it does at all because of the increased 

tariffs on tomatoes coming into the U.S.? Does 

this go down the supply chain? 

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 Do consumers and retailers and other 

customers push back at it? But, you know, we're 

right now, you know, this is a test case that may 

drive us into a different, at least my view of it 

is, if the case goes forward and there's a final 

decision -- and it's applied to domestic 

industry, how does the domestic industry, does 

that help them or does that really kind of harm 

in terms of losing their opportunity for more 

market access domestically? 

 We'll see. I mean, to me it's, you 

know, the process is moving forward. It's been 

clunky. It's not as efficient as the regional. 

It's easy to file a complaint or file a suit as 

the seasonal perishable provision would. 

 But, you know, the tomato process 

we're moving forward. Allison may kill me. I 

mean, I don't know what else to say about it 

except, you know, we're watching this. We're not 

involved in that issue. 

 We're not taking sides on that issue. 

We've made everybody mad every time we say 

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something about the tomato issue, whether it's 

the domestic industry or the Mexican industry. 

 So we are staying out of that. But we 

still believe USDA is still, to your point about 

enforcement it does enhance enforcement. It does 

have better sanitary -- provisions that were not 

in the original 1994. 

 Sure that's a 30 something year old or 

40 year old trade agreement. There are going to 

be agreements made. We've had a lot of changes 

in trade during that time. 

 So, yes, we were supportive of the 

negotiation. 

 CHAIR CARR: But 25 years later we 

knew the biggest problem of NAFTA is we didn't 

have a regional ability to buy --

 MR. GUENTHER: That's true. 

 CHAIR CARR: -- and the industry said 

we need this. But unfortunately, it was traded 

away again. And that particularly impacts about 

five southern states more than it does everybody 

else. 

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 My last comment or question is and 

Tommy brought it up is collateral damage to these 

trade situations. And we're witnessing it in the 

industry right now. 

 So cherries lost its ability to market 

to China. Twenty five percent of domestic 

production of sweet cherries goes to China or 

used to. 

 USDA and the administration put 

cherries on the trade mitigation list and farmers 

got direct payments and such is that. The intent 

was they would be able to go establish other 

markets. 

 Unfortunately, what they did is they 

then decided to market that crop back within the 

United States. And peaches right now are 

suffering the lowest prices we've ever seen 2004 

because cherries had a year to prepare to market 

their crop plus they're getting federal funds to 

help market their crops. 

 So there is going to be a ripple 

effect to other commodities that originally we 

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never thought were going to be impacted. But 

there is a huge impact. 

 MR. GUENTHER: I apologize I did not, 

I mean you're right, I mean we're seeing that in 

these markets. Apples is another example. Some 

of the states outside of Washington State are 

experiencing low prices. 

 But you're right it is not, as I said 

it's not a good solution to this trade 

mitigation, period. It's just not. It's a bandaid. It's a short term fix. 

 I don't think any of the programs, in 

my personal opinion, are really designed to help 

our industry and the way our industry works 

efficiently. I know that some have been happy 

with mitigation payments but also the purchases 

but some are unhappy because of the way this 

process works. 

 It just doesn't work for them. And 

the way we are forecasting compared to some of 

the other crops who got the bulk of the trade 

mitigation, we do have a small group in our 

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association world that are looking at what would 

be a better solution if we have a third round of 

language. 

 So let's just say I think there may be 

a third round of trade mitigation. And outside 

of the scope of the three programs that they put 

together and -- but we've got to come up with, to 

your point, commerce we've got to show that USDA 

administration saying this is just not working 

for us, that we need some other things. 

 CHAIR CARR: That's the reason I 

wanted to raise it with you. Tomorrow the group 

can talk about it. But so there is going to be 

this ripple effect. 

 Other commodities are going to be 

affected. And we are going to start working on 

that now to understand those impacts because it's 

easy to say China has got a lot of the cherries 

account so obviously they were impacted. 

 But now what is, what other things 

have been impacted? Grapes is another one is 

right now potentially going to go through a 

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dumping case potentially as well. 

 There's been a huge disruption due to 

these trade wars and they're only going to get 

worse. And again, back to the comments you made 

we've lost some provisions to help certain parts 

of this country to defend themselves. 

 So again just want to raise that with 

our organization, but again, commend you for 

everything you all have done to increase 

consumption. 

 MS. GLEASON: I have one last 

question. You mentioned the Child Nutrition 

Reauthorization Act. And I'm not sure if that's 

been discussed in any of the subcommittees. 

 But I'm just wondering if you have any 

ideas or suggestions that this committee can use 

to make sure that local production is 

prioritized? 

 MR. GUENTHER: So Steve is going to 

like this question. He knows what I'm going to 

say. Well so just to give kind of an overlay of 

China. So the bill was supposed to be 

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reauthorized in 2014, is that right, I think it 

was '14 or '15. They did not get to it. 

 It's not like at the end of the day 

like a Farm Bill and other laws. So the current 

programs continue to move as they are for, as the 

2010 bill was written or law was written. 

 So there is a renewed effort in this 

new Congress, the Senate in particular. Senator 

Roberts, the Chairman of the House Senate Act 

Committee Ranking Member Stabenow said they want 

to get this done. 

 Some of you probably know, Senator 

Roberts is retiring. This is kind of one of his 

things. He's got the Farm Bill under his belt. 

His last one he wants to get this bill into 

reauthorization. 

 We expect they are going to introduce 

a bill in the September time frame when they get 

back from the recess, the August recess. So in 

terms of programs, so I'll start with the easy 

ones and I'll get to the harder one at the end. 

 As you know, the last one, it 

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increased -- servings increased of vegetables in 

all forms by a cup. So half a cup for breakfast, 

half a cup for lunch. 

 So that was a good win overall for the 

entire industry. Another thing we're focusing on 

is the grants to get more money into the 

equipment grants for schools. 

 A lot of schools are looking to, they 

have access to more fruits and vegetables. They 

need infrastructure. And so that's another area 

we're focusing some time on. 

 The one that is near and dear to our 

heart and some here and some not, one section 

here it's in your heart, is the Fresh Fruit and 

Vegetable Program. So Steve and I have had many 

discussions over too long of a time. 

 And this program basically is a 

program that provides a fresh fruit or vegetable 

snack during, not during lunch or breakfast but 

during the classroom environment. It is, started 

out as a pilot for states. Now it's nationwide. 

 It has about four million kids who 

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participate in the program. But there is a push 

to make it all forms, not just lunch. 

 You know, part of this that there is 

a significant portion of the school feeding 

programs that accept all forms and this program 

is a small, little program that really should be 

left alone and helps complement some of the 

things that are going on in the school lunch. 

 Steve disagrees. Some of you others 

may disagree. But that's fine. We -- and that's 

fine. And it's been an ongoing battle. It has 

probably been one of the stickiest battles that 

we've had over the years. 

 When you're thinking about this 

program it's authorized under the Farm Bill and 

nutrition. So every basically two years we kind 

of come up with this interesting debate on 

Capitol Hill about how the program has been run. 

 So, you know, that's kind of the 

biggest issue for us as United. But certainly 

this committee, you know, if you address 

nutrition or nutrition issues, you know, it's 

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going to come up in this space. 

 So, you know, so that's, those are 

probably the three big things. The half cup 

increase or the cup increase, make sure that 

doesn't go away. 

 That helps everybody which the 

equipping grants would be the third or second 

area we would like to spend, you know, get that 

permanent in the Child Nutrition Reauthorization. 

Right now we have an annual appropriation, sort 

of an annual funding for that program. 

 We get money each year and we have to 

ask the appropriators. This would make it 

mandatory money for the equipping grant program 

schools can apply for and then the Fresh Fruit 

and Vegetable Program. 

 MS. GLEASON: Is there anything in the 

current, in any of the current programs that 

prioritizes local, like American production? 

 MR. GUENTHER: So in school there is 

the farm, well actually more through the Farm 

Bill than it is Child Nutrition Reauthorization. 

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 MS. GLEASON: Okay. 

 MR. GUENTHER: If you want to know 

about this more I mean I could, you know, I know 

you were speaking with Jennifer from our team 

later. She is our nutrition policy expert. 

 She can come and talk to you about 

that. Most of that is farm, school. There are 

some Buy American local provisions. But it's not 

as prevalent in Child Nutrition Reauthorization 

as it is in the Farm Bill. 

 CHAIR CARR: We have time for maybe 

one more question. 

 MR. ZEA: This is more of a statement 

than anything. But it always surprises me that 

the issue of price and elasticity does not come 

up more often. 

 When you're seeking solutions and you 

ignore that, we continue to try to find these 

magic pills that are going to sort of separate us 

from the reality that, you know, in our case our 

prices are up to 100 percent greater in certain 

markets than Chilean, for instance. 

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 And there's only so much a consumer is 

willing to spend, especially when the quality, 

you know, you can differentiate all you want and 

for good reason. But in some cases people don't 

have the power to distinguish between what's good 

and what's not. 

 And I tell our growers all the time I 

have no idea how you guys succeed because the 

amount of inputs anywhere in the U.S., certainly 

in California the amount of input that you've got 

to put into a product to send out in the market 

and slug it out with a competitor that has a 

third of them or less, it's remarkable we succeed 

the way we do. 

 And so programs like NAP for us and an 

export level are absolutely huge. Innovation 

grants, all those kinds of things that make us 

smarter and better are absolutely significant. 

 But ultimately, you're still going to 

have to ask those developing markets, those 

mature markets or even our domestic markets, 

you're going to have to ask those consumers to be 

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able to raise their game, make more money, spend 

more of their discretionary income on food. 

 And that is a big ask. And I don't 

know that this committee is ever going to find a 

solution to it. 

 MR. GUENTHER: I think it's, when we 

are challenged with it all the time. I mean we 

are in committees and boards and we have, I know 

other groups have. I mean it's a tough, you 

know, how do you find a solution to that? 

 It's replacing costs, you don't like 

blueberries, buy strawberries. You know, 

consumers just, they have a lot of, we spoil the 

consumers on levels. 

 And, you know, we're now seeing that 

whether it's the Chinese right now are saying 

don't buy anything American. You know, I don't 

think we'll ever get to that point here in the 

U.S. 

 But you're right. I mean it's 

something that I don't know how you, it's hard to 

find a solution to that. It's really hard to 

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find a solution. 

 CHAIR CARR: Robert, thank you. Did 

we have anybody else for public comment? 

 MR. HUGHES: No, additional public 

comments. There is one statement that I want to 

make. When Robert talked about the ATAC's, the 

Agricultural Technical Advisory Committee. 

 That set of committees are a factor 

just like you all. And so if the Trade Group 

for the committee as the whole wants to 

coordinate or collaborate with ATAC let me know 

and I can reach out to the group federal officer 

that officially is over that set of committees. 

 And the rules on those committees 

occur under FAS, Foreign Agriculture Service. 

 MR. WILKINS: We need all the 

collaboration we can. So I would love to see us 

work with them on that. 

 MR. HUGHES: Okay. We can coordinate 

after. 

 MR. WILKINS: You can put that on your 

to do list, the one, two pages you have to do. 

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 MR. HUGHES: Up next, we've got 

yourself given the trade war. Just a sort of 

formality about each of the workgroup 

presentations that are going to be happening 

today, there is need to look for discussion on 

the recommendations in the approved period 

because you guys are going to be going into your 

workgroups tomorrow to refine, retool and make 

recommendations that are given to them. 

 And they are good to go. But all of 

the final authorization activity will take place 

after presentations today. 

 CHAIR CARR: And just to be fair, all 

the groups and all the speakers we're going to 

adhere to the schedule as best we can. So, you 

know, questions and answers to the speakers just 

understand if we reach a point because we have 

other speakers to come and may have more 

questions, we will have to move on and come back. 

 So if we don't get questions answered 

today then we can do that tomorrow. But we want 

to give all the speakers an appropriate time to 

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speak and then have everybody have the same 

chance to ask the same questions then or the same 

amount of time. 

 MR. HUGHES: And if, Tommy, you finish 

your presentation early the next presenter is 

going to be Jason Hafemeister and he is on his 

way. And so if he's a little bit late we'll move 

to the break and start when he arrives. 

 MR. WILKINS: So a question, Darrell. 

I wish somebody else would have went first, but 

here we are. Am I supposed to read this? I'm 

just curious what --

 CHAIR CARR: Well, our format is we're 

going to put it up on screen, yes. But maybe 

we're just going to read what has been, the 

recommendation you provided. 

 Again, we're not going to dive into 

discussions on those. That's just going to be 

the current state of where that working group is 

today. 

 Then each one of the working groups 

has at least one technical speaker that will 

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speak to that topic. We will have questions and 

answers of that speaker. 

 And then again, take all your 

thoughts, your comments and go back to your 

working groups tomorrow. So the only thing we're 

doing right now is each committee is just 

basically saying what you said or what you put in 

print. 

 MR. HUGHES: I am asking each 

committee, the subcommittee lead to come up to 

the mic so that those members of the public can 

hear you. The last time you projected and it 

worked well. 

 This time it's difficult for folks in 

the gallery to hear. 

 MR. WILKINS: First of all, I'm Tommy 

Wilkins. And I'm leading the Trade Group. And 

as you've already seen today, this is a very 

emotional, huge topic on the plate today. 

 And I want to applaud everyone on the 

membership of this committee. I believe their 

heart is good and I believe we're here to form 

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some solutions. 

 And so I want to thank everyone on 

there. I think the objective statement is around 

the first lines. We're, the Fruit and Vegetable 

Industry Advisory Committee recognizes the 

importance of trade in today's economy and how 

particularly fruit and vegetable industry. 

 And there are many ramifications to 

exactly how that works. We're getting more and 

more competition every day. We want to protect 

our American industries. 

 And so, you know, our objective is the 

implementation of these recommendations with 

leave not only to increase production and 

consumption of domestic, American fruits and 

vegetables on all farms, fresh, frozen, canned, 

dried and 100 percent used domestically and open 

doors around the world. 

 So we're going to the recommendations. 

The first one that we have is Buy American. 

 We've heard about Canada subsidizing 

or giving tax incentives. I think all of this 

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is, there's many, many things that we need to do. 

But we need to enforce the Buy American 

requirements. 

 How we do that is a subject to, you 

know, our finding that we're subsidizing the 

school, for one instance the school lunch menu 

but then they're buying foreign products. We 

just want to reiterate that we want to buy 

American in as many things as what we're doing. 

 A tremendous amount of information in 

here and I'm not going to read it word for word. 

So our recommendation is that the committee 

supports the Buy American agreement for school 

food purchase enhanced by Section 4207 of the 

Agriculture Improvement Act of 2018. 

 The committee requests that the 

Secretary consider meaningful improvements in the 

guidance for and enforcement of provision and ask 

the Secretary to keep the committee advised of 

his actions. 

 Recommendation revisions include the 

following. Strike the significant cost 

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difference differential language from the Buy 

American exceptions provided the schools by this 

exemption is significantly too ambiguous and does 

not recognize the amount fruit and vegetable 

options that are available should desired first 

choice be cost prohibitive. 

 Require public notice when schools 

elect to purchase foreign source food product 

instead of domestically produced including and 

requiring the schools maintain documentation to 

justify foreign purchase of fruits and vegetables 

over domestic. 

 For instance, whether alternative 

supplier sources were considered, whether bids 

were sought at the best time of the year to allow 

domestic participation, whether substitutions 

were considered. Applesauce instead of peaches, 

pears instead of the mixed fruit, et cetera. 

 Establish financial commercial 

restricted from supplier, penalties for food 

distributors that misrepresent their food 

products or boost with foreign source products 

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for contracted domestic food products. 

 So the next is our trade promotion. 

And our recommendation coming from our committee 

is that this workgroup recommends to the Fruit 

and Vegetable Industry Advisory Committee that 

issued and informed the Secretary of its concerns 

and requests that the Secretary make our position 

known to the President and Congress. 

 The critical importance of ensuring 

that the export market promotion programs 

continue to be made available to U.S. agriculture 

to successfully compete against foreign 

competition in U.S. and export markets and that 

the available funding for the programs be 

increased to offset the imbalance of trade 

restrictions and the impacts of trade deputies. 

 The Trade Group also recommends to the 

Fruit and Vegetable Industry Advisory Committee 

that it should inform the Secretary of its 

interest in developing sustained U.S. grown food 

program that offers additional promotional 

support for helping all agricultural cooperatives 

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compete against foreign competition within the 

United States. 

 The USDA needs to develop trade 

agreements with Mexico, Europe, Peru, Brazil that 

work for U.S. farmers to give ample opportunity 

to survive while ensuring year round supplies. 

The recommendation statement on seasonal 

protection on fruit and vegetable quota on the 

imports of fruits and vegetables. 

 So in the, yes, on the recommendation 

subject was the protecting the USDA grower. The 

USDA needs to develop trade agreements that I 

spoke about in the recommendation with the 

seasonal protection on fruit, vegetable quotas on 

imports on fruit and vegetables. 

 So is there any questions or comments 

about what the Trade Group has looked at? That 

is a quick version. 

 CHAIR CARR: We're going to hold the 

questions and discussion until tomorrow. 

 MR. WILKINS: I was supposed to say 

that. 

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 CHAIR CARR: Yes. 

 MR. HUGHES: All right. So the next 

speaker on the schedule is Jason who has not 

arrived yet. And so we're going to go ahead and 

break early if you want. 

 CHAIR CARR: That is perfectly fine. 

So take a 15 minute break. If not, he could come 

down to the next committee meeting and read that. 

 MR. HUGHES: So we'll take the 15 

minute break and after that if Jason is not here 

we'll move on to Production. 

 CHAIR CARR: So let's be back at 

10:25. 

 (Whereupon, the above-entitled matter 

went off the record at 10:10 a.m. and resumed at 

10:25 a.m.) 

 MR. HAFEMEISTER: Great, thanks for 

having me this morning. Welcome to our visitors, 

so welcome to D.C. 

 My name is Jason Hafemeister. I serve 

as the Secretary of Agriculture counselor on 

trade. I'm originally from California so I'm 

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close to California. 

 Came out to Washington almost 30 years 

ago. I thought I would stay for one year and 

here I am, still here. 

 I've worked in FAS, Foreign 

Agricultural Service over at USTR, the Trade 

Representative's Office in the private sector and 

now serve as the Secretary of Trade Counsel. 

I've been involved in trade policy, trade 

negotiations, market analysis that whole time. 

 So while my roots are in the lettuce 

industry I've worked across all sectors of U.S. 

agriculture in trade policy, trade negotiations. 

 And so what I thought I would provide 

to you is sort of an overview of where our trade 

policy is on agriculture, some of the big issues 

we're facing, some of the hot issues of the day 

just to give you sort of a broad perspective. 

 And then would leave up for you to 

interrupt me if you want to focus in on a 

particular question or issue of concern or we'll 

leave some time at the end where we can have more 

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discussion. 

 But this is meant to be a conceptual, 

broad based overview and I can try to handle 

whatever specifics you guys have the best I can 

when we get to that. So I think what I'll sort 

of focus on is my remarks first on the agenda how 

trade is important to agriculture. 

 And agriculture is important to trade. 

Second, a little bit about the ongoing trade 

issues we have right now. You know, China, 

Japan, and Europe, USMCA so this sort of update, 

put those in perspective. 

 And then talk a little bit about 

things we're doing to find more customers 

overseas for our farmers. But to step back, I 

think one way to think about the current moment 

we have is how are we organizing trade globally 

because we've got farmers all over the planet who 

want to grow. 

 Many of them are surplus producers. 

Many of them are fine customers in other 

countries. How are we going to organize this 

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trade so producers and consumers can most 

efficiently and fairly get to business? 

 And so that's, I think, sort of the 

underlying theme that's behind a lot of these 

specifics. And I'll talk about that as we go 

through it. 

 So next slide please. So first of all 

just to talk a little bit of why our culture is 

so focused on trade. What this chart here shows 

is the source of gross cash receipts and where do 

our farmers get their money, right? 

 Most of it comes from the market. If 

it's in crops, if it's in livestock. This comes 

from the sales price and the volume that they 

sell. 

 And so we -- and you'll see in the 

report about having a strong producer economy, 

strong rural America, we are very interested in 

ways to strengthen income for farmers. 

 And so really the most effective way 

to do that is to help them get a better price 

when they're selling in the market. Payments are 

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important. 

 The last few years, even more 

important but they are not the difference makers. 

It's the market income that our farmers make that 

matters. 

 And so when we think of having to help 

our farms get better prices one of the best ways 

to do that is to help them access more customers, 

to expand demand, to increase the amount of 

people who are interested in buying their 

product. 

 And so that's why we're so focused on 

trade. Next slide. So the process, U.S. 

agriculture generally we are very competitive 

producers. Nearly all sectors of U.S. 

agriculture are exporters. 

 That is, we're looking for customers 

overseas. And in most of these cases, nearly all 

cases we export more than we import which is a 

sign of our competitiveness, we can out compete 

other groups. 

 And even in certain areas where we are 

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net importers, where our imports are greater than 

our exports, there's a lot of, there are other 

factors that frequently relate to that. So we 

import a lot of fancy wine in this country. 

 We make great wine too. But there is 

just great demand for fancy wine. We import 

stinky cheese. We're massive dairy producers. 

We export a lot of dairy products. 

 But people like French cheese and that 

stuff. We import a lot of tropical products, 

things that we don't produce here, pineapples and 

coconuts and coffee. 

 And some of that competes, you know, 

sugar we're producers. Of course, there's 

counter-seasonal trade so that in the winter we 

import a lot of fruits and vegetables. 

 So one of the conclusions I thought 

this slide illustrates is that one of the reasons 

we hear so much from our farmers about trade is 

because we are not only trade importers for farm 

income, but we're competitive producers. 

 This agriculture is looking for 

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opportunities to compete and perform. Next 

slide, please. And another illustration of that 

is how for certain of our sectors exports are a 

very large share of where the crop goes. 

 You know, half of our wheat, half of 

our soy beans, half of our rice is exported. 

Around 80 percent of our tree nuts are exported. 

You know, 20, 30 percent of many fruits and 

vegetables, dairy products, meat products they're 

found, customers are found overseas. 

 And so losing those markets is a real, 

it's really a problem for us and we're finding 

that now out now because with China we're losing 

a big market that a lot of times we don't have 

alternative places for that product to go. 

 It sits on the domestic market, drives 

down the price, that drives down farm income. So 

really we have organized in many ways our 

agriculture around the fact that we're 

competitive surplus producers and we need to find 

customers overseas. 

 Next slide. Now, I would like to 

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remind people that in terms of policy, what can 

we do to help farm income, what can we do to help 

producers? I'm very interested in things we can 

do to help make better customers. 

 How can we have more, how can we help 

people in other countries increase their 

consumption of agricultural products because we 

stand to benefit? 

 What this chart here shows is what 

happens with a marginal dollar, what a consumer 

does with it. So you get me here USA, you give 

me an extra dollar, what am I going to spend it 

on? 

 Well ten percent of it will go to 

food. But the rest of it I'll waste on things 

like education, housing and transportation and 

all this. 

 You give someone in the Democratic 

Republic of Congo an extra dollar and they'll 

spend more than half of it on food. And so 

that's a great thing. 

 Obviously we want people to have 

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better lives, to be eating more if they need 

more. But we in agriculture, we are 

beneficiaries of that. That increases demand for 

our products. 

 This helps supply new customers, helps 

bid out the prices we get. So underlying our 

policies really has to be how do we activate 

these 95 percent of the world's customers who are 

outside of our borders to make them more 

effective purchasers of our crops? 

 Next slide, please. So one way to 

think about all this is how we organize trade. 

We'll get to the policy here. 

 And in my mind, the way to think about 

it is, so we had this really amazing change in 

the world population and economy 75, 80 years ago 

coming out of the World War II period. 

 Well if you look back on human history 

you can quote Thomas Hobbes, I think his name is, 

that most people lead lives that are short, 

difficult and painful or something like that. 

And that's the history of most humans, right. 

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 And what this chart here shows, the 

red area is the number of people who live below 

the poverty line, who live in extreme poverty. 

And for most of history that's everybody. 

 Most everybody is living in extreme 

poverty. And it's very interesting to see here 

is the Industrial Revolution starts and all of a 

sudden you start having more people leading more 

comfortable lives. 

 But then here we come coming out of 

World War II the whole narrative of humankind has 

flipped. Now, we have less people living in 

extreme poverty than ever before and we have all 

of these people here who are living outside of 

poverty now. 

 So it's a great story of 

accomplishment. Lives are better than they have 

ever been and why has that been. I think a big 

part of it has been the post-World War II 

economic system that we set up which was founded 

in security. 

 We have NATO. We have the United 

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States guaranteeing the peace. It was bounded in 

open markets. 

 So we set up the GATT within the WTO 

which said we were going to allow people to trade 

with each other more freely and that will 

encourage people to invest and innovate and 

develop new technologies and increase their 

production because they will have customers. 

 And so coming out of that we've got 

this amazing boom of the economy and lifestyles. 

And we as farmers have been the beneficiary 

because we chart against that. 

 Here's U.S. ag exports, right. As we 

have more people living longer with more money in 

their pockets they're consuming more of our 

agricultural products. 

 So it's a story of people doing good, 

lives are better and farmers are doing well when 

that happens. So I think that's really 

fundamental to me when we talk about how we want 

to organize trade. 

 Next slide. So one indicator of this 

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has been tariffs and taxes that go on imported 

products. So over time if you go back here to 

the GATT in 1945 and then the WTO formed here, 

NAFTA comes in here we've generally seen trade 

become more free. 

 And the reduction means that tariffs 

is an indicator of that. That's a sign of our 

success. Tariffs have been coming down and 

that's helped foster this economic growth. 

 So next slide. As we look forward to 

customers, you know, we still see a lot of 

potential for gains overseas. 

 It's interesting, this data point, 

September of 2018, that's when we flipped over 

from having more people who were poor or 

vulnerable on the planet to now there's more 

people who live in middle class or rich economic 

situations, right. 

 And the next slide shows that we 

expect that trend. So we see growing middle 

class or growing wealth globally which means more 

market opportunities for us. 

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 So as surplus producers, as people who 

are competitive producers who are looking for 

customers, there's a lot of opportunity. All 

right, next slide. 

 So now we're coming back to some of 

the more current issues. So this shows total 

U.S. agricultural exports and billions of dollars 

for our top five markets. 

 You know, the top six markets that we 

sell to U.S. agricultural exports account for 

about 60 percent of total ag exports, right. So 

one of the lessons for us is don't screw it up 

with the big markets because they're important. 

They're large. 

 And the good news is that for four of 

the five despite all of the trade conflict and 

the uncertainty we are holding together pretty 

well. We've increased actually sales to Canada. 

 Mexico, Japan and the EU in fact has 

gone up slightly as well. So that is despite all 

the threats about trade wars, those markets are 

holding. 

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 Obviously, China is a different story. 

That's where the trade war is hot and heavy and 

we've seen the effect on our sales. 

 But one point is that these big 

markets matter a lot to us. We spend a lot of 

time, how can we keep what we have or try and 

grow them. 

 Next slide. So go back, sorry. I 

skipped a slide. The other thing when we talk 

about markets is that as important as those big 

markets are we have what you would call a long 

tail distribution if you look at our sales. 

 We sell a lot to these big countries. 

But we sell to over 100 countries locally, all 

right. There's over 30 markets that we sell a 

billion dollars or more to. 

 And so there's a lot of money to be 

made in the Philippines and Indonesia, in 

Vietnam, in Columbia, in, you know, Morocco. So 

by themselves they don't get up here in these big 

double digit ten, 15, 20 billion dollar markets. 

 But that's where we have a lot of 

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sales and that's where we see a lot of growth. 

So as we organize our thinking we want to protect 

and grow these big markets. 

 But it's the rest of the markets out 

there that matter a lot to us. And how can we do 

markets in the rest of those countries? 

 Well, we need a predictable, open, 

market based, rules oriented environment where 

we're not relying on government intervention, 

trade wars or threats of trade wars to solve our 

problems. 

 We want predictability and certainty 

in our ability to make sales happen. Okay, next 

slide. 

 So let's go here. So let's talk a 

little bit about some of the headwinds that we're 

facing in terms of restrictions on U.S. ag 

exports. 

 This chart here shows how U.S. 

products have been affected by retaliatory 

tariffs by other countries. All right. So 

because of the steel tariffs we put on other 

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countries many of them have retaliated. 

 And because of the China tariffs, the 

IPR related tariffs we've seen retaliation from 

China. So what this shows is China is now about 

there, so over $100 billion of U.S. ag products. 

 Twenty-two percent of those tariffs 

hit agriculture. Basically all the agriculture 

we send there, $20 billion is being faced with 

tariffs, $79 billion of non-ag exports are being 

hit by tariffs. 

 Well, when we had the Mexico tariffs 

in place for steel they targeted agriculture. 

Seventy-two percent of the tariffs they put on ag 

products. 

 Canada hit ag somewhat, but they've 

gone. China has tariffs in place on steel and 

targeted ag. So this goes through some of the 

restrictions that we're facing. 

 Higher tariffs as a consequence of 

these trade actions and how other countries are 

choosing to target agriculture. Next slide. 

 So this is just a reminder, steel 

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tariffs are still in place. We removed them with 

Canada and Mexico. But EU, India, China are 

still imposing retaliatory duties on U.S. 

products. 

 And I think one important thing here 

as we talk about steel, what this chart shows is 

going back ten, 15, 13 years relative prices of 

steel. U.S. is the blue, all right. Red is 

China, green is Europe. 

 So the U.S. has always been a high 

cost steel producer, right. For various reasons, 

we're relatively high cost producers. So our 

prices have generally been higher than world 

prices. 

 We maintain those prices because there 

are anti-dumping and countervailing duties in 

effect on some of our biggest competitors, China 

for example. So there's very little steel in the 

United States even before all this trade war 

because we had anti-dumping and duties on them. 

 So that has helped keep U.S. prices 

relatively high. But then with the trade 

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actions, the 232 tariffs we saw a spike in U.S. 

steel prices because we were restricting supply. 

 So that is starting to come back down 

now. And as the economy slows people are 

figuring ways to work around it. We are seeing 

some greater U.S. production of steel as well, as 

you would expect, the more money you can make the 

more production. 

 So the steel has been in effect for 

U.S. agriculture and really behind it has been 

this question of how do we keep U.S. prices high? 

Next slide. 

 So this is one of the effects when we 

try and talk about, well, how do we see the 

effect of the trade war? So here's U.S. steel 

prices again in blue. They went up. Now they're 

modulating. One of the effects is that things 

made with steel have gotten more expensive. And 

then one of the effects is then not related to 

steel but more to the IPR, which means prices for 

U.S. commodities like soy beans are targeted and 

fall. So there's a relationship here between our 

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higher tariffs and what some other countries are 

doing. Next slide. 

 So we are -- the big story on the 

retaliation has been China. So you can see 

across all of the products that we export who is 

bearing the biggest brunt. So this was last 

year's data. And you can see China is hitting 

everything sort of blue. But we do see some 

pretty important effects from Mexico, Canada and 

Europe as well, and now India is coming in. So 

we've taken off Canada and Mexico, 232. So 

that's good news. But the rest of these are 

still in effect. 

 So next slide. So one thing to keep 

an eye on is that we're looking at a similar 232 

action on automobiles. The Department of Commerce 

has submitted a report to the President saying --

evaluating the national security implications of 

imported automobiles to U.S. national security. 

 And the President is weighing whether 

or not to take action like we did with the steel 

and aluminum to impose tariffs. And so that's --

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I think he got a report in May, and he said he 

would decide in six months. So November this will 

be a really big trade thing. 

 What this chart here shows is U.S. 

automobile production in blue. And then U.S. 

automobile employees in automobile production, so 

people making vehicles and parts. And so you see 

the recession is here. There's a big effect. 

People stop buying cars when the economy is in 

recession. But you see that we bounce back over 

time. But you also see that and what's really 

striking here is the efficiency that we see in 

automobile production. It takes a lot less 

workers now to produce more output volumes than 

ever before. And of course that's part of the 

story here, right, is the manufacturing jobs. 

There are jobs that support middle class 

families. 

 There are less of them in automobiles 

than there were before. Now a lot of that has to 

do with productivity, right? We are more 

automated than ever before. We are more 

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productive than ever before. But some of it has 

to do with import competition as well. So I 

think, I would just start to say that this, I 

think, is one of the big factors behind that, the 

broader issue. 

 Next slide. Same idea, next slide. 

So what this chart here shows is our top six 

markets here. Remember, here's our top six 

markets. Remember, they account for 60 percent 

of our ag exports. 

 And so Korea is 6 percent, Canada is 

15 percent, billions of dollars. They account 

for $83 billion for a total of $140 billion in ag 

exports. They are also our top six suppliers of 

automobiles, right. So Canada our biggest market 

last year was our fourth biggest supplier. They 

accounted for 16 percent of auto imports of $53 

billion. So we import $332 billion of automobiles 

and parts and export to those same six countries 

$83 billion. So as we move forward if there is 

some negotiation or some trade issues with these 

countries, there certainly is an expectation 

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given the way the countries have targeted ag in 

the past that agriculture might be caught in the 

middle of the fighters. 

 So I think the good news is Canada and 

Mexico have already negotiated a sort of get out 

of jail free card. They have negotiated quotas 

that are substantial. So even if we do impose 

new tariffs on autos, presumably they've already 

got a safe harbor. So that's good. 

 We're negotiating right now with 

Japan, where certainly their desire to keep the 

market open for automobiles is a priority. So if 

we get a negotiation done with Japan, hopefully 

that will avoid any sort of trade conflict there. 

 China, of course, we're in the middle 

of a giant negotiation. I'm not sure how this 

will change that. We're already putting tariffs 

on their products. They're already putting 

tariffs on ours. 

 Korea has already in the first year of 

the Administration in 2017, reached a trade 

agreement with the U.S. that had auto provisions. 

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So they might be able to argue that they don't --

they shouldn't be subject to any further auto 

actions. 

 And then the EU is probably in some 

ways most exposed in that they are a big exporter 

to us. We are supposed to be talking about a 

trade negotiation, but right now it's hard for 

that to get traction. 

 So auto is the big thing for us, 

because we have big trade actions. There could be 

some spillover on agriculture. 

 Okay, let's turn to the next issue 

USMCA. You may have heard of NAFTA. The 

President has called it the U.S. Mexico Canada 

Free Trade Agreement. I'm trying to brand it as 

USMCA. USMCA, say it softly. Say it to 

yourself, USMCA. 

 So I put this chart up here because it 

shows how and I came to Washington in 1991 right 

when NAFTA was being negotiated, and it was being 

passed, Ross Perot, the giant sucking sound and 

all that stuff. 

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 So NAFTA has like really been 

controversial ever since I've been paying 

attention to it, and this chart shows that. Here 

the question is: overall do you think NAFTA is 

good or bad for the U.S. economy? 

 And so this was kind of underwater 

like 40 people saying, yes, we think NAFTA is 

good. And then it's really interesting to see 

what's happened in the last five or six or seven 

years. All of a sudden, NAFTA got really popular, 

right. And so part of it has to do with the 

recession and then the recovery. People are 

usually more pro-trade when the economy is doing 

better. 

 Part of it, I don't know, part of that 

had to do with the 2016 election. I think a 

number of these Democrats now are saying they 

support trade just to stick it to the man. I 

don't know if they're really reliable trade 

supporters. But if Trump is against it, they are 

for it. 

 But anyway, NAFTA has never been more 

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popular, right? And so right now we have before 

Congress USMCA, which has gotten most of the old 

NAFTA in it with a few adjustments. And so it's a 

big priority for us to get that thing approved by 

Congress. You saw earlier Canada and Mexico are 

our top two markets now that China has fallen, so 

for ag products. So we want to have the ability 

to keep those markets open. Certainty for those 

customers is important to us. And so passing 

USMCA, taking the threat of losing NAFTA off the 

table, is a really big deal. 

 Next slide. Just one way to 

illustrate that, this shows Mexican imports of ag 

products and what the U.S. share is, all right. 

So Mexico imports over $1 billion of wheat every 

year; 57 percent of that comes from the U.S., 

right? A lot of the rest comes from Canada, the 

other NAFTA partner. They import $2 billion of 

soy beans; 94 percent come from the U.S. They 

import $1 billion of poultry and 79 percent. 

 So Mexico is a great market for us. 

It's not surprising. It's right next door. 

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We've got close economic ties, business ties. 

There's no tariffs between us. And there's to 

some degree a lot of complementarity. You know, 

we are land extensive producers. They are less 

available land, more labor intense producers. We 

send to them a lot of our row crops, a lot of 

livestock. They send a lot of tropical products 

and fruits and vegetables to us, and we sell 

counter seasonal trade both ways. 

 So it's a really big thing for us to 

launch that. So that's why getting USMCA through 

Congress is one of top priorities. Next slide. 

 Same idea, next slide. You know, one 

way to think about it is the Farm Foundation did, 

they hired Commerce to say: what are the benefits 

of USMCA? 

 And they said well if we pass USMCA, 

we'll have some more exports. We'll grow because 

we've got some more dairy access out of Canada, 

basically is what that shows. So there's some 

small positive. But what happens if we don't 

have USMCA? What if we pull out of NAFTA? Then 

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we're going to see our exports revenue fall by $2 

billion. 

 So I think this illustrates there's 

some positive things about USMCA. But really 

it's this negative consequence that we really 

want to avoid. 

 Okay, next slide. So let's talk a 

little bit about China now. So this is how I 

think about China. You go back 20 years ago and 

you look at China and India, and they would look 

very similar to you, right. 

 They are developing countries, a 

billion people, large land mass, very selfsufficient in agriculture production. Their 

borders were closed. They didn't import much. 

They didn't export a whole lot, right. So that 

was 20 years ago. Then China joined the WTO in 

2001. They lowered a number of their tariffs. 

They made a number of other economic policy 

changes. I think they decided to embrace 

comparative advantage. They said, look, we are 

going to be exporters of manufactured products, 

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and we're going to recognize that we've got 

limits on the productivity of our agriculture 

products. 

 And then the difference here is what 

the red area shows is India's trade balance with 

the world. India, despite having a billion 

people, despite having huge challenges in terms 

of available land and available water and low 

productivity, is a net exporter of food products 

in the world. They're the top sugar exporter. 

They're the top wheat exporter. They're the top 

beef exporter, a big rice exporter. Whereas 

China is a huge net importer of food products of 

the world, right. 

 And so to me this is a case of India 

joined WTO in 1948, and they locked in high 

levels of protection. The average allowed tariff 

on agricultural products in India is 113 percent. 

 For some products it's up to 300 

percent. China's average allowed tariff is like 

15 percent. And so not only are the tariffs low, 

but it just shows the policy of China has allowed 

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more imports, right. They're following a 

different path. And it's of course been a big 

deal for us in agriculture. China is such a big 

market for us. 

 So next slide, getting back to how 

making the world a better place can be to our 

benefit, this shows over time the economic growth 

in China, the number of people who live above $10 

a day is now 80 percent, I'm sorry, 25 percent of 

Chinese people. The number of people who live 

between $3 and $10 a day is the vast majority. 

The number of people below $1.25 has gone from 

more than half to just a sliver, all right. 

 So China has jumped on economic 

development. That has improved their living 

conditions. Next slide, real GDP. Next slide is 

child mortality. Children are surviving better. 

And we are beneficiaries because they are eating 

more, they're importing more. And so when we or 

U.S. markets' ability to sell, this is really 

about China. 

 There was a story about some English 

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textile manufacturer in the late 1800s who said, 

you know, if you just add an extra inch to every 

Chinaman's shirttail, we'll all be rich. And I 

get a sense that's kind of how we look at China 

now. If every Chinese person ate another apple. 

If every Chinese person had an extra slice of 

bread, just imagine. So we look at China that 

way a lot. 

 Next slide. So this shows the index, 

right. See how the trade war has not affected 

our industrial exports as much as China. Like 

what does China import from us from industrial 

products? They import a lot of inputs. Like they 

import a ton of semiconductors. They import a 

lot of things that they put into machines that 

they then export somewhere else. So they have 

been careful not to shut off that trade. What 

they have shut off is the ag trade, right. They 

have found other suppliers for agriculture. 

 So the decline of U.S. exports to 

China has really been mostly felt on the ag. 

Next slide. So here is our total exports of ag 

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products to China over time. You know, big grain 

price spiked, pushed this up and modulated and 

then started here with the trade actions. Next 

slide. This shows for different products our 10 

year high. You always think that's normal, and 

we should even be growing it. That's the 10 year 

high. This was last year, 2018. 

 So for individual sectors, here's soy 

beans, celebrated soy beans, they need their own 

index over here. It's so much bigger than 

everything else. So this is how this was felt on 

an individual product. Next slide. Okay, so go 

back, sorry. So with China, it's hard to keep up 

with this because things happen from day to day 

to day. You know, yesterday the President made 

an announcement about delaying some tariffs. So 

this thing is a very dynamic situation. 

 You know, what we've done on the ag 

side is we said look, we're very concerned about 

bad policy in China. China's failure to protect 

intellectual property, China's forcing technology 

transfer. Chinese protectionism generally is 

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bad. It's not only unfair to U.S. companies who 

want to do business in China, but it's 

constraining economic growth in China. And we 

think if China had a more open economy, if they 

had a more rules-based economy Chinese economic 

growth would be better, and we would have better 

access to those customers because there wouldn't 

be those barriers, and we would have richer 

customers in China. So do us a favor, China, make 

the reforms to become a more modern trading 

partner. So that's what we want. 

 On the other end of this trading 

conflict with China right now is that if we see a 

more open Chinese market, it's going to be great 

news for us because we'll have better access to 

customers who will have more money to spend. But 

in the interim, obviously there's a lot of 

conflict going on right now. And agriculture is 

caught in the middle of it. So our objective is 

then let's use this negotiation to solve some 

discreet problems we have in agriculture. 

 China right now bans the import of 

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U.S. poultry. There's no reason for that. China 

right now bans the import of beef that's been 

treated with hormones. There's no reason for 

that. You know, China right now has got a whole 

bunch of restrictions that we would like to fix. 

So we're trying to get that stuff on the table in 

this negotiation. But of course, getting the 

tariffs off and going back to normal but in a 

better environment for China we think is going to 

be better for us. But we're right in the middle 

of all that. 

 Okay, next slide. So this is Japan, 

right. So Japan is one of our top markets. It's 

a very good market for us in ag products. It's a 

high value market, a high price market. And for a 

number of commodities it's like one of our top 

markets. What's interesting is we sell lots in 

Japan despite facing really high tariffs. 

 Japan is a country that is interested 

in protecting its agricultural sector and uses 

tariffs as a way to limit competition. So 

despite relatively high tariffs, it's one of our 

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top markets and really important for a range of 

products. 

 Next slide. So we had a problem in 

Japan that is when negotiating trade agreements 

with other countries in which it was lowering the 

tariffs that it will impose on our competitors, 

right. 

 So here's a great one. Right, $2 

billion market for us. We pay a 38.5 percent 

tariff. In fact, it can be as high as 50 percent 

because the surge of imports Japan can snap that 

tariff up. They have committed under the CPTPP, 

the Trans-Pacific Partnership, to lower the 

tariff on beef down to 9 percent. It's our 

biggest market for beef, and now we run the risk 

that Australia and New Zealand, Canada, Europe 

they will grow in the face of this lower tariff, 

right. So this is a problem across the board. 

 We want a trade agreement with China 

because less tariffs mean we'll compete better 

with Japanese product. Less tariffs mean we'll 

compete better with third countries. 

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 Next slide. What this shows is just 

sort of nuts and bolts. So under WTO 

commitments, Japan said we promise never to 

charge more than 50 percent on imported beef, 50 

percent, right. Day to day they charge 38.5 

because they don't want to tax their consumers 

too heavily because they're big beef importers. 

So that's what we pay, 38.5. This purple on here 

shows the Free Trade Agreement Australia 

negotiated, where the tariff on Australian beef 

would go down to 28 immediately and then slowly 

over time fall beneath 20 percent. 

 So we're at 38.5 tariff, they're at 20 

percent tariff. So we went into the TPP saying 

we're going to not only get rid of this 

discrimination in Australia, but we're going to 

do better than that. So the TPP deal brings that 

tariff down to 9 percent. So as long as we're 

outside the TPP, as long as we don't have a trade 

agreement with Japan, we face Canada, Chile, 

Mexico, New Zealand, Australia, this 9 percent 

tariff, we're at 38.5. So we've got to get a 

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deal, we hope, that will bring us down. So you 

can see that across the board that's the tariff. 

All right. So this is a very prescient 

negotiation. 

 You know, part of the leverage from 

this is the 232 action on automobiles, which is 

hanging out there. So there's a lot of pressure 

particularly to get an agricultural deliverable, 

to get at least an agriculture deal in the short 

term even if it's not a full blown free trade 

agreement across every single product. 

 So big priority for us to make sure 

that comes about. Okay, next one. So there's a 

lot of talk about EU. One of our top markets. 

 It's a frustrating market for me to 

look at as an economist. I don't see the -- you 

know, Europeans are good farmers. They make a 

good product. But it's not a lot better than 

ours. But somehow we are importing a lot more 

European products than we are exporting to 

Europe, right. So we have this trade deficit 

which, you know, in some cases it makes sense. It 

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makes sense for us to have a trade deficit with 

New Zealand. There's nobody in New Zealand to 

buy our product, and they're good producers. 

 I don't know why we have a trade 

deficit in Europe. So that's frustrating. And 

the reason, of course, is there's a lot of trade 

barriers -- high tariffs, unjustified health and 

safety measures, and just a lot of restrictions. 

Next slide. So you look at what we sell to 

Europe. We sell quite a bit of soy beans, $2 

billion a year, quite a bit of almonds. But the 

rest of the stuff, not a ton, right. 

 And my concern is that Europe needs 

our soy beans because they need protein, so they 

found a way to let our product in. And they need 

our almonds, because how can you have a proper 

almond croissant without an almond? But this 

other stuff, you know, they are not really 

interested in the competition. So they haven't, 

you know, may not be direct protectionism. 

Sometimes it is, but they're not facilitating. 

 So this is our objective. And it's 

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tricky because there's a tariff element to it, 

would have higher tariffs on us. But also 

there's just the regulatory environment which is 

very difficult for us to deal with because of the 

way that we produce products. 

 The next chart just shows what we 

import from the EU. Again, there's fancy wine. 

You know, a lot of sort of consumer-oriented 

products, a lot of cheese. And so we do take in 

a lot of products from Europe. All right. So 

those are sort of the big countries that we're 

working on trade issues right now, trade policy 

issues. 

 The next slide just to me sort of 

wraps it up as to why we focus so much on trade 

policy on trade negotiations, and why I think 

it's so important to agriculture. What this chart 

here shows is all of these countries that we've 

had trade agreements with, free trade agreements 

plus China joined the WTO, cases where we've had 

a chance to sit down with other countries and 

negotiate: are you going to reduce your tariffs, 

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or are you going to reduce your barriers? 

 So in each of these cases, you'll see 

the U.S. export, the average exports for the five 

years before we had the deal is much less than 

the five year average after we had the deal. And 

that's not surprising because when we do a trade 

agreement, countries agree to reduce their 

barriers to our products. We are competitive 

producers. So in a free trade environment, we 

are going to do well. And in addition, what 

trade agreements do is they increase the overall 

economic growth in these countries. Remember, 

trade agreements are pro-competitive. They're 

encouraging more play at market forces in these 

economies and it's fostering economic growth. 

 So we have better access to more 

wealthy customers. It's not a surprise that we 

sell more once we do trade agreements. And so 

for us, focused on finding customers, that's why 

we're so interested. 

 So next chart. So when we talk about 

where we want to see further opportunities, where 

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there's going to be more customers, it's really 

in Asia. This is where we have growing 

populations, we have growing economies, we have 

real resource constraints on their ability to 

competitively bring us ag products. We have a 

lot of differentiation in what we produce. 

 Many of these are tropical countries. 

We are a temperate country. And so these are the 

kinds of things that as we go forward that if we 

can reduce barriers, improve the environment, 

this is where we'll really be able to move the 

needle. So then the country here is our exports 

in 2017, and the U.S. market share of 

agricultural products in that region. So we sold 

1.6 billion to India, but we're only 6 percent of 

the import share. 

 So there's lots of room to grow there. 

And with Japan, a little bit better, we sold them 

11.9. We have 25 percent market share. That's 

why we don't want to lose this as other countries 

face lower tariffs; we've got to at least keep 

that. 

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 Okay. So that's that. Why don't I 

just stop there and see if there's some questions 

or comments. 

 MR. SMITH: One of the things that 

affects the processing industry is the canned 

steel imports on canned products. For example, 

our canning costs, the tariff on that is 25 

percent, but yet China can import to us with no 

tariff on their can. 

 MR. ZEA: Yes, steel faces the tariff. 

 MR. SMITH: But their can does not face 

the tariff. And so I just wanted to bring that 

up that's remains a really critical point to the 

processing industry. 

 MR. HAFEMEISTER: Yes, I'm fully aware 

of that, yes. 

 MR. SMITH: And we've met before. 

 MR. HAFEMEISTER: Yes, I appreciate 

that. 

 MR. WILKINS: Where do you see U.S. 

with USMCA? 

 MR. HAFEMEISTER: Thank you for that. 

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You know, I don't have any special knowledge. I 

mean my, the biggest insight I have is I'm really 

impressed with the Administration and the 

Congressional House leadership and their message, 

discipline on this. 

 You know, whenever you hear the 

Speaker of the House or other senior leaders in 

the Democratic Party talking about the trade 

agreement, it's always very positive. It's like 

we want to find a way to get it done. We're 

working closely with the Administration. And we 

think there is a path to do this. We think it 

will happen by the end of the year. 

 And then on the Administration side, 

it's very much we're working closely with the 

Speaker. We think we have a good process. So 

everyone is being optimistic, optimistic, 

optimistic. So you know, it's a real problem 

when you start seeing the finger pointing and the 

egg throwing, right. And so we're not there. 

And so you know, the conventionalism, I agree 

with, which is why votes are there in the House. 

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If you sent that up today, we would get that 

thing across. So it's really a question I think 

of, you know, how and when the Speaker feels like 

she's got the terms she needs for whatever 

internal dynamics she's working to be able to 

bring it across. And, you know, we had a summer 

deadline. That's slipping, but there is by all 

accounts serious engagement. So I'm certainly 

hopeful that we can get it done this year. 

 MR. WILKINS: Do you have any insight 

on what she is looking for? 

 MR. HAFEMEISTER: No, I don't. They 

talked about these four areas where the House 

leadership has set up working groups: labor, 

environment, pharmaceuticals and dispute 

settlement, right. 

 And so labor and environment is a 

longstanding issue in Washington in terms of 

trade politics. You know, how do we get other 

countries to make commitments on labor and 

environment standards, and how do we use a trade 

agreement to enforce them? 

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 So letting people know the outlines of 

how to negotiate that. Pharmaceuticals, there's 

this question of -- it's a little trickier. I'm 

not an expert on it. 

 You know, on the one hand are we by 

giving longer patent protection to U.S. 

pharmaceutical companies, are we impairing our 

ability to have those pharmaceuticals in this 

country, or can we somehow foster trade in 

pharmaceuticals to Mexico and Canada to help 

lower our prices? 

 So that's -- I think that's 

complicated, and for me it's complicated. And 

the last one is on dispute settlement right, 

which is this question of: we do a trade 

agreement, and is it going to be binding? Is it 

going to be enforceable? And the problem within 

NAFTA was that any individual country could say 

once they're in a dispute where we say hey, 

Mexico, those anti-dumping duties on high 

fructose corn syrup, they're unjustified. 

There's no reason for that. You do not find 

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unfairly traded product. We're going to sue you. 

Mexico would have the ability to say, you know, 

we're just going to pull the plug on that 

process. We're going to block the expert panel 

from meeting. 

 So do we want to strengthen that by 

saying, no, just because it's inconvenient for 

you doesn't mean you can avoid a lawsuit here, or 

are we going to try and find some other way to 

enforce these commitments? 

 And so that's where, you know, the 

politics is. If we're going to get labor and 

environment commitments, how enforceable are 

those going to be inside an agreement, and how 

strong is that mechanism going to be? 

 So the good news is it's discreet. 

It's four specific issues where experts are 

sitting down and talking. So that's a sign of 

progress. 

 MR. ERICKSON: Question, on Slide 16 

this triggered a question I've had for some time 

and you happened to present a slide there that 

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reminded me. January 11, 2018, imports of steel 

declared a national security threat. Do you know 

if, are there triggers -- are there actual 

triggers in place and data that is utilized to 

determine that something has become a national 

threat, or is it an arbitrary decision? 

 And following that, what are your 

thoughts on when you look at the growing U.S. 

population and the volume of product that is --

of food that is imported to the United States 

versus what is produced in the United States, 

there's a growing gap. 

 Does in your estimation, a threshold 

exist there where at some point somebody may say 

this is really concerning, this is approaching 

national security threat levels? 

 MR. HAFEMEISTER: Yes. So it's 

interesting. This law, Section 232 of the Trade 

Act, is very general. 

 It says should the President determine 

after having consultation from, you know, the --

including the input from the Secretary of Defense 

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that there is a national security threat, he may 

take action including tariffs to restrict 

imports. And it doesn't enumerate specific 

triggers or standards for what that is. So 

there's legislation right now. Congress is 

saying we gave President Obama a lot of power 

here, and maybe we need to define it better. So 

there's some effort in Congress to do that. But 

in the interim, this is authority that the 

President has. 

 In the case of steel, the metric that 

the Commerce Department developed was that they 

said, you know, we need to have a strong steel 

industry to have a strong national defense. 

We've got to have access to U.S. steel. And how 

are we going to determine what's a strong steel 

industry? They said, well it's going to be based 

on capacity and utilization. They said it was 80 

percent. If we can get capacity and utilization, 

all of our steel plants working up to 80 percent, 

then that's an indicator there is a strong, 

healthy steel industry. 

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 So let's put tariffs in place which 

will encourage domestic producers to ramp up 

production because they will compete better 

against imports until we can get back to this 

threshold of capacity utilization. 

 So that's the logic behind it. We 

don't know the auto logic. That one is still 

being closely held. But the President has to 

make a determination based on some fact patterns, 

but there's quite a bit of discretion behind it. 

 So that's the first part of your 

question. The second part was, you know, is 

imports as a share of consumption and production, 

as that grows what that does that mean? So let's 

go back a couple slides here, one more. So we've 

talked a lot about trade deficits. This is 

related to what you're saying. Since I have a 

slide, that's what I'm going to talk about even 

if it's not your question. So we've talked a lot 

about trade deficits. So what this chart here 

shows is our trade deficit is in red, right. 

2002 was almost $500 billion. Now, we're around 

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here around $800 billion in terms of a trade 

deficit with goods, not staking out services, 

right. This is just goods, merchandise trade. 

 But what I find interesting is look at 

where our trade in oil and gas has been. So it 

used to be that oil and gas imports, our deficit, 

we were importing so much petroleum, Saudi 

Arabia, Mexico, Venezuela, Canada and all these 

countries sell us oil because we're big oil 

consumers in the U.S. Half of our trade deficit 

was because of our oil and gas deficits. All 

right, so that's 2011. Well, what's happened 

since then and today is the fracking boom, right. 

Now, we're like producing more oil and gas than 

we ever have. Look what happened to the oil and 

gas trade deficit. It's disappearing. There is 

some talk that we might be a net exporter of 

natural gas and petroleum in the near future 

because we're cranking so much out through 

fracking. 

 So we think that well gosh, if the 

major component of our trade deficit is oil and 

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gas, and we're no longer importing so much oil 

and gas that would help our trade balance. Look 

what happened to the trade balance. Right, it 

didn't move much. So to me the point is these 

trade balances are factors of macroeconomic 

forces, right. 

 The United States is a great economy. 

It's the best economy in the world. We suck in 

investment like nowhere else, right. Countries 

come to the United States to invest. They bring 

foreign currency here and they say, my gosh can I 

buy some land, can I buy some plants, can I buy 

some stocks. We are a profligate people. We have 

huge debt, next slide. We run a huge budget 

deficit, right. Here's our deficit -- budget 

deficit. 

 So we're always putting out T-Bills. 

Oh my gosh, someone has got to finance the budget 

deficit. How do you pay for that? China, these 

Europeans, Japanese they bring their foreign 

currency over here and they buy T-bills, right. 

 So we're a wash with foreign currency. 

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And we're rich. Oh my gosh, we're rich. So what 

do we do with all of that? We don't save it. You 

know personal savings rates in this country are 

small, small, small. We consume. We buy stuff, 

right. We're champion consumers. And so that --

let's go back to trade deficit. So that's what 

drives this trade deficit. It's the strength of 

the U.S. economy, the strength of the dollar. 

It's our savings habits, our consumption. Now the 

only time this deficit shrinks is when we have a 

recession, then we're not buying as much. 

 And so you can see this with China, 

right. We are restricting Chinese exports, but 

we're buying from Vietnam instead, right, because 

we are consumers. We want this stuff. Now there 

are certain factors, you know, certain sectors 

where supply will be shortened and there is some, 

you know, increased production in the U.S. But 

these factors I think are really, really much 

bigger than a lot of sort of the individual 

pricing. 

 So even though we've got lots of 

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unfair trade practices out there, you know. China 

is a great example. There's 15 things I want to 

fix in China, and that will help our sector if we 

had a more fair trade agreement. But I don't 

this is going to be an indicator of success or 

failure. 

 CHAIR CARR: I'm going to limit it to 

one more question. 

 MR. LIPETZKY: Jason, I appreciate the 

focus on Japan and the fact that we're no longer 

part of the TPP. Where are we headed after 

Japan? Is it Taiwan? Is it other places where 

we need to wrap up that bilateral side of it, or 

is there any appetite at all to kind of rejoining 

some of the TPP side or GATT? 

 MR. HAFEMEISTER: Well, I think 

there's two sides to that equation. One will be: 

where do we see market opportunities? Keep 

going, keep going, keep going, keep going. 

Sorry, you're going the wrong way. It's Asia, 

right, that's where we see a lot of market 

opportunity. So part of that is the TPP 

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countries. Part of that is these TPP countries. 

So we would love to get into negotiations with 

them. And partly we need to catch up on TPP, and 

also these are our targets. 

 But there's, I think the other side to 

be aware of is that there is also a lot of 

concern about unfair trade practices from some of 

these countries. A lot of Chinese manufacturing 

are moving to Vietnam. The Vietnam trade deficit 

is growing because we're importing more from 

Vietnam. For India, a lot of complaints, unfair 

trade practices there. And so Europe is a place 

where we're on the verge of a trade negotiation 

to deal with unfair trade practice. So those are 

places where we might have some leverage to say, 

you know, since we're unhappy with the way you 

guys are acting, we want to fix some things. 

These are some things in agriculture we should 

fix. So some of that overlaps here. 

 CHAIR CARR: Jason, are you going to 

be around for a while, or what's your schedule? 

 MR. HAFEMEISTER: Yes, I have a couple 

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of minutes. I've got to be back. But I can 

spend maybe 5-10 minutes here. 

 CHAIR CARR: So if we have any 

committee members that didn't get a question 

answered in the group and want to go speak with 

Jason now before he leaves, he's going to wrap up 

any of our conversations, please do so and try to 

give everybody the same chance. 

 MR. HAFEMEISTER: I went over time, 

sorry. 

 CHAIR CARR: No problem. We know this 

will be a challenging day. When questions get 

started they keep going. But Jason, appreciate 

your presentation and sharing all this with us. 

And again, if anybody wants to meet you in the 

back. 

 MR. HAFEMEISTER: Thank you for your 

time. 

 MR. SMITH: Since I think I'm the one 

in between lunch, I will try and make this quick. 

Okay, I first of all want to start out thanking 

the Production Workgroup. Everybody worked 

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diligently to get this done. Charles had it all 

started for us taking good notes and putting 

things together. And the group came together 

really well. And we were, I think one of the 

first groups to get things done. And so I 

appreciate everybody's commitment and joining in 

to get this done. 

 The objective statement of the 

Production Workgroup just recognizes that we have 

a lot of production challenges and that we do 

need assistance with them. We targeted four 

things that we wanted to talk about. Research, 

crop insurance, over-spray and packing and 

chemical labels. So we'll get into those 

particular recommendations and overviews. 

 So first of all, we're on research. 

It was our opinion that most agriculture research 

funding goes into agronomic row crops due to just 

the market potential for everybody to capture the 

returns on that. And as such, the specialty crop 

research has lagged. And we still have 

significant production challenges that are not 

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being addressed. 

 For example, productivity on corn and 

soy beans if you look at the chart has just gone 

like this, straight up with the introduction of 

GMO and a lot of the new technology that's coming 

along. 

 That's not happening with specialty 

crop industry because of consumer pushback on a 

lot of these new technologies. So we're dealing 

with old technologies and competing against a lot 

of new technologies. The budget constraints of 

public universities. They're still not being 

adequately funded to support our industry. 

Extension outreach programs are limited at the 

universities. 

 And so the daily challenges of a lot 

of production is not getting addressed. If you 

get some big issue coming along, you know, you'll 

get funding for some big issues. But everyday 

production needs is basically going unmet by a 

lot of the university extension. In addition 

then, a lot of specialty crop fruit and vegetable 

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producers are smaller, don't have the access to a 

lot of the same types of expertise that a lot of 

the agronomic crops have. 

 Okay. Specifically our recommendations 

on research. We noted that private commercial 

organizations are excluded from publicly funded 

research. And John, you had a lot to say about 

this. And we felt it was important to open that 

up because so many of the new technologies and 

stuff is being done privately, and not as much by 

the university and those types of public 

organizations. 

 We also believe that specialty crop 

research funding being protected from new and 

emerging crops that are not specifically listed 

as a specialty crop, and specifically we talked 

about the impact on what could be our industry by 

the decisions to define hemp as a specialty crop. 

If that starts to take away research funding from 

specialty crops because they'll be getting a 

piece of the pie that's been allocated. And all 

of a sudden those pieces get smaller for 

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everybody else. 

 So the recommendations to deal with 

these things, we would request that the Secretary 

support additional base funding for specialty 

crop research. We would also recommend that the 

Secretary review this decision including hemp, 

looking at the potential negative impacts to 

existing specialty crops. In particular, about 

funds for research, SCRI grants and any ways to 

determine that hemp will dilute the limited 

research funds that the Fruit Industry Advisory 

Committee recommends that they reclassify hemp or 

limit the crop from access to SCRI funding until 

additional money would become available. 

 All right. So on crop insurance, it 

was noted pretty pointedly that federal crop 

insurance is a viable tool for risk management. 

But the coverage for fruit and vegetables 

woefully lacks. Not just lacks, it's woefully 

lacking for specialty crops compared to agronomic 

crops, corn and beans. 

 As a producer myself, I can guarantee 

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myself a profit before I plant because of the 

federal crop insurance. And the crop insurance 

program is so poor, particularly for tomato 

production, that as a company we had to start our 

own insurance company to provide our growers 

anything that was useful, and it's still not as 

good as the crop insurance for commodity crops. 

 So that's kind of a basis for where 

some of this came from. We certainly do 

appreciate the NAP Program. But we need a lot 

more parity in crop insurance than what we can 

currently find in those programs. And you can 

read some of the particulars about that. 

 Recommendations, we urge the Secretary 

to make it a goal to ensure that fruit and 

vegetable farmers have access to coverage that 

are on par with row crops. And so I think that 

speaks pretty pointedly to that. 

 Okay. The next section is a little 

bit more lengthy. But it was important to 

several on our group. That's about over spray 

and off target chemical applications and legacy 

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materials. And we pointed out the introduction 

of dicamba to all our crops has exposed most 

fruit and vegetables to a risk that was not 

previously known three years ago. So this is a 

very new dynamic that's come into the fruit and 

vegetable world. 

 We described this particular chemistry 

is known and was proven to move off target by 

several methods, could move great distances and 

affects almost everything in the agronomic fruit 

and vegetable world. 

 And an increase in pollinator habitats 

are also real important to fruit and vegetable 

pollination and production. It affects organic 

producers at the risk of losing their organic 

certification. But one of the biggest things 

about this is that it does not possess residue 

tolerance for almost all food crops. Almost 

every other chemistry has a residue tolerance 

that says as long as it's underneath, it's still 

a wholesome, legal, marketable product. 

 Almost all through crops have a zero 

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residue tolerance for dicamba. And as such, it 

would be crop destruct if a hit was taken. And 

there is not enough insurance to compensate for 

damages, and federal crop insurance is not even 

covering over spray damages. So everybody is 

real vulnerable to a high degree or risk. 

 The real acrimony that's coming from 

this is extensive. People can't sit on school 

boards together, church boards sitting next to 

people in a pew because they've had off target 

incidences that were not compensated for. 

 Okay. The recommendations about this. 

This is that the USDA, EPA and FDA should 

recognize that dicamba does move off target, and 

not hide our heads in the sand about that, and 

establish a reasonable residue tolerance. We 

believe that buffers around sites should be a 

minimum of a mile to the closest sensitive plant, 

and application should be limited to more 

desirable circumstances such as lower temperature 

and humidity. 

 Several states have imposed an 85 

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degree limit on this in their own states, and it 

should be limited to pre-plant, pre-season that 

would reduce the potential for off target 

movement. 

 Number two, due to the overwhelming 

reports of dicamba volatilization and lack of 

adequate due process for specialty crop growers 

whose crops in likelihood have been affected by 

the tendency to move off target, we strongly 

recommend that the registrations for the new 

products that are for soy beans and cotton over 

the top, in crop not be renewed when the current 

registration expires. 

 And in addition, we recommend the EPA 

evaluate the performance of these products for 

safety after this season and make an appropriate 

judgment about their use in 2020 even before the 

registration expires. We also recommend USDA 

Pesticide Data Program work with EPA to ensure 

that dicamba registration is not renewed until 

such a time when research can prove with 

certainty that specialty crop producers will not 

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be adversely affected by any form of off target 

movement. 

 Our recommendation number three, it 

was brought up that there are legacy materials 

that have been used 30, 40 years ago that are 

still showing up on residue samples. And these 

legacy materials have long been prohibited but 

now with better detection methods they're still 

showing up. And we recommend that the presence 

of one of these legacy materials that have not 

been applied should not be considered an 

adulterated product or subject to regulatory 

action. 

 And then we also number four, 

recommend that USDA require biotech developers to 

seek necessary reviews by the USDA for genetics 

and EPA for corresponding pesticide registration 

simultaneously resulting in a joint approval 

process and that the two agencies increase their 

collaboration before these things are approved. 

 So for example, with the dicamba 

situation the seed was approved before EPA 

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approved the chemistry. And so for about two 

years there was a lot of dicamba being used on 

the actual crops and seed before there was even a 

label registration for that. 

 That caused a lot of problems. It 

also created a real pressure point for EPA to 

approve the use of dicamba because since the seed 

was out, people were already using it anyway. And 

so if these things would have been done together 

there may not have been that same pressure to 

approve. 

 Move on to inconsistency of labels. 

Some chemical labels have the same active 

ingredients, but they are extremely inconsistent 

in how they can be used and for what crops. For 

example, some crops will list products for fruit 

and vegetables. Some products with the same 

active ingredient will specifically list certain 

crops and exclude others even though technically 

they're still a fruit and vegetable type of 

thing. 

 So we've looked at this and we 

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thought, okay, how can we do it? And we thought 

that USDA should work with EPA to make sure 

chemical manufacturers write their labels in a 

uniform manner across all the different options, 

particularly since so many things have gone 

generic that a producer can easily determine the 

correct requirements, and USDA and EPA should 

work together to establish crop groups that are 

consistent with each other. And so some of this 

goes away of understanding what you can use and 

what you can't use on certain crops. Is that 

good? 

 MR. HUGHES: Thank you. Just one quick 

reminder that with all the recommendations that 

you guys draft and eventually finalize, you have 

to keep in mind that the USDA will only have so 

much influence over certain recommendations or 

positions that deal with other agencies. When 

there's a collaborative relationship that exists, 

great. But when it comes to tracking the 

progress of certain recommendations, it gets into 

an unknown space. 

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 So I just wanted to make sure that I 

state again because there's a lot of EPA that's 

involved in those recommendations. The next 

presenter is going to be the USDA's Brenda Foos 

who is part of the -- actually I'm sorry, she's 

the director for the Science and Tech Monitoring 

Division, right? 

 MS. FOOS: Actually it's the 

Monitoring Program Division. 

 MR. HUGHES: Monitoring Programs. 

 MS. FOOS: It's the Science and 

Technology Program. 

 MR. HUGHES: Yes, okay, all right. 

She introduced herself. 

 MS. FOOS: I can do that. 

 MR. HUGHES: And I thought Brenda would 

be good because the Pesticide Data Program falls 

under her unit, so I figured it would be good for 

her to provide an overview since that topic was 

very, inside of your recommendations. 

 MS. FOOS: So thank you, Darrell. I'm 

Brenda Foos. I'm the director of the Monitoring 

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Programs Division. It is also part of the 

Agricultural Marketing Service like specialty 

crops is at the root of the Science and 

Technology Program. 

 And our main program in my division is 

the Pesticide Data Program, which is incorporated 

in one of the recommendations you just heard 

about. So I'm going to give an overview 

presentation and talk a little bit about the 

dicamba information that we have. 

 But first, I really want to thank you 

for inviting me and for your interest in our 

program. This is actually my very first 

presentation about the program because I've only 

been the director for four months. So I'm glad 

to have the opportunity. 

 MR. HUGHES: There's a tech glitch. 

It's coming. There we go. 

 MS. FOOS: All right, there we go. 

PDP was initiated in 1991 to collect data on 

pesticide residues in food. Our mission today is 

to provide high quality nationally representative 

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pesticide residue data for U.S. foods. 

 The Food Quality Protection Act of 

1996, known as FQPA, directs the Secretary of 

Agriculture to provide improved data collection 

of pesticide residues, standardized analytical 

and data recording methods, and increase sampling 

of foods most likely to be consumed by infants 

and children. And PDP is performing this mandate 

under the FQPA. Additionally, PDP provides EPA 

with data for dietary risk assessments as a part 

of their registration review process. And we 

provide the Food and Drug Administration 

information to help inform better planning and 

monitoring under their authority to enforce the 

tolerance for maximum residue levels in the U.S. 

 The PDP data also is routinely used in 

the marketing of U.S. food commodities, including 

building consumer confidence and negotiating with 

foreign trade partners. The next slide. 

 In this presentation I'm going to walk 

you through our approach to accomplishing this 

mission. And this is the overview slide. The 

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basis of our program is really cooperative 

agreements with the states. Currently ten states 

participate in PDP, and the cooperative 

agreements between USDA are with the State 

Departments of Agriculture. Through our program 

plans, which are available on our website, we 

direct states' monitoring efforts including which 

commodities will be sampled, when and for how 

long. 

 States conduct the sampling within 

their states, and the samples are then shipped to 

the specified state laboratories for residue 

analysis. States then provide data to the USDA, 

and it is reviewed by the chemists in the program 

and added to our ever growing database. Each 

calendar year the results are compiled to develop 

our annual summary. And when the summary is 

released, we also post all of the data for the 

year to our website so that it is available to 

everyone who wants to use it. 

 Next slide. The ten states shown in 

green on this map are those that currently 

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participate in the PDP Programs or Cooperative 

Agreement with the USDA. They are New York, 

Maryland, North Carolina, Florida, Michigan, 

Ohio, Texas, Colorado, California and Washington. 

Our sampling design also draws in crops that are 

marketed in 13 additional states, and they are 

shown on the map in yellow. 

 Through our partnership with the 

states, the states handle the sample collection 

and analysis, with some states doing both 

sampling and laboratory work and others doing 

only the sampling. Our USDA PDP staff serve as 

liaisons for the states for sampling lab data 

review and assisting with other needs. And next 

slide. Sorry, it's got animation. I thought I 

took that out. I apologize. 

 MR. HUGHES: Do you want me to go back 

to this one here that has all the bullets there? 

 MS. FOOS: I think we're good. We'll 

just keep going. 

 MR. HUGHES: Okay. 

 MS. FOOS: Sorry about that. I 

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apologize. I thought I had taken that out so you 

could see everything at once. 

 So PDP selects commodities for 

sampling based on input from EPA regarding the 

current risk assessment needs. The high 

consumption commodities are rotated in and out of 

the program because we are not able to do 

continuous monitoring of all crops. Other 

specific crops are added to the rotation as data 

are needed. The selection of commodities 

emphasizes consumption by infants and children as 

directed by FQPA. 

 It may be of interest to you all to 

know that fruits and vegetables most consumed by 

kids are apples, oranges, corn and potatoes. The 

analytes or pesticides tested in the program are 

specific to each commodity, and we also 

coordinate that with EPA and FDA in identifying 

the priority compounds. I'll elaborate more on 

the commodities and the analytes in the upcoming 

slides. 

 So since its inception in 1991, PDP 

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has tested more than -- exactly 126 commodities. 

And as you can see here these are primarily fruit 

and vegetable commodities. Some commodities have 

only been through sampling and testing one time, 

and others have rotated through the program 

multiple times. I want to let you know that we 

are currently testing 14 commodities. Those are 

cantaloupe, bell pepper, bananas, basil, garbanzo 

beans, hot peppers, kiwi, mustard greens, oats, 

canned peas, radish, rice, canned spinach and 

frozen strawberries. 

 For the year, PDP will collect about 

10,000 food samples resulting in approximately 2 

million pesticide commodity data point pairs. 

Cumulatively through the PDP history then that's 

about 265,000 food samples that have been 

analyzed and more than 34 million pesticide 

commodity data points. 

 Next slide. You may be wondering at 

this point how it is that we collect all of these 

samples. What we do is we first start with our 

colleagues at the National Agricultural 

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Statistics Service to devise the nationally 

representative sampling plan based on the 

populations of the ten participating states, 

which include major fruit and vegetable 

production states and represent all U.S. census 

regions. 

 NASS uses the probability proportional 

to size model to determine how many samples there 

are collected at each of the sites in each of the 

states. Sampling sites are selected randomly but 

are rated to reflect the volume of product the 

site handles. Some of these factors can include 

pounds of produce the facility handles or the 

square footage of the facility. The idea is 

really that larger facilities that distribute 

more commodities are sampled more often than 

smaller sites. 

 The samples include foods that are 

domestic and imported, as well as organic and 

conventionally grown foods. So most fresh 

commodities are sampled on a two year basis and 

are then rotated out. This rotating commodity 

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sampling allows us to test a wide variety of 

commodities over time. The sampling time frame 

also allows us to capture data from different 

times of the year when certain commodities are 

available primarily as domestic or imported 

product. 

 A good example is blueberries. During 

the summer months, most of the blueberries that 

are available for purchase are domestically grown 

and then during the winter months, they are 

primarily imported product. 

 In addition, this approach also 

captures these intense pressures and growing 

conditions. Processed foods, such as baby food, 

that are generally available year round, have 

shorter sampling periods. 

 A commodity will reenter the program 

for sampling every five years if it's highly 

consumed by children or can reenter as data are 

needed. An example is that apples are often 

sampled. And I, since arriving, have been 

working to reach out to potential stakeholders 

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working in each of these commodity areas when we 

put something into the rotation, and I'd be happy 

to add any of you all to our list of people to 

reach out to, or your colleagues, just let me 

know later on. 

 So that bring us to the actual 

sampling. The sampling approach that I just 

described yields 59 samples per commodity per 

month, for most foods. This equates to over 800 

samples collected each month from across the 

country for analysis, and over 700 samples per 

year per commodity. 

 The sample information, including 

foraging, and organic claim, and many other data 

fields, are captured electronically by the state 

employees on site before the samples are shipped 

to the laboratory for analysis. 

 And as you can see, that is done in 

the field in the picture here with the bananas. 

Our sampling sites include locations that are 

closest to the consumer and samples are collected 

within hours of reaching a consumer. 

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 This includes distribution centers, 

terminal markets, and in some cases, retail 

locations. This results in PDP data that are 

consumer exposure levels, rather than the farm 

gate levels. 

 This allows time for degradation of 

products applied both pre and post-harvest, and 

the consumer exposure levels at PDP monitors are 

important factors in the pesticide dietary risk 

assessments. 

 Collection at these locations allows 

for representative sampling that closely 

resembles what consumers are purchasing, and in 

addition, these sites also have more information 

available about commodities than retail locations 

would have. 

 As per our nationally representative 

sampling approach, the number of samples 

collected from each state is proportioned 

according to the state's population, with more 

populated states collecting more samples per 

commodity per month, as illustrated in the table. 

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 So for example, when we are sampling 

oranges, the sample size is 5 pounds. So 

California will collect 13 5-pound samples per 

month and ship them off to the laboratory. 

 The next slide is about the 

laboratory. Once the samples arrive at the 

laboratory, they are prepared using common 

consumer practices and washed under gently 

running cool water. 

 Depending on the sample size stamped 

on the type of sample, consumer product practices 

include preparation such as peeling the bananas, 

and coring the apples, and removing the husks, 

and loosening the kernel from the corn, as shown 

here in the picture. 

 Samples are then homogenized in labgrade food processors, if needed, and separated 

into analytical portions. 

 All of our labs now use a month by 

catchers method for extraction. This multiresidue method allows labs to perform extraction 

of multiple pesticides in a fraction of the time 

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and the cost of older methods. 

 Previous extraction methods also 

generated a large amount of hazardous waste, 

thereby, increasing the costs. Our sample 

preparation SODs are posted on our web site, if 

you're interested in more details. 

 Following the extraction, the samples 

are ready for laboratory analysis. PDP has 

tested over 500 pesticides, metabolites, and 

isomers in the multi-residue method, but not all 

pesticides are tested on each commodity, rather, 

the actual number tested in each sample depends 

on the commodity, the pesticides that are 

requested as a priority for each commodity, and 

laboratory capabilities. 

 The compounds include many common 

pesticides, such as carbamates, organophosphates, 

pyrethroids, neonicotinoids, and triazoles. The 

PDP laboratories use very good quality 

instrumentation with gas chromatography, GC, and 

liquid chromatography, LC, coupled in tandem with 

mass spectrometers detection systems for 

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simultaneous identification and quantification of 

pesticides. 

 With this instrumentation, we are able 

to identify a large number of residues at very 

low limits of detection, or LOD. The LODs vary 

by commodity and residue, but are in the low 

parts per billion range. 

 These low LODs are also very important 

for the dietary risk assessment applications of 

PDP data. 

 All of the resulting data from the 

state laboratories are then reported back to 

USDA, where they are reviewed by the staff 

chemists in our office and incorporated into the 

database. 

 Our laboratory approach also includes 

a robust QA/QC program to help ensure the quality 

of the resulting datum. Each lab runs blanks, 

spikes, and process controls with each sample 

set. The lab must perform matrix spikes at least 

quarterly for each analyte and crop combination 

it reports, and that evaluates both the analyst 

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and the instrument performance. 

 Methods are validated for each 

commodity and pesticide and that also establishes 

the limits of detection and quantification at 

that time. 

 Proficiency testing takes place three 

times a year and all labs within the PDP program 

are ISO accredited. 

 Now to the uses of our data, because 

we really are a data program. PDP data are used 

in a number of applications and you heard about 

most of these when we talked about mission. 

 When the pesticide goes through EPA's 

registration and review process, there are times 

that additional data are needed to assess the 

potential dietary risk of that compound, and PDP 

provides the high-quality nationally 

representative data for those risk assessments, 

which are the basis of EPA's pesticide 

registration and cancellation decisions. 

 PDP data often replace model data and 

there's a benefit then to understand the actual 

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consumer exposures. 

 PDP data show that over 99 percent of 

the samples tested have pesticide residues below 

the tolerance established by EPA. I'm going to 

repeat that because I'd like you to really think 

through how that's a testament to the good work 

of the farmers of the United States that over 99 

percent of the samples tested have pesticide 

residues below the tolerances. 

 And knowing this, I think, helps 

establish consumer confidence in the U.S. food 

supply. 

 On a monthly basis, we also monitor 

the residue levels that come in and if a 

presumptive tolerance violation is found, we pass 

that data along to FDA, because they have the 

enforcement authority over residues. 

 However, they do not take enforcement 

action on PDP data, they simply incorporate it 

into their planning for the actions that they 

take. They do their own monitoring that is not 

nationally representative and not throughout the 

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course of the year, like ours is. 

 MR. SMITH: Can I ask a question? 

 MS. FOOS: Sure. 

 MR. SMITH: How does that 99 percent 

compare to the imported products? 

 MS. FOOS: So there are some domestic 

violations, but it is the majority are the 

imported products. I don't have a slide on that, 

but I mean, I could have my data analysts run a 

query and pass the information on to Darrell if 

the committee would like that information. 

 We have a huge amount of data, as I 

described to you, and I was about to tell you how 

it's all available on the Web site, but we can do 

custom queries too. And I'm actually about to 

show you one about dicamba, but let me finish 

this slide, then we'll move on to dicamba. 

 So also when a trade partner has a 

concern about the pesticide residues in U.S. 

commodities, the Foreign Agricultural Service 

often uses PDP data to alleviate those concerns 

and help resolve the trade disputes. 

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 So now, in addition to the daily uses 

I just described to you, we get a lot of requests 

for specialized queries of the database, and I 

have a really exceptional data analyst who's so 

good at these things. 

 I've heard that you all are interested 

in dicamba, I saw the recommendations that you 

just had about that, there were quite a few, and 

so in this slide and the next one, I'm sharing a 

summary of all of the dicamba data available in 

the PDP database, which, frankly, is not a lot of 

data. 

 Of the more than 250,000 samples in 

the database, only the 12,905 that are listed 

here have been analyzed for dicamba. 

 Now, the likely explanation for this 

low number is also illustrated on this slide and 

was brought up by your workgroup chair. 

 Over on the right side, you can see 

that most of the commodities in this table really 

have tolerances for dicamba. And in the 

selection of analytes, we always give priority to 

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the analytes that have tolerances for the 

commodity. 

 So pesticides that are not priority 

analytes are routinely reported by the 

laboratories if they're a part of the multiresidue method, as I mentioned to you earlier, 

when we were talking about the laboratories, but 

dicamba and the other acid herbicides require 

additional laboratory preparation, so it's not 

routinely done, and we currently have only one 

state that reports it as a part of their data. 

 So as you can see on this slide, the 

only commodity with a tolerance for dicamba is 

milk, and of the 1875 milk samples analyzed, none 

of them contained even detectable levels of 

dicamba. 

 And then in the second dicamba slide, 

you can see that the only other commodity with a 

tolerance is corn and they wanted to know, it's a 

typo here, and the two empty blocks, the 

tolerances for the canned corn and canned peach 

should be the same as the frozen ones. 

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 But also on this slide, you can see 

that dicamba has only been detected in 11 of the 

12,905 samples, and all of those were water 

samples. 

 So in summary, dicamba has not been 

detected in any fruit or vegetable samples that 

PDP has collected over the last 23 years. And 

I'm somewhat concerned that this isn't really the 

information that you were looking for, but we can 

discuss that in just a few minutes because I'm 

almost done with my slides. 

 I want to leave this presentation with 

you all knowing that all of our data are publicly 

available. Every year, we produce an annual 

summary of PDP, and I'll hold it up here, I 

brought a copy, that includes an informative 

narrative and robust data tables for the year. 

 We are currently finalizing the 2018 

annual summary and it should be ready in a couple 

of months, but I'd be happy to send you the 2017 

annual summary in hard copy, if you're 

interested, or it's also available on our Web 

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site, and the web address is given here at the 

bottom of the page. 

 Also on the PDP Web site, you can 

download annual data files or you can use the web 

app that allows public searches of PDP data where 

you can search using a combination of commodity, 

pesticide, and year. 

 It's a very handy tool and I encourage 

you all to check it out if you have a need. So 

with that, I'd like to thank you again for 

inviting me to give the presentation. My contact 

information is here at the bottom of the slide if 

you have any future questions, but I'll take any 

current questions you have right now. 

 MR. KIRSCHENMANN: So on the dicamba 

thing, is it --

 MR. HUGHES: Hey, Brian, can you 

project a little bit? 

 MR. KIRSCHENMANN: Yes, so on the 

dicamba debate on not finding the residues, is 

there a half-life issue? Because some of the 

herbicides that we get presented with on drift 

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issues are present in the crop in the growing 

season, but are not present by the time they hit 

the consumers. 

 So at what point is it adulterated and 

not adulterated? 

 MS. FOOS: So I have to tell you, I 

apologize, I'm not familiar with the adulterated 

versus non-adulterated issue. That's not a part 

of our program and maybe if one of you all could 

explain that to me, I could answer the question 

better. 

 But so obviously, if things are --

have degraded past the metabolites that we looked 

for, we won't find them, but in particular, the 

dicamba just doesn't work with our standard 

methods. 

 So it requires extra preparation and 

the laboratories don't do that unless asked. And 

we only ask if there's a tolerance, right? If 

there is a tolerance, it moves up in priority, 

and so mostly, they just don't report it because 

it's extra work. Yes. 

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 MR. ZEA: To go back to follow on 

Steve's comment, because I was going to ask the 

same question. 

 MS. FOOS: Right. 

 MR. ZEA: It's obviously one that all 

of us in here, probably, or many of us, assume 

would happen. 

 MS. FOOS: Right. 

 MR. ZEA: But how compelling is that 

to the statisticians that it's mostly imported 

product and it's a very, very small percentage 

overall. 

 MS. FOOS: And it's still a very small 

percentage overall. I have not seen a 

statistical analysis of it. At PDP, we're 

primarily in the data collection business and we 

don't do a lot of analysis. If you Google PDP 

and pull up a bunch of research articles written 

by people who don't work for me, and that really 

is part of our mission. We make our data 

publicly available. 

 So I can pull data and give you a 

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table of what we know, but we haven't really 

analyzed it, I think, as you're asking. Yes? 

 MR. WINGARD: Would you go back to 

Brian's answer? Did you say or did I -- I know 

what your answer was, but did you mean that 

because it's difficult to test for, the 

government just doesn't test for dicamba very 

much? 

 MS. FOOS: Yes, sir. 

 MR. WINGARD: So even though your data 

looks good, that's only a small portion of that 

100,000 you sample every year, or whatever the 

number was. 

 MS. FOOS: That is correct. We have 

265,000 food samples that have been analyzed 

overall and only 12,000 that have been analyzed 

specifically for dicamba. 

 MR. SMITH: In what year was this 

chart done? 

 MS. FOOS: Oh, I just made that chart. 

2017. That's our current publicly released data. 

We're still working on the QA of the 2018 data. 

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 MR. SMITH: So I'm just going to make 

a comment that there wasn't a lot used yet in 

2017. 

 MS. FOOS: Okay. So this is a really 

new problem. 

 MR. SMITH: It's a new problem. 

 MR. WINGARD: So based on your 

numbers, only 4 percent of your samples, 4.5 

percent --

 MS. FOOS: Right. 

 MR. WINGARD: -- to be a little more 

accurate, of your samples are actually tested for 

dicamba. 

 MS. FOOS: That is correct. 

 MR. WINGARD: Okay. 

 MR. SMITH: And I would comment that 

all the stuff coming out of California wouldn't 

have it on it anyway because it's not approved 

there. 

 MS. FOOS: Okay. California is the 

lab that currently reports it, probably for that 

reason. I did not know that. I think you just 

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educated me, but yes, all of the newest data --

so the data table I gave you on dicamba is over 

23 years. The newest data that we have received 

are all from the California state laboratory. 

 MS. HARPER-LARSEN: So I will address 

adulteration --

 MS. FOOS: Okay. 

 MS. HARPER-LARSEN: -- in simplistic 

of terms where it's meaningful to you. If it's 

not legally allowed to be used, it's adulterated. 

 MS. FOOS: Okay. 

 MS. HARPER-LARSEN: Okay. 

 MR. WINGARD: Or if it's over the 

limit. 

 MS. HARPER-LARSEN: Or if it's over 

the limit for MRLs, okay? In terms of 

pesticides. Now, we also deal with it being, you 

know, inedible quality, and microbial 

contaminates, and a lot of other additional 

hazards, including radiological thing, okay? But 

in your terms of that, okay? 

 MS. FOOS: Okay. So in the samples we 

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have, there's really no evidence of adulterated, 

as you would call it. We usually call them -- if 

there is no tolerance and we find it anyway, we 

would describe that as just identifying a 

residue. 

 We don't call it adulterated. If we 

find it over the tolerance, we would call it a 

presumed tolerance violation. We did give both 

of those -- both types of data to FDA for their 

evaluation, but we haven't had any on dicamba, so 

we haven't given them the information. 

 It seems as though you all have 

information, maybe, in California, is where 

that's coming from, that dicamba is adulterating 

in the way that would have a relationship with 

pesticide residues, is that correct? 

 Maybe somebody can educate me on that 

too, how, sort of, it's -- how you have evidence 

of dicamba adulterating residue samples, because 

it's not from my data. Is it from somebody 

else's data? 

 MS. HARPER-LARSEN: Because it's 

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privately tested and required by customers. The 

audits. 

 MS. FOOS: Okay. 

 MS. HARPER-LARSEN: And there are 

contracts that are specific, probably quite a few 

of us in the room have, particularly in the last 

two years, that have provisions specific to 

dicamba and a couple of other chemical residues 

that we're actually prevented from having them on 

our chemical list, even if it is permitted use. 

 MS. FOOS: Tell me that one more time. 

 MS. HARPER-LARSEN: So retailers won't 

let us use it if we sold crops. 

 MS. FOOS: Okay. All right. They 

don't want your crops skewing your private 

detection or them in their private detection. 

 MS. HARPER-LARSEN: Well, they don't 

spend money. They put it on us. 

 MS. FOOS: Okay. I don't know what to 

say. It sounds like you're looking for things 

that we --

 (Simultaneous speaking.) 

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 MS. FOOS: When I pulled up the 

dicamba data, I figured it wasn't going to be 

what you all wanted to see, but it's what we 

have. 

 MS. HARPER-LARSEN: Well, we're glad 

that you got some data to start with. I think it 

gives the working group in particular, some 

additional information to proceed with. In 

regards to what you see here relating to, 

particularly, the water, because that's used, I 

mean, especially when we look at the tested and 

finished water, even though you had part per 

trillion --

 MS. FOOS: Right. 

 MS. HARPER-LARSEN: -- okay, it's 

still --

 MS. FOOS: It's in the realm. 

 MS. HARPER-LARSEN: Right. And the 

various ways that agriculture and the public, you 

know, also use that in needing to, sort of, have 

that research and it being a bit more robust 

probably begs the question. 

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 But I wanted to highlight to you that, 

in particular, I did not see watermelons listed 

here. And the reason why those are particularly 

on the radar is, they cause the shot heard around 

the world related to dicamba. 

 So everybody thinks it's a soybean and 

a corn issue, but it wasn't. It was a customer 

of mine. 

 MS. FOOS: It was what? 

 MS. HARPER-LARSEN: It was a customer 

of mine that shot and killed another farmer. 

 MS. FOOS: Oh. 

 MS. HARPER-LARSEN: Oh, yes. And with 

that being said, it was relating to a future 

watermelon crop. It was not a commodity crop at 

the time. And so noticeably missing from this 

data list is watermelon. 

 MS. FOOS: All right. So I'm looking 

in the annual summary, as I said, robust data 

tables in the back, watermelon has rotated 

through our program three times. The most recent 

time ending in June of 2015. 

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 MS. HARPER-LARSEN: So that's prior to 

it. 

 MS. FOOS: Yes, I think so. I mean, 

to get at your question about why don't we do 

everything, we have a pretty limited budget. We 

do these multi-residue methods so we can get the 

most we can for -- within our -- within what we 

can work with. We only do 14 commodities at a 

time. 

 I would imagine around the table here 

you represent well more than 14 commodities. And 

so it's all we can do. 

 MR. SMITH: Could you comment, what 

kind of relationship you have with EPA that could 

enhance the correlation between the two agencies? 

 MS. FOOS: So I can speak to my own 

program and the pesticide data program, and our 

exchange of data on residues, I think -- I don't 

know, Darrell, have they had any engagement with 

Office of Pest Management Policy? 

 MR. SMITH: No. 

 MS. FOOS: No. Okay. So USDA also, 

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at the very high level, has an Office of Pest 

Management Policy, and they also work with the 

EPA on a number of issues. Much broader than 

residue analysis. 

 I think they might have more 

information you would be interested in, but from 

us, from our perspective on residue analysis, our 

program and the dietary risk assessments are both 

mandated under the Food Quality Protection Act. 

 And so we work very closely together 

that our data is helpful to them in conducting 

the dietary risk assessments. 

 And as I mentioned before, it often 

replaces the model data and in that way it's 

advantageous because the data does show that, 

generally, the foods are all meeting the 

tolerances. 

 And so our relationship is really 

about what are the current risk assessment needs, 

which chemicals are undergoing the registration 

review in the upcoming timeline that we might be 

able to provide timely data, and particularly, 

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about which commodities to reenter the program, 

focusing on those ones for infants and children. 

 MR. SMITH: So could you provide them 

-- looking at this list of no tolerances, could 

you provide them encouragement, in some form, to 

help get those established? If we make this 

recommendation, comes out of this group, to the 

USDA, you know, it's not to EPA, can your group 

influence EPA to do something about that? 

 MS. FOOS: We certainly can share it. 

I think that maybe that Office of Pest Management 

Policy does more on the bigger picture. I think 

it's possible, after hearing what the pesticide 

data program is about, that you all would want to 

consider changing that recommendation, just say 

USDA, but then you could get our influence and 

Pest Management Policy. 

 MR. SMITH: Okay. 

 MS. GLEASON: I'm wondering, if you're 

using these recommendations or these -- this data 

is to make recommendations about whether 

something should be registered or registration 

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should be cancelled? 

 MS. FOOS: We do not. 

 MS. GLEASON: Okay. 

 MS. FOOS: We just make the data 

available. The EPA does all of the analyses. 

 MS. GLEASON: Okay. 

 MS. FOOS: FDA does --

 MS. GLEASON: Does it have to be a 

certain -- I mean, there's so little -- it seems 

like there's so little data right here around 

dicamba, does there have to be a certain, like, 

number of samples, or a certain level of data 

that you have to provide around --

 MS. FOOS: So there are, and I'm 

sorry, I don't know off the top of my head, when 

I read to you the 800 samples per commodity per 

year, that is based on the minimum means. 

 So what I can tell you is, I don't 

think that EPA is using these data in the dicamba 

assessments. I don't know off the top of my 

head, know what assessments EPA is doing for 

dicamba, though, because we simply share data and 

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we don't engage them in the analysis. 

 MS. HARPER-LARSEN: How about FDA, all 

that, are they -- are you sharing any of this 

data with the FDA? 

 MS. FOOS: We do share data with them 

too. And I know for a fact that they do not take 

enforcement violations actions based on PDP data. 

They will look at what we found and what they 

found in their non-nationally representative 

sampling. 

 My understanding is they do more 

targeted sampling. And maybe they would take 

what we find and devise a targeted sampling or 

decide that they don't need to do a targeted 

sampling, but we just help them in planning the 

projects. 

 MR. SMITH: Brett? 

 MR. ERICKSON: Does your agency ever 

have discussions regarding the fact that the data 

that you guys put out is utilized by -- or used 

to publish this dirty dozen list and the impacts 

that that data has and how it's twisted, or taken 

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out of context, or on relativity, you know, how 

that impacts growers and producers in the -- in 

this room and in the country? 

 MS. FOOS: So I have heard discussions 

about that even in my short time here. And 

because we make it publicly available, the public 

is able to do with it as they want. We do not 

issue our own analyses. We don't do the EPA 

analyses and we don't do any other group's 

analyses either. 

 I think you have to weigh, at least in 

my opinion, you have to weight that some people 

will use it in a way you don't like, with other 

people will use it in a way that you do like. 

And overall, the data are very supportive of the 

food quality in the United States, and should 

build consumer confidence overall, to encourage 

people to eat more fruits and vegetables. 

 You look unsatisfied with that answer. 

 MR. ERICKSON: Well, I agree with you 

on the fact that people take -- you can take a 

piece of data and turn it into whatever you want. 

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 MS. FOOS: Absolutely. And we have 

tried to remain a data program and not a -- not 

the policy program, which is why, maybe, the 

Office of Pest Management Policy would be able to 

better engage in some of the things you've been 

discussing. 

 CHAIR CARR: Time for one last 

question? 

 MS. FOOS: Well, everybody wants 

lunch, so thank you very much for inviting me. 

And I want to tell you, when I was on the way up 

here in the elevator, a gentleman was commenting, 

he saw the Fruit and Vegetable Industry Committee 

on the rolling screen, he's like, wow, I want to 

go to their lunch. 

 If you guys are having some great 

fruit and vegetable lunch, can I be invited? I 

suspect it's like other committees where you have 

to go get your own lunch. 

 CHAIR CARR: That's probably a good 

thing. Darrell, you can lead into that and talk 

about it over the next 75 minutes. 

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 MR. HUGHES: All right. Over the next 

75 minutes, you're free to eat lunch wherever you 

want, just be back in time. 

 CHAIR CARR: So we're meeting back 

here at 1:30? 

 MR. HUGHES: Back here at 1:30. 

 CHAIR CARR: Is it 1:30? 

 MR. HUGHES: 1:25. 

 (Whereupon, the above-entitled matter 

went off the record at 12:16 p.m. and resumed at 

1:31 p.m.) 

 MR. TALAN: Good afternoon, everyone. 

It's a pleasure to be here. I'm David Talan with 

the Bureau of Labor Statistics. I am the program 

manager for the Quarterly Census of Employment 

and Wages. 

 MR. ROBISON: Ed Robison from Bureau 

of Labor Statistics. I'm a mascot, they have a 

group mascots, and we have not QCEW, but we have 

Census of Employment and Wages, also have current 

population survey, and I'm well aware over the 

years, with other groups, that there are 

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differences in our ag data and various other ag 

data that's out there. 

 MR. JONES: Hi. I'm John Jones, same 

thing, BLS, but I'm in the Occupational 

Statistics Program specifically. I'm a columnist 

there. 

 I'm here representing, actually, 

another colleague that wrote a paper on the ag 

industry when we did the Green Services Job 

Survey, and it's 2011, so it's eight years ago, 

but apparently you guys want to hear about it, so 

I'm here. 

 CHAIR CARR: Thank you. Your name one 

more time. 

 MR. JONES: It's John Jones. 

 MR. HUGHES: And that's it for now. 

Brian Pasternak is on the agenda to group 

presentation later. He's in the back. You guys 

will meet him later and there's one additional --

oh, yes, that's right. David Hines, right? 

 CHAIR CARR: David Hiles. 

 MR. HUGHES: Hiles? 

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 CHAIR CARR: Hiles, H-I-L-E-S. 

 MR. HUGHES: He's on his way via bike, 

maybe, so -- which is great exercise, being 

healthy. 

 MR. ERICKSON: How many labor speakers 

do we -- all these guys are going to speak after? 

 MR. HUGHES: Two. 

 MR. ERICKSON: Two. 

 MR. HUGHES: Yes. 

 MR. ERICKSON: Thank you. 

 MR. HUGHES: And we just have them on 

deck in case you ask questions, to provide their 

support. 

 MR. ERICKSON: Okay. I'll run through 

our stuff really quick so our speakers can come 

up. It's interesting that Immigration and Labor 

are not as high of a topic as some of the other 

stuff we've talked about today. It's 

interesting. 

 So I'd like to thank the group, in 

particular, Chalmers was very helpful in helping 

put together some language for some of our 

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requests. 

 Somebody very wise told me, and you 

may have heard this before, but we can import our 

food, or we can import our labor, we can choose, 

either way, foreign hands will be harvesting 

those products. 

 It would be preferable that those 

hands are picking that product that is grown here 

in the U.S. 

 I'm not going to go through our 

objective statement here, I'm just going to jump 

into -- we read that last time, our first 

recommendation was, we request the Secretary's 

collaboration with other agencies to remove the 

ten-month rule. 

 The most commonly accepted 

interpretation by U.S. Department of Labor is 

that temporary means employment of less than ten 

months and we would like to remove that ten-month 

rule to read less than one year. 

 Recommendation Number 2, we request 

that USDA research methods to make the Farm Labor 

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Survey more robust. It is our understanding that 

the new survey, moving forward, that some of the 

key areas of improvement are identified, 

employers who use H-2A labor designed to 

determine base wages for various occupations 

within ag by separating out base wages, overtime 

wages, and bonuses, all things which had 

previously been used in reporting wages. 

 The intent in separating out these 

wage add-ons is to determine and publish the base 

wages paid in various ag occupations which could 

then be used DOL in its adverse wage 

calculations. 

 So we request that the Secretary 

monitor this process very closely and work 

closely with the Secretary of Labor to ensure the 

refined data that is collected is used to support 

agricultural employers and the American farm 

worker. 

 Recommendation Number 3, we request 

that USDA work with other agencies to change the 

rule related to 51 percent are more a product 

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coming from outside the H-2A farm applicant 

because many growers also pack for others, as we 

see consolidation in the industry and a lot of 

labor challenges, a lot of these packing houses 

are packing product that is not only their own, 

and that is important to those growers who rely 

on that person to pack and market and ship their 

product. 

 Recommendation Number 4, we request 

collaboration between the Secretary of Labor and 

USDA to have -- create a meaningful impact for 

employers utilizing the H-2A program by 

developing a program that identifies preferred 

employers who possess solid history in the 

program for an expedited and more streamlined 

application process. 

 That's pretty self-explanatory. 

Recommendation Number 5, we can breeze through 

because that is -- we still have some discussion 

within our group on Recommendation Number 5, and 

which we will be discussing tomorrow. That is my 

report. 

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 MR. HUGHES: All right. I think we 

have Jody up now from NASS, and Jody will 

introduce himself when he comes up. 

 MR. MCDANIEL: All right. Good 

afternoon, everybody. I get the fun spot. You 

guys just filled your stomachs, so I'm not 

anticipating any questions, so we'll be good. 

 I'll forewarn you, I went a little bit 

old school and low tech on the fact that I didn't 

build a slide deck for today, so what I really 

want to do is, sort of, explain what we have as 

far as data from the National Ag Statistic 

Service. 

 But first and foremost, who am I and 

why I am standing here with you guys today? So 

I'm Jody McDaniel. I'm actually the chief of our 

Environmental, Economic, and Demographics branch. 

So my program is split into two areas. I oversee 

the dissemination of the census of agriculture, 

which, of course, is a very broad program, but I 

also oversee all of the annual program efforts, 

such as the Farm Labor Survey, which I suspect, 

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based on Recommendation Number 2, we might talk a 

bit about today. 

 So delving in a little bit, just an 

overview of the farm labor statistics at NASS. 

So for perspective, we have two funding streams 

at NASS, so we also have two data streams, one of 

those being the Census of Agriculture, the other 

being the Farm Labor Survey. 

 So to give you some context, the 

Census of Agriculture has been at NASS since 

1997. It's actually conducted in the years 

ending in 2 and 7, so that's every five years. 

It targets everyone with a $1000 of sales or 

potential for sales. 

 So it takes a look at use, ownership, 

production practices, income, expenditures, and 

really, the census is the voice for all American 

farmers and ranchers, because it's that one 

opportunity that the USDA has to publish that 

granular level of data all the way down to the 

county level. 

 So now, reason we're here today, labor 

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data. So what do we get out of the Census of 

Agriculture? We get state and county data on the 

number of farms that employ individuals for more 

than 150 days or less than 150 days. We get a 

farm count. 

 We get the total number of workers. 

We also do a more granular approach and do a 

breakout by farms by number of workers, so 

categories such as one worker, two workers, nine 

or more, so you get an idea of the density, and 

the total payroll. 

 What you don't get is a wage rate. 

That wage rate is a function of our annual 

program, which is the Farm Labor Survey. 

 So that, in itself, is the basis for 

employment and wage estimates coming from the 

USDA. One thing to remember, so my counterparts 

from BLS and DOL here at the table, NASS focuses 

on a producer-driven survey. 

 Our survey goes out to respondents, as 

we refer to them, or any survey organization 

does, but our sampling base for the farm labor 

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program are actually producers that earn $1000 or 

more on an annual basis. 

 We collect that data, actually, four 

times -- or twice a year for four different 

reference weeks, so those reference weeks are the 

week that includes the 12th of the month in 

January, April, July, and October. 

 We then subsequently publish that data 

twice a year for 15 multi-state regions. This is 

in cooperation with our partners from DOL, so we 

do have a lot of ongoing conversations with 

Brian, specifically. 

 Some data that you get out of that, of 

course, are the number of workers, the average 

hours worked, and the average hours worked per 

worker. Quarterly, of course, is when that data 

is published, even though it comes out twice a 

year, and then you get hourly wage rates for 

field workers, livestock workers, field and 

livestock workers combined, and all hired labor. 

 From 2014 forward, we've actually been 

publishing data at a national level for the 

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standard occupational classifications, so that 

breaks it out a little closer. So when you -- I 

think I heard mention picking your fruit or 

produce here so we can bring the labor in, so 

graders, and sorters, and pickers are some of 

those categories. 

 So that's sort of the history of the 

labor program and where we were 18 months ago. 

To bring you a little more up to speed, which, I 

noticed from your recommendation that you're well 

aware of the fact that we are -- we've been 

through a period of about two years of survey 

improvements on the farm labor program. 

 At one point in time the sample size 

was around 14,000, twice a year. The sample size 

right now has been increased to between 34,000 

and 39,000, twice a year. 

 That long-term goal is to be able to 

actually, in those 15 multi-state regions, to be 

able to publish that more granular data down to 

the occupational level. 

 So you'll be able to see out of our 

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report, that'll come out, actually, in November 

will be the first time we've published that, it's 

going to be an average wage rate for graders and 

sorters at those 15 regions. 

 It's going to be much different. 

Another effort, which I saw in your 

recommendation, was the base wage rate. We've 

done a large amount of cognitive research and 

reached out to industry, as well as producers, to 

better understand where we can develop the 

instrument so that respondents can actually get 

the data back to us to set the most meaningful 

wage rates, which is, at the end of the day, our 

goal. 

 Those wage rates are going to still 

continue to be set in the same fashion that they 

always have been. So we will have an average 

gross wage rate, which is published four times, 

four quarters, a year, which then is weighted and 

provide an annualized average wage rate. 

 In addition to that, we also are going 

to be publishing a base wage rate for the first 

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time this fall. That base wage rate has been the 

result of some research and finding out how to 

best help producers give us that data, so that we 

can make sure that we account for things like 

piece rate appropriately, which is always a 

concern. 

 It's a reporting challenge. So that 

sort of is a quick rundown. I will be really 

honest, I think the value is from being here with 

you and actually taking questions before I turn 

it over to Brian. 

 So if you have questions specifically 

about the NASS program, I'm happy to entertain 

any of those. 

 CHAIR CARR: Jody, I have several 

questions. Going back to your two different 

surveys, the census survey, there are a group of 

employees that are not counted in that, is that 

correct? The ones that were for farm labor 

contractors. 

 MR. MCDANIEL: So again, our 

population that we survey are producers of 

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agriculture, so what you're talking about is 

actually an independent contractor who hires farm 

labor, so that would be more of an agribusiness. 

 CHAIR CARR: Right. And the last 

survey was about 2.4 million employees in 

agriculture in the last Farm Labor Survey, is 

that correct; census? 

 MR. MCDANIEL: Farm Labor Survey or 

census? 

 CHAIR CARR: The census; 2017 census. 

 MR. MCDANIEL: So apparently, I did 

not plan on talking about census data. I brought 

the Farm Labor Report, but I'm going to take you 

at your word that that is -- yes. 

 CHAIR CARR: I guess where I'm trying 

to go with this for the group is, we have yet to 

have been able to find any reliable data that 

tells us how many hired farm workers there are in 

agriculture. 

 MR. MCDANIEL: So there is -- and 

that's the benefit of having some of our partners 

here in the room, they do look at a different 

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universe than we do for population, so again, the 

strength of the survey from NASS is going to be 

based on our population, which is the producer 

themselves, but I fully recognize that that farm 

labor contractor component serves a lot of value 

and I may misspeak on which labor survey, but is 

it QCEW that captures the farm contract? 

 CHAIR CARR: Right. 

 MR. MCDANIEL: Yes. So if you have 

more specific questions about it, I would 

actually say, when we finish both presentations, 

maybe more of a conversation about that at that 

time. 

 CHAIR CARR: Well, one thing from just 

the industry as a whole is, when we go on the 

Hill and talk with our representatives and stuff, 

and we talk about immigration reform, not 

necessarily what we're talking about right now, 

but not having a clear understanding of what our 

labor pool really is, really -- especially when 

you get into the discussions of caps and 

adjustment of status for workers. 

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 It would just be really great to 

figure out where we could go to to understand 

what our labor pool size really is. 

 MR. MCDANIEL: Agreed. Being a 

statistical organization, we inform policy. We 

don't enforce policy. So what I can tell you is 

that, we survey producers and that is our world. 

That is our population. 

 So what you're asking for is more of 

a blended data product that would be parts from 

each of our specific --

 CHAIR CARR: And that may be the goal 

for me today is just to figure out which one --

which survey I need to take from you and which 

survey I need to take from them to combine and 

blend them together. 

 So talk about your changes. And we 

are familiarized -- I am familiar with the fact 

that you're trying to get down to at least five 

categories on the new survey, and livestock 

workers, harvesters, or farm workers, and then 

graders and sorters, I think that you're asking 

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managers. 

 MR. MCDANIEL: Yes. 

 CHAIR CARR: And then I don't know 

what the fifth classification would be. When you 

publish those wages at the granular level, being 

the base, are you also going to publish them as 

five rates there, and on your gross wages, are 

you just going to do one or are you going to do 

gross wages for all five categories again? 

 MR. MCDANIEL: So it's going to be on 

the fitness for use, so again, this is the first 

full cycle of the expanded sample, so we've 

gotten the first two quarters in, and my staff 

are analyzing it right now. 

 Look at the second installation of 

that data in October. We'll compile those 

together and what we'll look at is the 

coefficient of variations wrapped around that 

data. 

 And any time that that data supports 

being published and can be used for the public 

good, we'll make it available to the most 

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granular level. 

 If we find that there's too much 

variance in the data and it would be misleading, 

then that data will not be disclosed. 

 CHAIR CARR: And then, of course, if 

your counterparts are going to speak, then it's 

my understanding that if USDA, NASS, is not able 

to produce a wage rate for a particular category, 

then they would fall back, under the rule change, 

they would fall back on their BLS data for --

 MR. MCDANIEL: Actually, I apologize, 

I can't speak to the rule, because even that's 

DOL, and I would ask that you all do Brian a 

favor, since it's in public comment, and not ask 

him either. 

 CHAIR CARR: That's going to be 

difficult. So you produce that survey, and that 

survey is ongoing, and talk to the group so they 

understand how the impact, or if you know yet, 

the impact of gross wages. 

 Currently, when a survey is done, it's 

basically, how many workers you have, what was 

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your total payroll for that period, doesn't take 

into account whether they worked overtime or not, 

it's just a straight wage rate then, correct? 

 MR. MCDANIEL: So what you get is, you 

get -- I come out to you as a respondent and say, 

sorry, need new glasses. Hi, Chalmers, you know, 

today we're going to talk about labor, we're 

going to talk about two quarters. What we're 

going to do is split that out into the farm labor 

types, so I'm going to assume you have some field 

workers. 

 So the respondent's going to go 

through the questionnaire and you're exactly 

right, how many laborers did you have? What were 

the total gross hours worked? What was the total 

gross wage paid? And then we create that ratio 

estimate for that wage rate. We don't actually 

ask the wage rate, which is a common 

misconception. 

 We ask the numerator and the 

denominator. 

 CHAIR CARR: Right. 

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 MR. MCDANIEL: And then it's weighted 

and that creates your wage rate. 

 CHAIR CARR: So making the changes, 

and I may be going way down in the weeds, in 

making the changes, how are you going to get to 

the granular level in terms of -- because I 

filled out your survey many times and, you know, 

it's the gross wages divided by the number of 

people, and you come up with that. 

 But now you're going to try to 

separate out piece work wages from --

 MR. MCDANIEL: We're not. What we 

found through research is, asking the -- so keep 

in mind, we write a survey instrument that's good 

for all parts of the industry. The group I'm 

here with today, piece rate is very important. 

It's a passionate part of the industry. 

 We don't have a specialized 

questionnaire just to collect piece wage rate. 

What we've done is created a one-page supplement 

that comes with that questionnaire, when you get 

it in the mail, to help you go into how to put 

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the data in the right column so it's the most 

reflective wage rate. 

 CHAIR CARR: And how did you go from 

1400 -- or excuse me, the 14,000 respondents to, 

hopefully, the 39,000? Because obviously, a lot 

of the challenge has been, there wasn't enough 

respondents in the past. 

 MR. MCDANIEL: It is a mechanism of 

funding. So again, I mentioned the NASS is 

funded through two appropriation streams, the Ag 

Labor Survey, or Farm Labor Survey, is part of 

the agriculture estimates funding stream. 

 We actually redirected funds from 

other parts of the program to amplify that. We 

are still receiving funding from the Department 

of Labor, so it is definitely a cooperative 

effort, but we supplemented that funding internal 

to the agency. 

 MS. HARPER-LARSEN: So does that mean 

you've got more people knocking on barn doors, so 

to speak, to get respondency or how are you -- I 

mean, you're looking at a two and a half times 

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increase, which is going to dramatically increase 

your sample pool, your data collection, your 

variances are probably going to get thrown out --

 MR. MCDANIEL: Well, actually, the 

beautiful part is, your variances with an 

increased sample size, theoretically, should 

reduce. So that's the beauty of adding more 

samples to it. 

 As far as the data collection effort, 

so keep in mind, the Farm Labor Survey is 

predominantly a mail, web, and telephone followup survey. We have five regional data collection 

centers across the country that seat more than 

800 people, give or take. 

 So we engage them first and foremost. 

If there's a specialized operation or a contact 

arrangement, we have 3000 additional contract 

employees who collect data that are part-time 

employees, so they'll be out to get the data as 

well. 

 But, yes, we're geared up. Collecting 

data is something we -- we've got it under 

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control, as far as --

 MS. HARPER-LARSEN: Well, I have one 

that goes to church with me, so --

 MR. MCDANIEL: They're lovely people. 

 MS. HARPER-LARSEN: -- he waits on us 

after church to get out. 

 MR. MCDANIEL: They're crafty. We 

love them, actually. Most of us start our career 

in the field, so we work with them closely. So 

I'm not aware of their payment structure, because 

actually, they work for the National Association 

of State Departments of Agriculture, not NASS. 

 MR. WINGARD: Now, my question is, 

going all the way back to, I think, Chalmers' 

first question, who can tell me or this group how 

many farm workers are in the U.S.? 

 MR. MCDANIEL: So when you say, farm 

workers, you're referring to people hired in 

through a business, you're talking about people 

hired in through a producer, so recognize the 

challenge we have, that we all have different 

authorities on the spectrum in which we collect 

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data. We are charged with collecting data from 

the producers. 

 BLS collects it on the entire 

workforce. What I would imagine you have to do, 

which, some of our partners in the Economic 

Research Service have been researching is how to 

harmonize that data across so you get a straight 

answer. One government data product. 

 Right now, there is not one. 

 MR. WINGARD: So nobody can tell us 

how many farm workers are in the U.S. Is that 

your answer? 

 MR. MCDANIEL: I can tell you the 

amount of farm workers employed by agricultural 

producers. I cannot tell you the amount that are 

employed by farm labor contractors. 

 MR. WINGARD: But is that data -- does 

somebody have that data? 

 MR. MCDANIEL: I would --

 MR. WINGARD: I mean, because to 

Chalmers' point, as we debate and contemplate 

labor --

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 MR. HUGHES: In other words, it sounds 

like one of our labor experts may be able to jump 

in to provide some insights. David --

 MR. MCDANIEL: Hiles. 

 MR. HUGHES: Hiles? 

 MR. MCDANIEL: Yes. 

 MR. HUGHES: Come on up for a second. 

 MR. WINGARD: I mean, you all just 

tell me true numbers and I'll be happy. 

 MR. MCDANIEL: You're good. Come on. 

It's a question, I'm sorry, but I can't answer. 

 MR. WINGARD: But I mean, you 

understand the value to that data for us? 

 MR. MCDANIEL: I fully do, but it is 

that challenge of, we all have a role to play in 

statistics, so fortunately, our partners are 

here. 

 MR. WINGARD: So before David starts 

speaking, just for the group's reference, you 

don't know -- so there is areas in the country 

where farm labor contractors are extremely 

important in the fresh fruit and vegetable 

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industry, and that's the predominant labor 

source, and then there's other parts of the 

country where it's direct site employers, where 

the farmer employs the labor himself. 

 So not knowing these two different 

pools, NASS is obviously counting the producer 

level, but again, we still, and maybe David has 

the answer to this, we have struggled to put 

these two numbers together to really have an 

accurate count of hired workers. 

 MR. HILES: Hello, you all. Okay. So 

I work for the Quarterly Census of Employment and 

Wages. I'm in charge of the branch that does the 

last review of the data before we put it out and 

try to make it safe for public consumption. 

 Dave Talan is the program manager for 

the Quarterly Census of Employment and Wages. So 

I'll try and answer some of the questions you 

have about how do we -- what kind of counts do we 

have for farm labor. 

 So the Bureau of Labor Statistics, 

most of the measures that we put out really are 

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focused on the non-farm portion of the economy. 

You guys are probably painfully aware of that. 

 The Quarterly Census of Employment and 

Wages actually does cover a large chunk of the 

agricultural portion of the economy. So when we 

say Quarterly Census of Employment and Wages, 

we're an administrative data program and we base 

our data on unemployment insurance, quarterly 

reports by every employer in the United States 

covered by the unemployment insurance system. 

 So we don't actually have people 

knocking on those barn doors because whoever's 

doing your bookkeeping is saying that to your 

State Department of Workforce Affairs, the 

Department of Labor, already. 

 So usually it's the unemployment 

insurance tax office. So we think we capture 

about half of employment in the agricultural 

sector because the coverage of the unemployment 

insurance system is based on the size of the 

workforce at the declared enterprise. 

 So we're focused on the number of 

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workers and when we're collecting data, we're 

interested in, what is the primary economic 

activity of the worksite that's reporting it. 

 So if it's a labor contractor, we're 

getting them classified into that industry. And 

in terms of agriculture, we know there's 

production, there's the warehousing part, you 

know, we think about elevators and all that, 

there's wholesale, processing, you know, 

processing, and then wholesale and retail. 

 So we have that entire stream of 

information, but I think you guys are sort of 

focused -- we focus mostly on the production 

side, or a little bit of processing, so both is 

the answer on that. 

 So we put out data four times a year. 

The next data we'll be putting out is for the 

first quarter of 2019, and that'll be coming out 

on September 4th. And the data that we're 

collecting for agriculture, we have 106,000 

establishments reporting to us each quarter. 

 And so we put out data at the national 

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level, we also put it out by state and by county. 

And the QCEW program has always had -- our 

program culture has been focused on local data. 

So if you're interested in knowing what ag looks 

like in a portion of your state or the county 

that you're in, you know, we already have that 

information. 

 So what are the data that we collect? 

Our data items are extremely simple because it's 

coming from this administrative data source. 

We're taking employment for the week of the 12th, 

as we commonly use across all statistical 

programs, for each month of the quarter. 

 So I'm just putting out first quarter 

2019, so that's January, February, March 

employment, and we're taking total wages for the 

quarter. 

 All right, so what are the total 

wages? We have no breakout of that wages. We 

have no data stream that tells us anything about 

hours. 

 Now, what we do is, we create a -- so 

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you've got a total -- quarterly wage total for 

every industry, and when we're doing it by the 

NAICS industry classification system, you've got 

the total wage number for anything down to the 

six-digit NAICS level. 

 We also create an average weekly wage 

number, and that's really a very crude measure. 

We take the total wages and then we take the 

average wage for that month one, month two, month 

three employment, that average employment for the 

quarter, and then divide average weekly wage, the 

total wages by 13 weeks in the quarter. 

 So you guys know that the number of 

hours that people work move up and down. It's 

not that regular, but that's what we offer. So 

another --

 CHAIR CARR: If I could interrupt you 

right there just a minute. 

 MR. HILES: Sure. 

 CHAIR CARR: So you do 13 weeks and 

what do you assume, is it a 40-hour work week, 

because you said you're not collecting the hours, 

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but you got a gross wage paid, or reported, and 

you're dividing that by 13 weeks to come to a 

weekly one, then the next step is, what do you 

divide that wage by to get to the hourly wage 

rate? 

 MR. HILES: All right. So you've got 

so the total quarterly wage, you've got a wage 

for the entire quarter, when you divide it by 13, 

it turns it into a weekly wage total. And then 

what we divide that by is by an average of the 

employment over the quarter, okay? 

 So total wages divided by employment 

gives you the average weekly wage per employee. 

 CHAIR CARR: So when somebody sees a 

weekly wage per employee, how would they 

determine that down to an hourly wage per 

employee? 

 MR. HILES: Right. So if you're going 

to do that, instead of dividing it by 13, you'd 

divide it by the number of hours that you wanted 

to arbitrarily assign to a quarter, because we're 

doing -- so the thing about -- when I say, 

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arbitrarily, we pick 13, that works, and then 

when you have a, you know, the kind of calendar 

that we have, but people who get paid every two 

weeks notice that some months you get paid three 

times in a month. 

 So there's some variation in the 

amount of pay that gets paid in the quarter, so 

you might have seven pay periods in one quarter 

and six in the next. Just the way the pay dates 

hit. 

 So we don't know the pay dates of 

those records, so we've got 106,000 

establishments in ag, we have over 10 million 

across the entire industry, and we don't have a 

data item in there telling us, you know, what 

your pay date is or whether you're paying once a 

month or once a week. 

 So when we add everybody up, people 

have different periods of pay. One unusual part 

of that is Federal Government, since we all get 

paid every two weeks, so we'll have some big 

spikes in those quarterly wage numbers. 

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 Another thing that we have is location 

quotients, which is a measure of the intensity of 

ag in a particular part of the country. So you 

can see which part of the country has a greater 

emphasis on ag, you know, at the county level or 

at the state level. 

 So I think the other thing that I 

think is important for this audience is, what are 

the kind of employers that we count in the 

administrative data of this unemployment 

insurance data that is our base for our data 

stream? 

 There's a federal definition that is 

based on 20,000 wages, 20,000 of wages in any 

quarter, in the current or prior year, or ten or 

more workers for one day in 20 weeks in the 

current or prior year. 

 And so if you think about the kind of 

farms that are going to have that, you're 

basically looking at your larger establishments. 

 But we actually -- it is actually 

supplemented in the number of states where 

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they've taken that federal guideline and asked 

for a more tighter definition of who's included 

in this unemployment insurance system. 

 So for California, you're in our scope 

and you're in the data that's reported for us, if 

you have one employee at a time, and wages more 

than $1000 in a calendar quarter. So that gets 

to pretty small establishments. 

 MR. HUGHES: David, let me jump in for 

a second. 

 MR. HILES: Yes. 

 MR. HUGHES: So we're 15 minutes off 

from shifting to Brian Pasternak's presentation, 

was there any additional questions that you all 

have for Jody? 

 CHAIR CARR: I have one more, Jody. 

 MR. MCDANIEL: Okay. 

 CHAIR CARR: Going back to your farm 

census, back in the number that matters, 2.4 

million employees recognized, that is actually 

owners, operators, and employees other than these 

employed by farm labor contractors. 

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 MR. MCDANIEL: Yes, sir. 

 CHAIR CARR: But the question with 

that is, is that a real number or if you employed 

a worker and I employed that same worker the next 

quarter, and then maybe somebody else employed 

them in the third quarter, because they actually 

moved around from farm to farm, aren't we all 

counting that same worker and that worker will be 

counted three times? 

 MR. MCDANIEL: For the census of 

agriculture, there would be that potential if 

they worked more than 150 days on multiple farms. 

In the annual program, no, it is the cycle of how 

the data is done. 

 CHAIR CARR: Right. That's weekly 

capture on that, so the difference between that 

is, and this is where the argument comes from, 

you got a census data that says there's 2.4 

million, but the largest pool you've had on a 

quarterly basis has been 817,000, I think? 

 MR. MCDANIEL: Yes, sir. 

 CHAIR CARR: That's a huge difference 

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when you're reporting the number of workers. So 

if you take the -- segue to July, August is 

obviously the busiest time of the year, it could 

be, for other people, not, but it's usually about 

800,000 workers reported, based on your survey 

data, but then you got a census data that says 

2.4 million, doesn't make sense. 

 MR. MCDANIEL: Yes, when you connect 

the two data streams, you hit the nail on the 

head, you've got the potential to where, because 

you asked about that for the year 2017. 

 CHAIR CARR: So in the fruit and 

vegetable industry, where we have a lot of 

seasonal work, workers do work from one operation 

to the next, because just the sheer nature that 

we don't have work in certain parts of the 

season, but somebody else may. Citrus in Florida 

versus onions in Georgia, you know, could be 

doing some type of work in California, then they 

go up to Washington state and pick apples. 

 MR. MCDANIEL: Yes, you're not finding 

traditional farmhands like where I grew up in 

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Southeastern Illinois that, somebody works fulltime year round, and they fix fence when they're 

not running a tractor. Yes, you find seasonal 

work. 

 MS. HARPER-LARSEN: Do you ask about 

that in the survey questions currently, you know, 

how many of these workers work for you X number 

of days? I mean, couldn't you work out an error 

rate based on that? 

 MR. MCDANIEL: So if you go back to 

the focus and the intent of the Census of 

Agriculture, it's to inform the broad sense of 

agriculture, which is the program Chandler had 

asked -- or Chalmers had asked about. 

 So if we go to the annual program, 

because of having that base week set on the 12th 

of a given month, that systemically takes care of 

itself, unless you are telling me there are 

workers who work on five different farms in a 

given five-day cycle. 

 MS. HARPER-LARSEN: They may work on 

two. Maybe three. 

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 MR. MCDANIEL: So when we do a sample 

of 39,000 farms, so for instance, if you receive 

a questionnaire, and you're representing X number 

of other farms, so it's that perspective piece. 

There's 2.04 million farms, roughly, and we're 

trying to project the labor for all of those, and 

we're doing it off of 39,000, so there's a lot of 

underlying statistical models and things that are 

done to account for the noise in the data. 

 MR. WINGARD: Couldn't you ask the 

question and let the answer -- or ask the 

question looking for the answer of full-time 

equivalents? 

 MR. MCDANIEL: There are a lot of ways 

we could go about looking at it, so I'll go back 

to, again, we're drafting a questionnaire to 

clear the Office of Management Budget, trying to 

minimize the burden on individuals as 

respondents, and still reach the broadest 

audience. 

 So how we go about doing that is, we 

collect hours and total wages, and total base 

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wages, because that's the most applicable across 

the industry as a whole, but, yes, we could ask, 

assuming that respondents are willing to give us 

that data. 

 MS. HARPER-LARSEN: We have to have 

that number in relation to full-time equivalency 

for FSMA data to know what our compliance states 

are. 

 MR. MCDANIEL: And I don't disagree, 

but again, you are part of a broader industry, 

and what we draft is a questionnaire that's 

supposed to be workable across all parts of the 

industry, so ranches in the west, grain farms in 

the Midwest and upper Midwest, produce farms, so 

it goes back to, we have to temper respondent 

burden, provide the data that meets the needs, 

because actually, the Farm Labor Survey informs 

two needs. 

 Most likely the reason I'm here today 

is because of the adverse effect wage rate and 

its impact on production agriculture, but also 

informs the parity priced indices, which is a 

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measure of the success of the agricultural 

sector. 

 So it's balancing those two primary 

data needs. 

 CHAIR CARR: The last question. You 

had on data from January of this year, already 

published in April of this year, already 

published, do you know what the increases are 

versus the same period the year before? 

 MR. MCDANIEL: As a matter of fact, 

those I have. So if you go year to year, so for 

the reference weeks, what you're going to find is 

that, on average, the average wage is around 

$14.71 an hour during April 2019. It's about a 7 

percent increase over April of 2018. 

 CHAIR CARR: Just so everybody knows, 

that's generally a straight correlation to what 

the annual increase is going to be in your area, 

so that you gave the national one, what is the 

highest region? 

 MR. MCDANIEL: I would love to tell 

you I memorized all the quarterly reports we 

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release every year, so if you were to look at 

wage rates by type of worker for January, for 

instance, the combined wage rate for all hired 

workers ranges from, and again, this is a quick 

scan, slightly less than -- or a little more than 

$12, and that's going to be in Florida, in 

January, to almost $17 in Hawaii at the same time 

window. 

 So there's a range, depending on your 

region. 

 CHAIR CARR: But you're saying, so 

last year, we all, under the incentive program, 

witnessed a 6.2 percent national increase in the 

AEWR, you're already targeting a 7 percent, based 

on your data, but there were regions, like 

Colorado, where Bruce is from, that saw a 22 

percent increase. 

 Is there one region right now that is 

screaming that they've got a pretty significant 

increase from one year to the next? 

 MR. MCDANIEL: Beyond Bruce? 

 CHAIR CARR: Well, Bruce --

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 MR. MCDANIEL: It's funny, Bruce's 

region has been screaming. I've had a lot of 

conversations about Bruce's region. 

 CHAIR CARR: Is that going to happen 

again going in 2020? 

 MR. MCDANIEL: So the thing that I 

hope I can convey today is that, because we are a 

non-policy forming, a statistical organization, 

our job is to collect the data, analyze the data, 

and put out the best data product that is 

reflective on what you all are telling us. 

 I will go to your comment about the 

impact of the AEWR on what you're seeing on the 

annual wage rate. We did a special tabulation, 

we've done it over the last two years, roughly 

less than 5 percent of the sampled respondents in 

our Farm Labor Survey actually even employ H-2A. 

 So I think there's, not saying myth 

busting, but there's a perception that the AEWR 

drives what we see in our survey, with only less 

than 5 percent on an annual basis, and I forget, 

I don't know the special tab number that it was 

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calculated off of, it's hard to believe that that 

is the full breadth of what's causing an increase 

in annualized wage rates. 

 CHAIR CARR: Well, I don't disagree 

with you at all. We got a decrease in supply of 

labor that is driving wage rates up. Now, having 

AEWR data out there in certain areas can't hurt 

you, BLS data in Saluda County in South Carolina 

versus Edgefield County, is completely different, 

because one respondent was H-2A respondent, who's 

put in his wage rates, and so you're talking a $4 

difference for the same occupation within 15 

miles. 

 So it is, again, data size and 

everything, but back to my question is, though, 

we're trending -- last year, we trend nationally, 

6 percent up, you're already saying the first two 

quarters are indicating a 7 percent increase --

 MR. MCDANIEL: That's 7 and 6, but 

yes. 

 CHAIR CARR: Okay. And there was some 

pretty big hits out, especially out in the 

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Colorado, Wyoming areas, and producers need to 

know if they're going to see this again. I mean, 

7 percent already is tough. 

 MR. MCDANIEL: So the one piece, and 

to speak specifically, so to go back and look at 

a trend line over a three-year cycle for, and, 

Bruce, sorry to pick on you, in Bruce's area, no 

one reached out to us in that two years out of 

those three years, where there was actually a 

declining wage rate on an annualized basis. 

 It's funny how data works that way. 

When you take it over a three-year cycle, they're 

showing the same percent increase as across the 

country. It just so happened that they're 

increase became very prevalent in one year's 

data. 

 So I'm painfully intimately familiar 

with the study. I spent the better part of my 

last six months having conversations about it. 

What I can tell you is, there were no anomalies 

in that data. The data is solid. The variances 

are tight. It is truly based on what producers 

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reported. 

 And there is a sample, so it is a 

sample of producers, and you have to take that 

into account, but it is very -- it is a 

reflective wage rate for what is reported. 

 I'm waiting for Darrell to pull me off 

the machine. 

 CHAIR CARR: David, back to Charles' 

question again, I think you said it, but how do 

you distinguish a farm labor contractor, is it by 

the employer's identification number that 

identifies him as not only as a farmer, but as a 

farm labor contractor? 

 How can you identify that -- how could 

I go to your data and ask you to tell me how many 

employees worked in July the 12th for a farm 

labor contractors in our force? 

 MR. HILES: We get that, and I'm going 

to follow-up on one other question about what 

happens with people who work in different 

establishments. 

 So we would call it a multiple --

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somebody who has multiple job offers. So say 

somebody works in a farm and also works in town, 

right? Our data is reported by employers, okay? 

So if the person's working in the farm enterprise 

and there in the scope, that's a count of one 

employee in that. 

 And then they're working in town in a 

department store, so we count one in that 

department store as reported as well. So one 

person, two jobs. 

 So how do we put employers into 

economic categories? So when an employer enters 

operation in the state, they have to register 

with the state unemployment insurance agency and 

they have to sort of self-identify, what are they 

doing? 

 There's like a -- you know, you got to 

a website, and there's a pulldown thing, and you 

try and find one that sort of matches what you're 

doing. And in many states, you'll type in a 

narrative as well. 

 So that'll be your initial selfNeal R. Gross and Co., Inc. 

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coding, and then there'll be a quality control 

work on that later one where we sort of see, does 

that match up with what we're getting for that 

employer. 

 That's the first time the person --

the employer shows up in our system. We also 

have a three-year cycle where we re-contact 

people saying, three years ago, you said you were 

doing Department of Labor contracting in, you 

know, in the Washington area, are you still doing 

that? 

 And they'll say, well, I'm still doing 

that work or I switched over to something else 

and I'm now in a different county. 

 So we're refreshing that 

classification every three years. 

 CHAIR CARR: My next question has --

 MR. HILES: So it's nothing to do with 

the EIN. We do have the EIN, but we're basing it 

on --

 CHAIR CARR: The occupation code that 

they put in. 

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 MR. HILES: It would be their industry 

code, so that we don't have any occupational 

information. 

 CHAIR CARR: So you go to these 

multiple classes of equipment operators, versus 

harvester, versus agriculture, how are you going 

to --

 MR. HILES: Those are all 

occupational. 

 CHAIR CARR: That's all occupational, 

so that wouldn't be covered under your survey? 

 MR. HILES: So if there's a company 

that's providing that service, so if there's a 

harvesting company that's coming in and running 

people's fields, right? That company is 

providing an agricultural support service. I 

can't remember exactly which one it would be. 

 So if that's what that company does, 

that's the primary job activity of that company. 

 CHAIR CARR: Well, let's take citrus 

harvesting in Florida. 

 MR. HILES: Okay. So you have a big 

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crew that comes into an orchard? 

 CHAIR CARR: Right. And they come in 

with --

 MR. HILES: So if they're not employed 

by the orchard owner, they're contracted. 

 CHAIR CARR: Right, right. And some 

of them are harvesters, some of them are 

equipment operators, and they could be supplying 

the packaging down the road, packaging that 

harvest as well, how do you determine the wages 

for those three different classifications when 

that employer most likely is filling out one --

that he's doing one service? 

 MR. HILES: Right. So this is all 

dependent on how the employer decides to organize 

his activity. If he wants to separately organize 

his workforce so the people running equipment are 

a different company than the one that's doing 

the, I don't know what you're calling, the 

picking or some other activity, then we would 

say, okay, well, you've got Company A, you've got 

Company B, and Company C, they're all actually 

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run by Enterprise Z. 

 But if they're saying, here's these 

three things, we're saying, what is the specific 

thing each entity is doing? 

 MR. HUGHES: Okay. Let me jump in 

really quickly. Because of the drilling, it's 

getting hard for Sam to transcribe and catch 

everything. I'm going to have multiple mics come 

up so that we can place them on the table and 

have them amplify the volume. 

 If you're speaking, I'm going to ask 

everyone to standup and project until the mics 

get here so that we can get everything on the 

record. 

 And you can go ahead and finish 

speaking, speak directly into the mic so that it 

captures it. 

 MR. HILES: All right. 

 MR. HUGHES: You're up next in, like, 

two minutes to transition. 

 MR. HILES: All right. So any other 

questions? 

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 CHAIR CARR: So again, Chalmers Carr, 

so that's still -- right now, because the H-2A 

program doesn't require different wage rates, one 

wage rate, no matter what, for farm workers, you 

don't have a subset of data to use going forward. 

That's what I'm concerned about it is, how we're 

going to make this transition when a farm labor 

contractor or a fixed site employer, I have 

grader, sorters, I have equipment operators, but 

I only report one wage. 

 MR. HILES: Right. 

 CHAIR CARR: So where's it going to be 

a starting point for this? How are we going to 

get started with this? 

 MR. HILES: Well, so the farm labor 

contractor will be doing the reporting to the tax 

group that we eventually get hold of that data. 

And there's no industry classification that's 

called H-2A. That's a type of worker and we're 

looking at, what is the economic activity, not 

the type of employee, so we don't have the 

occupational stuff. 

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 Department stores have lots of truck 

drivers, but I just -- we just know that they're 

a department store. They do the department 

store, they have the retail location, they have a 

warehouse, they have a corporate headquarters. 

 Warehousers are classified as 

warehouse industry, not in department stores. So 

you had a question in the corner? 

 MR. WINGARD: I just want to know, how 

do we tell how many farm workers are in the 

country, because as we debate, potentially, a new 

guest worker program, we need a number that we 

can hang our hat on. 

 MR. HILES: All right. So we count 

those people that are in those bigger 

establishments, right? And so when we compare 

our count of agricultural employment, we're 

counting it -- we're comparing it against the 

household survey that the BLS conducts that has a 

national number for agricultural employees, which 

includes people that are self-employed and also 

people that are on -- in a wage and salary job in 

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the agricultural sector. 

 And that's the household survey, and 

that's -- they have an estimate there, and what 

our number coming out of our thing for the larger 

operations, is about half that count. 

 So, you know, I'm not going to tell 

you to multiply it by 12, by 2, but some people 

might do that. And the thing is, like, for 

California, I was talking earlier that some 

states, a number of states, tighten up the 

definition so they're getting the much smaller 

establishments. 

 California, Washington State, one 

employee, and then they have an exclusion for 

labor that's working there between school terms, 

so your summer, you know, kids from high school. 

Florida, 5 employees in 20 weeks, Texas, 3 

employees in 20 weeks, Minnesota, 4 in 20 weeks, 

so those are the exceptions for that -- the much 

looser category specified by the Federal 

Government. 

 So I think if you wanted to get that 

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universal count, it might be that that current 

population survey number might be a good one to 

take a look at. 

 MR. WINGARD: Maybe NASS should ask 

one question, how many workers worked on your 

farm or how many contract workers do you have, 

instead of relying on your contractor to go to a 

different -- to reply to a different survey. 

 I know we're running out of time. 

 MR. MCDANIEL: I'll entertain the 

question and then I'm going to transition it over 

to Brian, which is who you all probably really 

want to talk to. 

 So I appreciate that you think it's 

that simple, and I'm sad that we aren't giving 

you the data that meets your need, so what I 

would offer is that we always have a public 

comment period when we put out a federal register 

notice for the program. 

 If this committee finds that there is 

a sliver bullet that, clearly, we cannot 

articulate from the federal sector, we are happy 

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to investigate how to best do that. 

 I appreciate your question, but in all 

honesty, if you hire a farm labor contractor, do 

you know how many people they have running that 

equipment at that orchard in Florida? Do you 

honestly care how many bodies they have on the 

ground, because we need to know the number of 

workers, not that the work is done. 

 I would assume, as producer, you care 

that the work got done and how much you paid. 

 (Simultaneous speaking.) 

 CHAIR CARR: I think we do. 

 MR. MCDANIEL: When we went out to do 

cognitive research, I appreciate that you're 

telling me you know, but I'm also -- we were not 

able to get that data. People were not willing. 

Yes. Thank you, Darrell. Thank you, all. 

 MR. HUGHES: All right. So before 

Brian talks, I was successful in convincing the 

contractors to stop doing what they were doing 

and move on to something else, but just in case 

some boss tells them that they need to go back to 

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working, I'm still going to have them come in and 

-- did they come in and put mics already? 

 CHAIR CARR: No. 

 MR. HUGHES: They haven't? Okay. So 

if that happens, we'll just keep going with the 

flow, but come on, Brian. If you don't mind, can 

you self-introduce while I --

 MR. PASTERNAK: Yes, I will. Good 

afternoon. I'm Brian Pasternak, Deputy 

Administrator, Office of Foreign Labor 

Certification. I work for the U.S. Department of 

Labor. 

 Been running the employment-based 

immigration programs in Labor for about the last 

15 years at the federal level. I used to work 

for about six years with the Department of Labor 

in the State of Maryland, involved some of these 

programs as well, so it's a pleasure to be here. 

 I do want to say that for this H-2A 

program, the department has two pending 

regulatory actions designed to modernize the H-2A 

program. This, as I understood it from the 

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request, we were -- I was to talk a little bit 

about the current state of the program as it 

exists. 

 If there is a need to discuss part of 

the proposed rule, then I informed Darrell that, 

you know, I got to do the APA requirement of 

filling out the ex parte form, I have to get the 

names of everyone here, and provide a summary of 

the discussion, so my intention was not to come 

today and talk about the proposed rule, the large 

one, which is part of the president's initiative 

to modernize the whole H-2A program, or big parts 

of it, was not something I was to discuss today. 

 So if the question comes up, just be 

aware that that's what I'll have to do. 

 Can you turn to the next one there? 

Coming into this program is not for the faint of 

heart. People think of it as a three-legged 

stool, but it's actually a four-legged stool, and 

we are the first step in the H-2A program. 

 Growers have to file applications with 

us, that's what our office does, our customer is 

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the employer. We don't deal with foreign 

workers. We don't get into visa status or 

anything like that. 

 So we are looking at the employer's 

need, we're looking at whether or not the work 

that they need performed qualifies as 

agriculture, and I'll talk a little bit about 

that in a minute. 

 We help facilitate the labor market 

test and there's no U.S. workers that have 

applied, that the grower can lawfully reject, 

we'll provide certifications, and then they're 

moving on to USCIS, which also kind of deals with 

the customer, the employer, to classify their 

request for workers under the H-2A visa. 

 But then the immigration system shifts 

and turns on its head, and it moves to being a 

more worker-based system, where the foreign 

workers are working with labor recruiters, or 

agents abroad, and they're going to consulates to 

get interviews, and then they got to make their 

way to the border, cross CBP, should they get 

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issued a visa. 

 So at any point in this process, which 

is a really fragile process, any grower could be 

denied any part or all of the workers, even from 

the start, once I even issue a certification. 

 Part of the reason why when you look 

at data in the immigration system, in H-2A, from 

where I start to where there are entries and 

exits out of the system, the numbers don't 

matchup because the numbers I see at the front 

end of the system are jobs. They're not 

associated with a person yet. 

 And in many cases, growers are 

estimating, at the time that they're filing with 

me, what they think they need. 

 We do have a bit of a practice in the 

office that we don't really, you know, question 

these numbers that you're asking for unless 

they're kind of wildly different from prior 

applications you're asking for. And we may ask 

for an explanation about why you need more or 

less in a certain year. 

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 We don't tend to get too involved in 

what the grower's actual need is, but we also 

don't, sort of, count it against the grower if 

they are, you know, maybe through an audit or 

something, we find that they have employed 75 or 

80 percent of the workers that they got certified 

for, there may be very legitimate reasons, based 

on climate or harvesting activities, or something 

like that, that may have not -- haven't had a 

need, actually, for all those workers they got 

certified for. 

 I think I'm on my own here. All 

right. And I didn't intend to go through all the 

slides. I always handout a few more slides than 

you really need, they're just good for reference 

purposes. 

 This is a picture of the program since 

'08. This is the fastest growing visa program 

that I got in the office, by far. We did more 

than 11,000 certifications last year. That's the 

largest I have done. 

 We've actually exceeded 12,000 already 

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this year, and I still got two months left in the 

fiscal year, so we are even heavier on volume 

this year than we were last year, and I'm just 

quite -- I'm not certain I'm going to be able to 

see the -- and I don't know where the ceiling is 

on this program just yet. 

 You know, we're up near a quarter of 

a million, we'll probably get near about 270,000 

this year, so that just sort of builds on the 

double-digit increases in the program. 

 You can see from the slide here that 

we have about a 97 percent certification rate. 

That's kind of an approval rate. So that should 

sort of tell you that, if you're a grower out 

there and you want to use the program, there's 

about a 97 percent chance you're going to get 

certified and be able to move forward, okay? 

 So it's not a denial-based program. 

The other is that the interesting stats that I 

like to point out is, you know, even though we 

issue almost 2/3 of the certs, 62 percent of the 

decisions we issue do go to an individual farm or 

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ranch; ranching operation. 

 If you look at the proportion of the 

labor needs that are going to farms, 42 percent 

of them are being filled by labor contractors. I 

think Chalmers made a comment about that and we 

have some pretty intense areas of the country 

that use the program and they predominantly use 

labor contractors, which is a perfectly valid 

business model. 

 But they are predominantly almost 

employing one out of every two workers that we're 

certifying, or demanding for jobs, and the trend 

down there for the top five states kind of shows 

you where we were about ten years ago and where 

we're at today, or last year, and it's even 

higher for those states today. 

 CHAIR CARR: Brian, can you speak to 

that statistic right there, the 43 percent of 

farm labor contractors, say, back in 2012, '13, 

when we were down at the 60,000, what was the 

ratio then? 

 MR. PASTERNAK: About in the low 30s. 

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 CHAIR CARR: It's believed that a 

majority of this growth that's happened in the 

program is happening through farm labor 

contractor employment --

 MR. PASTERNAK: Correct. 

 CHAIR CARR: -- but not necessarily 

farmers participating in the program. 

 MR. PASTERNAK: Correct. Yes. 

Absolutely. We were seeing a lot more demand for 

use of the labor contractors in the program, 

which, quite frankly, is servicing dozens of 

individual farms, so we totally get that. 

 This is just another snapshot of how 

our workload looks. The last chart I showed you 

is year-to-year demand, this is a look at how the 

growers come to us for workload needs -- or labor 

needs, during the course of a calendar year. 

 When you look at the blue line, which 

is 2008, versus what we got in last year in the 

program. So you can see one of our issues that 

we have, because we process these applications 

for employers -- I strayed from the mic, can you 

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go back? 

 Sorry. If you look at the top end of 

the blue line, in January, there was one point of 

the year where we got, you know, about 1,000 

applications in that month. And that's a lot of 

the early planting season, kind of, applications 

that we get. 

 Last year, we saw at least that volume 

for almost five months out of the year. And I 

used to be able to staff this program and our 

processing centers pretty equitably, where I 

could put a lot of people on the processing line 

in January and February, work through a big bulk 

of applications, and then move them off to work 

H-1B applications, or 2B applications, or green 

cards. 

 And now that same workload is bigger 

and lasting longer in the processing center, and 

it comes twice a year. 

 So it's a program that is really, 

really taking off. And I think at, sort of, last 

estimates, we're talking about what's the total 

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size of the farm labor force, you know, when 

you're doing 270,000 jobs and you may get 2.4 

million, or it's probably a little bit higher 

than that, you know, that's almost 15, 20 percent 

of the domestic labor force in this country and 

agriculture possesses an H-2A visa. 

 MR. ERICKSON: You're describing 2019, 

right? 

 MR. PASTERNAK: This one is last year. 

 MR. ERICKSON: Is 2018. 

 MR. PASTERNAK: And it's even more 

sustained this year. It's pretty close to the 

same. 

 MR. ERICKSON: Just, like, for my 

visual -- for my brain, could you, like, kind of, 

like, draw a line there for what you think 2019 

looks like? 

 MR. PASTERNAK: So taking in, again, 

sort of, one more month, at this filing volume 

level, right, so it's getting much bigger. And, 

you know, driving the demand, yes, I mean, it's 

the labor contractors, but also, I mean, the 

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domestic farm labor force, I mean, there is a 

fairly strong demographic crisis coming in 

agriculture. 

 And I don't care if you say the number 

is 2.4 million or 3 million. When the average 

age of that population is in the 40s, are 

demonstrably not migrating much anymore, are 

staying retained with the same employer they 

worked for for longer, and their kids aren't 

being trained to go into the fields, I don't care 

what the number is, there is a demographic 

crisis, because that's not the available labor 

pool. 

 If you stop and think about it, the 

big number is not the available labor pool. 

That's not the group of people who might be 

interested in these kinds of jobs. 

 So to think the conversation is 

clearly more nuanced about, what does the 

domestic farm labor force really look like from 

the demographic standpoint? Because I see a 

demographic crisis in agriculture is, really, the 

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farm labor. 

 I mean, my girls are in high school, 

one going to college, they haven't been trained 

to work in the fields. They're being asked to go 

into STEM. So where is the labor coming from? 

 CHAIR CARR: Well, you started out 

with saying, you don't know where the ceiling is 

of the program, and we sat here 15 minutes before 

that trying to figure out the labor pool, it's 

somewhere between NASS' 812,000 on a hired week, 

and the farm labor contractors employee base, 

which is probably somewhere truly about 1.4 

total. 

 MR. PASTERNAK: Mm-hmm. 

 CHAIR CARR: You take 90 percent of 

that, that's your ceiling in ten years. You're 

going to get to that level in ten years in this 

program. 

 MR. PASTERNAK: That's probably pretty 

realistic. 

 CHAIR CARR: There's nowhere else this 

labor's coming from. 

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 MR. PASTERNAK: Yes, in my comment 

about the 270,000 divided into the 2.4, it's 

actually 270,000 into the 1.4. It's worse. The 

penetration rate of H-2A visa in agriculture 

where agriculture sector is needed, is higher. A 

lot higher. 

 CHAIR CARR: What is your percent of 

reducing an employer -- because you have to do 

your labor cert and make there's no labor, what 

percent of these in the recruitment process are 

numbers actually lower from what an employer puts 

down based on the labor survey saying there's 

workers available? 

 MR. PASTERNAK: Hardly any, because 

the labor market test, and I'll get to this in a 

second, because the processing time, which is 

predominantly defined under statute, when you can 

file, when I can issue an initial decision, and 

when I have to issue a cert, is so crunched that 

there's absolutely little actual positive 

recruitment that a U.S. worker could affect my 

decision. 

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 That's why the program has something 

that's called a 50 percent rule, which is a 

method of how the program deals with allowing a 

grower to move forward to bring in foreign 

workers to give American workers a continued 

opportunity to possibly see the job and apply for 

the job. 

 So the certifications and the 

processing these applications, on average, are 

anywhere from 15 to 20 days. There's only one 

visa program that I process faster than that, and 

that's H-1B, and the whole reason it's faster is 

because Congress said, you got seven days to get 

rid of this case. Yes, sir. 

 MR. SMITH: Has there been any thought 

process to allowing H-2A workers in a processing 

plant that does fresh produce, or, like in our 

case, we do tomatoes, fresh tomatoes, but we 

can't use H-2A workers in the factory because 

that's classified different, but it's a farm 

product, and it's the same problem of 

availability of workers that's in the fields. 

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 MR. PASTERNAK: Yes, I think much 

depends on like in particular if you own the 

facility, is the facility located on the farm, 

off the farm --

 MR. SMITH: It's off the farm. 

 MR. PASTERNAK: Yes, I mean, some of 

the issues around what, and this is what I was 

going to get to before, or on this page was, the 

work has to constitute agricultural labor 

services, which are effectively defined by 

Congress under two statutes, that are, although 

broad in scope of the services that might be 

incorporated, have some built-in limitations 

around where that work is being performed and by 

whom. 

 MR. SMITH: So is there any chance 

that that could be changed at some point from a 

Department of Labor standpoint? 

 MR. PASTERNAK: So again, what I'll 

say is, Congress set the statute up to provide 

two statutory definitions for what constitutes 

agriculture, Fair Labor Standards Act, Internal 

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Revenue Service, I heard a comment made about, or 

one of the recommendations about, 51 percent and 

all this other stuff, I mean, that's not an 

Executive Branch decision. That's actually 

statutory by the Internal Revenue Service. 

 But the statute also permits the 

Secretary of Labor to define agriculture, other 

forms of agriculture, to be incorporated in H-2A, 

and that is a regulatory issue, again, which we 

have out on the street today. 

 MR. SMITH: Yes, because we can't use 

H-2B because we don't start harvest until August 

and all the H-2Bs are all gone way before that. 

 MR. PASTERNAK: Yes, exactly, you're 

way late in the H-2B season. H-2B has its own 

issues. For policy reasons, Congress did not 

want, you know, an unlimited number of workers 

coming in on H-2B, that's for sure. 

 So let me just say that, here, who's 

using the program? We talked about H-2A labor 

contractors, agricultural associations are, sort 

of, set aside. Under the law, they can use the 

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program in three ways. They can file to employ 

workers directly, they can file on behalf of one 

of their members as an agent, or they can file as 

joint employers with multiple manners. 

 So we have a mix in the program. We 

have some associations using the program in 

different ways for their members. We do tend to 

encourage the association model because we do 

think that you can get some economies to scale 

with members being able to file big master 

applications and individual members can share 

labor and transfer labor as it's needed, so 

there's some other built-in flexibilities. 

 MR. SMITH: I got it. 

 MR. PASTERNAK: You got it? Can you 

go back real quick? Sorry. And then the other 

issue that comes up in the H-2A program is --

well, it's not too often, but it's this last 

bullet, this last one about the need being 

seasonal or temporary. 

 We really, demonstrably, the work is 

seasonal. There might be some occupational areas 

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that could cause some issues in the program 

around whether or not you're really using the 

program for temporary work purposes, or are you 

really -- is it really a permanent need that you 

have for this job. 

 Agriculture is kind of a funny area. 

I mean, we have bread-and-butter harvesting, 

planting, cultivating, jobs, but there are other 

fringe jobs that are supporting the farm labor 

operation, like, packing, on farm, or camp cooks, 

or housekeepers taking care of housing for your 

farm labor force. 

 They can actually get H-2A visas 

because they're actually performing work that is 

in conjunction with the farming operation. You 

can do -- we certify crop dusters or farm 

equipment mechanics that operate and repair 

equipment in the fields, things like that, so 

there's some areas of H-2A that most people don't 

know about that can qualify, depends on the 

circumstances, but there are some built-in 

limitations. 

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 I do want to talk about wages for a 

second. There was a lot of discussion about the 

AEWR. H-2A is very unique among any program I 

got around wages. 

 CHAIR CARR: We got one question, 

Brian. 

 MR. PASTERNAK: Oh, sorry. Yes, sir. 

Yes, ma'am. Sorry. 

 MS. ELLOR: In the work that Chalmers 

and Brad did, in the recommendations, they 

pointed out that the ten-month inspection on 

statutory, that's regulatory. And I work in the 

mushroom industry, and of course, we can't 

participate --

 MR. PASTERNAK: Are they underground 

mushrooms? 

 MS. ELLOR: No. 

 MR. PASTERNAK: Oh, okay, because we 

had some underground mushroom group in 

Pennsylvania recently. 

 MS. ELLOR: Of course. And they were 

able to get their visas --

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 MR. PASTERNAK: No. You're going to 

work. 

 MS. ELLOR: And of course, lots of 

agriculture has gone to year-round work, so is 

that something you can address --

 MR. PASTERNAK: I didn't hear that. 

 MS. ELLOR: -- regulatorily, through 

regulatory means, as opposed to a legislative? 

 MR. PASTERNAK: Yes. Yes, to answer 

your question, yes. 

 MS. ELLOR: To work that into the 

wherever the ten-month --

 MR. PASTERNAK: Yes, I'm just -- sure, 

I mean, I understand that the definition of what 

constitutes work that is temporary in nature, it 

goes back to the '70s. The Labor Department had 

a policy back then that they denied every 

application that lasted longer than 11 months. 

 Resulted, when the immigration law was 

passed in '86, and that was the '70s, and the '86 

law was passed, there was a big fight between INS 

and Labor about what would constitute a temporary 

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job, and there was an OLC opinion, which led to 

what you see in USCIS' regulation, that the job 

last less than a year. 

 But they, in themselves, wouldn't 

approve a job lasting, likely more than 10-1/2, 

or 11 months, or 10 months, for that matter. The 

ten-month issue came up because of, ironically, a 

permanent green card case that was processed in 

the mid '90s, called Vito Volpe. 

 And there we had a landscaping 

employer trying to use the permanent green card 

program to employ a worker for nine or ten months 

out of the year. The judge in the case said that 

any job that was recurring, any recurring 

seasonal or peak-load job that lasts longer than 

ten months is inherently permanent in nature. 

 So people talk about the ten-month 

rule. It's a longer history of both what power 

the Labor Department in the '70s had been 

reviewing the concept of the temporary need in 

conjunction with other court decisions that have 

been issued. 

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 And of course, if you read the herder 

rule that was published 2015 in the last 

administration, there is a ten-month rule for 

range production of livestock that's not sheep or 

goat herding, right? 

 So then that sort of became part of 

the, sort of, codifying some of that. Outside of 

that, we don't strictly deny out of ten months if 

it's longer, but we raise -- it raises a question 

which then you have to explain to us how the 

nature of your need is temporary and not 

permanent, okay? 

 So it's a threshold. The ten-month 

issue is a threshold. It's not a regulatory 

provision, so you're actually right about that. 

 MR. WINGARD: I want to make a comment 

about that, and I don't mean to be smart here, 

but perhaps the length of the contract should be 

based on how many months we want to eat, because, 

I mean, we talk about our food supply here. 

 MR. PASTERNAK: It's not based on how 

much you want to eat, it's based on the need for 

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your services, and I understand what you're 

saying, although, I know that there's a lot of 

industries out there that can produce back-toback contracts for services. 

 So organizing your operations based on 

strict contracts, is that what you want to do, to 

fit into a window, isn't really a natural need. 

It's an artificial need, particularly when this 

is supposed to be a bit of a seasonal 

agricultural program. 

 So I guess I'm a little skeptical 

about that. We see this being artificially 

driven in non-agriculture is in construction, 

where people do exactly that, organize their 

contracts for landscaping to fit a particular 

window. 

 MR. WINGARD: I understand, and I just 

want a deal that allows Americans to feed 

Americans here, but I want to ask you about 

deadlines. What happens if a grower or an 

applicant misses a deadline in this process? 

 MR. PASTERNAK: Which deadline? 

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 MR. WINGARD: Well, like, if I got a 

deadline to get you something and my people don't 

get it to you --

 MR. PASTERNAK: Sure. 

 MR. WINGARD: -- does my application 

get kicked out or does it just get stopped or? 

 MR. PASTERNAK: That's a good 

question. So we have windows in which we believe 

that growers need to be filing their 

applications. We don't have a whole lot of noncompliance around windows for filing for us. 

 If there's a piece of document that I 

need, workers compensation documents, or farm 

labor contractor license, or housing 

documentation that I need, we're not denying 

those cases. We will hold them. We'll keep them 

in abeyance and we'll keep reminding either the 

grower, or the state workforce agency, or whoever 

I need to get that document from. 

 Look, we've got this application, we 

need this document. Used to be back a while ago, 

there was a policy to deny these cases and just 

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reject them, kick them out. But the denial at 

our level is pretty much a death blow and you 

have to start the whole process over again, so we 

do hold them. 

 MR. WINGARD: Well, I appreciate that. 

I reckon my main message here is, we had a couple 

of situations where we were just transferring 

workers from one state to another, because our 

production moved based on time of the year, and 

it took, like, 22 extra days to get the workers 

approved to get on a bus and travel 300 miles 

down the road. 

 So I had a lot of product in Florida, 

and no workers, a lot of workers in Carolina, but 

no product. 

 MR. PASTERNAK: Sure. Yes, it depends 

on where you're at in the process, because if you 

got certified, there's certified job 

opportunities and all you need to do is transfer 

status of those workers to the new covered 

worksite from us, you're dealing directly with 

USCIS. 

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 MR. WINGARD: Well, yes, I don't know 

which part of the government it was, but my point 

is, when we hit all our deadlines and the 

government can't, and we're dealing with crops 

that grow in 25 -- well, not 25, probably 30, 35 

days, then all of a sudden it becomes kind of 

painful because we got crops we can't get out of 

the field. 

 MR. PASTERNAK: Yes. 

 MR. WINGARD: And I got orders I can't 

fill. 

 MR. PASTERNAK: Don't disagree with 

that. That's a big problem on the government's 

end. Part of the reason why when I was showing 

the volume slides is, a lot of modernization and 

a lot of electronic filing stuff that we do in 

our -- in our -- at our level, and there's no 

electronic filing going on at USCIS, maybe there 

is now, I don't know, is there? 

 MR. WINGARD: Electronic filing? Yes. 

 MR. PASTERNAK: Electronic filing. 

Okay. For all the right paperwork? 

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 MR. WINGARD: Not all the right 

paperwork. 

 MR. PASTERNAK: All right. We have no 

recourse but to try modernizing all the proposed 

ideas that can streamline the program, maybe to 

even give us less workload at the front end, or 

provide more flexibility for the grower, or us, 

to be able to issue decisions or move -- take the 

next step on it. 

 So a lot of what we've been doing is 

in reaction to a lot of the volume that we've 

seen, typically because we know we've got 

timelines we have to try to meet. 

 MR. SMITH: And, Brian, to that point 

and to Chalmers point, and I know you don't want 

to talk about the new rules, but under the 

current rules, as a fixed site employer, he has 

to have an application for his farm in South 

Carolina and he has to have a completely separate 

one for his application in Florida, and he can't 

move those workers from one to the other, he has 

to actually transfer them. 

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 But if Chalmers were to register 

himself as a farm labor contractor, and listed 

both of those sites on his application when he 

did it, he would have been able to move those 

workers from one place to the other without doing 

any transfer. 

 MR. PASTERNAK: As long as they were 

in the same area and same employment, which is 

the biggest problem with the labor contractors, 

is, they tend to stretch their worksites too far 

and they get denied, or they get questioned and 

they're told, you can't have that same -- those 

same worksites on an application. 

 CHAIR CARR: I will say that the 

delays have gotten better. They're not near as 

bad as they were a few years ago, maybe. 

 MR. PASTERNAK: Where are you from? 

 CHAIR CARR: I don't know if I want to 

tell you. 

 MR. PASTERNAK: The state. 

 CHAIR CARR: South Carolina. 

 MR. PASTERNAK: Oh, okay. All right. 

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 CHAIR CARR: And to that point, right, 

I do the same thing, because I'm --

 MR. PASTERNAK: I'm like you. 

 CHAIR CARR: But, you know, we file 

six a year and this is the last two years has 

been better than the previous four, but even 

then, so we've never had a contract delay from 

DOL and in regards, even going through notice of 

deficiencies and everything else, so I know your 

workload has grown. 

 And I do understand things that are in 

the proposed rule to even make that better, 

because I'd somebody that'd benefit from some of 

those. But, you know, you're going to have to 

deal with this, and I know you're trying to get 

funding and everything else, but this growth at 

23 percent is only going to get -- it's growing 

that fast and so we know challenges are in front 

of you. 

 There's other challenges with the 

Department of State with the consulate notice. 

 MR. PASTERNAK: Yes. 

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 CHAIR CARR: But your team has been 

doing a great job. 

 MR. PASTERNAK: I appreciate that 

comment and I think one of the frustrations that 

we have around the funding issue is that, this is 

a public, you know, piece of information, we are 

appropriated by the Congress. We're dependent on 

the Congress doing its job on time and giving us 

adequate funding. 

 And we do propose ideas for funding 

and things like that, but, boy, I tell you, when 

you get a shutdown, we don't work. And there was 

a time in 2013 where we got shutdown for three 

weeks and I thought, when I came back in the 

office, I thought it was a hurricane had hit the 

country, because I was hearing from Florida and I 

was hearing from Arizona, and California, and 

Washington, who needed all these fall harvesting 

orders, and we couldn't work on any of them. 

 So the only fortunate thing for us 

was, last year, remember the government shutdown 

we just went through, they did get our budget 

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passed on time. If they hadn't of done that, and 

we got lumped into the Homeland Security Bill 

that went with that 40-something day government 

shutdown, we wouldn't have been on the job. 

 Nobody would have been able to access 

the program. There's no provision for going 

around us. 

 MR. HUGHES: I want to jump in real 

quick. So we're at the 15-minute break mark. We 

could just keep going until, like, 3:15, and push 

the break to 3:15, or go ahead and take the break 

now and then have you come back after the break. 

It's your call. 

 MR. PASTERNAK: Okay. So we're on 

wages. And you guys talked -- we already talked 

a lot about wages. H-2A is unique because we've 

got a wide array of different wage 

considerations. AEWR is just one of them, but 

there is another concept called prevailing hourly 

or piece rate wages in this program. Talk about 

that in a second. 

 I hardly ever see collective 

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bargaining wages. And then of course, you got 

federal and state minimum wages, but those are 

irrelevant, because the AEWR basically dominates 

everything, as we were just talking about. Go 

ahead and change the slide. 

 You all know, we do work with Jody, we 

work with the NASS staff with the farm labor 

survey. Our role in that, and I want to be clear 

about it, we do provide the financial, some parts 

for financial support for that survey. I'm the 

lead working with the NASS folks. 

 We don't get involved in our office in 

collecting data, we don't get involved in 

calculating anything, we don't analyze data that 

comes in, I literally get the data when you get 

it, when it comes out in the public publication. 

 So it's a set of numbers that we get 

from USDA and this sort of use of the Farm Labor 

Survey has a mass history to it with the Labor 

Department, dating all the way back to 1986, '87, 

when it was first used as a source for the AEWR 

by the Reagan administration. 

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 The Labor Department was sued on its 

use, defended the use of it, and ultimately, 

they've been using it ever since. 

 There is a very strong, I would say, 

form the last administration, defense in our 

current regulations for using this survey because 

of who it does serve, not -- you know, no offense 

to our BLS counterparts, but BLS was a data 

source that was used for one year in the Bush 

administration, based on the different policy 

determination, and since then, we've been back to 

the USDA Farm Labor Survey. 

 So we don't typically get involved at 

all with the calculations or anything. The NASS 

staff handle all that. 

 CHAIR CARR: So, Brian, but can you 

speak to who owns the definition of the adverse 

effect wage rate? Was that out of the language 

or is that through the Department of Labor? 

 MR. PASTERNAK: That's the Labor 

Department regulation. Yes, it is, and thank you 

for mentioning that. So that is the weighted 

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combined field and livestock hourly rate of pay 

that we've been using for years. 

 And it just operates as a mass wage 

floor. So I think the -- you know, and this is a 

factual statement, wage floors can be horribly 

inequitable in any sort of employment situation, 

and agriculture can be really bad, because you 

basically, theoretically, you can pay the picker 

$15.03 in Washington State, and the supervisors, 

H-2A supervisors, could be paid $15.03. 

 We have construction laborers that can 

qualify under H-2A to build livestock pens on 

farms, you can get an H-2A visa to be -- as a 

construction laborer to build livestock pens to 

maintain livestock, well, the construction wage 

in a local area could be at least double, you 

know, what the AEWR might be. 

 So the disadvantage of the wage floor 

is that it is a broad-based wage for everything, 

everything, and it's combined. And so we don't 

make distinctions when we're looking at an 

application and it's a grain harvesting 

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operation, or it's an apple harvesting operation, 

or it's a camp cook, or it's a construction 

laborer, the same minimum wage is still looked 

at. 

 CHAIR CARR: But out of the IRCA 

definition in '86, which is where that was 

derived from, it was designed to make sure that 

foreign workers did not depress wages for 

American workers so that producers wouldn't 

choose to go get foreign workers over American 

workers, correct? 

 MR. PASTERNAK: That's the intent, 

yes. Actually, you would likely more to find 

that in the Congressional record, as opposed to 

the actual statute, because statute doesn't 

actually mention the word AEWR, more the 

Congressional record and the history that went 

with the '86 law mentioned those things. 

 CHAIR CARR: So my question earlier 

was, is what was the number of, you know, 

certifications you lowered because of 

recruitment, and you said hardly --

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 MR. PASTERNAK: Yes. 

 CHAIR CARR: And it's less than 1 

percent. 

 MR. PASTERNAK: Yes. 

 CHAIR CARR: But more importantly, 

then you went on to 50 percent. What does your 

data say, out of all the H-2A employers, the 

11,000 certifications you did last year, going 

through to the 50 percent point, how many U.S. 

workers actually took those jobs? 

 MR. PASTERNAK: Sure. So that's 

difficult to answer because we don't -- growers, 

and you know this, you're not required to give me 

your 50 percent recruitment report. 

 CHAIR CARR: Right. 

 MR. PASTERNAK: We sort of say, we'll 

pick it up on an audit if you get audited. Now, 

we only audit a sample of H-2A employers to begin 

with, but form the sample data that we've been 

given, we have seen factually that most American 

workers, and a lot of them tend to be the 

returning workers, like, the people you may have 

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had in the prior season coming back because they 

like to work with you, or things like that, 

predominantly, those workers are coming somewhere 

near the start date, 30 days after, but then it 

really drops off. 

 It really drops off. And those 

workers getting picked up by the grower, doesn't 

mean they have to kick the H-2As out, right? 

Your H-2As are now onboard by the time some of 

that happens, the question is going to be whether 

you got the housing for everybody, you have the 

full-time work for everybody, that kind of thing, 

so growers don't have to actually get rid of 

their H-2A workers, but they do have to make a 

business decision about whether they can take on 

the American worker and also fully employ, you 

know, the H-2As. 

 But it's still, again, it's not going 

to be a large percentage of American workers 

still coming, once you get past 30 or 45 days, it 

really, really drops off. It goes next to 

nothing. 

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 Does that answer your question? 

 CHAIR CARR: I think I'll have a 

follow-up comment. 

 MR. PASTERNAK: All right. 

 MR. TISON: How does your numbers play 

with states that are raising their minimum wages 

up to $15 an hour? And how's that going to make 

-- what kind of adjustments are you going to 

have? 

 MR. PASTERNAK: None. None. Depends 

on who it is. 

 MR. TISON: I know in Florida, we're 

fixing to have a voting initiative to raise it to 

$15. 

 MR. PASTERNAK: Yes. I know in 

Maryland, and I come from Maryland, and the 

problem with the state minimum wage law is, you 

got to be careful, you have to pay attention as 

to whether or not certain groups of workers are 

being excluded from the state minimum wage law. 

That's the other thing that is kind of hard for 

us to deal with. 

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 But my home state of Maryland did pass 

a law to try to get to 15 bucks an hour for --

over, like, the next five-year period, so we do 

pay attention to the updates from the states on 

their minimum wages, but for us, we have to do 

one more deep dive and we got to at least look at 

the law to see if there's any exclusions for ag 

workers. 

 I mean, Maryland, for example, the 

seafood processing industry has an exemption for 

the state minimum wage law. 

 CHAIR CARR: But to answer your 

question, Washington State has one of the highest 

state minimum wages --

 MR. PASTERNAK: Yes. 

 CHAIR CARR: -- and it's the secondfastest H-2A growing state in the country. 

 MR. PASTERNAK: Yes, that's right. 

Exactly. 

 CHAIR CARR: Brian, my comment was, is 

through the data that we know, and we provide it 

internally, but also through the organization I 

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work with, it's less than 5 percent of Americans 

actually apply for H-2A jobs and less than 1 

percent actually finish those contracts. 

 So my whole comment to this is going 

back to the adverse effect wage rate, who are we 

trying to protect? If there's no American worker 

out there wanting these jobs, then who are we 

trying to make sure we don't adversely impact? 

 MR. PASTERNAK: Well, just bear in 

mind that the wage that we're trying to get at, 

which says whether or not the importation of the 

worker is going to adversely affect wages of 

similarly employed workers in the area, we're 

trying to get at, what are growers paying these 

workers now so that we can at least have that 

average guaranteed when the foreign workers are 

coming in. 

 Not that the people sitting around the 

area are going to apply for the job, but if they 

did, then they wouldn't be adversely affected. 

The labor market test is a different 

consideration. There's a lot of other things 

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that go into adverse effect, you know this, that 

make the program inherently uniquely different 

than any other visa program we have. 

 We don't have other -- we don't have 

Microsoft offering housing to Indian-based 

programmers. Microsoft's not even doing a labor 

market test in H-1B. Get an H-1B visa, you don't 

have to do any labor market test. You can get 

exemptions from it. 

 That's a common misunderstanding of 

the H-1B program. Only certain groups of H-1B 

dependent companies do labor market tests that 

even the statute gives exemptions to doing the 

labor market test if you pay more than $60,000 a 

year, or you're going to bring a foreign worker 

that has a Master's Degree or higher. 

 So you have lots of very high skilled 

workers coming in to this country, through the H1B visa program as an example, and I'm not 

badmouthing the H-1B visa program, I'm just 

giving it as a point of reference, where you 

think there's a lot of American workers that are 

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skilled and may be doing this work, they're 

coming in, there's still labor market tests going 

on. They're still advertising. 

 But in H-2A, it's the most intensive 

and expensive labor market test that's going on, 

both before, while you're with me, and then after 

I'm out of your hair. It's just, that's the 

reality, and some of it is all of this history 

that has been built up that led to the '86 law 

and the Congressional record that goes with it. 

It fits the program we're living with now. 

 So to Chalmers' point, you see the 

volume of the program growing. We're still 

having to work this in the law that was passed in 

'86. For God sakes, it was conceived of in the 

'70s and the early '80s, at a time when the 

domestic farm labor force was very different and 

American agriculture was very different. 

 Sorry. That's the answer --

 CHAIR CARR: You're all right. You're 

all right. 

 MR. PASTERNAK: Sorry. Can you just 

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real quick? Real quickly, the AEWR is one thing. 

There are certain areas of the country that have 

to also consider these prevailing wage or 

prevailing piece rates. These wages come from 

our state Departments of Labor. Okay. 

 So we have some money that goes to the 

state Departments of Labor. They have the 

authority, the independent authority as a state 

entity, to go out and decide, you know what, we 

want to conduct a wage survey on apple 

harvesting, pear harvesting, cherries, whatever, 

different types of agriculture activities. 

 Florida has a bunch of them, that sort 

of thing. So we get those directly from our 

state Departments of Labor. There's a really old 

set of methodology around it, they're very 

different than USDA, these have nothing to do 

with USDA, but if they come into us and they're 

valid, and they're almost 99 percent piece rates, 

and they're valid, we post them. 

 So if a grower comes in with an order 

to me in Washington State and says, we're going 

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to doing Gala apple harvesting, our staff look at 

the Washington site, and our site, but the 

Washington to see if there's any new Washington 

wage data out there on piece rates for apple 

harvesting for Gala, because if there is, then a 

growers going to have offer at least that piece 

rate. 

 Now, the piece rates are out there. 

Growers don't have to offer piece rates, but if 

they want to, there may be a wage out there that 

they have to deal with. 

 It's usually states like California, 

Washington, New York, some of the big more 

intensive ag states do give us some wages that we 

have to consider. 

 So I just wanted to say as a matter of 

point of reference, that's the other thing that 

we deal with. 

 CHAIR CARR: And, Brian, if I can just 

share with the group, because I know where you're 

going on that, and just, so in Washington State, 

they did publish, and they didn't just publish it 

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for Gala apples, they published it for about 

several different varieties, including McIntosh, 

so they have wage rates anywhere from $16.40 to 

$23 on harvesting apples. 

 Their AEWR is $15, so not only does 

the employer have to pay that wage rate for 

Galas, but if they go over to that block in the 

afternoon and pick McIntosh, they got to pay a 

different wage rate, all because the state 

workforce agency published these piece rates this 

year. 

 MR. PASTERNAK: Yes. And I think we 

got almost 60 different kinds of wage piece rates 

for different kinds of harvesting activities by 

crop, and in some cases, a lot of varieties of 

that crop for that activity. 

 And that's the tension in the program 

is, should those piece rates be more marketdriven as opposed to being determined by a state 

survey that is done at a one snapshot of a 

particular part of the year? 

 Okay. So we talked about wages. 

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That's the first step. You got to figure out 

what wage you're going to offer. And then as 

Chalmers mentioned, the second step is, you're 

filing a job with the state. 

 So in Washington's case, you're filing 

directly with the Washington Employment Security 

Department. If everything is good, they start 

the process of recruiting at that point. Now, 

that's happening about 60, 70 days before the 

start date, 75, 60, go ahead. 

 I'm going to leave this with you, but 

this is just a summary of the things that, if 

you're coming into this program, you have to be 

aware of, and things that the rule requires you 

to provide to these workers, and potentially, any 

domestic workers who are not local, the ones that 

can't get back home to their permanent residence. 

 I'll call them migrant farm domestic 

farm workers. Which again, as I mentioned, is 

getting lower and lower in this country. People 

are migrating a lot less. 

 Housing, workers comp, tools, meals, 

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meals aren't at no cost. Meals, you actually can 

charge some for meals. The transportation, 

subsistence to bring workers in and out of the 

country. A lot of these things, you go back to 

the history of this program since 50 years ago. 

 In the '50s and the '40s, you'd see 

these guarantees. And 3/4 guarantee. You know, 

3/4 of the work contract. 

 Okay. Let's skip this one. That's 

just general stuff. All right. You filed with 

the state, then you file with us, and this is all 

happening about, I don't know, we typically get 

applications 50 days before you need the workers 

to start work, but 45 days is sort of what, you 

know, generally, the law, you're supposed to be 

doing, and I don't require you to file earlier 

than that, but you can. 

 These are the basic documents that you 

send to me at the initial part of the application 

process, we have an electronic filing system, you 

can upload, scan documents, you don't have to 

email us a piece of paper. 

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 We have absolutely excellent 

compliance around electronic filing in H-2A. 

Over 90 percent are filing electronically. We 

still get paper applications, which we have to 

data enter, it's very annoying, but we do have a 

very high compliance rate. 

 And the data of the mail-ins that we 

get, people give us email addresses, so we end up 

data entering it and communicating with them 

electronically. Go ahead. 

 All right. Statutorily, I have to 

issue an up or down decision on seven days. 

Seven days after I get the application. That's 

by law. All right. If it's a deficiency, we'll 

give you an idea of what to correct. If it's 

accepted, then we're going to issue an acceptance 

letter, authorize recruitment, you'll get some 

recruitment instructions, and then you'll be told 

of any other documents that we might need that 

can help issue the certification. 

 We also work with the state workforce 

agencies because many of them have to do the 

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housing; inspecting the housing. 

 This is the basics of doing what we 

call positive recruitment for American workers. 

The note that I will place here is that we do 

have a pending regulatory action that the 

department proposed to eliminate the continued 

use of print newspaper ads. 

 So that is sort of a pending 

regulatory action which is active and the 

administration is committed to finalizing that 

regulatory action, but I'm not -- I can't comment 

any more than that. 

 So currently, you come to me today, 

you do have to do print newspaper ads and some 

other things, but we do have a proposal out there 

that would propose to eliminate it and we'll see 

how that works. 

 And just so we're all clear, you file 

at day 45, I have 7 days to issue up or down, 

that takes you to about 38 days before you need 

the workers, and if I give you the up signal, 

under the law, I have to issue the decision, as 

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long as I've got everything in my hand, 30 days 

before the start date. 

 And that's where some of the delays 

may occur, because I might be waiting for a state 

to give me a housing inspection report, the 

workers comp document may not cover the period, 

you may not have given me assurance you're going 

to renew it, that sort of thing. 

 Those are issues that could cause us 

to hold the application for a little bit longer 

waiting for you or waiting for the state to 

actually give us something. 

 And we have a proposal out there now 

waiting for OMB approval to further expedite 

moving from me to CIS, we have a proposal out 

there to transform the issuance of our labor 

certs to electronic decisions. 

 Currently, Chalmers knows this, we 

print the certification on physical paper and 

mail it to you, which you then have to use and 

send to CIS, so we have a proposal out there 

pretty actively, which we hope will be approved 

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in this month, that we will issue a one-page 

electronic certification that's emailed to the 

customer and they're able to print it out, attach 

it to their petition, and just move on to CIS 

very quickly. 

 For us, it's that whole issue of, how 

do we get people from one part of the system to 

the next, or one step to the next, as quickly as 

we can, knowing that now we're within 30 days 

where the workers got to come to the farm. 

 MS. HARPER-LARSEN: Before you go on, 

are you looking at an opportunity, instead of --

of course they need an email copy just for their 

records, but for your system to talk to their 

system? 

 MR. PASTERNAK: Yes. Yes, absolutely. 

We did a very innovative thing that we were 

hoping to replicate in these other visa programs. 

We had to implement a new visa program for the 

Commonwealth of Mariana Islands, which is out in 

the middle of the Pacific Ocean. And our 

regulation there for the first time ever, we 

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regulated that we would issue electronic certs 

and transfer the electronic data to USCIS on 

behalf of the customer. 

 So obviously, our goal here with H-2A 

and for H-2B and others is that we will give you 

an electronic copy of everything that you can 

print out, and you'll need to keep one for your 

compliance file. But the one page ecertification, when you take it to CIS, if they 

want to see the full certification, they come 

into my system and grab the data. Yes. Yes. 

We're there. 

 CHAIR CARR: But you also have to do 

a biannual form to make sure your forms would 

match up with data transfer, but you've done that 

now, I believe. 

 MR. PASTERNAK: Well, we need to have 

approval yet, but that is -- we've already done 

it in CW and we're doing it on 2B, so I don't 

have any concerns that we'll be able to do it in 

A. Yes. But that's another way that the system 

gets a little more efficient in talking from --

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to itself about what the customer needs. 

 MS. HARPER-LARSEN: Well, you also 

have a validated source from a regulatory body 

from another regular -- 

 (Simultaneous speaking.) 

 MR. PASTERNAK: Yes, yes. And that's 

exactly right. Those are the conversations we've 

had with CIS to the point where, two weeks ago, 

they put out a public announcement on H-2B saying 

that, going forward, the customer only has to 

give USCIS, on H-2B, the one-page decertification 

that we got approved by OMB. 

 And so now the paperwork has been 

utterly eliminated between us and CIS for the 

employer/customer, and we're really hoping that 

they'll do exactly the same thing for H-2A, but 

take from you that one-page de-cert. I think 

that'll be a big help. Yes, sir? 

 MR. WINGARD: In my experience -- and 

I want you to comment on it briefly. So for the 

sake of round numbers, let's just use even 

dollars. I was paying my harvesters $11, the 

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harvest manager $12 an hour, and the harvest 

supervisor $15 an hour to incentivize those guys 

to do a better job. I was told by our H-2A 

consultant, or whatever, that I couldn't pay 

above the H-2A rate. 

 MR. PASTERNAK: Now, the H-2A rate is 

just the wage floor. 

 MR. WINGARD: Well, we were -- 

 MR. PASTERNAK: It's not the wage 

ceiling. 

 MR. WINGARD: Well, that's -- 

 (Simultaneous speaking.) 

 MR. WINGARD: We were trying to 

incentivize -- 

 MR. PASTERNAK: Sure. 

 MR. WINGARD: -- you know, efficient 

work. And it was advertised in our contracts, 

which should incentivize higher wages, but we 

were told we couldn't do that. 

 MR. PASTERNAK: I'm happy to send them 

to staff and some ideas saying, you know, you can 

put in even provisions for pay for the returning 

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ones, right? You're going to get some new ones 

and you're going to get some returning ones, you 

can actually offer better wages to the returning 

ones from the new ones that may be coming in. 

 You just have to be transparent about 

it, and you have to treat everybody equally so 

that American worker has that kind of experience 

that you're working for or that it actually was 

the person that is returning, you got to make 

sure that they're being offered exactly that same 

benefit as the H-2A worker. 

 MR. WINGARD: Charles, what you're --

and I don't know who your person is, but you can 

put supervised men there, but if you didn't 

disclose the wage rate of $12 an hour for that 

line worker and $13 for that, if the USG comes in 

and audits you -- 

 MR. PASTERNAK: Yes. 

 MR. WINGARD: -- and finds that you're 

paying those workers that, then they're going to 

fine you because you didn't advertise that to the 

American worker who could've had a choice between 

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the job -- 

 MR. PASTERNAK: Yes, yes. 

 MR. WINGARD: -- because they're all 

about protecting the American worker. 

 MR. PASTERNAK: You're talking about 

Mike? 

 CHAIR CARR: No. He's using -- well 

 (Simultaneous speaking.) 

 MR. PASTERNAK: Oh, I'm sorry -- 

 (Simultaneous speaking.) 

 CHAIR CARR: But that's what's 

happening with your enforcement side. 

 MR. PASTERNAK: Yes. That's exactly 

right. Yes. The southeast enforcement guys 

would probably look at it that way. 

 (Simultaneous speaking.) 

 CHAIR CARR: -- completely different 

than the previous administration it's always what 

people want to look at. 

 MR. HUGHES: So because we're four 

minutes or three minutes, now, out from the 

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break, I want to see if there were any lingering 

questions for the other deal experts because we 

do have our next speaker, the Administrator of 

Rural Development, that has arrived, and so I 

want to make sure we break on time and start on 

time so that we don't take up -- or, eat into 

that presentation from the Administrator. 

 CHAIR CARR: I guess to be brief, 

because there may be questions -- Brian, will you 

be around -- 

 (Simultaneous speaking.) 

 MR. PASTERNAK: I can hang around. 

 CHAIR CARR: Yes. People can swap 

back and ask you or during break -- 

 (Simultaneous speaking.) 

 MR. PASTERNAK: Yes. That's fine. 

Yes. 

 MS. HARPER-LARSEN: Can we just make 

sure that we get contact information for each of 

the -- 

 MR. PASTERNAK: Yes. Yes. I'll have 

that. 

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 MR. HUGHES: Send a picture so we know 

who is who now. 

 (Laughter.) 

 MR. PASTERNAK: I'll probably -- 

 MR. HUGHES: Let me grab my government 

phone here. 

 CHAIR CARR: Is there anybody from BLS 

that hasn't spoke that's here? 

 MR. HUGHES: There are, like, three 

people. They brought their whole department with 

them. 

 CHAIR CARR: Well, they introduced 

themselves -- 

 (Simultaneous speaking.) 

 MR. HUGHES: Yes. They introduced 

themselves earlier, and the one person that 

wasn't here, he spoke the most out of all three, 

so you've heard from -- 

 (Simultaneous speaking.) 

 CHAIR CARR: But if I understand you 

right, we cannot ask questions about the BLS data 

that you're proposing to use in the new rule 

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based on these new wage classifications. Is that 

correct? 

 MR. PASTERNAK: I would advise that 

you -- we not do that here without, you know --

getting into a conversation about it would not be 

a good idea. 

 MR. HUGHES: Yes 

 MR. PASTERNAK: Yes. 

 CHAIR CARR: Thank you for all you've 

given us here today and -- 

 (Simultaneous speaking.) 

 MR. PASTERNAK: Sure. Absolutely. If 

there's any follow-up question, run them through 

staff, and I'll be happy to answer them and give 

you more information about them. 

 CHAIR CARR: All right. Thank you, 

Brian. 

 MR. PASTERNAK: Thank you. 

 CHAIR CARR: So we're going to take a 

break for 15 minutes. Be back at 3:30, staying 

on schedule. 

 (Whereupon, the above-entitled matter 

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went off the record at 3:13 p.m. and resumed at 

3:31 p.m.) 

 MS. HARPER-LARSEN: All right, 

everybody. If you could go ahead and take your 

seats. I'm going to turn the meeting over to 

Darrell and we're going to have an overview of 

the Farm Labor Housing Direct Loans & Grants 

Program from the Administrator, Bruce Lammers. 

 MR. HUGHES: So I'll just invite Bruce 

Lammers up to the podium. And just for 

clarification of the record, Bruce Lammers is the 

Administrator of Rural Development. 

 MR. LAMMERS: Rural Housing. 

 MR. HUGHES: Rural Housing? 

 MR. LAMMERS: Rural Housing Service, 

 MR. HUGHES: Oh, Rural Housing 

Service. That's under RD. All right. There we 

go. Yes. 

 MR. LAMMERS: Would you like to invite 

somebody else? 

 MR. HUGHES: Sure. No, no. Go ahead 

and take over. Go to the next slide, just let me 

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know, and I'll go ahead and --

 MR. LAMMERS: I've got some highlights 

here, so you can follow me this way, if you don't 

mind. Good afternoon. 

 All right. So everybody's here and 

it's not -- we're not between cocktails -- or, 

lunch and cocktails yet, but pretty -- closer to 

cocktails than we are to lunch. 

 As was said, I'm the Administrator of 

the Rural Housing Program. Rural Housing 

includes multifamily housing, single family 

housing in rural America as well as community 

facilities. So we like to -- I like to see it as 

a large bank. And I came from banking. I had a 

career of quite a few years of -- in banking, and 

I bought a small bank in '06 that sold in 2016, 

and made it through the recession; the Great 

Recession. And was able to sell the institution. 

I worked for my -- the people that acquired me, 

and decided that this is something that I wanted 

to do to give back to the industry. 

 So I'm a political appointee that has 

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banking experience, and we like to think -- or, 

we believe that this is a large bank that we're 

running. We make loans and grants, but that's a 

little bit of background. I grew up in a small 

town in Wisconsin, so I understand a little bit 

about agricultural production. Very little. 

What I understand is that I went to school with 

kids that came home -- came to school in the 

morning and smelled like they'd been in the barn, 

working. 

 Then I also got the opportunity to 

bale hay, and lived in a community where we had a 

packing plant that packed vegetables. And I was 

just saying to one of my folks that's here from 

the agency, I said, when I was a kid, I lived 

near the canning factory and there were all these 

people that were really migrants, and they came 

in, and there was housing there, so we had farm 

labor housing. So all of a sudden I'm trying to 

-- from 40, 50 years ago, I'm connecting the 

dots, so I see that. 

 So if you have any questions or any 

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suggestions as we go, I've got an associate, C.B. 

Alonso, who's with me, and he's the one that's 

either going to take the tough questions or write 

down your suggestions if you have them. 

 So I don't know what you know about 

Farm Labor Housing, but we provide financing for 

on-farm and off-farm housing for year-round and 

seasonal labor. If it's off-farm, means it's not 

collocated with the farm. If it's on-farm, it 

tends to be located with the farm. 

 Borrowers may apply. If they're not 

able to obtain commercial credit at a rate that's 

acceptable to provide lower-income tenants 

competitive rent, borrowers have to have 

experience managing similar housing properties, 

or control the deductibility. Borrowers include 

farmers associations, farm workers and 

nonprofits, state and local government entities, 

as well as federally recognized tribes. 

 Funds that are available, given the 

current yield curve, we still have a positive 

interest rate. But given the yield curve the way 

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it is right now in the capital markets, it may 

not look like as much of a deal, but we've got 

low interest rates. We also issue grants that 

are up to 90 percent of the project cost. 

 Payback is 33 years, 1 percent 

interest rate fixed for the life of the loan, 

which is still competitive with traditional 

financing, although it's getting there. The offfarm labor housing is available through --

annually through a Notice of Solicitation 

Application. That occurs annually and it's 

published in the federal register. The 

government lingo is we file a NOSA and that's 

when people know that they can apply. 

 On-farm labor housing is a year-round 

opportunity for credit. Preference is given to 

applications of off-farm that leverage other 

sources of funding. So those projects -- and 

I'll give you some -- a little bit of data in a 

little bit -- little while, but the off-farm tend 

to be larger projects. The on-farm tend to be 

really two to four units, maybe even one unit 

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that are housing on the farm. 

 Our program is generally appropriated 

$30 to $40 million a year for the program. And 

again, the loans are generally a 75 percent loan 

and 25 percent grant for not-for-profits. Offfarm, again, the limit for the award is $3 

million, which could be all loan or a grant 

combination. And as I said before, the off-farm 

-- or, on-farm is smaller units. So the --

basically, the funds are used for construction or 

improvement or repair of housing for domestic 

farm laborers. 

 So the irony -- or, the difference in 

the Farm Labor Housing Section 514 Program is 

that it's not -- the larger projects of off-farm 

labor aren't limited by the population density of 

the MSMA of the area that you're applying in. So 

generally you'd not be eligible if you're 35,000 

people or above on a normal USDA housing. 

 I think it's 35, right? The 35 

population requirement is generally for 

multifamily, and for farm it's not a requirement, 

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so you could actually -- as long as you're 

serving farm labor or retired farm labor, it can 

be a -- more of an urban area, although likely 

rural in character. 

 So the people that can occupy are 

laborers and -- including fish and oyster farms 

as well as on-farm processing plants like packing 

plants for pea farms. And then retired or 

disabled farm laborers, you must be a U.S. 

citizen, permanent resident or a H-2A visa 

holder. And it's generally for the low-tomoderate income households. 

 So for off-farm, the borrower must be 

a nonprofit. And for on-farm, the borrower must 

be a family farmer or family-owned operation. In 

the on-farm, the borrower is not to generate a 

profit from this, but to provide reasonably 

priced rental housing. And again, for off-farm, 

it's going to be nonprofits that generally 

operate these. 

 So it could be a farm group could get 

together, put together a nonprofit in their 

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community to be able to finance the housing for 

them. And the goal isn't for the group to make 

money. It's to build a nest egg to provide 

maintenance for the properties and reasonable 

housing for the tenants. 

 There's an application process, and, 

again, the off-farm is an annual appropriation, 

the -- or, on-farm is -- you can apply yearround. We offer no-cost assistance to the 

application process and we do technical 

assistance. 

 At this point, I'm going to give you 

a couple -- given the fact that I came from 

banking, I like numbers. The projects that we 

have in our portfolio right now, off-farm are 310 

projects, on-farm 214. But live-in units, or 

total units, 16,467, or an average of 53 units in 

each loan for the off-farm. And you can see the 

on-farm are -- average units are two with 432 

properties that we've financed. So really is --

off-farm tends to take the day. 

 Being from Wisconsin, it's -- I want 

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to point out that we have six on-farm properties 

and three off-farm properties that have been 

financed for a total of 69 properties. But the 

leader in the nation is California, followed by 

Arkansas, and Florida next. And again, you can 

kind of see the big push, or the big benefit, is 

that the nonprofits that access the off-farm 

labor housing. 

 And that's kind of our portfolio in a 

nutshell. Got suggestions, desirements or 

questions, I'd be happy to handle them. And I'll 

turn to C.B. once you ask a question because I 

only -- having been here for two and a half 

months, I've learned a lot, but there's a lot of 

knowledge that I haven't gained and I probably 

won't. 

 CHAIR CARR: Is a unit a bed? 

 MR. LAMMERS: It's a rental unit. 

 CHAIR CARR: How many -- okay. Is it 

-- sometimes we talk about beds and units? 

 MR. LAMMERS: Yes. These are 

apartments. 

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 MR. BROWN: And how many people can 

stay in a unit? 

 MR. LAMMERS: I'm going to turn to -- 

 MR. ALONSO: A unit can be both. An 

actual live-in unit can be multi-room or a bed 

depending on the type of housing that you build. 

 MR. BROWN: And what are the number of 

beds in a room? 

 MR. ALONSO: There are specifications 

in our regulations on what you can build and what 

you cannot build. Our regulation is called --

the development regulation, it's 1924(a) and 

that's got all the stipulations of building --

for building farm labor housing in there. It's a 

good regulation for architects. 

 MR. LAMMERS: But what was off-farm, 

are apartment-type units that are -- families are 

living there. 

 MR. BROWN: Okay. 

 CHAIR CARR: So for clarity, and I had 

asked for this speaker to be here. 

 MR. ALONSO: Thank you. 

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 CHAIR CARR: So I think we're going to 

see a lot of activity in your apartment because 

of the simple fact up until 18 months ago, H-2A 

workers were not allowed to use 514 housing. So 

it got put in through Congress that now H-2A 

workers are able to use 514 housing. And as we 

all know, housing is the second biggest barrier 

to entering the H-2A program. 

 So there's a lot of industries that 

never had to supply housing or there's areas in 

the country where you can't build. Florida's in 

a major housing deficit right now. So there's a 

model for nonprofits that could be -- it could be 

a nonprofit, but it could be a revenue generator. 

For farmers, people you all represent, this is 

going to become a major source for doing -- as we 

just talked about earlier with Brian being here, 

the growth in H-2A is exponential, but you still 

have to have housing. And so having farmers 

having access to build housing where you can get 

low-interest loans and do this outside of your 

farm operating funds and stuff, there's going to 

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be a lot of demand on this. 

 And I really advise anybody that you 

all are targeting to look at it because that's --

because it's relatively been an unused or an 

unknown about program because, again, most of the 

labor growth has been in the H-2A program and 

they weren't accessible to these funds. 

 (Simultaneous speaking.) 

 MR. LAMMERS: So if you can find a 

nonprofit, like a housing authority, and partner 

with them, it's a prefect avenue for you not to 

have to build or manage the housing, but to be 

able to sponsor the desire to get it. 

 MS. HARPER-LARSEN: I'm currently 

curious about the monies that are available for 

refurbishing because we have a large amount of, 

what we call, older camps that are not currently 

being used that could and are already permitted 

to a point, but could be refurbished, expanded 

upon, facilities added to make this 1924(a) 

requirement. Can you explain if there are any 

differentials for funding for remodeling versus 

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new builds? 

 MR. LAMMERS: You can use the funds to 

be able to remodel or maintain or improve the 

property, yes. 

 MS. HARPER-LARSEN: Are there -- 

 MR. LAMMERS: Any deeper and I'm going 

to have C.B. answer the question. 

 MS. HARPER-LARSEN: This is going to 

be deeper because we've got farmers -- 

 (Simultaneous speaking.) 

 MR. LAMMERS: Get ready, C.B. 

 MR. ALONSO: All right. 

 MS. HARPER-LARSEN: All right. Do you 

give a funding bonus -- 

 MR. ALONSO: No. 

 MS. HARPER-LARSEN: -- differential, 

whatever you want to call it, for a farmer versus 

a random nonprofit? 

 MR. ALONSO: Well -- 

 MS. HARPER-LARSEN: Okay. We'll 

expect that that will come from one of our 

committees. 

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 MR. LAMMERS: I would say that, no, 

but the nonprofit is probably where the -- for 

the $3 million limit, that's where you're going 

to find the opportunity. I mean, on-farm housing 

is sort of a one, two, three, four. And if you 

want any volume like you're talking about, you're 

going to need to team up with a nonprofit to be 

able to get it done. 

 CHAIR CARR: I would disagree with 

that statement. 

 MS. HARPER-LARSEN: I would too. 

 CHAIR CARR: I mean, we've built 150 

beds, which has been five units in the last five 

years. So, I mean, as far as the H-2A program, 

you're going to be looking at farmers that are 

going to put in 30 to 60 beds, and these will be 

units for people to room and built to the codes 

and everything like that. 

 MR. LAMMERS: But they can't be for 

profit. 

 CHAIR CARR: No. Not for profit, no. 

No. 

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 MR. LAMMERS: Okay. That's -- 

 CHAIR CARR: In fact, a lot of this 

farm -- if you're in the H-2A program, you have 

to provide it for free. 

 MS. HARPER-LARSEN: Yes. 

 CHAIR CARR: That's the challenge. So 

like I said, a lot of -- question would be, in 

the last five years, have you always used your 

annual allotment of money, or has there been 

money left over every year? 

 MR. ALONSO: We've used it 

 CHAIR CARR: You've used it? So you 

have enough applications to -- in the past to use 

all that monies? 

 MR. ALONSO: Yes, sir. Like the 

administrator said, it's between $30 and $40 

million and we get applications through the 

nation. However, California is the most prolific 

one, and that's for, typically, new on-farm 

labor. The NOSA allows acquisition of none RD 

projects for rehab, okay? You own an RD project 

you want it rehabbed, then you come through an 

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internal process. 

 CHAIR CARR: And I think I kind of 

asked that question. Is there a difference 

between -- is there a preference over the farmer, 

which is what USDA is supposed to be servicing 

versus the -- a nonprofit. So when you go into 

that application process, are we weighted 

equally? And then what is the -- what's then 

deciding who gets to go and who doesn't get to 

go? Is it the amount of money I'm requesting? 

If I'm already requesting 40 percent cost share 

versus 75 cost share? 

 MR. ALONSO: Let me answer it this 

way. I'm going to say off-farm versus on-farm. 

Formally, the on-farm will be the farmer versus 

the off-farm will be the nonprofit. They're two 

different processes. Our focus has been on a 

farm so that the preponderance of the funds that 

we get we put into a farm housing; however, we 

are funding every application that comes through 

for on-farm housing. 

 Now, if you guys decide to increase 

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the volume of applications coming in, then we may 

get, you know -- that in the future, we'll need 

to reallocate. But right now, we're satisfying 

that demand from both sides, on-farm and offfarm. 

 So for the group to understand that, 

you already mentioned California. There's 

several farmer labor contractors, but there's 

pretty big ones out there that are using off-site 

because they got to provide housing, too. And 

they're using these funds to build in areas of 

California where you can build still within 

driving distance of where they're servicing 

farmers, and so that's where -- so not 

necessarily nonprofit because they're finding 

somebody else to build it. 

 But that's what they're building it 

for so that farm labor contractor can have 

housing to put his H-2A workers there to farm. 

But farmers are going to have that same 

challenge, so I just want everybody to understand 

that. But that's where the -- we talk about the 

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growth of farm member contractors and they've 

already figured out this pool of money's there 

too. 

 And farmers catch on really quick as 

well; otherwise, you know, we're all going to be 

guys that -- but you're looking at a paradigm 

change as you have this transition to the H-2A 

program -- or, my believe you'll have to, is then 

now you got to provide housing. If you didn't 

provide housing, you better start figuring out 

how you're going to build it. And it's not 

cheap. It's $5,000 to $10,000 a day. And cheap 

as you can go is $5,000 and most of the time it's 

going to be 8 to 10. So if you got to fill that 

many beds, you know what the cost is. 

 MR. WINGARD: Suppose I have an 

opportunity as a farmer to buy a small apartment 

complex and it's in need of some repair. Not a 

lot. Maybe a roof and, you know, some other odd 

and end stuff. Would that qualify? 

 MR. ALONSO: Yes. 

 MR. WINGARD: Thank you. 

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 (Simultaneous speaking.) 

 MR. ALONSO: Let me expand on that. 

 (Simultaneous speaking.) 

 MR. ALONSO: I would say, yes, of 

course. However, it all depends on how you're 

going to set up the ownership. If it's going to 

be housing for your farm only -- 

 MR. WINGARD: Yes. 

 MR. ALONSO: -- then we have to go 

through the on-farm and there are some 

limitations as to whether it come from your 

ability to find similar -- well, conventional 

plans externally. See, what we're trying to 

target here are folks that cannot obtain this --

reasonable financing to provide housing for their 

workers. 

 If we look at your financial statement 

and we say, well, you know, you have ample 

ability to get financing elsewhere, you may not 

qualify. 

 MR. BROWN: Is on-farm physically --

let's say you have local farm sites. Does it 

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have to be on one of those farm sites or can onfarm be a separate piece of property as long as 

the workers are working just for you on that 

property? 

 MR. ALONSO: Exactly. As long as the 

worker that resides on that project works for 

you, your on-farm project can be anywhere. 

 MR. BROWN: Okay. 

 CHAIR CARR: You had a question? 

 MR. ZEA: Yes. Just curious because 

your admission that it's coming in -- later 

contractors are already onto it. Have you seen 

any evidence of pushback from local communities, 

particularly with planning agencies and 

permitting and all of that? I would think 

California you would've seen it -- 

 (Simultaneous speaking.) 

 MR. LAMMERS: I don't -- I'm going to 

say, I don't think so. But the -- I think the 

NOSA closes -- I mean, the applications are going 

to close the end of this September, so there may 

be projects out there that hadn't gotten the 

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community's ire yet. 

 MR. ZEA: Right. 

 MR. LAMMERS: That's a reasonable 

thing, but I -- 

 CHAIR CARR: That was my -- part of my 

question was, because farm labor contractors are 

working in multiple farms and stuff, there's 

rules about how far away they can be from the 

farm, but they're able to pick their sites where 

there may not be the right -- they may be able to 

do it in a part of the county that doesn't have 

it. But where if you're a farmer and you're in 

that county and you want to have that housing as 

close to you as you want, you may be -- by county 

ordinance, you may not be able to build. And I 

think, you know, the person will. So that's just 

kind of, like, the landscape that people 

understand. 

 MS. HARPER-LARSEN: Quick question, 

maybe for the both of you. Are we putting 

farmers at a -- being at a disadvantage here if 

we have a good year versus five previous bad 

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years, and you have a farm labor contractor who 

keeps reporting he didn't make any money? 

 MR. LAMMERS: Most farmers can't make 

any money anyhow, right? Every year's a tough 

year, even if you make money. But I will tell 

you, where Congress is right now is that if we're 

using -- and this goes from my experience in SBA 

lending to discussions at USDA. If you're 

providing favorable financing for people that can 

get financing elsewhere, we shouldn't be doing 

that. 

 And the SBA's gone through making all 

sorts of rules that banks have to certify that 

the borrower wouldn't get the money elsewhere if 

they weren't -- if they -- that they weren't 

qualified to get it elsewhere. So you got to be 

the lender of last resort and a prudent lender at 

the same time under the SBA program. So there is 

not as much noise on that in the USDA program, 

but it's a consideration that, if you can go to 

your bank and get reasonable money or, you know, 

you can find other sources of financing, by all 

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means, it's going to be hard -- once we get -- as 

you say, if the avalanche is coming here. If 

there's competition for the money, it's going to 

end up being looked at even harder above what 

we're using the money for. 

 (Simultaneous speaking.) 

 CHAIR CARR: And the farm labor 

contractors aren't going out and getting these 

loans. They're partnering with a nonprofit. 

They're going to then have a different set of 

standards to prove financial eligibility -- 

 MR. LAMMERS: Much cleaner. 

 (Simultaneous speaking.) 

 CHAIR CARR: Much cleaner. 

 MR. LAMMERS: Much cleaner is what, 

you know -- and there's all sort of 

considerations. Are we competing with the 

private sector and the money that we're giving 

out as well? You know, we're here to help the 

tenants as much as we are to help the farmers, 

so. 

 MR. TALBOTT: We had worked with Child 

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& Migrant services put in a lot of this housing 

over the last 20, 25 years. And all we were --

it was a nonprofit that put on-farm housing in a 

rental agreement with the farmer, and that system 

worked pretty well. We tried to go to 

centralized housing and there was too much 

community kickback. Like, we don't want 

centralized migrant housing, so you will run into 

it -- 

 (Simultaneous speaking.) 

 MR. LAMMERS: And you don't want to 

build housing projects tomorrow. 

 MR. TALBOTT: Right. 

 MR. LAMMERS: And that's the concern 

that you're going to see. Yes. And I'm coming 

from that as a -- from a practical, private 

industry standard rather than administrator of 

the USDA. Thank you for your time and interest, 

and I think I've got C.B.'s name in the 

attachment that's in here. Feel free to take a 

look. Thank you. 

 CHAIR CARR: So the group -- where's 

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he at? I'm just going to make a comment and say 

they handcuffed us by not letting us talk about 

the proposed rule that's out and, you know, as 

released. But in that proposed rule, if you 

notice -- if you understand the growth in the H2-

A and there's a housing shortage, a lot of people 

have used public housing, meaning hotels or 

apartments, to put H-2A workers in. 

 And the rule currently says, if it's 

not on-site farming housing, then it must meet 

state or local standards. So a hotel room has 

two queen beds in it, you put four people in it. 

But that same hotel room doesn't have enough 

window square footage to the floor square footage 

to justify four people. Under the proposed rule, 

they're going to make all public housing has to 

meet federal standards. 

 So if you've been using a farm labor 

contractor or you, yourself, has been using a 

hotel, and by state and local standards you can 

put four people in there, there's a very good 

chance that next year -- if this rule ever gets 

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passed and gets adopted, you would lose that or 

reduce your ability to only put two people in 

there because you have to meet federal standards, 

right? It's going to be a huge change for all 

the growth that's happened. 

 You saw that growth. And a lot of 

that growth was, as we determined, farm labor 

contractors who have been using public housing. 

And farm labor contractors maybe actually put six 

people in this room instead of four. But now, 

you, as a joint, employer, you would be subject 

to those same rules. So, again, I think this 

whole housing thing is only going to get worse, 

and that's why I wanted you all to hear about it. 

 MR. HUGHES: So inside of the briefing 

book, there is web printout of housing program 

101 that just talks about a lot of some of the 

stuff that's on the PowerPoint, but in more 

detail. And some other, just, additional 

information about, like, where they're coming in 

from, so. 

 MS. HARPER-LARSEN: And I just shared 

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with Darrell -- and felt that that was a very 

important thing because I was already drafting an 

email back there saying, where's all this at so 

that we can share it? So we're almost to the end 

of the day, okay? Food safety has been wanting 

to get to know each other and also get to know 

quite a few people from the USDA and the FDA. 

 And I would remiss if I didn't thank 

the members of our subcommittee, in particular, 

Molly Gleason, for stepping in a couple of times 

when I was driving down the road and she was 

taking active notes, and also Leanne Skeleton, 

for being present and offering to collaborate 

amongst the different associations and agencies 

to really come together for things to help us. 

 You guys will see that we have an 

objective statement that's pretty broad. And 

what I want to point out to you is that we see 

the role of the American producer, packer, and 

processor brands that we have a responsibility 

for the safety and security in our great nation. 

And we wholeheartedly support holding foreign 

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producers, packers, processors, and their 

importers immediately accountable to all Food 

Safety Modernization Act requirements. 

 Moving onto the next slide, you'll see 

that we have recommendation subjects. These are 

drafted a little bit differently than what many 

of your other subcommittee have had. And the 

reason for that is, our subcommittee is focused 

on, primarily, collaborating with the FDA in its 

capacity and then also the CDC in its capacity. 

So we're looking to make recommendations for more 

effort. 

 We encourage the FDA to continue to 

work with growers to develop science-based water, 

microbiological testing standards in a timely 

manner, so we're going to have Dr. Jennifer 

McEntire from United Fresh join us after my 

comments to explain to many of you the technical 

requirements that we're currently facing and what 

the climate is there. 

 We wish to protect producers and 

packers from undue economic burden related to 

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increased microbiological testing requirements. 

Within that capacity, we want increased funding 

for on-farm water sampling. We want more 

research projects, financial assistance for small 

and very small operations that have to comply as 

well, and the development of an online produce 

safety rule grower training available in English 

and Spanish. 

 For many of you who have not had the 

opportunity to sit in a chair for seven full 

hours and go through a certification program 

unlike any other that has been developed, it's 

not currently available online and it's not 

available in Spanish for anyone who has employees 

in Spanish that are involved in your process. 

 We encourage the re-evaluation of ag 

water testing requirements annually; so that will 

be important as Jennifer addresses things. And 

we also are looking to potentially establish a 

grower stakeholder advisory group in relation to 

the Produce Safety Rule and Preventive Controls 

for Human Food. The important thing to 

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understand there is that Preventive Controls for 

Human Food extends well beyond fruit and 

vegetables. It extends to all other human foods 

that are not currently regulated, okay? 

 Moving onto the next slide, we 

encourage development of FSMA Procure Safety 

Rule, Preventive Controls for Human Foods, and 

Foreign Supplier Verification Program interactive 

decision trees to assist entities in determining 

which rules they must comply with and when. If 

you guys will remember the dialogue that we had 

of, well, it's currently under enforcement 

discretion. I don't know how comfortable you 

guys feel about that. Wouldn't it be nice to 

have something that was more definitive and a 

resource to have in your file? 

 We encourage FSMA Foreign Supplier 

Verification Program modules focused on helping 

distributors, wholesalers, and cross-stocking 

facilities, and aggregation facilities to fully 

comply. We're not going to keep the safety of 

our American public at a priority if we don't 

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help these folks comply. 

 You guys have also remembered that we 

spent quite a bit of time hearing from Ken 

Petersen from the USDA Auditing Office and he 

spoke with us about the USDA GAP Plus+ Program. 

We invited him to speak with us on one of our 

additional calls, and based on that additional 

call, we decided to include more support for 

funding and personnel, marketing, and education 

outreach so that we can have the USDA GAP Plus+ 

Audit Program, which is GFSI technically 

equivalent and FSMA recognized, to be more 

readily available. 

 Let me give you an instance right now. 

Currently, Wal-Mart will not permit, unless it's 

its own discretion, anyone who sells more than $2 

million annually of any produce item the ability 

to be USDA GAP Plus+ audited. Why? Well, it 

says, in quote, it's not a GFSI benchmarked 

audit, end quote. 

 And what did we learn from Ken 

Peterson? USDA cannot be GFSI benchmarked 

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because they are not funded multi-year. So let's 

help them get more traction and we will help 

ourselves have a cheaper audit process that meets 

our standards. We encourage the FDA to perform 

more sampling, inspection, and documentation 

review of foreign grown, packed, and processed 

fruits and vegetables. 

 Moving onto the last slide, we 

encourage the FDA to perform more targeted 

Foreign Supplier Verification Program inspections 

on produce items that have caused outbreaks in 

the United States. Currently, according to FDA, 

unless we're dealing with an active outbreak or 

recall, they have to have the produce inside the 

United States before they can to an inspection. 

 The last two are incredibly important 

to several members of our committee. We 

encourage the USDA to work with the FDA and the 

CDC to hold town hall-style meetings to improve 

understanding of growing, harvesting, packing, 

and traceability processes prior to issuing 

additional fruit and vegetable consumer 

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advisories. 

 As you guys will well know, we had 

much discussion at our last meeting about the 

millions of dollars and potential, at least, 

terminal market disruption, and sometimes we have 

seen long-term market disruption for entire 

commodities, which have detrimentally affected 

the American farmer. 

 We encourage the USDA to work with FDA 

and CDC to develop a fresh fruit and vegetable 

regional food safety technical expert and 

regional growth stakeholder advisory committee 

focused on improving and advising during the 

consumer advisory process. As we have seen from 

the previous consumer advisories that have been 

issues, we have had days, weeks, and sometimes 

months where we didn't have critical information 

that all of us could've shared in five minutes 

because we know the practices and we can offer 

that advise. So I submit these for your review 

and we're going to review them in our work brief. 

 MR. HUGHES: Perfect timing. You can 

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introduce yourself. This Jennifer from United 

Fresh, but I'm sure she'll tell you all about 

herself and what she does. 

 MS. MCENTIRE: Hi. Good afternoon, 

everyone. I'm Jennifer McEntire with United 

Fresh Produce Association. I am the VP of Food 

Safety at United Fresh. I've been with United 

for about three years. By way of background, I 

am a food microbiologist. By background, I've 

always worked in the D.C. area for almost 20 

years for science societies, trade associations, 

always working in the food safety states. And 

United, obviously, are focused on fresh produce. 

 So I was asked to come here and talk 

a little bit about water specifically. But I'll 

say based on Kiley's comments and the 

recommendations she just shared, I'm happy to 

tackle really any subject. It's pretty fun for 

me to talk about food safety regulations. This 

is my forward button? No? You got it. 

 (Simultaneous speaking.) 

 MS. MCENTIRE: All right. So a few 

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key points that I want to lead off with. The 

first is, there's no -- I think there's no 

dispute that water needs to be appropriate for 

its use when we're talking about the produce of 

fresh produce, whether we're talking about 

irrigation water, frost protection, through 

packing, processing, even washing your hands, 

it's clear that water needs to be of adequate 

quality. 

 The regulatory requirements are on 

pause, so this is a part of the Produce Safety 

Rule, and I'll go into that a little bit more 

what the current requirements on the books are, 

and the reasons, in my opinion, why they're 

appropriately on pause right now and why they do 

need to be reconsidered. 

 From my perspective in working with 

our membership, I see -- I've observed a shift in 

mindset around how do we manage water. And I 

know Kiley mentioned in a couple of her bullets 

around testing of water. Well, maybe we just 

need to take a step back and re-evaluate if 

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testing is even the answer. So this was started 

-- I would say an initial conversation within the 

Leafy Greens industry, especially in California 

and Arizona, based on a couple of outbreaks that 

clearly had something to do with water. When you 

find that exact packaging in the water, you can't 

just ignore that. 

 So we've seen movement within 

California, specifically through the California 

Leafy Greens Marketing Association, a way that 

they're taking a different approach to water. 

And the rest of our membership are looking at 

other commodities. They're paying attention and 

wondering, how is this going to impact them 

knowing that buyers hear that California romaine 

producers are doing one thing. Is everyone going 

to expect that now apples and citrus and other 

commodities should also follow suit. 

 And in some ways, I think maybe some 

aspects are appropriate. Others are not. And so 

I think as we talk to FDA, as we think about what 

should be a regulatory requirement, we need to be 

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pretty cautious in our evaluation of what's going 

on and the scientific support for these actions. 

 So what's in the rule right now? So 

I pulled down just a little snippet. The obvious 

one that all ag water must be safe and it's 

adequate sanitary quality for its intended use. 

But what does that mean and how do you verify 

that? How do you prove that? Especially, when 

we're considering that it's not just production 

of fresh produce here in the United States, but 

the production of fresh produce in other parts of 

the world that's going to be important. So how 

can we make sure that it's clear what this means? 

And that's where this rub. 

 So within the rule right now, there 

are very, I'd say, pretty detailed requirements. 

Very specific requirements around the microbial 

limits for generic E. coli that's used as a core 

indicator organism. So it gets pretty 

complicated. There's this microbial water 

quality profile that's four years' worth of data 

that kind of keeps on building upon itself. 

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There's a geometric mean and a number established 

there of 126. Where'd you come up with -- that 

seems awfully specific; 126. And then a 

statistical threshold value recognizing that 

there's going to be some flux from time to time. 

 There's also something called a dieoff provision that if your water doesn't meet 

these microbial limits that there is kind of an 

option to us time as a factor, up to a few days, 

to get where -- assumed that those limits are 

going to go down just to due to natural die-off. 

 That is on the pre-harvest side, when 

we're talking about water that's going to be used 

during harvest and then following harvest for 

washing produce, processing. That water needs to 

have a different level where there's no E. colis 

detected, so cleaner level, basically. 

 So the challenge is with the rule as 

written, really, one is around math, so how do we 

get this geometric mean and how do we find this 

statistical threshold value. And there are 

little calculators that a couple of academics 

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have developed to help people input their test 

numbers and make sure that they're within the 

range. 

 There's also the logistics, so you 

have to do this testing for each water source. 

Well, what does that mean? And what -- you're 

using a water source that somebody else is also 

using, do you both have to test it? And what if 

you get different numbers? So, you know, there's 

some logistical challenges. Initially, when the 

rule was put out, the method was pretty 

prescripted. We were successful in working with 

FDA to allow some additional methods, additional 

options to develop these numbers. 

 But to me, as a microbiologist, the 

question really needs to be, is this even the 

right standard. So even if growers could do 

these tests, understood what one water source 

meant, had the math down, had the method down, 

are we even asking the right question here? Is 

this the right standard? 

 I'm not convinced that it is because 

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we know that generic E. coli is not a very good 

indicator. We also know that in the Yuma growing 

region that, when the canal water was tested, 

that water met the FDA requirements with --

passed with flying colors. And yet, the outbreak 

strain was found there. 

 So FDA recognizes this, too. I think 

they've been beat up a good bit over ag water. 

And that's -- these are the reasons why this part 

of the rule, Subpart E, is now on pause. So FDA 

needs time to compile and interpret the science. 

I would suggest that we can keep developing the 

science. I'm not sure that we'll get any closer 

to a single answer that works for all commodities 

in all growing regions and considers all 

different types of growing operations and all 

different types of water uses. 

 Again, this part of the rule is pretty 

prescriptive and I wouldn't be surprised if rule 

making is required. But rule making takes a lot 

of time and we're already kind of behind. And I 

feel like I'm feeling the criticism when the 

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press calls me and says, oh, there's yet another 

outbreak and yet again we can point to water. So 

why is the industry pushing back on this part of 

the rule? And it becomes difficult to explain, 

so I think we'd all like to see -- I know I would 

like to see this part of the rule finalized, but 

in a way that makes good sense and is 

appropriate. 

 So the Produce Safety Alliance, with 

support from the FDA, about a year and a half ago 

convened a water summit. It was quite an 

experience with a lot of people there in 

Cincinnati, as well as online at different 

satellite locations. So it was very robust 

discussion where many of these issues were 

brought to light, went into some detail. 

 I don't know that -- again, that 

anybody had, like, some solution that would work 

in all circumstances. So it was a great start to 

the conversation. If you're interested, there is 

a link there that you can read the full report. 

 So now fast forward a little bit to 

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this outbreak in Yuma, Arizona, and the filing of 

that shiga toxin-producing E. coli in the canal 

water, and the leafy greens industry then, you 

know, just a few months later around 

Thanksgiving, sort of a similar thing happened in 

California where the outbreak -- that outbreak 

strain, a different one, was found in sediment of 

a reservoir -- a water reservoir. 

 So what to do? And the leafy greens 

industry maybe, in some ways, threw in the white 

towel a little bit and said, we just have to 

assume that surface water is contaminated. Maybe 

testing is not the answer. Maybe we can't test 

our way to safety. Maybe we just need to flip it 

and recognize that there are some types of water 

sources that are inherently riskier. Other types 

of water sources that aren't, but the other 

factors come into play. So it's not just the 

source, but how is that water going to be stored, 

how is that water going to be conveyed, and then 

what, ultimately, is the use of that water. 

 So if we're talking about overhead 

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irrigation, that's very different from drip 

irrigation. And then furrow irrigation is 

arguably maybe a little somewhere in between. 

But is the water touching the crop? Is the crop 

getting saturated with this water? Is water 

contact incidental? These are all factors that 

should be considered. 

 So the California LGMA has now 

finalized their water metric. If you're not 

familiar with the California LGMA, I'm happy to 

explain that structure, but it is organized under 

the State of California. It's voluntary, but 

it's not that voluntary if you want to have a 

market share. 

 So within California, this is now the 

law of the land for production in California. 

And the question has been, well, is Arizona going 

to follow suit now that Arizona has a leafy 

greens marketing agreement, too? But they're use 

of water and their sources of water a little bit 

different, so they're still working on that. And 

then the rest of the industry has said, well, is 

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this now going to be imposed upon us? And should 

it be imposed upon us? 

 United Fresh's secretary for the 

harmonized standard -- the harmonized standard is 

the standard that the USDA HGAP Plus+ is built 

off of -- and there is a water requirement within 

the harmonized as there are water requirements in 

most GAP audits. And we learned from our -- the 

other organizations that we've worked with that 

understanding how to assess the risk of ag water 

was the most challenging part, or the part that 

had the most variation and interpretation amongst 

growers. 

 So independently and prior to these 

big outbreaks, we had started down the path of 

trying to put some guidance together for growers 

on, what does it mean to assess the risk of your 

agricultural water? And really we came up with 

basically the same thing that the California LGMA 

had come up with. 

 Although we recognize that different 

crops are different, some are stored after 

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harvest. There maybe be some die-off there, the 

use of water is a little bit different, but we 

took this similar risk-based approach in 

determining what quality of water is appropriate 

for its intended use. And there's a detailed 

hazard mitigation table that accompanies that. 

 Currently, the Center for Produce 

Safety, which is a -- which funds produce safety 

research, is actively soliciting research 

proposals from five different regions of the 

United States and within each region requiring 

that there be five sites per region that would 

also evaluate water issues, especially around 

water treatment. 

 So if we're going to be treating 

water, how can we do it in a way that is 

effective, that is validated, that is -- that 

recognizes the environmental impact that one may 

have. You know, we don't want to have unintended 

consequences here in haphazardly treating water. 

And how does it apply to more than just leafy 

greens? So that work is -- hopefully, will be 

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starting soon. The proposals are still out being 

requested. 

 So in terms of what we need, I think 

we do need more science, but we can't wait for 

the science. We need to communicate what we 

already know. So, you know, people have been 

collecting data. Individual growers have their 

water quality tests, have their data, and so this 

needs to be part of the discussion too, coming 

forward and sharing that information with the 

agencies as FDA is considering how to adapt the 

rule. 

 We'll continue to collaborate. We've 

got a review coming up in just a couple of weeks 

where, within our food safety group, we'll be 

talking about, if FDA came to United today and 

said, well, what do you think we should put in 

the rule? We want to have an answer, and so 

we're working on that, again, following a riskbased, science-based approach, recognizing the 

science is incomplete, but will probably always 

be incomplete. 

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 So as members ask -- as growers ask, 

well, what should I do now given that the rule is 

on pause, it's do what you've been doing and do 

the right thing. So test your water, make sure 

that the water is appropriate for use if you're 

not treating that water, but go ahead and don't 

just do nothing. 

 So I'll stop there. I'm happy to take 

any questions on either the water topic or, 

really, I feel pretty comfortable talking about 

anything that Kiley mentioned as well. 

 MR. BROWN: Going back to Kiley's 

comment, this is a critical issue, getting major 

retailers to accept the USDA GAP Plus+. I mean, 

right now, especially this year where we had a 

horrible transition from Georgia to Michigan, you 

know, these smaller growers, the under the 2 

million in sales growers, they're not 

incentivized to get GFSI, so we can't buy from 

them as a larger grower/shipper/packer. 

 You know, from the large retailers, we 

can get an exception, but then they want you to 

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get paperwork and a commitment from the smaller 

growers that they're going to go up to the next 

level, but these guys aren't going to do it. And 

I think that if we could really focus on getting 

the retailers to accept the USDA Harmonized GAP 

Plus+ would be a major win because this product, 

you know, it's safe product. 

 MS. MCENTIRE: Yes. Which, you know, 

as Kiley said, even the USDA Harmonized GAP Plus 

is recognized by GFSI, so retailers should be --

should accept it. Now, it's not truly 

benchmarked because it can't be the structure 

that is through government. You cannot -- it's 

ineligible for true bench marking. But it has 

been recognized. On the technical side, it has 

been recognized by GFSI. 

 So this is really frustrating to me to 

hear that the buyers continue to deny market 

access when the product has -- and the production 

processes have been demonstrated to be in 

accordance with the Harmonized. And so --

 MR. BROWN: The bigger problem is that 

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they have local programs and they will accept 

that product from the small growers in a local, 

regional area. But for us, at our volume, we 

can't buy that product from that same grower and 

fit it into our DCs in a different area. I mean, 

it's just ridiculous. 

 MS. MCENTIRE: It is. I mean, it's 

not logical, right? So I do have one member of 

my team, Dr. Emily Griep, who is focused on the 

Harmonized. And a big part of what she's doing 

is reaching out to the buying community, to the 

big buyers, to try to educate them about 

Harmonized, whether it's through USDA or through 

one of the other audit organizations, to invite 

them to participate in a process as we update the 

Harmonized so that they see the rigor, the -- you 

know, the science behind the standard. And 

ideally, our objective is to increase acceptance 

of the Harmonized. 

 MR. BROWN: Thank you. 

 CHAIR CARR: Anybody else? 

 MS. HARPER-LARSEN: Number one, thank 

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you very much for presenting. You did mention 

the die-off rate, and at CPS there was some 

science that was presented that the die-off rate 

may not actually be accomplishing what is written 

into the regulation? 

 MS. MCENTIRE: Yes. And we have this 

odd situation where, at the equivalent, we go 

four days to achieve your data. I kind of 

skipped over it, but it was on the slide that was 

in the California LGMA that -- for overhead water 

use that it is 21 days. So that's quite a 

difference between, you know, four days being 

adequate, saying, no, it has to be for -- at 

least for leafy greens, has to be 21 days. 

 This is an area where I suspect we may 

have differences for different commodities, that 

there are, in fact, different die-off rates 

depending on the density you're planting, the --

yeah, it's really about the amount of UV light 

that's contacting the microorganism on that 

surface. 

 So I think this is an area where we 

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can make improvements, but there's adequate data 

not just those presented at CPS, but there's been 

some additional research that shows, under many 

circumstances, where these may not be protective. 

So I would be very cautious about relying on 

those four days. It's not to say 21 is perfect, 

even for romaine. We simply don't know. But it 

was -- felt that that was a prudent timeframe to 

use for leafy greens. 

 MS. HARPER-LARSEN: Since we see that 

leafy greens and their conversation of what they 

do tends to work its way through the rest of the 

industry, what do you see coming down the pipe 

for us as many of us approach our planting 

season? 

 MS. MCENTIRE: First, I think that 

it's important to communicate -- and, you know, 

this is a responsibility that I'll take on, to 

communicate to bios that not all products are 

leafy greens, that the risk is different 

depending on the product and, you know, several 

aspects and attributes of that commodity. 

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 So I would not want to see someone 

just take the California LGMA water metrics and 

replace leafy greens with fresh produce. I don't 

think that would be appropriate. But the concept 

of assessing the risk of your water and being 

able to defend -- particularly, if you're using 

surface water to be able to defend why that water 

is not risky. I think that that's where growers 

should be very mindful of how they're going to 

make the case because it's obvious that testing 

for generic E. coli is not the way to measure or 

assess the risk of that water when it comes to 

public health associated with the consumption of 

that product. 

 MS. HARPER-LARSEN: Can you address 

some of our bullet points and maybe give us --

since she's not going to be available to us 

tomorrow, United's opinion of some of those? And 

 MS. MCENTIRE: Sure. So I left my 

notes at my seat, but I do remember a few of my 

comments. One is that I would be very cautious 

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about the perception that there would be an 

unfair expectation of foreign production versus 

domestic. So there should be -- absolutely 

should be a level playing field, and I think that 

we need to urge the agencies to ensure that, 

indeed, there is. 

 So even as we're talking about water 

or other aspects of production, that what U.S. 

producers -- is standard that U.S. producers 

need, that we have a way of verifying that that's 

being met for all types of fresh produce that's 

going to be coming into the United States. But I 

don't think that we should feel that we need to 

only inspect farm produce, and that domestic 

produce is, you know, always going to be okay 

because, clearly, the evidence supports that we 

have issues domestically as well. So I think 

that having -- you know, just maybe wordsmithing 

a little bit to make sure that that's clear is 

one area I have good feedback. 

 I was surprised to see mention of the 

Prevent Controls Rule because that is for 

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facilities that are required to register with FDA 

-- oh, thank you. Yeah, all my notes. And I 

will leave them with you. The Preventive 

Controls Rule only applies to facilities required 

to register with FDA, and it's very clear that 

farms are not required to register with FDA. 

 As you mentioned, the Preventive 

Controls Rule covers breakfast cereal and 

crackers and, you know, like, everything in the 

grocery store that's not regulated by USDA and 

FSIS with very few FDA exceptions is covered 

under Preventive Control. So I don't think you 

want to get lost down the Preventive Controls 

track. I think stay focused on the Produce 

Safety Rule is where I would encourage the group 

to focus. 

 On working with the agencies, with FDA 

and CDC, with our advisories, this is something 

that United is committed to because it's just a 

whole lot of work when you're the one fielding 

hundreds of calls and texts and emails. It's 

like, oh, I need -- I have a real motivation to 

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make sure that things like this don't happen 

again. 

 I can say that we've made progress. 

I feel -- I see that we've made progress in 

working with the agencies and having better 

communication and better dialogue. There are 

some legal barriers and there are some, just, 

situational kinds of barriers. 

 So, for example, the idea of having a 

fresh fruit and vegetable regional food safety 

technical expert and regional grower/stakeholder 

advisory committee to be able to work with the 

agencies, well, what if a member of that 

committee is the one that's -- that maybe we 

don't know it up-front, but later it's found out 

that they were involved in this situation, you 

know? How do you prevent that sort of conflict 

of interest when the reason that an advisory is 

issued is because all the facts aren't known yet? 

 So there are some real challenges in 

establishing those types of relationships and in 

establishing those boards or committees or groups 

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of experts that the agencies can tap in the event 

of an outbreak investigation. Nevertheless, I 

think that there are things that we can do that 

kind of get at that. 

 And so myself and Dr. Bob Whitaker of 

PMA, who I've worked very closely with, we have a 

proposal into both FDA Frank Yiannas and CDC Amy 

M. Williams about structure through with 

collaboration could be improved. And both before 

as well as during, and then even after an 

outbreak to do, sort of, that hotwash, that 

debrief, on a situation. 

 So I think that we're all kind of 

seeing things the same way, that what's happening 

now is not ideal, not where we want to be, and 

all recognize the need to collaborate. But I 

think exactly how we do that -- there are some 

legitimate issues that need to be overcome. 

 This one -- my main point's really the 

foreign piece, the preventive controls piece, the 

working with the agencies, and then even some of 

the language around the FSVP. The FSVP 

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inspections are not of produce. They're not of 

product, any product. It's the inspection of the 

importer and the importer's records. So that 

produce can still be inspected, but it would be 

inspected under the Produce Safety Rule, and that 

would be done in-country. 

 So FDA does have staff around the 

world and will perform on-farm inspections for 

fresh produce that is going to enter the United 

States, just, it's not under FSVP. FSVP is for 

the importer. And just today, FDA came out with 

their announcement of how they have issued a 

warning letter, which, you know, is one of the 

bigger sticks that FDA has to work with: a 

warning letter against an importer. 

 It wasn't related to fresh produce. 

It was related to a tahini product. But there is 

a new type of import alert that FDA now has at 

its disposal that will detain product at the 

border if the importer is known not to comply 

with FSVP. And there's no way that you can test 

your way out of it, so it's unlike other import 

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alerts. I found that to be very interesting and 

potentially quite powerful. So that's my 

feedback on your bullets. 

 MS. HARPER-LARSEN: Thank you. 

 CHAIR CARR: Any other questions? 

 MR. SIEVERT: I have a question. 

 MS. MCENTIRE: Sure. 

 MR. SIEVERT: So have we made enough 

progress since the last two advisories to where, 

if something happens again, we will be able to 

get enough resources together to do the actual 

recall versus the advisories? Is it that much --

but I'm sure there's been a lot of dialogue about 

how we execute that. 

 MS. MCENTIRE: So no matter how I 

think about it, I think I come up with an answer 

of no. And in part, this is because one of the -

- well, the reason that an advisory is issued is 

because FDA can't trace back to determine who is 

producing that contaminated product. So there's 

a fundamental traceability issue that is not 

unique to fresh produce, but I think that it is -

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- I think traceability -- because of the 

perishability of the product, we rely more 

heavily upon traceability, upon records that 

exist. 

 When I'm talking about traceability, 

I'm not talking about what's printed on a package 

or the sticker that's on a case. I'm talking 

about the records that exist in systems. 

Sometimes they're on clipboards or file cabinets 

or in an ERP system or a warehouse management 

system. 

 But trying to stitch all these bits 

and pieces of information, starting with, like, 

my shopper card data at the grocery store, what 

did I buy? And when we use something like a 

generic PLU. All that I bought is a head of 

cauliflower. Even if it's branded. You know, if 

you were using the generic PLU, that information 

is then lost and it's, well, hey, grocery store, 

whose cauliflower were you selling at this rough 

timeframe? And trying to go back from different 

parts of the country and figure out who's that 

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common cauliflower grower. 

 It's immensely complicated and the FDA 

and CDC are not -- they are no longer willing to 

spend however many weeks or months trying to 

collect this information while people continue to 

get sick. They feel that they know that it's 

cauliflower, they're going to make a -- put out 

an advisory to stop the consumption of 

cauliflower until they can figure out whose it 

is, if they can even figure it out. 

 That's one of the reasons that I 

think, as an industry, we need -- that's an area 

where we can do better. I think on the 

contamination side, how do we prevent 

contamination from occurring in the first place. 

If we don't have outbreaks, then, you know, we 

don't find ourselves in this situation. That's 

another area where we can do better. 

 If we do have outbreaks, and 

especially if traceability is poor, that's an 

area where I do see improved communication. The 

nature of the communications I get -- the heads 

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up that I get from FDA and CDC -- more so from 

CDC because they're non-regulatory, so it's a 

little easier to have a conversation with them. 

I have seen improvements there, but at that 

point, in my opinion, it's kind of already too 

late. Does that answer your question? Is that 

the answer you were expecting? 

 MR. SIEVERT: Not the answer I wanted, 

but, yeah, I understand. 

 MS. HARPER-LARSEN: Talk about the 

collaborative idea that you have already brought 

to FDA and CDC. Is that something that you can 

send over to us for our work group to look at so 

that we could consider your thought process as 

well as our own? 

 MS. MCENTIRE: Yeah. I don't see why 

not. 

 MS. HARPER-LARSEN: All right. 

 MS. MCENTIRE: You know, once you send 

it off to FDA and CDC, it's FOIA-able anyway, so 

it's out there. It was done under the banner of 

the Romaine Task Force, but it -- that case in 

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particular is definitely not unique to romaine. 

I think that it's applicable, really, to any type 

of food, any type of situation. 

 MS. HARPER-LARSEN: And do you know 

where we stand, really, with narrowing down 

further in Yuma, in particular, right now, beyond 

the last report that came out -- 

 MS. MCENTIRE: Of the -- 

 MS. HARPER-LARSEN: -- number of 

fields? Like, have they been able to actually go 

 MS. MCENTIRE: I think the records are 

what they are. And so from the traceability 

standpoint, you know, it sent FDA and the state 

off in -- you know, hunting around this wide 

geography of possibilities. We can be reasonable 

confident that every single one of those 

possibilities isn't it, but there's way too much 

noise in the traceability records and not the 

clear signal. So unless testing found a 

positive, I think we're kind of stuck with what 

the trace-back investigation showed. 

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 MR. WILKINS: Going back to his 

question, I understand why you said no about the 

advisory inspect. In '07, '08, '09, somewhere in 

there, there was an advisory not to eat tomatoes 

and it did not end up being a tomato. 

 MS. MCENTIRE: Right. 

 MR. WILKINS: Do we feel that we've at 

least -- can narrow it down to the correct 

commodity? 

 MS. MCENTIRE: You know, that's 

usually the first question that I'm asked when 

there's a hint of an outbreak. How can you be 

sure that it's romaine or papayas or basil or cut 

melon or whatever piece, maybe -- how can they be 

sure? And I think the -- especially after the 

tomato issue, CDC and FDA, they don't want to be 

wrong. 

 So I think they've learned their 

lesson, and they usually share the 

epidemiological data that supports their 

assertion that it is whatever product they say it 

is. But we were all relying on people's memories 

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about what they ate, and you are trying to 

compare that to, you know, for this whole 

population, what did they eat that was different 

from what we would've expected people to have 

eaten. 

 And the what we would've expected 

people to have eaten data are imperfect and not 

necessarily current, but they are in the process 

of being updated. CDC is working on that. And I 

think that's an area where you may want to 

explore if there is an opportunity to help CDC 

get a sense of, what do people eat today? You 

know, consumption habits have changed. There are 

different products that are popular, so looking 

at data that are a decade old and saying, well, 

you know, 67 percent of people in 2008, I think 

this data may not be -- you know, it doesn't help 

us. 

 So there are still challenges on the 

epi side, making sure that we do have the right 

product. But at least in the past several 

outbreaks, the data have been pretty compelling. 

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 MR. WILKINS: So just identify that 

you know the commodity and you know the source. 

And they're not certified under the basic, like -

-- is there any heat being thrown back on that 

retailer that they did not buy the basic food 

safety requirements that's recommended? 

 MS. MCENTIRE: From a regulatory 

standpoint, I have not seen that happen. But 

with that said, something like Foreign Supplier 

Verification Program or the supply chain program 

under Preventive Controls is quite new. So there 

wasn't really an opportunity -- FDA didn't have 

the ability to enforce that against the buyer, 

you know, for buying from someone who was -- had 

substandard practices. The enforcement has 

always been against the person who had 

substandard practices. That's on the regulatory 

side. 

 On the civil litigation, the lawsuit 

side, then, you know, lawyers will go after 

anybody in the supply chain who has money, and 

usually that's not the grower. Usually, it is 

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somebody later in the supply chain. So I think 

retailers feel -- should increasingly feel that 

financial pressure to make sure that they are 

buying from reputable suppliers and should have 

that motivation. 

 MR. WILKINS: Are we missing that in 

a bullet somewhere? You know, that the -- you 

know, I work for a family-owned company of retail 

stores, and the FDA advised that we pull it, no 

questions asked, okay? And I would say a 

majority of retailers are going to do that. So 

now you're falling back to retailers that 

possibly did it right, the producers that did it 

right. And I think there's a -- there are always 

people that are cutting corners and one bad apple 

 (Simultaneous speaking.) 

 MS. MCENTIRE: Right. 

 MR. WILKINS: -- the whole barrel. 

 MS. MCENTIRE: Right. 

 MR. WILKINS: And I just think that, 

you know, if we find out the source, and that was 

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bought without the minimum food safety standards, 

that that's one more step. I think if retailers 

-- if we're doing it right, we ought to be --

have some protection from those that don't. 

 MS. MCENTIRE: And, you know, the 

majority of people within the industry are those 

good players. It is, kind of -- usually it seems 

to be a bad apple type of situation, and it 

really ticks off the people who are making those 

investments in food safety, who are doing the 

right thing. And they want some sort of credit 

for that. 

 And at this point in time, it's more 

difficult to figure out how to clear them, how to 

communicate that they're not involved. That even 

if we don't know who is involved, that we can be 

reasonably certain that this population is not 

involved. There's not a good mechanism right now 

to do that. 

 I did observe, though, that the Food 

Marketing Institute, which is the trade 

association that represents the retailers, they 

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put out their recommendations to their members --

to the retail members on leafy greens. And one 

of the recommendations is to only purchase -- if 

you're purchasing leafy greens from California or 

Arizona, to only purchase from those who are 

following the LGMA standards, and were audited to 

the LGMA standards. 

 So, again, it's a voluntary program. 

It does cover, like, 99 percent of production, 

but there's a lot of production out there. So 

that 1 percent is -- you know, still somebody is 

buying it. So determining how we ensure that 

it's communicated through to procurement, you 

know, that suppliers need to provide reasonable 

demonstration of food safety is critically 

important. 

 MS. HARPER-LARSEN: And I think maybe 

what we see in food safety is a different sort of 

in vernacular, okay? But when we're talking 

about retailers or buyers in particular, we're 

talking about internal requirements. And what 

we're sort of looking at with our bullet points 

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is legal minimums. So audits are not a 

requirement legally as it stands right now, so 

they -- that goes into a business decision of the 

buyer and of the retailer. 

 So when we're talking about 

establishing a level playing field, bringing 

everybody up to minimum produce safety rule 

standards, both domestically and foreign, is 

where we, as a grower community, have to work to 

do that, okay? And then establishing with brands 

that we won't allow purchases beyond established 

minimums, so -- okay? 

 And let's talk about this, okay? 

Deviating from your own internal specification, 

okay? That's incredibly important as well. Or 

maybe it's from a commodity standpoint as well as 

our subgroup. And I know our subgroup was, like, 

willing to look at anything within our 

recommendations. We just have to make sure that 

we're talking, sort of, the same language. 

 A audit requirement from a retailer 

versus a legal requirement from a regulatory 

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body. And unfortunately, they are two different 

animals. I'd love to see the audit requirements. 

Makes it a whole lot more simple, and it gives us 

metrics. Defined metrics that we have historical 

on. But audited, unfortunately, does not mean 

safe. 

 MR. WILKINS: Yes. And you got the 

whole local piece of it. 

 MS. HARPER-LARSEN: That's correct. 

 MR. SIEVERT: You got the outside 

purchasing piece, also. 

 MS. HARPER-LARSEN: That's correct. 

 MR. SIEVERT: So you don't have enough 

product and you go buy it from somebody else, and 

you don't know for sure. You'd think it is -- 

 MS. HARPER-LARSEN: And you buy it 

from an audited facility -- 

 (Simultaneous speaking.) 

 MR. SIEVERT: -- or whatever. You 

know what I mean? 

 MS. HARPER-LARSEN: And I think that's 

what we maybe need to look at as an industry, and 

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that's probably beyond the capacity of our 

subcommittee and of this committee, but our trade 

organizations and coming up to a standard of 

behavior where we have a supply chain that is as 

infallible, okay, as we ultimately strive to be. 

That when we have the opportunity to buy and make 

a dollar, that we make sure that it's not at the 

compromisation of an entire commodity group. 

 MR. SIEVERT: I don't look at it as --

I'm looking at it more from if Dole doesn't have 

enough product and they have to go buy from 

somebody that they know exactly what they bought. 

I guess I'm looking at it more that way. I think 

you have a -- we have so many rules around what 

we can and can't buy to protect our members. 

There's nobody out there making that unsafe 

decision to buy on the outside to save the dollar 

from somebody that we don't know we're doing 

business with. 

 MR. WILKINS: You just made some 

audibles that you're not 100 percent sure that, 

like in Dole's case, that they did what they --

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 (Simultaneous speaking.) 

 MR. SIEVERT: No. And I know. Any 

XYZ Company -- 

 (Simultaneous speaking.) 

 MR. SIEVERT: Let me correct that. 

That's XYZ Company. I'm not saying Dole or GNA 

or anybody. But my point is, that companies are 

out there buying to fulfil orders, and it's not 

all their product. And if they grow 95 percent 

of their product, to me, they're buying 100 

percent of their product because that's what I --

we've had conversations today about people buying 

product from other people to get it into -- to 

handle year-round capacity, right? 

 So it's not a -- I think it happens 

out there. I think that's where we don't know --

I'm assuming, because I think the one romaine 

advisory was -- most of the sicknesses came from 

food service. Is that correct? The first one? 

Or was it the second one? 

 MS. MCENTIRE: The second one. It is 

easier to have a cluster of illnesses that you 

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can trace from food service. It's kind of harder 

to pick up through retail. It's kind of easier 

to tell did everybody all eat in the same 

whatever restaurant. So there may be a little 

bit of bias -- but there can also be different 

supply chain channels and so -- 

 MR. SIEVERT: Right. 

 MS. MCENTIRE: -- that can be helpful 

in trying to tease apart what's happening. 

 MS. HARPER-LARSEN: But, Tommy, if you 

get something that you feel like our subgroup 

needs to talk about, I'd hate to pull you away 

from trade, but come over and let's talk about it 

because -- 

 (Simultaneous speaking.) 

 MR. WILKINS: I just know that in both 

of our instance, we've thrown away an immense 

amount of food and it's warranted. I mean, if 

there's an advisory that you can get sick from 

cauliflower, we have to pull it. There's no -- 

 MS. HARPER-LARSEN: Right. 

 MR. WILKINS: That's not the question. 

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But for those that try day in and day out to do 

their job with the rules that we are, I guess I 

don't know that we police the bad eggs. I don't 

know that we can. But it's just an -- it's 

expensive not to pull it from the shelves, but 

it's expensive to pull it from the shelves. 

 CHAIR CARR: Anything else? 

 MR. WILKINS: Thank you. 

 CHAIR CARR: Thank you. 

 MS. MCENTIRE: Thank you. 

 CHAIR CARR: Darrell, do we have any 

housekeeping? 

 MR. HUGHES: Yes. Just briefly talk 

about tomorrow. So we'll kick the day off, going 

into work groups and refining recommendations, 

position statements. I think the overall goal is 

to pinpoint which ones need work and try to work 

on them collectively within the work groups, and 

then come together and then Chalmers will have 

like what we did today with each of the leads, 

present the status. 

 If there are any recommendations that 

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you think are good to go, let's at least mark 

those off and then put them before the full 

committee so that we make sure that we're all on 

board. Like, okay, the work group says XYZ 

recommendation. We don't think it needs any 

changes. I think it's a good idea to make sure 

that the full committee is on board. Does that 

make sense? 

 And we can do that for any 

recommendations that any work group thinks that 

they're solid on. Any recommendation that needs 

work, obviously, we'll work on that in committee 

-- I mean, within your subcommittee work groups, 

and then you'd come back and give an update on 

where you think you want to go, get some insights 

from your members. And then even beyond that, 

work over the next few months just making them 

what you all want them to be. 

 CHAIR CARR: So let me expand on it a 

little bit more. So the general thought is if we 

come back tomorrow, we get together, break into 

our work groups for about an hour. Some people 

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may already have their work done that they may 

have caused some work to be done. Then come 

back, we can get 45 minutes for each working 

group to talk. And if we can get to a consensus 

place within that 45 minutes, we can vote on and 

approve it. If we can't get to a consensus 

place, we go to the next group. 

 And if somehow we're running ahead of 

schedule on one group or the other and we got 

time at the end, we can then come back to the 

other group. Otherwise, if we don't get there in 

that 45 minutes, that means we're going to be 

working with this after this committee meeting, 

being on conference calls and emails and stuff 

like that. 

 If that's acceptable to everybody, 

knowing each topic has got a lot of different 

variables to it, deciding an allocation of time 

has to be the order of the day; otherwise this 

work could dominate your whole day and we 

wouldn't get anywhere else. So if that works for 

everybody, then we will do that and come back. 

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And I don't know how we're going to put it on the 

board if we got new ones, so. 

 MR. HUGHES: Yes. So what I'm 

thinking is each lead, if you have your -- do you 

have your laptops here? 

 I've got an adaptor. I'll bring my 

adaptor, we can just swap out laptops because I 

don't want you to waste time emailing them to me 

and then they get lost in the cloud somewhere --

 CHAIR CARR: Some may be more 

converse, some may be easier to agree to, some 

may really have, you know, more in-depth 

conversations, or they -- I do want to give 

everybody the time to share their opinions on all 

the different working groups, so. 

 MR. WILKINS: Are those PDF files 

you've sent us or can we do some doctoring on 

them? 

 MS. HARPER-LARSEN: On the 

presentations. 

 MR. WILKINS: Yes. 

 MR. HUGHES: Yes. 

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 MS. HARPER-LARSEN: They're PPTXs, 

aren't they? 

 MR. HUGHES: Yes. They're PPTXs, yes. 

You can update them from there, yes. Do you -- 

 MS. HARPER-LARSEN: Can we do a 

subcommittee consent agenda, like, if we come 

together, we can go ahead and just say, we 

consent. We have a consent agenda for this 

entire part of the presentation with these 

particular amendments? 

 CHAIR CARR: Yes, but it will be open 

to the whole group to not be a consensus or to 

offer suggestions or anything like that. 

 MR. HUGHES: Right. But think what 

she's saying is, like, if the Food Safety 

Subcommittee or work group says, we agree to move 

all of these forward to the full committee, that 

can happen in one move. And then from there, 

it's up to the full committee to assess each one 

and determine whether to not you, as a unified 

body, wants to accept it or ask for changes or 

whatnot. 

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 MS. HARPER-LARSEN: And we can do that 

with some modifications that we've already made 

as long as we read them aloud and present them as 

one -- 

 (Simultaneous speaking.) 

 MR. HUGHES: Right. Yeah, yeah, yeah. 

 MS. HARPER-LARSEN: Yes? 

 CHAIR CARR: So let me back up on 

that. Would you be able to provide the language 

-- the change language? 

 MS. HARPER-LARSEN: Yes. 

 CHAIR CARR: Yes? Okay. As long as 

you -- 

 MR. HUGHES: Right. Yes. 

 MR. SMITH: What constitutes 

consensus? 100 percent? 90 percent? What's the 

threshold -- 

 (Simultaneous speaking.) 

 MR. HUGHES: Where's my book? Where's 

my Roberts Rules of Order? 

 MS. HARPER-LARSEN: Is it a -- are we 

66 and two-thirds? Are we simple majority? Is 

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it a all yay or it's an all nay? 

 MR. HUGHES: I would say simple 

majority. 

 MS. HARPER-LARSEN: Okay. 

 MR. HUGHES: Oh, yes, that's right. 

We do have a policy statement. I forgot I 

created that. 

 (Laughter.) 

 (Simultaneous speaking.) 

 MR. HUGHES: I'll provide that for 

everyone tomorrow because I have to do a little 

with it. But we'll make sure that that's clear 

at the top of the meeting tomorrow. 

 CHAIR CARR: All right. So I do have 

a motion and a second to adjourn, but I do want 

to say, is there anything else that anybody would 

like to bring up and discuss? 

 MS. GLEASON: Just a quick question. 

If we don't reach consensus today, what are the 

final dates that we have to -- 

 MR. HUGHES: Well, no one's going to 

reach a consensus today. We're going home today. 

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 MS. GLEASON: I mean -- sorry, 

tomorrow. Tomorrow. 

 CHAIR CARR: Well, this committee ends 

in the end of September with the annual budget, 

so we need to be done; otherwise, we're not a 

standing committee the 1st of October. 

 MS. GLEASON: Sure. Okay. Perfect. 

 CHAIR CARR: Is that correct? 

 PARTICIPANT: Yes. 

 MR. HUGHES: This committee does not 

-- oh, from a monetary standpoint, yes. From a 

monetary standpoint, that is absolutely true. 

From a charter standpoint, your charter expires 

March 2020. And so will we meet again and spend 

money after September? No. But can we have a 

conference call? Yes. 

 CHAIR CARR: Can I get a consensus 

that we want to have this done by the end of 

September? 

 (Chorus of yes.) 

 MR. HUGHES: I like that idea. 

 CHAIR CARR: Anything else? 

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 MR. TISON: I amend the motion to 

adjourn to a motion to recess -- 

 CHAIR CARR: Thank you. So amended. 

 MR. HUGHES: 8:00 a.m. back here, 

ready to go. 

 (Whereupon, the above-entitled matter 

went off the record at 4:58 p.m.) 

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abeyance 279:17 

ability 21:7 23:21 78:16 

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able 5:9,22 16:5,11 17:1 

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abroad 258:20 

absolutely 24:14,15 

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academics 352:22 

accept 58:14 85:5 

361:14 362:5,11 

363:1 392:21 

acceptable 49:22 

318:13 390:16 

acceptance 303:16 

363:18 

accepted 204:16 

303:16 

access 10:8 32:4 34:4 

34:22 38:4,19 48:9 

54:12,13 65:21 66:6 

75:11 77:10 84:9 

103:8 124:19 130:7 

130:15 137:16 145:15 

155:1 156:13 157:16 

286:5 323:7 325:20 

362:19 

accessible 326:7 

accompanies 359:6 

accomplishing 166:21 

364:4 

accomplishment

108:17 

account 30:8 81:19 

111:10 119:9,12 

213:4 219:2 238:9 

245:4 

accountable 342:2 

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141:8 

accredited 178:8 

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acre 24:20,20 25:21 

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act 48:22 82:13 83:9 

95:15 144:19 166:2 

195:9 270:22 342:3 

acting 151:17 

action 19:9 117:16,21 

134:6 145:2 161:13 

179:19 304:5,9,11 

actions 26:14 95:20 

114:20 116:1 121:3 

121:10 129:3 179:20 

198:7 256:21 351:2 

activate 107:7 

active 162:13,18 304:9 

341:12 346:13 

actively 57:19 305:22 

359:9 

activities 23:9 260:8 

298:12 300:14 

activity 31:3 91:11 

228:3 248:19 249:16 

249:20 251:20 300:16 

325:2 

actual 18:20 25:16 

144:3 162:3 173:6 

176:12 178:22 260:2 

268:20 290:15 324:5 

372:11 

adapt 360:11 

adaptor 391:6,7 

add 5:5 128:2 173:3 

232:18 

add-ons 205:10 

added 167:15 169:9 

326:20 

adding 222:7 

addition 31:15 137:10 

154:21 160:14 172:12 

174:14 181:1 212:21 

additional 90:4 97:21 

156:4,14 168:6 

178:15 182:9 189:19 

192:8 202:19 222:17 

234:14 340:19 345:7 

345:7 346:22 353:13 

353:13 365:3 

Additionally 166:9 

address 60:9 66:2 

85:21 184:1 189:5 

275:5 366:15 

addressed 56:16 67:4 

154:1,17 

addresses 34:5 303:8 

343:18 

adequate 160:7 285:9 

349:8 351:6 364:13 

365:1 

adequately 154:13 

adhere 91:15 

adjourn 3:22 394:15 

396:2 

adjustment 215:22 

adjustments 123:3 

293:8 

administration 49:12 

50:3 52:20 53:7 79:9 

81:9 120:21 140:3,11 

140:14 166:12 277:3 

287:22 288:5,10 

304:10 311:19 

administration's 52:8 

administrations 48:19 

administrative 227:7 

229:10 233:10 

administrator 2:4,11 

6:6 256:10 312:3,7 

315:8,12 316:9 

329:16 338:17 

admission 334:11 

adopt 38:15,16 

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adult 16:3 

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185:4,5,7 189:10 

190:1,6 

adulterating 190:14,19 

adulteration 189:6 

advantage 125:21 

advantageous 195:15 

adverse 205:12 239:20 

288:17 295:5 296:1 

adversely 161:1 295:8 

295:12,20 

advertise 310:21 

advertised 309:17 

advertising 297:3 

advise 314:3 326:2 

347:20 

advised 95:19 380:9 

advises 61:20 

advising 347:13 

advisories 347:1,15 

368:18 372:9,12 

advisory 1:3,8 47:1 

59:21,22 60:3 61:19 

90:7 94:5 97:5,18 

156:11 343:20 347:12 

347:14 369:12,18 

372:18 374:8 377:3,4 

386:18 387:19 

advocate 19:22 

AEWR 241:14 242:13 

242:19 243:7 274:3 

286:18 287:3,21 

289:17 290:16 298:1 

300:5 

Affairs 2:8 8:18 44:10 

227:14 

affect 268:21 295:12 

afford 19:3 

affordable 18:22 

afternoon 46:5 201:12 

207:5 256:9 300:8 

316:4 348:4 

ag 2:9 7:21 8:3 29:14,15 

30:11 32:13 62:4 

68:22 109:13 111:11 

113:17 114:5,13,15 

114:17 119:10,13 

120:1 123:7,13 

128:18,21,22 129:18 

131:14 138:5 202:1,1 

202:8 205:6,11 

207:12 221:10 229:4 

232:13 233:3,5 294:7 

299:14 343:16 351:5 

354:8 358:10 

age 266:6 

agencies 15:4 161:19 

163:18 194:15 204:14 

205:21 303:22 334:14 

341:14 360:11 367:5 

368:17 369:5,13 

370:1,21 

agency 13:18 198:18 

221:18 246:14 279:18 

300:10 317:15 

agenda 10:10 16:22 

101:6 202:17 392:6,8 

agent 272:3 

agents 258:20 

ages 11:22 

aggregation 344:20 

Neal R. Gross and Co., Inc. Neal R. Gross and Co., Inc. 

(202) 234-4433 (202) 234-4433 Washington DC Washington DC www.nealrgross.com www.nealrgross.com 
398 

ago 6:12 67:15 72:2 

76:1 100:3 107:16 

125:9,17 158:4 161:5 

202:10 211:8 247:8 

262:14 279:21 283:16 

302:5 308:8 317:20 

325:3 355:10 

agree 34:11 41:10 68:3 

69:20 137:7 140:21 

199:20 391:11 392:16 

agreed 41:15 58:20 

216:4 

agreeing 71:10 

agreement 49:14 51:12 

51:20 56:21 58:7,12 

58:15 61:3 74:20 

76:16 78:9 95:13 

120:22 121:15 132:19 

133:9,20 134:11 

137:7 140:9 141:22 

142:16 143:14 150:4 

168:2 338:4 357:19 

agreements 53:2 54:11 

55:2 56:16,17 58:19 

59:2 62:9,10 78:10 

98:4,12 132:4 136:19 

136:19 137:11,13,18 

167:2,4 

agribusiness 214:3 

agricultural 2:8,12 3:5 

3:19 25:3 90:7 97:22 

100:6 106:7 109:16 

111:7,10 126:18 

131:20 134:8 138:14 

165:2 170:22 180:20 

205:18 224:14 227:5 

227:18 240:1 248:16 

252:17,20 253:1 

270:9 271:21 278:10 

317:6 358:18 

agriculture 1:1 6:16 

8:18 9:2 31:1 61:19 

90:15 95:15 97:11 

99:21 100:13,16 

101:7,8 103:14,16 

104:22 105:19 107:2 

114:7,7,12,21 116:10 

120:2 121:11 125:14 

126:2 127:3 128:19 

130:18,21 134:9 

136:17 151:18 153:17 

166:4 167:5 192:19 

207:19 208:7,10 

209:2 214:1,6,19 

221:12 223:12 228:6 

228:20 235:11 237:12 

237:13 239:21 248:6 

258:7 265:6 266:3,22 

268:4,5 270:22 271:7 

271:8 273:6 275:4 

289:7 297:18 298:12 

agrochemicals 44:14 

agronomic 153:18 

155:3 156:20 158:10 

ahead 13:2 43:6 99:4 

250:15 286:11 287:5 

301:10 303:10 315:4 

315:21 316:1 361:6 

390:8 392:7 

aid 52:7,10 80:11 

air 11:19 

alert 371:18 

alerts 372:1 

alleviate 180:21 

Alliance 355:9 

Allison 2:14 28:3 41:8,8 

43:1 54:13 65:22 75:5 

77:17 

Allison's 67:13 

allocated 155:21 

allocation 390:18 

allotment 329:9 

allow 4:22 24:19 54:14 

58:5 96:15 109:4 

353:13 383:11 

allowed 62:10,13 

126:17,20,22 189:10 

325:4 

allowing 269:3,16 

allows 8:7 16:9 22:19 

25:7 172:1,3 174:6,11 

175:21 184:5 278:18 

329:20 

almond 135:17,17 

almonds 135:11,16 

Alonso 2:6 318:2 324:4 

324:9,22 327:12,15 

327:19 329:11,15 

330:13 332:21 333:2 

333:4,9 334:5 

aloud 393:3 

alternative 53:8 96:13 

105:15 

aluminum 117:22 

amazing 107:15 109:10 

Ambassador 49:21 

ambiguous 96:3 

Amelia 2:9 44:8 

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amended 396:3 

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America 8:15 28:20 

73:5 102:18 316:12 

American 11:21 40:17 

41:2,19 57:18 58:3 

67:9 70:9 73:7,13 

86:19 87:8 89:17 

94:11,15,20 95:2,9,13 

96:2 205:18 208:17 

269:5 290:9,10 

291:20 292:16,19 

295:6 296:22 297:18 

304:3 310:7,22 311:4 

341:19 344:22 347:8 

Americans 278:18,19 

295:1 

Americas 2:14 12:15 

28:4 37:7 

amount 29:15 39:19 

88:9,10 92:3 95:10 

96:4 103:9 176:3 

180:12 212:8 224:14 

224:15 232:7 326:16 

330:10 364:19 387:18 

amounts 52:9 

ample 4:22 98:5 333:18 

amplify 31:6 221:14 

250:10 

AMS 2:4 68:15 

Amy 370:7 

analyses 197:5 199:8,9 

199:10 

analysis 100:10 167:13 

168:10 173:11,17 

176:8 186:15,17 

195:4,7 198:1 

analyst 177:22 181:4 

analysts 180:9 

analyte 177:21 

analytes 169:16,20 

181:22 182:1,4 

analytical 166:5 175:18 

analyze 242:9 287:14 

analyzed 170:17 181:15 

182:14 187:2,15,16 

analyzing 217:14 

ancestors 12:2 

animals 384:2 

animation 168:15 

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308:9 371:12 

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183:14,19,21 184:4 

193:19 207:21 209:13 

210:2 235:13 237:15 

240:18 242:14,21 

322:7 329:9 395:4 

annualized 212:20 

243:3 244:10 

annually 319:10,11 

343:17 345:17 

anomalies 244:20 

answer 45:15 49:6 

185:10 187:4,5 

199:19 224:8,12 

225:11 226:8,18 

228:15 238:11,12 

275:9 291:12 293:1 

294:12 297:19 314:14 

327:7 330:13 350:1 

354:14 356:13 360:18 

372:16 375:6,7,8 

answered 91:20 152:5 

answers 57:12 71:1 

91:16 93:2 

anti-dumping 35:9 

115:16,20 142:20 

anticipating 207:7 

anybody 69:18 90:3 

152:15 313:7 326:2 

355:18 363:21 379:21 

386:7 394:16 

anymore 266:7 

anyway 21:2 30:20 

62:18 74:6 122:22 

162:8 188:18 190:3 

375:20 

APA 257:6 

apart 387:9 

apartment 325:2 

332:17 

apartment-type 324:17 

apartments 323:22 

339:8 

apologize 51:3 80:3 

168:16 169:1 185:7 

218:11 

app 184:5 

apparently 202:11 

214:11 

appetite 150:14 

applaud 93:20 

apple 50:9 128:5 290:1 

298:10 299:1,4 

380:15 381:8 

apples 80:5 169:15 

172:20 175:13 236:20 

300:1,4 350:17 

Applesauce 96:17 

applicable 6:21 239:1 

376:2 

applicant 206:1 278:21 

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206:16 275:18 279:5 

279:20 282:18,20 

283:3,13 289:22 

302:19 303:13 305:10 

319:11 322:6,10 

330:7,20 

applications 9:1 157:22 

177:9 178:11 257:21 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
399 

259:20 263:21 264:5 

264:6,14,15,15 269:9 

272:11 279:10 302:13 

303:4 319:17 329:13 

329:17 331:1 334:20 

applied 77:6 161:11 

174:7 258:11 

applies 368:4 

apply 45:11 86:15 

269:6 295:2,19 

318:11 319:14 322:8 

359:21 

applying 73:18 320:17 

appointee 316:22 

appreciate 4:5,6 7:1 

41:9 49:5 52:8 139:18 

150:9 152:13 153:6 

157:10 254:14 255:2 

255:14 280:5 285:3 

approach 67:3 166:21 

172:12 173:7 174:18 

177:16 209:7 350:11 

359:3 360:20 365:14 

approaches 27:16 

68:12 

approaching 144:15 

appropriate 91:22 

160:16 349:3 350:20 

355:8 359:4 361:5 

366:4 

appropriated 285:7 

320:2 

appropriately 213:5 

349:15 

appropriation 86:10 

221:10 322:7 

appropriators 86:13 

approval 45:11 161:18 

261:13 305:14 307:18 

approve 5:10 162:7,11 

276:5 390:6 

approved 91:6 123:4 

161:20,22 162:1 

188:18 280:11 305:22 

308:12 

approximately 170:13 

April 210:7 240:7,14,15 

Arabia 147:8 

arbitrarily 231:21 232:1 

arbitrary 144:6 

architects 324:15 

area 31:20 39:13 56:18 

73:12 84:10 86:8 

108:2 126:5 240:18 

244:7 247:10 273:6 

283:8 289:16 295:13 

295:19 320:17 321:3 

348:10 363:3,5 

364:15,22 367:20 

374:12,18,21 378:10 

areas 38:6,11 43:19 

52:2 55:20 56:2 57:11 

103:22 141:13 173:1 

205:3 207:18 225:20 

243:7 244:1 262:6 

272:22 273:19 298:2 

325:10 331:11 

arenas 32:21 

arguably 357:3 

argue 121:1 

argument 235:17 

Arizona 285:17 350:4 

356:1 357:17,18 

382:5 

Arkansas 323:5 

Arlington 1:9 

arm 46:15 

arrangement 222:17 

array 286:17 

arrive 17:13 175:6 

arrived 99:4 312:4 

arrives 92:8 

arriving 172:21 

articles 186:18 

articulate 254:22 

artificial 278:8 

artificially 278:12 

Asia 53:2 138:2 150:20 

aside 271:22 

asked 70:3 185:18 

234:1 236:11 237:14 

237:14 267:4 324:21 

330:3 348:14 377:11 

380:10 

asking 40:16 93:9 

187:2 216:9,22 

220:13 259:18,20 

353:20 

aspects 350:20 365:22 

367:8 

assertion 377:21 

assess 178:15 358:10 

358:17 366:12 392:19 

assessing 366:5 

assessment 169:5 

177:9 195:19 

assessments 166:10 

174:10 178:18 195:8 

195:12 197:20,21 

assign 231:21 

assist 37:7,9 344:9 

assistance 153:11 

322:9,11 343:4 

assisting 168:14 

associate 318:1 

associated 8:6 259:12 

366:13 

association 2:7,13,14 

12:15 28:4 37:7 81:1 

223:11 272:8 348:6 

350:10 381:22 

associations 47:21 

271:21 272:6 318:17 

341:14 348:11 

assume 12:4 186:6 

219:10 230:21 255:9 

356:12 

assumed 352:10 

assuming 239:3 386:17 

assurance 305:7 

ATAC 90:11 

ATAC's 90:6 

ate 12:2 128:5 378:1 

attach 306:3 

attachment 338:20 

ATTENDANCE 2:1 

attention 15:17 122:3 

293:18 294:4 350:13 

attributes 365:22 

audibles 385:21 

audience 233:8 238:20 

audit 260:4 291:17,18 

345:11,20 346:3 

363:14 383:21 384:2 

audited 291:17 345:18 

382:6 384:5,17 

auditing 9:10 345:4 

audits 191:2 310:17 

358:8 383:1 

August 1:7 83:19 236:2 

271:12 

Australia 132:16 133:9 

133:16,21 

Australian 133:10 

authorities 223:22 

authority 145:9 166:14 

179:17 298:8,8 

326:10 

authorization 91:11 

authorize 303:17 

authorized 85:15 

auto 61:5 119:17 

120:22 121:2,9 146:7 

automated 118:22 

automatically 23:1 

automobile 118:5,6,6 

118:13 

automobiles 61:5 

117:16,19 118:19 

119:15,18 120:12 

134:6 

autos 120:8 

availability 269:22 

available 10:4 42:5 

67:18 96:5 97:11,14 

124:5 126:8,8 156:14 

167:6,19 172:5,9,15 

174:15 180:14 181:10 

183:14,22 186:21 

197:5 199:6 217:22 

266:12,15 268:13 

318:20 319:9 326:15 

343:7,13,14 345:13 

366:17 

avalanche 337:2 

avenue 22:17 326:11 

average 126:17,20 

137:3,5 210:14,15 

212:3,17,20 230:6,9 

230:10,11 231:10,13 

240:13,13 266:5 

269:9 295:16 322:17 

322:19 

avocados 31:9 67:16 

avoid 32:6 120:14 

125:6 143:8 

award 320:6 

aware 36:1 61:16 

139:15 151:6 201:21 

211:11 223:10 227:2 

257:15 301:14 

awfully 352:3 

B

B 249:22 

baby 13:19 172:14 

back-to- 278:3 

backed 50:8 

background 317:4 

348:8,9 

bad 122:5 129:20 130:1 

283:16 289:7 335:22 

380:15 381:8 388:3 

badmouthing 296:20 

balance 18:3 126:5 

148:2,3 

balanced 17:13 

balances 148:5 

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bananas 170:8 173:19 

175:12 

band- 80:10 

bank 316:14,16 317:2 

336:21 

banking 316:14,15 

317:1 322:14 

banks 336:13 

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Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
400 

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317:9 

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369:7,8 

Bars 31:18 

base 20:15 66:17 156:4 

205:5,6,10 209:22 

212:7,22 213:1 217:6 

227:7 233:11 237:16 

238:22 267:11 

based 15:5,18 21:17 

22:3 24:17 47:6 60:1 

101:3 113:8 145:17 

146:9 169:4 171:2 

188:7 197:17 198:7 

208:1 215:3 227:20 

233:14 236:5 237:9 

241:14 244:22 260:7 

268:12 277:19,21,22 

278:5 280:9 288:10 

314:1 345:7 348:16 

350:4 360:20 

basic 302:18 379:3,5 

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56:10 60:16 84:17 

85:16 93:7 114:7 

124:20 154:20 218:22 

233:20 287:3 289:8 

320:10 352:17 358:19 

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209:15 210:2 235:20 

242:21 244:10 

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328:13,16 332:15 

339:12 

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133:4,7,10 

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believe 16:15 20:2 34:3 

36:2 40:17 41:2 54:9 

64:6 65:5 67:9 70:12 

72:8 78:4 93:21,22 

155:13 159:17 243:1 

279:8 307:16 317:2 

332:8 

believed 263:1 

bell 2:1 170:8 

belt 83:14 

bench 362:14 

benchmarked 345:19 

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127:18 

beneficiary 109:11 

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106:8 127:7 178:22 

214:21 284:13 310:11 

323:6 

benefits 124:15 

best 41:13 52:18 54:16 

67:3 68:18 76:12 

91:15 96:15 101:4 

103:7 148:8 213:3 

242:10 255:1 

better 6:16,17 9:17 

25:19 31:14 47:15 

65:18 78:6 81:2 88:18 

102:21 103:7 106:4 

107:1 108:17 109:18 

122:14 127:6,17 

130:6,6,15 131:9,10 

132:20,22 133:17 

134:18 137:16 138:18 

145:7 146:3 161:8 

166:13 185:11 200:5 

212:10 244:18 283:15 

284:6,12 309:3 310:3 

332:10 369:5,6 

374:13,18 

beyond 48:3 241:21 

344:2 376:6 383:11 

385:1 389:16 

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big 29:7 32:21 41:17 

42:6 86:3 89:3 100:16 

105:14 108:18 111:13 

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121:5,9,10 123:4,11 

124:10 126:12 127:2 

127:3 129:1 133:7 

134:12 136:11 147:9 

154:18,19 232:21 

243:22 248:22 257:12 

264:13 266:15 272:10 

275:21 281:13 299:13 

308:18 323:6,6 331:9 

358:15 363:10,12 

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149:20 196:12 252:15 

264:17 265:20 362:22 

371:14 

biggest 16:4 78:15 

85:20 115:17 117:6 

119:15,16 132:15 

140:2 158:16 283:9 

325:7 

bike 203:2 

bilateral 53:2 150:13 

bill 34:5,12 40:8 47:18 

47:19 49:9 50:6 73:10 

75:19 76:2,3,3 82:22 

83:4,6,14,15,18 85:15 

86:22 87:10 286:2 

billion 29:16,19,20 31:2 

112:16,21 114:5,8,9 

119:13,13,18,18,20 

123:15,18,20 125:2 

125:13 126:6 132:9 

135:11 138:15 146:22 

147:1 177:7 

billions 111:7 119:12 

binding 142:16 

bios 365:19 

biotech 161:15 

bipartisan 49:18 

bit 4:12 14:16 16:22 

24:10 34:9 40:20 

45:22 46:15 50:9 

57:12 59:9 68:14 

69:11 75:4 92:7 101:9 

101:13 102:8 113:16 

125:8 135:10,11 

138:18 146:10 157:20 

165:9 184:18 192:21 

207:8 208:2,3 228:14 

257:1 258:7 259:16 

265:3 278:9 305:10 

317:4,5 319:19,20 

342:6 345:3 348:15 

349:12 354:8 355:22 

356:11 357:20 359:2 

367:19 387:5 389:20 

bits 373:12 

blanks 177:18 

blend 216:16 

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block 47:21 56:4 68:6 

68:15 143:4 300:7 

blockchain 23:13 26:1 

26:19,19,21 27:3 

blocking 57:4 

blocks 182:20 

blow 280:2 

blown 134:10 

BLS 202:4 209:18 

218:10 224:3 243:8 

252:19 288:8,8 313:7 

313:21 

blue 115:8 116:16 

117:8 118:5 263:18 

264:3 

blueberries 29:3 67:12 

89:12 172:7,8 

board 29:8 55:5 132:18 

134:2 389:4,7 391:2 

boards 89:8 159:9,9 

369:22 

Bob 370:5 

bodies 255:6 

body 55:1 308:3 384:1 

392:21 

boggling 72:7 

bolts 133:2 

bonus 327:14 

bonuses 205:7 

book 340:16 393:19 

bookkeeping 227:13 

books 349:13 

boom 109:10 147:13 

boost 96:22 

border 258:22 371:20 

borders 107:9 125:15 

borrower 321:13,14,16 

336:14 

borrowers 318:11,14 

318:16 

boss 255:22 

bottom 184:2,12 

bought 41:16 69:17 

73:21 316:16 373:16 

381:1 385:12 

bounce 118:10 

bouncing 21:17 

bounded 109:1 

BOWMAN 1:13 34:2,21 

35:10 71:15 

box 48:3 

boy 285:11 

Brad 274:10 

brain 265:15 

branch 207:17 226:13 

271:4 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
401 

brand 121:15 

branded 373:17 

brands 341:20 383:10 

Brazil 98:4 

bread 128:7 

bread-and-butter 273:7 

breadth 243:2 

break 5:4 62:5 92:8 

99:5,7,10 286:9,11,11 

286:12 312:1,5,14 

314:20 389:21 

breakfast 84:2,19 368:8 

breakout 209:8 229:19 

breaks 211:2 

breeze 206:18 

Brenda 2:7 164:4,16,22 

Bret 1:15 39:12 59:19 

65:15 

Brett 198:17 

Brian 1:17 2:15 184:17 

202:17 210:12 213:11 

218:13 234:13 254:12 

255:19 256:6,9 

262:17 274:6 282:14 

288:16 294:20 299:19 

312:9 314:17 325:17 

Brian's 187:4 

bridge 63:17 

brief 312:8 347:21 

briefing 340:15 

briefly 308:20 388:13 

bring 5:7,22 8:7 17:10 

30:15,17 38:3 47:18 

55:18,21 134:1 138:5 

139:12 141:6 148:10 

148:20 173:6 211:4,9 

269:4 296:15 302:3 

391:6 394:17 

bringing 29:12 383:6 

brings 50:3 133:17 

broad 100:18 101:3 

207:20 237:12 270:12 

341:17 

broad-based 289:19 

broader 119:5 195:3 

239:10 

broadest 238:19 

brought 75:4 79:2 

161:4 181:18 183:16 

214:12 313:10 355:16 

375:11 

BROWN 324:1,7,19 

333:21 334:8 361:12 

362:22 363:20 

Bruce 1:19 2:11 241:16 

241:21,22 244:7 

315:8,9,11 

Bruce's 242:1,3 244:7 

brunt 117:6 

buckets 52:9 

bucks 294:2 

budget 148:14,15,18 

154:11 194:5 238:17 

285:22 395:4 

buffers 159:17 

build 199:17 207:10 

289:12,14 322:3 

324:6,10,11 325:11 

325:20 326:12 331:11 

331:12,16 332:11 

335:15 338:12 

building 166:18 324:13 

324:14 331:17 351:22 

builds 261:9 327:1 

built 14:17 72:6 297:9 

328:12,17 358:5 

built-in 270:13 272:13 

273:21 

bulk 80:21 264:13 

bullet 254:21 272:19 

366:16 380:7 382:22 

bullets 168:18 349:20 

372:3 

bunch 131:5 186:18 

298:13 

burden 238:18 239:16 

342:22 

Bureau 201:14,17 

226:21 

bus 280:11 

Bush 288:9 

busiest 236:3 

business 16:7,10 18:15 

18:20 27:8 35:3 36:11 

39:6 40:19 102:2 

124:1 130:2 186:16 

223:19 262:9 292:15 

383:3 385:19 

businesses 6:22 

busting 242:19 

busy 6:9,10 7:2 

button 348:20 

buy 8:14 12:9 33:8 

41:19 67:8 69:17 

71:17 72:9 73:5,6,13 

78:16 87:8 89:12,17 

94:20 95:2,8,13 96:1 

135:3 148:12,12,12 

148:21 149:4 332:17 

361:19 363:4 373:15 

379:5 384:14,16 

385:6,11,15,17 

buyer 379:13 383:4 

buyers 64:7,18 65:3 

350:15 362:18 363:12 

382:20 

buying 37:15 42:4 70:1 

95:7 103:10 118:9 

149:11,14 363:11 

379:14 380:4 382:12 

386:8,10,12 

C

C 249:22 

C.B 2:6 318:1 323:12 

327:7,11 

C.B.'s 338:19 

cabinets 373:9 

calculated 243:1 

calculating 287:14 

calculations 205:13 

288:14 

calculators 352:22 

calendar 167:16 232:2 

234:7 263:17 

California 25:13 45:19 

55:4 73:20 88:10 

99:22 100:1 168:4 

175:3 188:17,20 

189:4 190:13 234:4 

236:19 253:9,13 

285:17 299:12 323:4 

329:18 331:7,12 

334:16 350:3,9,9,15 

356:6 357:8,10,12,15 

357:16 358:19 364:10 

366:2 382:4 

call 3:2 4:4 5:15 55:22 

66:19 112:11 190:2,2 

190:6,7 245:22 

286:13 301:18 304:3 

326:17 327:17 345:8 

395:16 

called 10:6 12:21 13:10 

61:18 121:14 251:19 

269:2 276:9 286:19 

324:11 352:6 

calling 249:19 

calls 7:15 345:7 355:1 

368:21 390:14 

camp 273:10 290:2 

camps 326:17 

Canada 28:18 35:17,20 

36:22 37:21 38:8 

58:13,13 60:20,20 

64:10,13,14 71:17,21 

72:1,6 75:11 94:21 

111:18 114:15 115:2 

117:9,11 119:11,15 

120:4 121:14 123:5 

123:17 124:19 132:16 

133:20 142:10 147:8 

Canadian 64:16 71:17 

72:9 

Canadians 64:11 

canal 354:3 356:2 

cancellation 178:20 

cancelled 197:1 

Cancer 11:22 

cannabis 13:14,18,22 

14:6,12 15:10 17:16 

19:21 20:1 23:16 

canned 94:16 139:5,6 

170:10,10 182:21,21 

canning 139:7 317:16 

cantaloupe 170:8 

capabilities 176:15 

capable 27:4 

capacity 37:1 145:18 

145:19 146:5 342:10 

342:10 343:2 385:1 

386:14 

capital 36:20 319:1 

Capitol 85:18 

caps 215:21 

capture 153:19 172:3 

227:17 235:16 

captured 173:15 

captures 172:13 215:7 

250:17 

carbamates 176:17 

card 120:6 276:8,11 

373:14 

cards 27:8 264:16 

care 237:17 255:6,9 

266:4,10 273:11 

career 223:8 316:15 

careful 128:17 293:18 

Carl 10:5 

Carolina 168:3 243:8 

280:14 282:19 283:21 

cars 118:9 

case 19:22 76:6,15 77:3 

77:5 82:1 87:20 

126:15 145:11 203:12 

255:21 269:14,18 

276:8,13 301:5 

366:10 373:7 375:22 

385:22 

cases 34:17 88:4 

103:18,19 134:22 

136:20 137:2 174:2 

259:13 279:16,22 

300:15 

cash 102:10 

catch 151:3 250:7 

332:4 

catchers 175:20 

categories 209:9 211:6 

216:20 217:9 246:12 

category 218:8 253:20 

caught 120:2 130:19 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
402 

cauliflower 373:17,20 

374:1,7,9 387:20 

cause 193:4 273:1 

305:9 

caused 162:5 346:11 

390:2 

causing 243:2 

cautious 351:1 365:5 

366:22 

CBP 258:22 

CDC 342:10 346:19 

347:10 368:18 370:7 

374:3 375:1,2,12,20 

377:16 378:9,11 

ceiling 261:5 267:7,16 

309:10 

celebrated 129:9 

census 171:5 201:15 

201:20 207:19 208:7 

208:10,17 209:1 

213:17 214:7,9,10,10 

214:12 226:12,17 

227:3,6 234:19 

235:10,18 236:6 

237:11 

center 264:18 359:7 

centers 174:1 222:13 

264:11 

centralized 19:6 338:6 

338:8 

cereal 368:8 

cert 268:9,19 

certain 39:11 66:1 

74:10 82:5 87:21 

103:22 105:3 149:16 

149:16 162:18 163:11 

163:17,21 172:4 

197:9,11,12 236:16 

243:7 259:22 261:4 

293:19 296:11 298:2 

381:17 

certainly 47:17 48:13 

48:18 52:8 59:18,18 

71:1 73:8 85:20 88:9 

119:22 120:11 141:8 

157:9 196:10 

certainty 113:12 123:8 

160:22 

certification 158:16 

256:11 259:5 261:12 

303:20 305:19 306:2 

307:9,10 343:11 

certifications 258:12 

260:20 269:8 290:21 

291:8 

certified 260:6,11 

261:17 280:18,18 

379:3 

certify 273:16 336:13 

certifying 262:12 

certs 261:21 305:17 

307:1 

cetera 96:18 

chain 38:5 76:22 

379:10,21 380:1 

385:4 387:6 

chains 68:1 

Chairman 44:19 83:9 

challenge 40:4,20 41:6 

53:13,20 70:2 213:7 

221:6 223:21 225:15 

329:6 331:21 352:18 

challenged 69:12 89:7 

challenges 16:4 42:15 

52:22 55:7 56:7,9 

73:19 126:7 153:10 

153:22 154:16 206:4 

284:18,20 353:10 

369:20 378:19 

challenging 152:12 

358:11 

Chalmers 1:10,12 

203:21 219:6 237:14 

251:1 262:5 274:9 

282:15 283:1 301:3 

305:18 388:19 

Chalmers' 223:14 

224:21 297:12 

champion 149:5 

chance 70:10 92:2 

136:21 152:8 261:16 

270:16 339:22 

Chandler 1:13 237:13 

change 35:8 42:21,21 

74:20 76:20 107:15 

120:17 205:21 218:9 

287:5 332:7 340:4 

393:10 

changed 56:12 270:17 

378:13 

changes 49:22 54:7 

78:10 125:20 216:17 

220:3,5 389:6 392:21 

changing 196:15 

channels 387:6 

chaotic 55:7,10 

character 321:4 

charge 133:4,5 226:13 

302:2 

charged 224:1 

Charles 1:21 53:14 

54:17 153:1 310:12 

Charles' 245:8 

chart 102:9 106:9 108:1 

109:12 113:19 115:6 

118:4 119:7 121:18 

122:3 136:6,17 

137:21 146:20 154:3 

187:19,20 263:14 

charter 395:13,13 

chartered 47:2 

cheap 332:12,12 

cheaper 10:6 346:3 

check 184:9 

cheese 104:7,9 136:9 

chemical 9:1 12:3,6 

62:4 153:14 157:22 

162:13 163:3 191:8 

191:10 

chemicals 11:17 

195:20 

chemistry 158:7,19 

162:1 

chemists 167:14 

177:14 

cherries 79:5,7,10,18 

81:18 298:11 

chief 13:9 207:16 

child 73:9 82:12 86:9 

86:22 87:9 127:17 

337:22 

children 48:10 127:17 

166:8 169:11 172:19 

196:2 

Chile 133:20 

Chilean 87:22 

China 45:5,21 50:9,20 

51:8,18 52:19 79:6,7 

81:18 82:22 101:10 

105:13 112:1 114:2,4 

114:4,16 115:2,9,17 

117:4,7 120:15 123:6 

125:8,9,10,17 126:13 

126:22 127:3,8,14,21 

128:4,7,11,12,21 

129:1,13,20 130:2,3,4 

130:9,9,13,22 131:1,4 

131:9 132:19 136:20 

139:8 148:19 149:12 

150:1,3 

China's 32:21 126:20 

129:20,21 

Chinaman's 128:3 

Chinese 51:1 73:21 

89:16 127:10 128:5,6 

129:22 130:5,14 

149:13 151:8 

choice 32:8 96:6 

310:22 

choose 204:4 290:10 

choosing 114:21 

Chorus 395:20 

chromatography

176:20,21 

chunk 227:4 

church 159:9 223:3,6 

Cincinnati 355:13 

circumstances 65:9 

159:20 273:21 355:19 

365:4 

CIS 305:15,21 306:4 

307:9 308:8,14 

citizen 321:10 

citrus 236:17 248:20 

350:17 

City 1:9 59:2 

civil 379:19 

claim 173:14 

clarification 315:11 

clarity 5:22 324:20 

class 110:17,21 118:17 

classes 248:5 

classification 217:4 

230:3 247:16 251:18 

classifications 211:1 

249:11 314:1 

classified 228:5 252:6 

269:20 

classify 258:14 

classroom 84:20 

clause 35:2 

cleaner 12:1 337:12,14 

337:15 352:17 

clear 215:19 238:17 

287:8 304:18 349:8 

351:13 367:19 368:5 

376:20 381:14 394:12 

clearly 254:21 266:19 

350:5 367:16 

clients 38:4 

climate 260:8 342:20 

clipboards 373:9 

close 15:17 17:4 29:5 

100:1 124:1 265:12 

334:21 335:14 

closed 125:15 

closely 45:14 46:21 

47:17 140:11,15 

146:8 174:12 195:10 

205:15,16 223:9 

370:6 

closer 37:15 211:2 

316:7 354:13 

closes 334:20 

closest 159:18 173:21 

cloud 391:9 

clunky 77:13 

cluster 386:22 

cocktails 316:6,7,8 

coconuts 104:12 

code 247:21 248:2 

codes 328:17 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
403 

Codex 45:4 

codifying 277:7 

coding 247:1 

coefficient 217:18 

coffee 104:12 

cognitive 212:8 255:14 

coli 351:18 354:1 356:2 

366:11 

colis 352:16 

collaborate 17:11 90:11 

341:13 360:13 370:16 

collaborating 342:9 

collaboration 90:17 

161:20 204:14 206:10 

370:9 

collaborative 163:19 

375:11 

collards 66:19 

collateral 50:12,16 79:2 

colleague 202:8 

colleagues 170:22 

173:4 

collect 15:9 25:19 27:1 

165:20 170:12,20 

175:3 210:3 220:19 

222:18 223:22 229:8 

238:22 242:9 374:5 

collected 24:5 171:9 

173:10,21 174:19 

183:7 205:17 

collecting 174:21 

222:21 224:1 228:1 

228:20 230:22 287:13 

360:7 

collection 166:4 168:9 

174:11 186:16 222:2 

222:9,12 

collective 286:22 

collectively 64:21 

388:18 

collects 224:3 

college 267:3 

collocated 318:9 

Colorado 13:7 68:22 

168:4 241:16 244:1 

colors 354:5 

Columbia 112:19 

column 221:1 

columnist 202:5 

combat 35:2 

combination 47:14 

177:21 184:6 320:8 

combine 216:15 

combined 210:20 241:3 

289:1,20 

come 12:18 22:5 26:10 

31:8 36:2 37:12 40:5 

42:15 46:5 49:13,21 

57:22 71:8,13 81:7 

85:17 86:1 87:6,15 

91:18,19 93:10 99:7 

108:10 116:3 123:19 

148:10 158:5 179:14 

203:15 212:1 219:5 

220:9 225:7,10 231:2 

249:2 250:8 256:1,2,6 

257:9 263:16 286:12 

293:16 298:4,18 

304:13 306:10 307:10 

327:21 329:22 333:11 

341:15 348:14 352:2 

356:18 358:20 372:16 

387:13 388:19 389:14 

389:21 390:2,10,22 

392:6 

comes 23:1 24:13 26:1 

71:4 102:12,13 110:4 

123:16,17 134:13 

163:20 196:7 207:3 

210:17 220:21 235:17 

249:1 257:14 264:19 

272:17 287:15,16 

298:21 310:16 330:20 

366:12 

comfortable 108:9 

344:13 361:10 

coming 31:11 32:11 

35:5 36:9 42:18 43:21 

57:4 64:2 65:13 66:8 

66:16 71:5 76:21 97:3 

107:17 108:10 109:9 

110:8 111:5 117:10 

154:5,18 159:7 

165:18 188:17 190:14 

206:1 209:16 228:18 

229:10 248:14 253:4 

257:17 266:2 267:5 

267:22 271:18 292:1 

292:3,20 295:17 

296:18 297:2 301:13 

310:4 331:1 334:11 

337:2 338:15 340:20 

360:9,14 365:13 

367:12 385:3 

commend 82:8 

commendable 72:18 

comment 11:3,7,14 

12:11,13 33:22 34:2,9 

39:5 62:10 79:1 90:3 

186:2 188:2,16 

194:13 218:14 242:12 

254:18 262:5 268:1 

271:1 277:16 285:4 

293:3 294:20 295:4 

304:11 308:20 339:1 

361:13 

commentary 36:13 

commenting 200:12 

comments 3:3 11:15 

20:10 27:17,20 41:8,9 

43:2,11 47:5 72:12 

82:4 90:5 93:4 98:16 

139:3 342:18 348:16 

366:22 

commerce 20:8 24:6 

25:11 27:3 81:8 

117:16 124:15 145:12 

commercial 96:19 

155:5 318:12 

commitment 153:6 

362:1 

commitments 133:3 

141:20 143:10,13 

committed 132:12 

304:10 368:19 

committee 1:3,8 3:4,6,9 

3:16 5:8,11 6:10,14 

7:17 8:4,5 9:4 20:10 

22:7 32:3 33:13 36:10 

37:10 40:4 43:11 

46:19 47:1,3 48:14 

49:6 52:4 59:9,21 

60:1,3,6,19 61:11,19 

61:22 62:16,17 63:3 

68:14 69:3 71:13 

82:16 83:10 85:21 

89:4 90:7,10 93:6,10 

93:21 94:5 95:12,16 

95:19 97:3,5,18 99:8 

152:4 156:12 180:11 

200:13 254:20 346:17 

347:12 369:12,14 

385:2 389:3,7,12 

390:13 392:17,19 

395:3,6,10 

committee's 7:22 

committees 7:10,12 

61:18 89:8 90:8,13,14 

200:18 327:22 369:22 

commodities 29:2,8 

66:2 74:14 79:22 

81:15 116:21 131:16 

166:17 167:8 169:3,6 

169:10,20 170:1,3,3,7 

171:16,21 172:2,4 

174:15 180:20 181:20 

194:8,11 196:1 347:7 

350:13,18 354:14 

364:16 

commodity 51:9,10 

52:13 56:10,10 60:2 

62:1 157:7 169:17 

170:14,18 171:22 

172:17 173:1,8,12 

174:22 176:11,13,14 

177:6 178:3 182:2,13 

182:18 184:6 193:15 

197:16 365:22 377:9 

379:2 383:16 385:8 

common 175:7 176:16 

219:18 296:10 374:1 

commonly 204:16 

229:12 

Commonwealth 306:20 

communicate 9:17 

360:5 365:17,19 

381:15 

communicated 382:13 

communicating 303:9 

communication 369:6 

374:21 

communications

374:22 

communities 334:13 

community 15:20 16:7 

16:9,14,17 17:12,19 

18:9,14 19:12 20:4 

25:4,8 26:4,16 31:19 

52:12 316:12 317:12 

322:1 338:7 363:11 

383:9 

community's 335:1 

comp 301:22 305:6 

companies 18:21 20:13 

32:12 66:12 69:22,22 

130:1 142:7 296:12 

386:7 

company 12:20 13:10 

63:10,22 157:4,5 

248:12,14,15,18,19 

249:18,21,22,22 

380:8 386:3,6 

company's 20:18 

comparative 125:21 

compare 180:5 252:16 

378:2 

compared 55:12 62:15 

80:20 156:20 

comparing 252:18 

compelling 186:9 

378:22 

compensate 159:3 

compensated 159:11 

compensation 279:13 

compete 42:16 65:12 

97:12 98:1 103:20 

105:1 132:20,22 

146:3 

competes 104:13 

competing 42:7,9,13 

65:2 154:10 337:17 

competition 30:20 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
404 

94:10 97:13 98:1 

119:2 131:21 135:19 

337:3 

competitive 103:14 

104:21 105:20 111:2 

137:8 318:14 319:7 

competitively 138:5 

competitiveness

103:20 

competitor 88:12 

competitors 115:17 

132:6 

compile 217:16 354:11 

compiled 167:16 

complaint 77:14 

complaints 151:11 

complement 85:7 

complementarity 124:3 

complete 63:19 

completely 243:9 

282:19 311:18 

complex 332:18 

compliance 17:20,21 

18:11 239:7 279:11 

303:2,6 307:8 

complicated 142:13,13 

351:20 374:2 

comply 18:10 343:5 

344:10,21 345:1 

371:20 

component 147:22 

215:5 

compound 178:16 

compounds 169:19 

176:16 

comprehensive 15:8 

17:18 20:6 24:18 

comprehensively

13:17 

compromisation 385:8 

conceived 297:15 

concept 276:20 286:19 

366:4 

conceptual 101:2 

concern 24:3 33:9 

51:20 100:21 135:13 

151:7 180:19 213:6 

338:14 

concerned 45:2 51:10 

68:5 129:19 183:8 

251:6 

concerning 144:15 

concerns 7:19 25:1 

41:17 42:2 97:6 

180:21 307:20 

conclusions 104:17 

condition 72:5 

conditions 127:16 

172:14 

conduct 167:10 298:10 

conducted 208:11 

conducting 195:11 

conducts 252:19 

conference 5:15 7:15 

390:14 395:16 

confidence 166:18 

179:11 199:17 

confident 376:17 

confirm 71:20 

conflict 111:16 120:14 

130:13,18 369:17 

Congo 106:19 

Congress 36:6 48:22 

50:6 73:15 83:8 97:8 

123:2,5 124:12 145:5 

145:8 269:13 270:11 

270:20 271:16 285:7 

285:8 325:5 336:6 

Congressional 140:4 

290:14,17 297:10 

conjunction 273:15 

276:21 

connect 236:8 

connecting 317:20 

consensus 5:11 390:4 

390:6 392:12 393:16 

394:19,22 395:17 

consent 392:6,8,8 

consequence 114:19 

125:5 

consequences 359:20 

consider 95:17 196:15 

298:3 299:15 375:14 

consideration 8:21 

73:10 295:22 336:20 

considerations 14:5 

286:18 337:17 

considered 8:14 96:14 

96:17 161:11 357:7 

considering 65:9 351:9 

360:11 

considers 354:15 

consistent 58:21 163:9 

consolidation 206:3 

constitute 270:9 275:22 

constitutes 270:21 

275:15 393:15 

constraining 130:3 

constraints 138:4 

154:11 

construction 278:13 

289:11,14,15 290:2 

320:10 

consulate 284:21 

consulates 258:20 

consultant 309:4 

consultation 144:21 

consume 149:4 

consumed 166:7 

169:14 172:19 

consumer 24:2 32:8 

38:19 39:8 65:20 66:4 

66:21 70:20 88:1 

106:10 154:8 166:18 

173:21,22 174:4,8 

175:8,11 179:1,11 

199:17 346:22 347:14 

347:15 

consumer-oriented

136:8 

consumers 29:2 30:16 

30:16 32:4,7 38:3 

66:12 77:1 88:22 

89:13,14 102:1 133:6 

147:10 149:5,15 

174:13 185:3 

consumes 65:22 

consuming 109:15 

consumption 29:1 33:5 

33:17 39:15 41:1,11 

47:15 66:1 72:16 

82:10 94:15 106:7 

146:13 149:9 169:6 

169:11 226:15 366:13 

374:8 378:13 

contact 15:3 184:11 

222:16 312:19 357:6 

contacting 9:19 364:20 

contained 182:15 

contaminated 356:12 

372:20 

contaminates 189:19 

contamination 374:14 

374:15 

contemplate 224:21 

CONTENTS 3:1 

context 199:1 208:9 

continue 16:10 42:21 

48:2,17 51:18 52:6,17 

54:9,10 69:4 75:17 

83:5 87:18 97:11 

212:16 342:13 360:13 

362:18 374:5 

continued 269:5 304:6 

continues 48:15 76:15 

continuous 34:18,19 

169:8 

contract 215:7 222:17 

254:6 277:18 284:7 

302:8 

contracted 97:1 249:5 

contracting 247:9 

contractor 214:2 215:5 

228:4 245:10,13 

251:8,16 254:7 255:3 

263:4 279:14 283:2 

331:18 336:1 339:19 

contractors 213:20 

224:16 225:21 234:22 

245:17 255:20 262:4 

262:8,19 263:10 

265:22 267:11 271:21 

283:9 331:8 332:1 

334:12 335:6 337:8 

340:8,9 

contracts 191:5 278:4,6 

278:15 295:3 309:17 

control 223:1 247:1 

318:16 368:12 

controls 177:19 343:21 

344:1,7 367:22 368:4 

368:8,13 370:20 

379:11 

controversial 122:2 

convened 355:11 

conventional 44:15 

333:12 

conventionalism

140:21 

conventionally 171:20 

conversation 24:11 

40:11 44:22 50:17 

215:12 266:18 314:5 

350:2 355:20 365:11 

375:3 

conversations 62:13 

152:7 210:11 242:3 

244:19 308:7 386:12 

391:13 

converse 391:11 

conversion 13:22 

convey 242:7 

conveyed 356:20 

convinced 353:22 

convincing 255:19 

cook 290:2 

cooks 273:10 

cool 175:9 

cooperation 210:10 

cooperative 167:1,3 

168:1 221:16 

cooperatives 97:22 

coordinate 90:11,19 

169:18 

coordination 7:16 

copy 183:16,21 306:13 

307:6 

core 351:18 

coring 175:13 

corn 50:14 142:21 

154:2 156:21 169:15 

175:14 182:19,21 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
405 

193:7 

corner 252:8 

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correct 11:11 58:7,9 

61:5 163:7 187:14 

188:14 190:16 213:19 

214:7 219:3 263:5,8 

290:11 303:15 314:2 

377:8 384:9,12 386:5 

386:19 395:8 

correlation 194:15 

240:17 

corresponding 161:17 

cost 42:12 64:22 65:7,8 

95:22 96:6 115:11,12 

176:1 302:1 319:4 

330:11,12 332:15 

costing 19:2 

costs 42:17 89:11 

139:7 176:4 

cotton 160:11 

could've 310:22 347:18 

Counsel 100:8 

counselor 99:21 

count 209:5 226:10 

233:9 246:5,8 252:14 

252:17 253:5 254:1 

260:3 

counted 213:18 235:9 

counter 124:9 

counter-seasonal

104:15 

counterparts 209:17 

218:6 288:8 

counterproductive

33:5 

countervailing 115:16 

counting 226:6 235:8 

252:18 

countries 32:11 42:19 

45:1,3,6 56:6,7 57:6 

63:6 66:14 101:22 

106:6 112:13,14 

113:6,21 114:1,20 

117:1 119:19,22 

120:1 125:12 132:5 

132:22 136:11,18,21 

137:7,12 138:7,20 

141:20 147:9 148:9 

151:1,1,8 

country 13:15 14:11,19 

15:4 25:14 30:4 57:5 

66:8 68:10 74:10 82:6 

104:4 131:19 138:8 

138:12 142:9,18 

149:3 173:11 199:3 

222:13 225:20 226:3 

233:3,4 244:14 

252:11 262:6 265:5 

285:16 294:17 296:18 

298:2 301:20 302:4 

325:11 373:22 

counts 226:19 

county 30:5,6,9,10 

208:21 209:2 229:1,5 

233:5 243:8,9 247:14 

335:11,13,14 

couple 7:4 21:16 72:1 

72:19 146:15 151:22 

183:19 191:8 280:6 

322:13 341:10 349:20 

350:4 352:22 360:14 

coupled 176:21 

course 56:20 104:14 

118:15 120:15 127:2 

131:7 135:6 180:1 

207:20 210:14,16 

218:5 263:17 274:13 

274:21 275:3 277:1 

287:1 306:13 333:5 

court 276:21 

cover 27:3 227:4 305:6 

382:9 

coverage 156:18 

157:16 227:19 

covered 227:10 248:11 

280:20 368:11 

covering 159:5 

covers 368:8 

CPS 364:2 365:2 

CPTPP 132:12 

crackers 368:9 

crafty 223:7 

cranking 147:19 

create 34:12 54:5,19 

206:11 219:16 229:22 

230:6 

created 16:8 22:18 

23:17 162:6 220:20 

394:7 

creates 26:3 220:2 

creating 20:3 22:17 

25:22 

credit 318:12 319:16 

381:11 

crew 249:1 

crisis 266:2,12,22 

criteria 45:11 

critical 17:7 97:9 

139:13 347:17 361:13 

critically 382:15 

criticism 354:22 

croissant 135:17 

crop 6:15 8:22 28:14 

44:10 68:6 79:15,19 

105:4 153:13,20 

154:8,22 155:13,16 

155:18 156:5,13,15 

156:16 157:2,2,7,11 

159:2,4 160:7,12,22 

163:8 177:21 185:1 

193:15,15 273:16 

300:15,16 357:4,4 

crops 52:12 79:20 

80:21 102:13 107:10 

124:6 153:18 155:3 

155:15,20 156:8,20 

156:21 157:7,17 

158:2,18,22 160:8 

162:3,15,16,19 

163:11 165:3 168:5 

169:8,9 191:13,15 

281:4,7 358:22 

cross 258:22 

cross-stocking 344:19 

crude 230:7 

crunched 268:19 

Crystal 1:9 

cultivating 273:8 

culture 102:8 229:3 

cumbersome 19:1 

Cumulatively 170:15 

cup 84:2,2,3 86:3,4 

curious 50:10 92:12 

326:15 334:10 

currency 148:11,21,22 

current 22:15 48:7 

54:21 60:10 61:14 

75:7 83:4 86:18,18 

92:19 101:16 111:6 

160:12 169:5 184:14 

187:21 195:19 201:20 

233:15,17 254:1 

257:2 282:17 288:6 

318:21 349:13 378:8 

currently 13:9 58:22 

157:12 167:2,22 

170:7 182:10 183:18 

188:21 218:21 237:6 

304:13 305:18 326:14 

326:17 339:9 342:19 

343:13 344:4,12 

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curve 318:21,22 

custom 180:15 

customer 66:17,17,20 

66:21 193:7,10 

257:22 258:14 306:3 

307:3 308:1,10 

customers 63:20 64:19 

65:18 76:17 77:2 

101:14,21 103:8,17 

105:10,21 106:4 

107:5,8 109:8 110:11 

111:3 123:9 130:7,9 

130:16 137:17,19 

138:1 191:1 

customize 15:18 

cut 377:13 

cut-off 45:10 

cutting 380:15 

CW 307:19 

cycle 63:19 217:12 

235:13 237:20 244:6 

244:12 247:7 

D

D.C 44:11 99:19 348:10 

daily 50:11 154:16 

181:1 

dairy 62:3 71:22 72:4,6 

75:9 104:7,8 105:9 

124:19 

damage 50:12,16 79:2 

damages 159:4,5 

Darrell 2:4 10:20 11:5 

46:7,15 92:9 164:21 

180:10 194:19 200:21 

245:6 255:17 257:5 

315:6 341:1 388:11 

database 167:15 

177:15 181:3,11,14 

date 36:1,3 232:16 

292:4 301:10 305:2 

dates 232:9,11 394:20 

dating 287:20 

datum 177:18 

Dave 226:16 

David 2:1,9,17 201:13 

202:20,21 225:3,18 

226:7 234:9 245:8 

Davis 9:14 

day 11:13 27:7 47:8 

65:6 83:3 94:10 

100:17 127:9,11 

129:14,14,15 133:5,5 

152:12 212:13 233:16 

286:3 304:19 322:21 

332:12 341:5 388:1,1 

388:14 390:19,20 

days 5:13 12:10 50:7 

67:19 209:4,4 235:12 

237:8 269:10,13 

280:10 281:6 292:4 

292:20 301:9 302:13 

302:14 303:12,13 

304:19,20 305:1 

306:9 347:16 352:9 

364:8,11,12,14 365:6 

DCs 363:5 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
406 

de-cert 308:17 

deadline 141:7 278:21 

278:22 279:2 

deadlines 278:20 281:3 

deal 29:7 30:7 34:6 

52:16 70:21 123:11 

127:3 133:17 134:1,9 

136:4 137:4,5 151:14 

156:2 163:18 189:17 

258:1 278:18 284:15 

293:22 299:11,18 

312:2 319:2 

dealing 36:15 37:3 

154:9 280:21 281:4 

346:13 

deals 258:13 269:3 

dear 46:20 84:12 

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debate 85:17 184:20 

224:21 252:11 

debrief 370:12 

debt 148:14 

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decertification 308:11 

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298:9 330:22 

decided 7:12 79:15 

125:20 316:20 345:8 

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decision 76:9 77:6 

144:6 156:6 268:18 

268:22 271:4 292:15 

303:12 304:22 344:9 

383:3 385:17 

decisions 155:18 

178:20 261:22 276:21 

282:8 305:17 

deck 203:12 207:10 

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decline 128:20 

declining 244:10 

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deductibility 318:16 

deep 294:6 

deeper 327:6,9 

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defended 288:2 

defense 144:22 145:14 

288:5 

defer 42:12 

deficiencies 284:9 

deficiency 303:14 

deficit 134:21 135:1,5 

146:21 147:2,6,10,16 

147:22 148:15,15,16 

148:19 149:6,7,10 

151:9 325:12 

deficits 146:16,20 

147:11 

define 145:7 155:18 

271:7 

defined 268:17 270:10 

384:4 

definitely 14:4 221:16 

376:1 

definition 233:13 234:2 

253:11 275:14 288:17 

290:6 

definitions 270:21 

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degree 124:3 159:6 

160:1 296:16 

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delegate 12:16,18 

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66:11,15,21,22 103:9 

104:6 107:3 263:9,15 

265:21 326:1 331:4 

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Democratic 106:18 

140:8 

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122:17 

demographic 266:2,11 

266:21,22 

Demographics 207:17 

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272:21 

demonstrate 17:21 

demonstrated 362:20 

demonstration 382:15 

denial 280:1 

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283:11 

denominator 219:21 

density 209:10 320:16 

364:18 

deny 277:8 279:22 

362:18 

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department 1:1 2:9,10 

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117:16 145:12 204:17 

221:15 227:14,15 

246:8,9 247:9 252:1,3 

252:3,7 256:11,16,20 

270:18 275:16 276:19 

284:21 287:20 288:1 

288:19,21 301:7 

304:6 313:10 

Departments 167:5 

223:12 298:5,7,15 

dependent 249:15 

285:7 296:12 

depending 18:19 25:17 

175:10 241:9 324:6 

364:18 365:21 

depends 176:12 270:2 

273:20 280:16 293:10 

333:5 

depress 290:8 

deputies 97:16 

Deputy 2:4 6:6 256:9 

derived 23:19 290:7 

DERRIN 1:20 

describe 14:15 190:4 

described 158:7 173:8 

180:13 181:2 

describing 265:7 

deserves 28:12 

design 168:5 

Designated 2:4 

designed 80:13 205:4 

256:21 290:7 

desirable 159:20 

desire 120:11 326:13 

desired 96:5 

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desktop 26:9 

desktops 19:8 

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126:6,7 131:18,22 

destruct 159:2 

detail 14:16 59:14 

340:19 355:16 

detailed 351:16 359:5 

details 6:19 176:6 

detain 371:19 

detectable 182:15 

detected 183:2,6 

352:17 

detection 161:8 176:22 

177:5 178:4 191:16 

191:16 

determination 146:9 

288:11 

determine 144:5,20 

145:16 156:10 163:6 

171:8 205:5,10 

231:16 249:10 372:19 

392:20 

determined 300:19 

340:7 

determining 344:9 

359:4 382:12 

detrimentally 347:7 

develop 36:21 98:3,12 

109:7 167:16 212:10 

342:14 347:10 353:14 

developed 8:21 145:12 

343:12 353:1 

developers 161:15 

developing 36:20 88:20 

97:20 125:12 206:13 

354:12 

development 127:15 

312:4 315:12 324:12 

343:6 344:6 

Deviating 383:14 

devise 171:1 198:13 

diabetes 39:13 

dialogue 344:11 369:6 

372:13 

dicamba 158:2 159:1 

159:14 160:6,20 

161:21 162:2,7 

165:10 180:16,17 

181:7,10,15,21 182:8 

182:13,16,17 183:2,5 

184:15,20 185:15 

187:7,17 188:13 

189:2 190:10,14,19 

191:8 192:2 193:5 

197:11,19,22 

die- 352:6 

die-off 352:11 359:1 

364:2,3,17 

dietary 166:10 174:9 

177:9 178:16 195:8 

195:12 

difference 96:1 103:3 

126:4 235:16,22 

243:12 320:13 330:3 

364:12 

differences 202:1 

364:16 

different 7:3 18:5,5 

38:8 57:5 59:22 60:1 

62:9 75:16 77:4 112:1 

127:2 129:4 163:4 

172:3 210:4 212:5 

213:16 214:22 223:21 

226:5 232:19 237:19 

243:9 245:20 247:14 

249:11,18 251:3 

254:8,8 259:19 

269:20 272:7 286:17 

288:10 295:21 296:2 

297:17,18 298:12,17 

300:2,9,13,14 311:18 

330:17 337:10 341:14 

350:11 352:16 353:9 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
407 

354:16,17 355:13 

356:7 357:1,21 

358:21,22 359:2,10 

363:5 364:16,17 

365:20 373:21 378:3 

378:14 382:18 384:1 

387:5 390:17 391:15 

differential 96:1 327:16 

differentials 326:22 

differentiate 88:3 

differentiation 138:6 

differently 75:20 342:6 

difficult 42:20 93:14 

107:21 136:4 187:6 

218:17 291:12 355:4 

381:14 

digit 112:21 

diligently 153:1 

dilute 156:10 

diminished 32:9 

direct 3:14 76:13 79:11 

135:20 167:7 226:3 

315:7 

directed 169:12 

direction 48:18,21 

56:19 

directly 67:4 250:16 

272:2 280:21 298:14 

301:6 

director 69:13 164:6,22 

165:15 

directs 166:3 

dirty 198:21 

disabled 321:9 

disadvantage 42:1 

289:18 335:21 

disagree 34:11 72:20 

85:10 239:9 243:4 

281:12 328:9 

disagreed 60:21 

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disappearing 147:16 

discipline 140:5 

disclose 310:15 

disclosed 218:4 

discreet 130:21 143:16 

discretion 146:10 

344:13 345:16 

discretionary 89:2 

discrimination 133:16 

discuss 5:9 34:7 41:18 

183:10 257:4,13 

394:17 

discussed 74:8 82:14 

discussing 65:11 200:6 

206:21 

discussion 4:9,17 55:6 

59:11 67:2 91:5 98:20 

101:1 206:19 257:9 

274:2 347:3 355:15 

360:9 

discussions 7:10 22:7 

62:7 84:16 92:18 

198:19 199:4 215:21 

336:8 

disease 56:3 

disposal 371:19 

dispute 141:15 142:14 

142:19 349:3 

disputes 180:22 

disrupt 26:11 

disrupting 16:6 20:7 

disruption 82:2 347:5,6 

dissemination 207:19 

dissertation 17:5 

distance 331:13 

distances 158:9 

distinctions 289:21 

distinguish 88:5 245:10 

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distribution 112:12 

174:1 

distributor 21:11,14 

distributors 96:21 

344:19 

District 73:22 

districts 73:17 

dive 92:17 294:6 

divide 230:11 231:4,8 

231:10,20 

divided 220:8 231:12 

268:2 

dividing 231:2,19 

division 164:7,9 165:1 

165:5 

doctoral 17:5 

doctoring 391:17 

document 279:12,19,21 

305:6 

documentation 96:10 

279:15 346:5 

documents 279:13 

302:18,21 303:19 

doing 6:20 7:5 14:18 

20:21 27:4 40:3,6 

55:9,14 70:1 93:6 

95:9 101:14 109:17 

109:18 117:2 122:13 

168:10,11 197:21 

227:13 230:2 231:22 

236:19 238:7,21 

246:16,20 247:9,10 

247:12 249:13,18 

250:4 251:16 255:20 

255:20 265:2 282:10 

283:5 285:2,8 296:6 

296:13 297:1 299:1 

302:16 304:2 307:19 

325:16 336:10 350:16 

361:3 363:10 381:3 

381:10 385:18 

DOL 205:12 209:18 

210:10 218:13 284:8 

Dole 385:10 386:6 

Dole's 385:22 

dollar 106:10,12,19 

112:21 149:8 385:7 

385:17 

dollars 19:2 31:10,11 

41:21 42:3,10 72:21 

111:7 112:16 119:12 

308:22 347:4 

domestic 31:1 36:12 

37:8,12,19 60:10,10 

60:11 63:11 64:8 65:5 

65:19 66:3 68:1,17,19 

69:9,10 70:12 75:16 

77:6,7 78:2 79:6 

88:21 94:15 96:12,16 

97:1 105:16 146:2 

171:19 172:5 180:6 

265:5 266:1,20 

297:17 301:16,18 

320:11 367:3,14 

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94:17 96:9 172:9 

367:17 383:8 

dominate 390:20 

dominates 287:3 

Donn 1:22 55:4 

door 123:22 

doors 94:18 221:20 

227:12 

dots 317:21 

double 22:11 112:21 

289:16 

double-digit 261:10 

download 184:4 

dozen 7:16 198:21 

dozens 263:11 

Dr 342:16 363:9 370:5 

draft 163:15 239:11 

drafted 342:6 

drafting 238:16 341:2 

dramatically 222:1 

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draws 168:5 

dried 94:17 

dries 53:12 

drift 184:22 

drilling 250:6 

drip 357:1 

drive 77:4 

driven 62:1 278:13 

300:19 

drivers 252:2 

drives 105:16,17 149:7 

242:20 

driving 243:6 265:21 

331:13 341:11 

drop 53:21 

drops 292:5,6,21 

Drug 166:12 

dry 37:2 

due 82:2 153:18 160:5 

160:7 352:11 

dumping 35:1 40:9 70:4 

70:17 82:1 

dusters 273:16 

duties 115:3,16,20 

142:20 

dying 11:21 

dynamic 56:12 129:17 

158:5 

dynamics 141:5 

E

E 1:13 351:18 352:16 

354:1,10 356:2 

366:11 

e- 307:8 

earlier 11:21 123:5 

182:6 253:9 290:19 

302:16 313:16 325:17 

early 46:22 50:3 92:5 

99:5 264:6 297:16 

earn 210:1 

easier 375:3 386:22 

387:2 391:11 

easily 163:6 

eastern 37:1 

easy 67:7 77:14 81:18 

83:20 

eat 30:16 31:16 32:1 

33:8,16 38:20 199:18 

201:2 277:19,22 

312:6 377:4 378:3,12 

387:3 

eaten 378:5,7 

eating 29:12 30:18 

41:14 67:14 107:1 

127:18 

echo 46:16 

economic 29:21 31:2 

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124:1 125:19 127:7 

127:14 130:3,5 

137:12,15 207:17 

224:5 228:2 246:12 

251:20 342:22 

economies 137:15 

138:3 272:9 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
408 

economist 134:16 

economy 29:15 30:2 

94:6 102:17 107:16 

109:10 116:4 118:9 

122:5,13 130:4,5 

148:7,8 149:8 227:1,5 

Ed 2:16 201:17 

Edgefield 243:9 

edible 14:1 

educate 190:17 363:12 

educated 189:1 

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effect 79:22 81:14 

112:3 115:17 116:9 

116:15 117:13 118:8 

239:20 288:18 295:5 

296:1 

effective 102:20 107:10 

359:17 

effectively 270:10 

effects 116:13,17,19 

117:9 

efficiency 118:12 

efficient 15:15 16:19 

18:13 19:11 20:3 

77:13 307:22 309:16 

efficiently 16:5 19:7,11 

26:8 80:15 102:2 

effort 76:2 83:7 145:8 

212:6 221:17 222:9 

342:12 

efforts 47:19,19 52:9 

167:7 207:21 

egg 140:20 322:3 

eggs 388:3 

eight 202:10 

EIN 247:19,19 

either 5:15 19:14 21:13 

199:10 204:5 218:15 

279:17 318:3 361:9 

elaborate 169:19 

elasticity 87:15 

elect 96:8 

election 122:16 

elections 51:6 

electronic 281:16,18,20 

281:21 302:20 303:2 

305:17 306:2 307:1,2 

307:6 

electronically 173:15 

303:3,10 

element 136:1 

elevator 200:12 

elevators 228:8 

eligibility 337:11 

eligible 320:18 

eliminate 304:6,16 

eliminated 308:14 

ELLOR 1:14 274:9,17 

274:21 275:3,7,11 

else's 190:21 

ELY 1:14 

email 27:21 302:22 

303:8 306:13 341:3 

emailed 11:15 306:2 

emailing 391:8 

emails 368:21 390:14 

embrace 125:20 

emerging 155:15 

Emily 363:9 

emotional 93:19 

emphasis 233:5 

emphasizes 169:11 

employ 209:3 242:17 

272:1 276:12 292:16 

employed 224:14,16 

234:22 235:3,4,5 

249:4 260:5 295:13 

employee 231:13,15,17 

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253:14 267:11 

employees 118:6 

173:16 213:18 214:5 

222:18,19 234:20,21 

245:16 252:20 253:17 

253:18 343:14 

employer 227:9 246:12 

247:4,6 249:12,15 

251:8 258:1,14 266:8 

268:8,11 276:11 

282:17 300:6 340:11 

employer's 245:11 

258:4 

employer/customer

308:15 

employers 8:7 205:4,18 

206:12,14 226:3 

233:9 246:3,11 

263:22 272:4 291:7 

291:18 

employing 262:11 

employment 30:6 

201:15,20 204:18 

209:16 226:12,17 

227:3,6,18 229:11,16 

230:10,10 231:11,12 

252:17 263:4 283:8 

289:6 301:6 

employment-based

256:13 

employs 226:4 

empty 182:20 

encourage 32:3 33:13 

69:4 109:6 146:2 

184:8 199:17 272:8 

342:13 343:16 344:6 

344:17 346:4,9,18 

347:9 368:15 

encouraged 60:6 

encouragement 196:5 

encouraging 32:6 

137:14 

encroachment 40:1,2 

endgame 54:20 

ends 19:2 395:3 

energies 33:19 

enforce 35:6 95:2 

141:22 143:10 166:14 

216:6 379:13 

enforceable 142:17 

143:13 

enforcement 13:7 18:6 

19:9 78:5,5 95:18 

179:17,18 198:7 

311:13,15 344:12 

379:15 

engage 44:22 198:1 

200:5 222:15 

engaged 7:17 

engagement 141:8 

194:19 

English 127:22 343:7 

enhance 76:2 78:5 

194:15 

enhanced 95:14 

enjoy 38:21 

ensure 157:15 160:19 

177:17 205:16 367:5 

382:12 

ensuring 97:9 98:6 

enter 22:14 58:7 303:5 

371:9 

entered 22:20 

entering 19:15 303:9 

325:8 

enterprise 227:21 

246:4 250:1 

enters 246:12 

entertain 213:13 254:10 

entire 16:3 25:5 84:5 

224:3 228:11 231:8 

232:14 347:6 385:8 

392:9 

entities 39:11 318:18 

344:9 

entity 250:4 298:9 

entries 259:8 

entry 22:11 

enumerate 145:3 

environment 47:11 

48:7 54:2,21 84:20 

113:8 131:9 136:3 

137:9 138:10 141:15 

141:17,21 143:13 

environmental 207:17 

359:18 

EPA 159:13 160:14,19 

161:17,22 162:6 

163:2,7 164:2 166:9 

169:4,18 179:4 

194:14 195:3 196:8,9 

197:5,19,21 199:8 

EPA's 178:13,19 

epi 378:20 

epidemiological 377:20 

equally 310:6 330:8 

equates 173:9 

equation 15:1,2 150:17 

equipment 84:7 248:5 

249:8,17 251:9 255:5 

273:17,18 

equipping 86:7,14 

equitably 264:11 

equivalency 239:6 

equivalent 345:12 

364:7 

equivalents 238:13 

ERICKSON 1:15 63:7 

67:6 143:20 198:18 

199:20 203:5,8,10,14 

265:7,10,14 

ERP 19:17 21:1,8,21 

22:20 373:10 

error 237:8 

error-prone 22:4,12 

errors 22:17 

ERS 29:4 

especially 31:21 37:1 

45:7 47:11 69:3 88:2 

192:11 215:20 243:22 

350:3 351:8 359:13 

361:15 374:20 377:15 

essentially 13:12 19:7 

establish 7:13 79:12 

96:19 159:16 163:8 

179:11 343:19 

established 7:6 179:4 

196:6 352:1 383:11 

establishes 178:3 

establishing 369:21,22 

383:6,10 

establishments 228:21 

232:13 233:20 234:8 

245:21 252:16 253:12 

estimate 219:17 253:3 

estimates 209:16 

221:12 264:22 

estimating 259:14 

estimation 144:13 

et 96:18 

EU 45:9 111:19 115:2 

121:4 134:14 136:7 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
409 

Europe 98:4 101:11 

115:9 117:10 132:16 

134:21 135:5,10,13 

136:10 151:12 

European 45:12 134:20 

Europeans 134:17 

148:20 

evaluate 160:15 359:13 

evaluates 177:22 

evaluating 117:18 

evaluation 190:10 

351:1 

event 370:1 

eventually 163:15 

251:17 

everybody 4:4,5 28:2 

32:10 34:20 48:15 

72:2 77:22 78:21 86:6 

92:1 108:4,5 152:8,22 

153:19 156:1 159:5 

193:6 200:9 207:5 

232:18 240:16 292:11 

292:12 310:6 315:4 

331:21 383:7 387:3 

390:16,22 391:14 

everybody's 4:7 153:6 

316:5 

everyday 154:19 

evidence 190:1,18 

334:13 367:16 

evidentiary 19:10 

ex 257:7 

exact 36:3 350:6 

exactly 24:8 94:9 170:1 

219:13 248:17 271:14 

278:14 294:19 308:7 

308:16 310:10 311:14 

334:5 370:17 385:12 

examine 6:14 

example 21:9 28:19 

37:20 45:5 52:22 80:5 

115:18 139:6 150:2 

154:2 161:21 162:16 

172:7,20 175:1 294:9 

296:19 369:9 

examples 67:17 

exceeded 260:22 

excellent 303:1 

exception 361:22 

exceptional 181:4 

exceptions 96:2 253:19 

368:11 

excess 35:5 

exchange 194:18 

exchanged 59:15 61:5 

excited 10:10 64:1 

exclude 162:19 

excluded 155:6 293:20 

exclusion 253:14 

exclusions 294:7 

excuse 46:7 58:13 

59:20 60:11 221:4 

execute 372:14 

executive 13:7 271:4 

exemption 96:3 294:10 

exemptions 296:9,13 

exercise 203:3 

exist 144:14 373:4,8 

existing 156:8 

exists 163:19 257:3 

exits 259:9 

expand 72:16 103:9 

333:2 389:19 

expanded 217:12 

326:19 

expanding 38:5,5 54:14 

expect 83:17 110:20 

116:7 327:21 350:17 

expectation 119:22 

367:2 

expected 378:4,6 

expecting 375:7 

expedite 305:14 

expedited 206:15 

expenditures 208:16 

expensive 64:4 116:18 

297:5 388:5,6 

experience 24:9,10 

308:19 310:7 317:1 

318:15 336:7 355:12 

experiencing 80:7 

expert 8:18 87:5 142:4 

143:4 347:11 369:11 

expertise 155:2 

experts 7:17 143:17 

225:2 312:2 370:1 

expires 160:13,18 

395:13 

explain 185:10 207:11 

277:10 326:21 342:18 

355:4 357:11 

explanation 181:16 

259:21 

explore 378:11 

explored 8:5 

exponential 325:18 

export 34:14,16 45:14 

64:10 88:16 97:10,13 

103:19 104:8 117:5 

119:19 125:16 128:16 

137:3 

exported 29:15 105:6,7 

exporter 121:5 126:9 

126:10,11,12,12 

147:17 

exporters 45:8 103:16 

125:22 

exporting 134:20 

exports 29:22 31:1,3 

32:13 51:8 104:2 

105:3 109:13 111:7 

111:10,11 113:18 

114:9 119:10,14 

124:18 125:1 128:11 

128:20,22 137:3 

138:12 149:13 

exposed 121:5 158:2 

exposure 174:4,8 

exposures 179:1 

extends 344:2,3 

extension 154:14,21 

extensive 124:4 159:8 

externally 333:13 

extra 106:12,19 128:2,6 

185:17,22 280:10 

extract 20:20 

extraction 175:20,21 

176:2,7 

extreme 108:3,5,13 

extremely 162:14 

225:21 229:9 

eye 40:16 117:15 

F

fabulous 45:17 

face 132:17 133:20 

138:21 139:11 

faced 114:8 

faces 16:14 28:14 

139:10 

facilitate 258:9 

facilitating 17:7 18:1 

135:21 

facilities 13:21 37:13 

37:18 171:15 316:13 

326:20 344:20,20 

368:1,4 

facility 171:13,14 270:3 

270:3 384:17 

facing 55:7 57:11 

100:17 113:17 114:18 

131:18 342:19 

fact 6:9 41:11 42:17 

57:21 105:19 111:19 

132:10 146:9 150:10 

198:6,19 199:21 

207:9 211:11 216:18 

240:10 322:13 325:3 

329:2 364:17 

factor 90:8 352:9 

factors 104:3 119:4 

148:5 149:16,19 

171:12 174:9 356:18 

357:6 

factory 269:19 317:16 

facts 369:19 

factual 289:5 

factually 291:20 

failed 57:18 

failure 129:20 150:6 

faint 257:17 

fair 34:4 42:7 52:5 65:3 

70:5 91:13 150:4 

270:22 

Fairfax 1:9 

fairly 102:2 266:2 

fall 116:22 125:1 133:12 

213:1 218:9,10 

285:18 

fallen 123:6 

falling 380:12 

falls 164:17 

familiar 9:10 28:5 61:10 

185:7 216:18 244:17 

357:10 

familiarized 216:18 

families 31:21 118:18 

324:17 

family 316:11 321:15 

family-owned 321:15 

380:8 

fan 67:9 

fancy 104:4,6 136:7 

far 35:15 40:3 68:4 70:7 

207:12 222:9 223:1 

260:19 283:10 328:14 

335:8 

farmer 40:17 41:2 70:10 

193:11 226:4 245:12 

321:15 327:17 330:4 

330:15 331:8 332:17 

335:12 338:4 347:8 

farmers 39:20 79:10 

98:5 101:15,18 

102:11,19 103:4 

104:19 109:11,18 

134:17 157:16 179:7 

208:18 263:7 318:17 

325:15,19 327:9 

328:15 331:14,20 

332:4 335:21 336:3 

337:20 

farmhands 236:22 

farming 44:15 273:15 

339:10 

farms 72:6 94:16 103:7 

209:3,8 233:19 

235:12 237:19 238:2 

238:4,5 239:13,14 

262:3 263:12 289:13 

321:6,8 335:7 368:6 

FAS 44:21 90:15 100:5 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
410 

fashion 212:16 

fast 284:18 355:22 

faster 10:6 269:11,12 

fastest 260:18 294:17 

father 39:5 

favor 130:9 218:14 

favorable 336:9 

FDA 7:16 159:13 

169:18 179:16 190:9 

197:7 198:2,4 341:7 

342:9,13 346:4,9,12 

346:18 347:9 350:21 

353:13 354:4,7,10 

355:10 360:11,16 

368:1,5,6,11,17 370:7 

371:7,11,14,18 

372:19 374:2 375:1 

375:12,20 376:14 

377:16 379:12 380:9 

February 229:15 

264:13 

federal 2:4 31:15 41:20 

42:3,10 48:10 72:21 

79:19 90:12 156:16 

157:2 159:4 232:20 

233:13 234:1 253:20 

254:18,22 256:15 

287:2 319:12 339:17 

340:3 

federally 69:5 318:19 

feed 26:7 278:18 

feedback 9:22 367:20 

372:3 

feeding 85:4 

feel 17:3 19:20 41:4 

43:11 71:9 75:5,6,6 

338:20 344:14 354:22 

361:10 367:13 369:4 

374:6 377:7 380:2,2 

387:11 

feeling 354:22 

feels 141:3 

felt 128:21 129:11 

155:8 341:1 365:8 

females 28:8 

fence 237:2 

field 23:2,2 42:13,16 

173:19 210:19,19 

219:10 223:9 281:8 

289:1 367:4 383:6 

fielding 368:20 

fields 8:8 23:6,7 173:15 

248:15 266:10 267:4 

269:22 273:18 376:10 

fifth 217:4 

fight 51:1 53:22 275:21 

fighters 120:3 

fighting 33:20 39:22 

40:1,1,2 52:21 56:9 

fights 34:13 56:14 

figure 65:18 67:2 73:15 

216:2,13 267:9 301:1 

373:22 374:9,10 

381:14 

figured 44:4 164:18 

192:2 332:2 

figuring 116:5 332:10 

file 77:14,14 257:21 

268:18 272:1,2,3,10 

284:4 302:11,16 

304:18 307:8 319:13 

344:16 373:9 

filed 302:10 

files 184:4 391:16 

filing 259:14 265:19 

279:9,11 281:16,18 

281:20,21 301:4,5 

302:20 303:2,3 356:1 

fill 53:6 281:11 332:14 

filled 207:6 220:7 262:4 

filling 249:12 257:7 

final 35:18 36:6 77:5 

91:11 394:20 

finalize 163:15 

finalized 355:6 357:9 

finalizing 183:18 

304:10 

finally 28:10 

finance 148:18 322:1 

financed 322:20 323:3 

financial 96:19 287:9 

287:10 333:17 337:11 

343:4 380:3 

financing 318:6 319:8 

333:15,19 336:9,10 

336:22 

find 10:14,15 11:5 

13:11 52:17 60:8 

64:17,21 67:7,20 

75:15 76:16 87:18 

89:4,10,22 90:1 

101:14 105:20 140:10 

142:22 143:9 147:4 

157:12 185:14 190:3 

190:7 198:13 214:17 

218:2 237:3 240:12 

246:19 260:5 290:13 

326:9 328:4 333:12 

336:22 350:6 352:20 

374:17 380:22 

finding 38:14 95:5 

105:12 137:19 184:20 

213:2 236:21 331:15 

finds 254:20 310:19 

fine 85:10,11 99:6 

101:21 310:21 312:16 

fine-tune 49:14 

finger 64:19 140:19 

finger-pointing 47:10 

53:16 

finish 92:4 180:16 

215:11 250:15 295:3 

finished 192:12 

firms 69:22 

first 35:13 36:8 41:9 

43:15 64:8 67:9 92:10 

93:16 94:4,20 96:5 

101:6 102:7 120:20 

146:11 152:21 153:5 

153:16 165:11,13 

170:21 204:12 207:14 

212:2,22 217:11,13 

222:15 223:15 228:18 

229:14 243:17 247:5 

257:20 287:21 301:1 

306:22 349:2 365:16 

374:15 377:11 386:19 

fiscal 261:2 

fish 321:6 

fit 278:7,15 363:5 

fitness 217:11 

fits 297:11 

five 67:15 78:21 79:6 

111:8,16 122:9 137:3 

137:5 172:18 208:12 

216:19 217:7,9 

222:12 237:19 262:13 

264:9 328:13,13 

329:8 335:22 347:18 

359:10,12 

five-day 237:20 

five-year 294:3 

fix 80:11 131:5 150:3 

151:17,19 237:2 

fixed 251:8 282:17 

319:6 

fixing 293:13 

Flavorful 38:21 

flavors 38:20 

flexibilities 272:13 

flexibility 282:7 

flip 356:14 

flipped 108:12 110:14 

floor 289:4,18 309:7 

339:14 

floors 289:5 

Florida 36:19 74:11 

168:3 236:17 241:6 

248:21 253:17 255:5 

280:13 282:20 285:16 

293:12 298:13 323:5 

Florida's 325:11 

flow 4:11 256:6 

flux 352:5 

flying 354:5 

FN 21:17 22:3 

focus 29:11 32:3 33:15 

33:18 100:20 101:6 

136:15 150:10 228:13 

237:11 330:17 362:4 

368:16 

focused 18:12 63:3,4 

69:8 102:9 103:12 

137:19 227:1,22 

228:13 229:3 342:8 

344:18 347:13 348:13 

363:9 368:14 

focuses 209:18 

focusing 55:15,20 84:5 

84:11 196:2 

FOIA-able 375:20 

folks 29:18 51:7,14 

53:11 59:1 93:14 

287:11 317:14 333:14 

345:1 

follow 186:1 316:3 

350:18 357:18 

follow- 222:11 

follow-up 245:19 293:3 

314:13 

followed 39:7 323:4 

following 95:22 127:1 

144:7 176:7 352:14 

360:19 382:6 

food 3:17 7:6,14 12:1 

30:15 33:17 89:2 

95:14 96:8,20,21 97:1 

97:20 106:15,20 

126:9,13 144:10 

158:18 165:21 166:2 

166:12,17 170:13,16 

172:14 175:17 179:11 

187:15 195:9 199:16 

204:4 277:20 341:5 

342:2 343:22 344:2 

347:11 348:6,9,12,19 

360:15 369:10 376:3 

379:5 381:1,10,20 

382:15,18 386:19 

387:1,18 392:15 

foods 29:12 30:17 33:6 

38:19 166:1,7 171:18 

171:20 172:14 173:9 

195:16 344:3,7 

Foos 2:7 164:4,8,11,15 

164:21,22 165:19 

168:19,22 180:3,6 

185:6 186:4,8,13 

187:9,14,20 188:4,10 

188:14,20 189:7,11 

189:22 191:3,11,14 

191:19 192:1,14,17 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
411 

193:9,12,18 194:3,16 

194:22 196:10 197:2 

197:4,7,14 198:5 

199:4 200:1,9 

footage 171:14 339:14 

339:14 

foraging 173:14 

force 245:17 265:1,5 

266:1,20 273:12 

297:17 375:22 

forces 137:14 148:6 

forcing 129:21 

forecasting 80:20 

foreign 2:8 7:20 8:7,18 

36:12 37:19 41:21 

42:4 90:15 95:7 96:8 

96:11,22 97:12 98:1 

100:5 148:11,20,22 

166:19 180:20 204:5 

256:10 258:1,18 

269:4 290:8,10 

295:16 296:15 341:22 

344:8,17 346:6,10 

367:2 370:20 379:9 

383:8 

foremost 207:14 

222:15 

forewarn 207:8 

forget 242:21 

forgot 394:6 

form 52:12,13 93:22 

161:1 196:5 257:7 

288:5 291:19 307:14 

formal 47:4 

formality 91:3 

Formally 330:15 

format 92:13 

formed 110:3 

former 13:6 

forming 242:8 

forms 84:2 85:2,5 271:8 

307:14 

forth 7:10 27:2 34:19 

51:13 56:12 

fortunate 285:20 

fortunately 225:16 

forward 7:22 10:18 

27:21 34:20 75:2 77:5 

77:12,17 110:10 

119:20 138:9 205:2 

210:21 251:5 261:17 

269:4 308:10 348:20 

355:22 360:10 392:17 

foster 110:9 142:9 

fostering 137:15 

found 18:18 19:4 22:11 

105:10,10 128:19 

135:15 179:15 198:8 

198:9 220:13 354:6 

356:7 369:15 372:1 

376:20 

Foundation 124:14 

founded 108:20 

four 7:6,12 37:1 44:17 

84:22 111:15 141:13 

143:17 153:11 161:14 

165:15 210:3,4 

212:18,19 228:16 

284:6 311:21 319:22 

328:5 339:12,15,21 

340:10 351:21 364:8 

364:12 365:6 

four-legged 257:19 

fourth 119:16 

FQPA 166:3,9 169:12 

fracking 147:13,20 

fraction 175:22 

fragile 259:3 

frame 35:21 58:2,2 

83:18 172:2 

framework 17:18 20:6 

Frank 370:7 

frankly 64:4 181:11 

263:11 

Fred 28:5 

free 17:6 43:11 110:5 

120:6 121:15 133:9 

134:10 136:19 137:9 

201:2 329:4 338:20 

freely 109:5 

French 104:9 

frequency 15:14 

frequently 104:3 

fresh 2:6,13,14 8:2 

12:14 28:3,15,20 

31:16,18 32:5 37:6 

40:22 46:3,4,14,19 

72:16 84:14,18 86:15 

94:16 171:20 225:22 

269:17,18 342:17 

347:10 348:2,6,7,13 

349:5 351:10,11 

366:3 367:11 369:10 

371:9,16 372:22 

Fresh's 358:3 

fringe 273:9 

front 33:17 259:10 

282:6 284:18 

fronts 13:21 

frost 349:6 

frozen 94:16 170:11 

182:22 

fructose 142:21 

fruit 1:3 45:8 47:1 52:11 

59:19,20 60:2 62:2 

66:7 68:9 84:14,18 

86:15 94:4,7 96:4,18 

97:4,18 98:8,14,15 

154:22 156:11,18 

157:15 158:3,5,10,13 

162:16,20 170:2 

171:4 183:6 200:13 

200:17 211:3 225:22 

236:12 344:2 346:22 

347:10 369:10 

fruits 25:3 32:5 48:9 

72:16 84:9 94:15 

96:11 98:9 104:16 

105:8 124:8 169:14 

199:18 346:7 

frustrating 134:15 

135:5 362:17 

frustrations 285:4 

FSIS 368:11 

FSMA 7:19 239:7 344:6 

344:17 345:12 

FSVP 370:22,22 371:10 

371:10,21 

fulfil 386:8 

full 3:4,6,9,16 5:7 6:14 

10:10 134:10 217:12 

243:2 307:10 343:10 

355:21 389:2,7 

392:17,19 

full- 237:1 

full-time 238:12 239:6 

292:12 

fully 6:19 139:15 215:4 

225:14 292:16 344:20 

fun 207:5 348:18 

function 209:13 

fundamental 55:22 

109:20 372:21 

funded 69:5 154:13 

155:6 221:10 346:1 

funding 31:1,5 52:10 

68:16 76:9 86:11 

97:14 153:18 154:19 

155:14,19 156:4,13 

208:5 221:9,12,15,17 

284:16 285:5,9,10 

319:18 326:22 327:14 

330:20 343:2 345:9 

funds 79:19 156:9,11 

221:13 318:20 320:10 

325:22 326:7 327:2 

330:18 331:11 359:8 

funny 242:1 244:11 

273:6 

furrow 357:2 

further 121:2 137:22 

305:14 376:6 

future 147:18 184:13 

193:14 331:2 

G

gain 29:21 

gained 323:15 

gains 110:12 

Gala 299:1,5 300:1 

Galas 300:7 

gallery 93:15 

game 89:1 

gander 32:15 

gap 144:12 345:5,10,18 

358:8 361:14 362:5,9 

garbanzo 170:8 

gas 147:5,6,11,14,16,18 

148:1,2 176:20 

gate 174:5 

GATT 109:3 110:3 

150:15 

GC 176:20 

GDP 127:16 

geared 222:21 

general 144:19 302:10 

389:20 

generally 103:14 110:4 

115:13 129:22 172:15 

195:16 240:17 302:15 

320:2,4,18,21 321:11 

321:19 

generate 321:16 

generated 29:19 176:3 

generator 325:14 

generic 163:6 351:18 

354:1 366:11 373:16 

373:18 

genetics 161:16 

gentleman 200:12 

gently 175:8 

geography 376:16 

geometric 352:1,20 

Georgia 63:16 236:18 

361:16 

getting 41:21 42:10 

46:8 79:19 94:9 

124:11 127:5 131:7 

154:17 155:20 228:5 

247:3 250:7 253:11 

265:20 292:7 301:20 

314:5 319:8 337:8 

357:5 361:13 362:4 

GFSI 345:11,19,22 

361:19 362:10,16 

giant 120:16 121:21 

girls 267:2 

give 12:16,21 44:4 46:6 

50:16 58:3 59:8 70:9 

72:21 82:21 91:22 

98:5 100:18 106:11 

106:18 152:8 165:8 

181:22 184:11 186:22 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
412 

190:8 208:9 213:3 

222:14 239:3 269:5 

282:6 291:13 299:14 

303:8,15 304:21 

305:5,12 307:5 

308:11 314:14 316:21 

319:19 322:12 327:14 

345:14 366:16 389:14 

391:13 

given 91:2,9 120:1 

184:1 190:11 237:17 

237:20 291:20 305:7 

314:10 318:20,22 

319:16 322:13 361:2 

gives 192:7 231:13 

296:13 384:3 

giving 13:5 43:10 94:22 

142:6 254:15 285:8 

296:21 337:18 

glad 45:17 165:15 

192:5 

glasses 219:6 

Gleason 1:15 82:11 

86:17 87:1 196:19 

197:3,6,8 341:10 

394:18 395:1,7 

glitch 165:17 

global 31:14 40:2 

globally 101:17 110:21 

GMO 154:5 

GNA 386:6 

goal 5:10 157:15 

211:18 212:14 216:12 

307:4 322:2 388:16 

goat 277:5 

God 69:19 297:15 

goods 147:2,3 

Google 186:17 

goose 32:14 

GORDON 1:16 

gosh 147:21 148:11,18 

149:1 

gotten 53:12 116:18 

123:2 217:13 283:15 

334:22 

government 14:21,22 

15:2,3 19:6,18 21:6 

22:13,16 42:11 47:16 

48:4 113:9 187:7 

224:8 232:20 253:21 

281:2,4 285:21 286:3 

313:5 318:18 319:13 

362:13 

government's 21:5 

281:13 

governments 13:15 

grab 307:11 313:5 

grade 175:17 

grader 251:9 

graders 211:5 212:3 

216:22 

grain 51:15,15 53:11 

129:1 239:13 289:22 

grains 62:3 

grant 68:7,15 86:14 

320:5,7 

grants 3:14 47:22 84:6 

84:7 86:7 88:17 156:9 

315:7 317:3 319:3 

granular 23:18 24:12 

208:20 209:7 211:20 

217:5 218:1 220:6 

Grapes 81:21 

greater 87:21 104:1 

116:6 233:4 

green 115:9 167:22 

202:9 264:15 276:8 

276:11 

greenhouse 36:21 38:8 

38:9 

greenhouses 38:10,12 

38:13 

greens 170:9 350:3,10 

356:3,9 357:19 

359:22 364:14 365:9 

365:11,20 366:3 

382:2,4 

GREG 1:20 

grew 236:22 317:4 

Griep 363:9 

grocery 67:17 368:10 

373:14,19 

gross 63:11 102:10 

212:18 217:7,9 

218:20 219:15,16 

220:8 231:1 

ground 24:14 255:7 

group 5:4 8:9 27:21 

60:5 62:19 64:6 72:14 

80:22 81:12 90:9,12 

92:19 93:17 97:17 

98:17 152:5 153:3 

157:21 192:7 196:7,8 

201:19 202:17 203:20 

206:20 213:17 214:16 

218:18 220:15 223:15 

251:17 266:16 274:19 

299:20 321:21 322:2 

331:6 338:22 343:20 

360:15 368:15 375:13 

385:8 389:4,10 390:4 

390:7,9,11 392:12,16 

group's 199:9 225:19 

groups 4:12 5:2 7:6 

17:12 28:1 34:16 51:9 

51:10 55:1 60:2 62:1 

62:2,5 89:9 91:14 

92:21 93:5 103:21 

141:14 153:5 163:8 

201:22 293:19 296:11 

369:22 388:15,18 

389:13,22 391:15 

grow 11:18 30:17 33:7 

40:16 42:11 63:12 

64:4 101:19 112:7 

113:3 124:18 132:17 

138:17 281:5 386:9 

grower 36:20 38:15 

98:11 258:11 259:3 

260:3 261:14 269:4 

278:20 279:18 282:7 

292:7 298:21 343:7 

343:20 363:4 374:1 

379:22 383:9 

grower's 260:2 

grower/shipper/packer

361:20 

grower/stakeholder

369:11 

growers 8:16 11:18 

37:21,21,22 39:1 

40:15 45:20 71:21 

72:1 88:7 157:5 160:7 

199:2 206:2,6 257:21 

259:13 263:16 279:9 

291:12 292:13 295:14 

299:6,9 342:14 

353:17 358:13,16 

360:7 361:1,17,18 

362:2 363:2 366:8 

growing 12:3,6 28:18 

29:12 33:6 38:5 65:13 

110:20,21 129:6 

138:2,3 144:8,12 

151:10 167:15 172:13 

185:1 260:18 284:17 

294:17 297:13 346:20 

354:2,15,16 

grown 69:16 97:20 

171:20 172:9 204:8 

284:10 346:6 

grows 146:14 

growth 110:9 113:1 

127:7 130:3,6 137:12 

137:15 263:2 284:16 

325:18 326:6 332:1 

339:5 340:5,6,7 

347:12 

guarantee 156:22 302:7 

guaranteed 295:16 

guaranteeing 109:1 

guarantees 302:7 

Guenther 2:6 46:3,12 

46:13 49:11 50:18 

52:6 53:19 55:13 57:8 

57:15 58:10 59:6,13 

59:16 60:20 61:2,6,9 

61:12,15 65:15 68:3 

73:6 75:3 78:17 80:3 

82:19 86:20 87:2 89:6 

guess 39:4 53:5 214:15 

278:11 312:8 385:13 

388:2 

guest 4:18 252:12 

guidance 95:18 358:16 

guide 62:19 

guideline 234:1 

H

H- 296:18 

H-1B 264:15 269:12 

296:7,7,11,11,20 

H-2A 48:20 65:1 205:4 

206:1,12 242:17 

243:10 251:2,19 

256:19,21 257:12,20 

258:15 259:7 265:6 

268:4 269:16,19 

271:8,20 272:17 

273:13,19 274:3 

286:16 289:10,12,13 

291:7,18 292:14 

294:17 295:2 297:4 

303:2 307:4 308:16 

309:3,5,6 310:11 

321:10 325:3,5,8,18 

326:6 328:14 329:3 

331:19 332:7 339:8 

H-2As 292:8,9,17 

H-2B 271:12,15,15,18 

307:5 308:9,11 

H-2Bs 271:13 

H-I-L-E-S 203:1 

H.R 58:6 

H2- 339:5 

H2-A 8:6 

habitats 158:12 

habits 149:9 378:13 

Hafemeister 2:8 92:6 

99:17,20 139:15,18 

139:22 141:12 144:17 

150:16 151:22 152:9 

152:17 

Hafemeister's 53:4 

hair 297:7 

half 7:16 84:2,3 86:3 

105:5,5,6 106:20 

127:13 147:10 221:22 

227:18 253:5 323:13 

355:10 

half-life 184:21 

hall-style 346:19 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
413 

hammer 18:7 

hand 37:4 142:5 305:1 

handcuffed 339:2 

handle 101:3 168:9 

288:15 323:11 386:14 

handles 171:12,13 

handout 260:14 

hands 204:5,8 349:7 

handy 184:8 

hang 252:13 312:12 

hanging 134:7 

haphazardly 359:20 

happen 12:11 39:12 

74:1 113:13 129:14 

140:13 186:7 242:4 

369:1 379:8 392:18 

happened 122:9 143:22 

147:12,15 148:3 

244:14 263:2 340:5 

356:5 

happening 30:13 33:1 

91:4 154:7 263:3 

301:9 302:12 311:13 

370:14 387:9 

happens 37:15 51:2 

106:10 109:19 124:21 

245:20 256:5 278:20 

292:10 372:10 386:15 

happy 6:8 20:9 28:7,9 

43:18 44:21 45:15 

49:6 80:15 173:2 

183:20 213:13 225:9 

254:22 309:20 314:14 

323:11 348:17 357:10 

361:8 

harbor 120:9 

hard 4:6 9:11 17:20 

51:11 54:5,19 58:18 

60:14 89:21,22 121:7 

129:13 183:21 243:1 

250:7 293:21 337:1 

harder 83:21 337:4 

387:1 

harm 77:8 

harming 32:12,13 

harmonize 224:7 

harmonized 358:4,4,7 

362:5,9,21 363:10,13 

363:16,19 

harms 32:9 

HARPER 21:16,20 22:2 

23:10 26:17 36:8 39:3 

57:14,17 58:22 59:8 

59:14 60:18 61:1,4,7 

61:10,13 

HARPER-LARSEN 1:12 

189:5,8,12,15 190:22 

191:4,12,17 192:5,15 

192:18 193:10,13 

194:1 198:2 221:19 

223:2,5 237:5,21 

239:5 306:11 308:2 

312:18 315:3 326:14 

327:5,8,13,16,20 

328:11 329:5 335:19 

340:22 363:22 365:10 

366:15 372:4 375:10 

375:18 376:4,9 

382:17 384:9,12,16 

384:21 387:10,21 

391:19 392:1,5 393:1 

393:7,11,21 394:4 

harvest 249:10 271:12 

309:1,1 352:14,14 

359:1 

harvested 13:20 15:11 

harvester 248:6 

harvesters 216:21 

249:7 308:22 

harvesting 204:5 

248:14,21 260:8 

273:7 285:18 289:22 

290:1 298:11,11 

299:1,5 300:4,14 

346:20 

hat 252:13 

hate 387:12 

haul 50:20 

Hawaii 241:7 

hay 317:12 

hazard 359:6 

hazardous 176:3 

hazards 189:20 

head 197:15,21 236:10 

258:17 373:16 

headed 150:11 

headquarters 252:5 

heads 159:15 374:22 

headwinds 113:16 

health 24:3 135:7 

366:13 

healthy 41:14 145:22 

203:4 

hear 6:2 10:10 44:20 

93:12,15 104:19 

140:6 202:11 275:6 

340:14 350:15 362:18 

heard 43:15 44:19 47:6 

94:21 121:13 165:7 

178:11 181:6 193:4 

199:4 204:3 211:3 

271:1 313:18 

hearing 35:22 46:4 

196:13 285:16,17 

345:3 

heart 17:4 46:20 84:13 

84:14 93:22 257:18 

heat 379:4 

heavier 261:2 

heavily 133:7 373:3 

heavy 112:2 

held 7:14 146:8 

hell 60:21 

Hello 226:11 

help 14:11 17:2 39:1 

47:16 48:5 49:2 63:18 

68:17 75:16,17 76:2 

77:8 79:20 80:13 82:5 

102:21 103:6,8 106:2 

106:2,4,5 142:10 

148:2 150:3 166:13 

177:17 180:22 196:6 

198:15 213:3 220:22 

258:9 303:20 308:18 

337:19,20 341:15 

345:1 346:2,2 353:1 

378:11,17 

helped 110:9 115:21 

helpful 73:14 195:11 

203:21 387:8 

helping 70:16 97:22 

203:21 344:18 

helps 26:21 62:19 85:7 

86:6 107:5,5 179:10 

hemp 20:1 155:18 

156:6,10,12 

herbicides 182:8 

184:22 

herder 277:1 

herding 277:5 

hey 38:16 64:19 142:19 

184:17 373:19 

HGAP 358:5 

Hi 6:7 28:2,5 202:3 

219:6 348:4 

hide 159:15 

high 38:21 115:10,12 

115:22 116:11 126:16 

129:5,7 131:15,15,18 

131:22 132:10 135:7 

142:20 159:6 165:22 

169:5 195:1 203:17 

253:16 267:2 296:17 

303:6 

high-quality 178:17 

higher 114:19 115:13 

117:1 136:2 262:16 

265:3 268:5,6 296:16 

309:18 

highest 39:13 240:20 

294:13 

highlight 193:1 

highlights 316:2 

highly 22:3 44:13 

172:18 

Highway 1:9 

Hiles 2:9 202:21,22 

203:1 225:4,5 226:11 

230:19 231:6,18 

234:11 245:18 247:18 

248:1,8,12,22 249:4 

249:14 250:18,21 

251:11,15 252:14 

Hill 50:4,11 85:18 

215:16 

Hines 202:20 

hint 377:12 

hire 255:3 

hired 124:15 210:20 

214:18 223:18,20 

226:10 241:3 267:10 

hires 214:2 

historical 384:4 

history 50:11 107:18,22 

108:4 170:15 206:14 

211:7 276:18 287:19 

290:17 297:8 302:5 

hit 9:11 114:7,10,15 

159:2 185:2 232:10 

236:9 281:3 285:15 

hits 243:22 

hitting 117:7 

Hobbes 107:19 

hold 98:19 183:15 

251:17 279:16 280:4 

305:10 346:19 

holder 321:11 

holding 111:17,22 

341:22 

home 294:1 301:17 

317:8 394:22 

Homeland 286:2 

homogenized 175:16 

honest 213:9 

honestly 70:20 255:6 

honesty 255:3 

hope 22:9 134:1 242:7 

305:22 

hopeful 141:9 

hopefully 4:14 5:8,10 

5:21 47:18 48:16 

57:12 120:13 221:5 

359:22 

hoping 306:18 308:15 

hormones 131:3 

horrible 72:5 361:16 

horribly 289:5 

hot 100:17 112:2 170:9 

hotel 1:9 339:11,13,20 

hotels 339:7 

hotwash 370:11 

hour 5:3 240:14 293:7 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
414 

294:2 309:1,2 310:15 

389:22 

hourly 210:18 231:4,16 

286:19 289:1 

hours 173:22 210:15,15 

219:15 229:21 230:14 

230:22 231:20 238:22 

343:11 

House 34:5 40:8 49:13 

49:16 83:9 140:4,7,22 

141:13 

household 67:15 

252:19 253:2 

households 321:12 

housekeepers 273:11 

housekeeping 388:12 

houses 206:4 

housing 2:6,11 3:13 

106:16 273:11 279:14 

292:11 296:5 301:22 

304:1,1 305:5 315:7 

315:13,14,15,16 

316:10,10,11,12 

317:18,19 318:6,7,15 

319:9,15 320:1,11,14 

320:19 321:18 322:1 

322:5 323:8 324:6,14 

325:4,6,7,10,12,19,20 

326:10,12 328:4 

330:19,21 331:10,19 

332:9,10 333:7,15 

335:13 338:1,3,6,8,12 

339:6,7,10,16 340:8 

340:13,16 

how's 293:7 

HUCKABY 1:16 

huge 29:9,14,21 30:7 

31:20 80:2 82:2 88:16 

93:19 126:7,13 

148:14,14 180:12 

235:22 340:4 

HUGHES 2:4 11:12 

13:2 27:14 43:4,16,20 

44:2,4 46:2,10 90:4 

90:19 91:1 92:4 93:9 

99:2,9 163:13 164:10 

164:13,16 165:17 

168:17,21 184:17 

201:1,6,8 202:16,22 

203:2,7,9,11 207:1 

225:1,5,7 234:9,12 

250:5,19 255:18 

256:4 286:8 311:21 

313:1,5,9,15 314:7 

315:9,14,16,21 

340:15 347:22 388:13 

391:3,22 392:3,14 

393:6,14,19 394:2,5 

394:10,21 395:10,21 

396:4 

human 22:3 107:18 

343:22 344:2,3,7 

humankind 108:11 

humans 107:22 

humidity 159:21 

hundreds 368:21 

hunting 376:15 

hurricane 285:15 

hurt 70:17 243:7 

husks 175:13 

Hyatt 1:9 

I

iceberg 73:21 

ID 15:14 

IDC 76:9 

idea 88:8 119:6 124:13 

171:14 209:10 303:15 

314:6 369:9 375:11 

389:6 395:21 

ideal 370:15 

ideally 363:18 

ideas 82:16 282:5 

285:10 309:21 

identification 177:1 

245:11 

identified 39:16 205:3 

identifies 206:13 

245:12 

identify 25:9 177:4 

245:14 379:1 

identifying 169:18 

190:4 

ignore 87:18 350:7 

II 26:22 107:17 108:11 

108:19 

III 1:10,12 

Illinois 237:1 

illnesses 386:22 

illustrate 123:13 

illustrated 174:22 

181:17 

illustrates 104:18 125:3 

illustration 105:2 

imagine 128:7 194:10 

224:4 

imbalance 97:15 

immediately 133:11 

342:2 

immense 387:17 

immensely 374:2 

immigration 48:13 

203:16 215:17 256:14 

258:16 259:7 275:19 

impact 30:1 80:2 

155:17 206:11 218:19 

218:20 239:21 242:13 

295:8 350:14 359:18 

impacted 80:1 81:19,21 

impacts 78:20 81:17 

97:16 156:7 198:21 

199:2 

impairing 142:7 

imperfect 378:7 

implement 306:19 

implementation 94:13 

implementing 35:16,19 

implications 117:18 

import 32:12 44:18 

63:13 103:19 104:4,6 

104:10,16 119:2,18 

123:18,20 125:15 

128:12,13,14,14 

130:22 131:2 136:7 

138:16 139:8 204:3,4 

371:18,22 

importance 94:6 97:9 

important 7:11 17:10 

23:8 26:6 29:10 34:7 

45:7 47:10 49:3 65:21 

101:7,8 103:1,3 

111:13 112:10 115:5 

117:9 123:9 132:1 

136:17 155:8 157:20 

158:13 174:9 177:8 

206:6 220:16 225:22 

233:8 341:2 343:18 

343:22 346:16 351:12 

365:17 382:16 383:15 

importantly 4:6 291:5 

importation 295:11 

imported 31:11 110:1 

117:19 133:4 144:10 

171:19 172:5,11 

180:5,8 186:10 

importer 126:13 371:3 

371:11,15,20 

importer's 371:3 

importers 28:15 73:2 

104:1,20 133:7 342:2 

importing 127:19 

134:19 147:7 148:1 

151:10 

imports 30:1 32:16 98:9 

98:15 104:1 119:17 

123:13,15 127:1 

132:11 139:6 144:1 

145:3 146:4,13 147:6 

impose 117:22 120:7 

132:6 

imposed 159:22 358:1 

358:2 

imposing 115:3 

impressed 140:3 

impression 71:16 

improve 31:5,16 138:10 

327:3 346:19 

improved 127:15 166:4 

370:9 374:21 

improvement 95:15 

205:3 320:11 

improvements 95:17 

211:13 365:1 375:4 

improving 347:13 

in-country 371:6 

in-depth 391:12 

incentive 241:12 

incentives 71:16 72:10 

94:22 

incentivize 67:8,20,22 

309:2,14,18 

incentivized 361:19 

incentivizing 68:8 

inception 169:22 

inch 128:2 

incidences 159:11 

incidental 357:6 

include 60:8 95:21 

171:4,12,18 173:20 

175:12 176:16 318:16 

345:8 

included 7:15 68:11 

234:2 

includes 174:1 177:16 

183:16 210:6 252:21 

316:11 

including 96:9 144:22 

145:2 156:6 166:17 

167:7 173:13 189:20 

300:2 321:6 

income 89:2 102:19 

103:4 104:21 105:17 

106:2 208:16 321:12 

incomplete 360:21,22 

inconsistency 162:12 

inconsistent 9:2 162:14 

inconvenient 143:7 

incorporate 179:19 

incorporated 165:6 

177:14 270:13 271:8 

increase 32:4 39:15 

41:11 66:1,9 82:9 

86:4,4 94:14 103:9 

106:6 109:7 137:11 

158:12 161:19 166:6 

222:1,1 240:15,18 

241:13,17,20 243:2 

243:18 244:13,15 

330:22 363:18 

increased 29:4,5 47:14 

54:14 76:20 84:1,1 

97:15 111:18 149:18 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
415 

211:16 222:6 343:1,2 

increases 33:17 107:3 

240:8 261:10 

increasing 29:1 33:5 

69:9 176:4 

increasingly 380:2 

incredibly 346:16 

383:15 

independent 214:2 

298:8 

independently 358:14 

index 128:9 129:10 

India 52:22 115:2 

117:10 125:10 126:6 

126:15,18 138:15 

151:11 

India's 126:5 

Indian-based 296:5 

indicating 243:18 

indicator 109:22 110:7 

145:21 150:5 351:19 

354:2 

indices 239:22 

individual 129:8,12 

142:18 149:20 261:22 

263:12 272:11 360:7 

individuals 209:3 

238:18 

Indonesia 112:18 

industrial 108:7 128:11 

128:12 

industries 94:11 278:3 

325:9 

industry 1:3 6:22 8:2 

9:13,17 13:14 14:6,12 

18:9 23:12,17 25:5 

28:14 29:1 30:11 

31:22 33:19 42:9,20 

44:13,15,16 47:1,20 

51:15,16 53:11 59:20 

60:11 64:6,20 65:17 

65:19 67:1 68:17 

71:22,22 72:4 74:3 

75:9,17 76:19 77:7,7 

78:2,2,18 79:4 80:14 

80:14 84:5 94:5,7 

97:5,18 100:12 139:5 

139:14 145:14,17,22 

154:8,13 155:17 

156:11 200:13 202:9 

206:3 212:9 215:15 

220:15,17 226:1 

228:5 230:2,3 232:14 

236:13 239:2,10,13 

248:1 251:18 252:7 

274:13 294:10 316:21 

338:17 350:3 355:3 

356:3,10 357:22 

365:13 374:12 381:6 

384:22 

industry's 6:18 

inedible 189:18 

ineligible 362:14 

inequitable 289:6 

infallible 385:5 

infants 166:7 169:11 

196:2 

influence 163:17 196:9 

196:16 

inform 14:12 97:19 

166:13 216:5 237:12 

information 9:13 16:5 

19:13,15 20:18 21:7 

49:9 62:14 95:10 

165:10 166:13 173:13 

174:14 180:10,11 

183:9 184:12 190:11 

190:13 192:8 195:6 

228:12 229:7 248:3 

285:6 312:19 314:15 

340:20 347:17 360:10 

373:13,18 374:5 

informative 183:16 

informed 97:6 257:5 

informs 239:17,22 

infrastructure 36:21 

42:12 47:15 84:10 

ingredient 162:18 

ingredients 162:14 

inherently 276:16 296:2 

356:16 

initial 246:22 268:18 

302:19 350:2 

initially 60:15 353:10 

initiated 165:20 

initiative 257:11 293:13 

innovate 39:2 109:6 

innovation 38:8 88:16 

innovative 306:17 

input 16:12 19:13 22:22 

50:10 88:10 144:22 

169:4 353:1 

inputs 62:4 88:9 128:13 

INS 275:21 

inside 143:14 164:20 

340:15 346:14 

insight 50:15 140:2 

141:10 

insights 225:3 389:15 

inspect 367:14 377:3 

inspected 371:4,5 

inspecting 304:1 

inspection 9:10 274:11 

305:5 346:5,15 371:2 

inspections 26:8,11 

346:10 371:1,8 

installation 217:15 

instance 53:3 87:22 

95:6 96:13 238:2 

241:3 345:14 387:17 

Institute 381:21 

institution 316:18 

instructions 303:18 

instrument 178:1 

212:11 220:14 

instrumentation 176:20 

177:3 

insurance 8:22 153:13 

156:15,17 157:2,2,5,7 

157:11 159:3,4 227:8 

227:10,17,20 233:11 

234:3 246:14 

integrate 21:3 23:4 

integrated 28:17,19 

integrated-owned

37:17 

integrators 23:3,6 

intellectual 129:21 

intelligence 71:13 

intend 260:13 

intended 45:16 351:6 

359:5 

intense 124:5 172:13 

262:6 

intensity 233:2 

intensive 297:4 299:14 

intent 79:11 205:9 

237:11 290:12 

intention 5:1 257:9 

interactive 344:8 

interest 17:8,12 27:8 

97:20 165:12 169:13 

318:22 319:3,6 

338:18 369:18 

interested 8:9 43:10 

76:4 102:18 103:10 

106:3 131:19 135:19 

137:20 176:6 181:6 

183:22 195:6 228:2 

229:4 266:17 355:20 

interesting 85:17 108:6 

110:13 122:8 131:17 

144:18 147:4 203:16 

203:19 261:19 372:1 

interface 22:19 

interim 130:17 145:9 

internal 141:5 221:17 

270:22 271:5 330:1 

382:21 383:14 

internally 294:22 

International 44:9 

interpret 354:11 

interpretation 204:17 

358:12 

interrupt 100:20 230:17 

intervention 113:9 

interviews 258:21 

intimately 244:17 

introduce 13:3 14:8 

83:17 207:3 348:1 

introduced 164:14 

313:12,15 

introduction 154:4 

158:1 

inventories 15:21 

inventory 13:12,16 15:5 

18:21 21:2 

invest 75:16 109:6 

148:10 

invested 36:19 

investigate 255:1 

investigation 370:2 

376:22 

investing 66:13 

investment 47:16 69:21 

148:9 

investments 381:10 

invite 12:19 27:14 

315:9,19 363:14 

invited 4:19 200:17 

345:6 

inviting 165:12 184:11 

200:10 

involve 38:4 

involved 6:20 13:14 

14:9,11 18:1 77:20 

100:9 164:3 256:17 

260:1 287:12,13 

288:13 343:15 369:16 

381:15,16,18 

IPR 114:3 116:20 

IRCA 290:5 

ire 335:1 

ironically 276:7 

irony 320:13 

irrelevant 287:3 

irrigation 349:6 357:1,2 

357:2 

Islands 306:20 

ISO 178:8 

isomers 176:10 

issuance 305:16 

issue 39:16 45:21 50:9 

55:16 63:8 70:17 71:6 

77:20,21 78:1 85:20 

87:15 100:21 119:5 

121:12 141:18 154:18 

184:21 185:8 193:7 

199:8 259:5 261:21 

261:22 268:18,19 

271:9 272:17 276:7 

277:14 282:8 285:5 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
416 

303:12,16,20 304:19 

304:22 306:1,6 307:1 

319:3 361:13 372:21 

377:16 

issued 97:6 259:1 

276:22 369:19 371:12 

372:18 

issues 6:15 7:17,18 

8:12,19 36:16 47:7 

48:22 49:15 53:18 

55:17 61:21 72:20 

85:22 100:16,17 

101:10 111:6 119:21 

136:12,13 143:17 

154:19 185:1 195:3 

263:20 270:7 271:16 

273:1 305:9 347:16 

355:15 359:13 367:17 

370:18 

issuing 346:21 

it'll 51:11 

item 232:15 345:17 

items 65:12 229:9 

346:11 

J

Jack 9:14 

Jackson-Gheissari 2:9 

43:13,17,22 44:3,7,9 

jail 120:6 

JANIS 2:2 

January 45:20 144:1 

210:7 229:15 240:6 

241:2,7 264:3,13 

Japan 53:3 101:11 

111:19 120:11,13 

131:12,13,18,19 

132:4,11 133:3,20 

138:18 150:10,12 

Japanese 132:21 

148:20 

Jason 2:8 53:3 62:18 

92:6 99:3,10,20 150:9 

151:20 152:6,13 

Jean 11:14,15 12:12 

JEFF 1:16 

Jennifer 2:13 87:4 

342:16 343:18 348:1 

348:5 

Jersey 63:16 

JIMENEZ 2:4 6:7 10:22 

11:4 

job 28:22 64:11 202:9 

242:9 246:1 248:19 

252:22 269:6,7 273:5 

276:1,2,5,14,15 

280:18 285:2,8 286:4 

295:19 301:4 309:3 

311:1 388:2 

jobs 30:4 118:16,17 

246:10 259:11 262:12 

265:2 266:17 273:8,9 

291:10 295:2,7 

JODI 2:12 

Jody 207:2,2,16 213:15 

234:15,16 287:6 

John 1:13 2:10 155:7 

202:3,15 

join 342:17 

joined 125:17 126:16 

136:20 

joining 153:6 

joint 161:18 272:4 

340:11 

Jones 2:10 202:3,3,15 

202:15 

judge 276:13 

judgment 160:17 

JULIE 1:16 

July 11:13 210:7 236:2 

245:16 

jump 204:11 225:2 

234:9 250:5 286:8 

jumped 127:14 

June 193:22 

Jungmeyer 12:14 

Jungmeyer's 27:15 

justify 57:3 96:11 

339:15 

K

K 2:1 

K.C 1:14 

keep 18:14 29:11 30:14 

51:18 95:19 112:6 

115:21 116:11 117:14 

120:11 123:8 129:13 

138:21 150:18,19,19 

150:19 152:13 163:16 

168:20 220:13 222:10 

256:5 279:16,17 

286:10 307:7 344:21 

354:12 

keeps 336:2 351:22 

KELLY 1:18 

Ken 345:3,21 

Kentucky 38:13 

kernel 175:14 

key 15:9 24:5 49:16 

205:3 349:1 

kick 280:1 292:8 388:14 

kickback 338:7 

kicked 279:6 

kid 317:15 

kids 31:16,21 84:22 

169:15 253:16 266:9 

317:8 

Kiley 1:12 349:20 

361:11 362:9 

Kiley's 348:16 361:12 

kill 77:17 

killed 193:11 

kinds 88:17 138:9 

266:17 300:13,14 

369:8 

KIRSCHENMANN 1:17 

184:15,19 

kiwi 170:9 

knees 58:4 

knew 74:14 78:15 

knocking 221:20 

227:12 

knowing 36:10 179:10 

183:13 226:5 229:4 

306:9 350:15 390:17 

knowledge 140:1 

323:15 

known 97:8 158:4,8 

166:3 369:19 371:20 

knows 72:3 74:2 82:20 

240:16 305:18 

Korea 45:6,7,21 53:2 

119:11 120:20 

Koski 2:10 13:1,4,6 

20:22 21:19 22:1,8 

23:15 26:18 27:6 

kudos 28:11,12 

L

L 1:16 

lab 168:13 177:18,20 

188:21 

lab- 175:16 

label 162:4 

labels 153:14 162:12,13 

163:3 

labor's 267:22 

laboratories 167:12 

176:19 177:12 182:5 

182:7 185:18 

laboratory 168:11 

173:17 175:4,6,7 

176:8,15 177:16 

182:9 189:4 

laborer 289:14 290:3 

laborers 219:14 289:11 

320:12 321:6,9 

labs 175:19,21 178:7 

lack 160:6 

lacking 18:12 156:20 

lacks 156:19,19 

lagged 153:21 

Lammers 2:11 315:8,10 

315:11,13,15,19 

316:2 323:18,21 

324:3,16 326:9 327:2 

327:6,11 328:1,19 

329:1 334:18 335:3 

336:3 337:12,15 

338:11,14 

Lance 12:14,16 27:14 

28:6 

land 23:7 124:4,5 

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357:16 

landscape 335:17 

landscaping 276:10 

278:15 

language 35:16,18,19 

35:20 62:8 74:16 81:3 

96:1 203:22 288:18 

370:22 383:20 393:9 

393:10 

laptops 391:5,7 

large 19:1 105:4 111:14 

125:13 176:3 177:4 

212:8 227:4 257:10 

292:19 316:14 317:2 

326:16 361:21 

larger 171:15 233:20 

253:4 319:21 320:15 

361:20 

largest 235:19 260:21 

LARSEN 21:16,20 22:2 

23:10 26:17 36:8 39:3 

57:14,17 58:22 59:8 

59:14 60:18 61:1,4,7 

61:10,13 

lasted 275:18 

lasting 264:18 276:5 

lastly 19:4 

lasts 276:15 

late 92:7 128:1 271:15 

375:6 

Laughter 313:3 394:8 

launch 124:11 

law 13:6 18:6 35:9 58:6 

64:15 83:6 144:18 

271:22 275:19,21 

290:18 293:17,20 

294:2,7,11 297:9,14 

302:15 303:14 304:22 

357:16 

lawfully 258:11 

laws 83:4 

lawsuit 143:8 379:19 

lawyers 379:20 

LC 176:21 

lead 93:10 107:20 

200:21 287:11 349:1 

391:4 

leader 323:4 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
417 

leaders 68:2 140:7 

leadership 140:4 

141:14 

leading 93:17 108:8 

leads 69:11 388:20 

leafy 350:3,10 356:3,9 

357:18 359:21 364:14 

365:9,11,20 366:3 

382:2,4 

Leanne 341:12 

learn 345:21 

learned 14:17 17:1,22 

19:21 323:14 358:8 

377:18 

leave 94:14 100:19,22 

183:12 301:11 368:3 

leaves 152:6 

led 276:1 297:9 

left 10:21 40:11 85:7 

261:1 329:10 366:20 

leg 58:3 

legacy 19:16 20:13,19 

21:21 157:22 161:4,7 

161:10 

legal 59:3,4 158:21 

369:7 383:1,22 

legalization 20:1 

legally 189:10 383:2 

legislation 145:5 

legislative 50:4 275:8 

legitimate 260:7 370:18 

lender 336:17,17 

lending 336:8 

length 277:18 

lengthy 157:20 

lesson 377:19 

lessons 111:12 

let's 22:21 33:15,21 

51:5 68:10 81:4 99:12 

113:15,15 121:12 

125:7 130:20 146:1 

146:14 149:6 248:20 

302:9 308:21 333:22 

346:1 383:13 387:13 

389:1 

letter 303:17 371:13,15 

letting 142:1 339:2 

lettuce 100:11 

level 42:8,13,16 68:21 

88:16 195:1 197:12 

208:20,21 210:22 

211:21 217:5 218:1 

220:6 226:7 229:1 

230:5 233:5,6 256:15 

265:20 267:17 280:2 

281:17 352:16,17 

362:3 367:4 383:6 

levels 9:2 89:14 126:17 

144:16 166:15 174:4 

174:5,8 179:14 

182:15 

leverage 31:4 50:4 

134:5 151:15 319:17 

leverages 31:10,10 

Lewis 2:10 13:6 

LGMA 357:8,10 358:19 

364:10 366:2 382:6,7 

liaisons 168:13 

license 279:14 

licensed 13:21 15:12 

15:19 

licensee 15:1 

licensees 15:4 19:12 

life 16:3 319:6 

lifestyles 109:10 

lifetime 39:8 

light 355:16 364:19 

Lighthizer 49:21 

likelihood 160:8 

limit 32:7,16 131:21 

150:7 156:13 160:1 

189:14,16 320:6 

328:3 

limitations 270:13 

273:22 333:11 

limited 154:14 156:10 

159:19 160:2 194:5 

320:16 

limits 126:2 177:5 

178:4 351:18 352:8 

352:10 

line 48:15 108:3 244:6 

263:18 264:3,12 

265:16 310:16 

lines 14:14 94:4 

lingering 312:1 

lingo 319:13 

link 355:21 

LIPETZKY 1:17 150:9 

liquid 176:21 

list 4:8 45:3 79:10 90:22 

162:16,18 173:3 

191:10 193:17 196:4 

198:21 

listed 155:15 181:14 

193:2 283:2 

listen 49:4 

literally 287:15 

litigation 379:19 

little 4:10,11 13:19 

14:16,16 15:8 16:22 

24:10 30:10 33:20 

34:8 40:20 45:22 46:1 

46:6,15 50:9 57:12 

59:9 68:14 69:11 75:4 

85:6 92:7 101:9,13 

102:8 113:16 115:18 

125:8 138:18 142:3 

157:19 165:9 184:18 

188:11 197:9,10 

207:8 208:3 211:2,9 

228:14 241:5 257:1 

258:7 265:3 268:20 

278:11 305:10 307:22 

317:4,5,6 319:19,20 

319:20 342:6 348:15 

349:12 351:4 352:22 

355:22 356:11 357:3 

357:20 359:2 367:19 

375:3 387:4 389:20 

394:11 

live 39:13 108:2,3 

110:17 127:8,10 

live-in 322:16 324:5 

lived 317:12,15 

lives 107:1,20 108:9,17 

109:18 

livestock 102:13 124:7 

210:19,20 216:20 

277:4 289:1,12,14,15 

living 108:5,12,14 

109:14 127:15 297:11 

324:18 

loan 319:6 320:4,7 

322:18 

loans 3:14 315:7 317:3 

320:4 325:21 337:9 

local 31:19 65:5 68:1 

82:17 86:19 87:8 

229:3 289:16 301:16 

318:18 333:22 334:13 

339:11,20 363:1,2 

384:8 

locally 112:14 

located 270:3 318:10 

location 233:1 252:4 

locations 173:20 174:3 

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locked 126:16 

LOD 177:5 

LODs 177:5,8 

log 21:15 

logic 146:6,7 

logical 363:8 

logistical 353:10 

logistics 353:4 

long 6:11 25:19 50:20 

61:16 84:16 112:11 

133:18,19 158:20 

161:7 167:9 283:7 

305:1 321:1 334:2,5 

393:3,12 

long- 54:5 

long-distance 7:3 

long-standing 52:15 

long-term 54:19 211:18 

347:6 

longer 109:14 142:6 

148:1 150:10 264:18 

266:9 275:18 276:15 

276:18 277:9 305:10 

374:3 

longstanding 141:18 

look 6:2 7:22 9:21 

10:18 19:6 21:5 22:6 

28:5,21 29:3 30:1 

32:4 34:14 38:22 

39:10 40:15 52:4 53:8 

66:8 67:22 70:16 91:5 

107:18 110:10 112:12 

125:10,10,21 128:4,7 

129:19 134:16 135:9 

144:8 147:4,15 148:2 

154:3 192:11 198:8 

199:19 208:15 214:22 

217:15,17 241:1 

244:5 254:3 259:6 

262:2 263:15,18 

264:2 266:20 279:20 

294:6 299:1 311:16 

311:20 319:2 326:3 

333:17 338:21 375:13 

383:18 384:22 385:9 

looked 38:2,7 98:17 

162:22 185:13 290:3 

337:4 

looking 30:2,11,14 31:4 

33:1 45:13 48:5 55:8 

72:19 81:1 84:8 

103:17 104:22 111:2 

117:15 141:11 156:7 

183:9 191:20 193:18 

196:4 221:22 233:20 

238:12,15 251:20 

258:4,5 289:21 

306:12 328:15 332:6 

342:11 343:19 350:12 

378:14 382:22 385:10 

385:13 

looks 187:11 229:4 

263:14 265:17 

loosening 175:14 

looser 253:20 

lose 138:20 340:1 

losing 77:9 105:11,13 

123:10 158:15 

lost 79:5 82:5 368:13 

373:19 391:9 

lots 131:17 138:17 

149:22 252:1 275:3 

296:17 

love 27:10 90:17 151:2 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
418 

223:8 240:21 384:2 

lovely 223:4 

low 80:7 126:8,21 177:5 

177:6,8 181:17 207:9 

262:22 319:3 

low-interest 325:21 

low-to- 321:11 

lower 11:22 37:4 

132:13,17 138:21 

142:11 159:20 268:11 

301:20,20 

lower-income 318:13 

lowered 125:18 290:21 

lowering 132:5 

lowest 65:8 79:17 

Lubbock 69:15 

lumped 286:2 

lunch 41:13,20 67:7,21 

72:22 84:3,19 85:2,8 

95:6 152:20 200:10 

200:15,17,19 201:2 

316:7,8 

lunches 31:13 67:8 

M

M 370:8 

M-E-T-R-C 13:10 

ma'am 274:8 

machine 245:7 

machines 128:15 

macroeconomic 148:5 

mad 77:22 

magic 87:19 

mail 220:22 222:11 

305:20 

mail-ins 303:7 

main 165:5 280:6 

370:19 

maintain 96:10 115:15 

289:15 327:3 

maintenance 322:4 

major 29:2 147:22 

171:4 325:12,16 

361:13 362:6 

majority 127:11 180:7 

263:2 380:11 381:6 

393:22 394:3 

makers 103:3 

makeup 36:10 60:19 

61:14 

making 19:11 37:10 

40:14 65:19 118:7 

127:6 220:3,5 336:12 

354:20,20 378:20 

381:9 385:16 389:17 

man 122:18 

manage 326:12 349:19 

management 156:17 

194:20 195:2 196:11 

196:17 200:4 238:17 

373:10 

manager 201:15 226:16 

309:1 

managers 217:1 

managing 318:15 

mandate 166:8 

mandated 195:9 

mandatory 86:14 

mangos 31:9 

manifest 22:21,22 

manner 163:4 342:16 

manners 272:4 

manually 19:14 

manufactured 125:22 

manufacturer 128:1 

manufacturers 163:3 

manufacturing 118:16 

151:8 

map 31:1,4 167:22 

168:7 

March 229:15 395:14 

marginal 106:10 

Mariana 306:20 

mark 22:9 286:9 389:1 

market 34:4,22 35:6 

53:10 54:12,13 65:21 

66:6 70:18 77:10 79:5 

79:15,18,20 88:11 

97:10 100:10 102:12 

102:22 103:4 105:14 

105:16 110:22 113:8 

119:15 120:12 123:21 

127:4 130:14 131:14 

131:15,15 132:9,15 

134:15 137:14 138:13 

138:19 150:18,21 

153:19 206:7 258:9 

268:15 295:21 296:7 

296:8,12,14 297:2,5 

347:5,6 357:14 

362:18 

market- 300:18 

marketable 158:21 

marketed 168:6 

marketing 68:9 69:9 

165:2 166:17 345:9 

350:10 357:19 381:21 

marketplace 29:13 

30:18 67:5 

markets 34:15,16 36:12 

51:11,18,19 52:7,18 

53:9 54:11 79:13 80:5 

87:22 88:20,21,21 

97:13 105:11 109:2 

111:8,9,13,21 112:5 

112:10,11,15,21 

113:3,4,6 119:8,9 

123:6,8 131:13,17 

132:1 134:14 174:2 

319:1 

markets' 127:20 

marking 362:14 

Maryland 168:3 256:17 

293:16,16 294:1,9 

mascot 201:18 

mascots 201:19 

mass 125:13 176:22 

287:19 289:3 

massive 104:7 

master 272:10 

Master's 296:16 

match 247:3 307:15 

matches 246:19 

matchup 259:10 

material 27:9 

materials 9:16 158:1 

161:4,7,10 

math 352:19 353:19 

matrix 177:20 

matter 7:17 99:14 112:5 

113:5 201:9 240:10 

251:4 276:6 299:16 

314:22 372:15 396:6 

matters 103:5 234:19 

mature 88:21 

maximum 166:15 

McDANIEL 2:12 207:4 

207:16 213:21 214:8 

214:11,20 215:9 

216:4 217:2,10 

218:11 219:4 220:1 

220:12 221:8 222:4 

223:4,7,17 224:13,19 

225:4,6,10,14 234:17 

235:1,10,21 236:8,21 

237:10 238:1,14 

239:9 240:10,21 

241:21 242:1,6 

243:19 244:4 254:10 

255:13 

McENTIRE 2:13 342:17 

348:4,5,22 362:8 

363:7 364:6 365:16 

366:20 372:7,15 

375:16,19 376:8,12 

377:6,10 379:7 

380:18,20 381:5 

386:21 387:8 388:10 

McIntosh 300:2,8 

meals 301:22 302:1,1,2 

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49:11,16 53:6 54:12 

55:6,10 59:18 60:16 

63:2 66:21 68:20 

71:21,22 72:1 74:2,9 

76:5 77:11,18 80:4,4 

87:3 89:7,9,20 132:20 

132:21 140:2 143:8 

146:14 180:9 187:5 

192:11 194:3 197:9 

221:19,22 224:20 

225:8,12 237:8 244:2 

265:21,22 266:1 

267:2 270:6 271:3 

273:7 275:14 277:17 

277:20 292:8 294:9 

328:4,12,14 334:20 

351:7 352:1,20 353:6 

358:17 361:14 363:5 

363:7 384:5,20 

387:18 389:13 395:1 

meaning 339:7 

meaningful 95:17 189:9 

206:11 212:12 

means 66:10 110:6,21 

116:20 197:17 204:18 

275:8 318:8 337:1 

351:13 390:12 

meant 12:5 101:2 

353:19 

measure 230:7 233:2 

240:1 366:11 

measures 32:9,10,18 

33:14 135:8 226:22 

meat 105:9 

mechanics 273:17 

mechanism 143:15 

221:8 381:18 

meet 6:17 18:16 20:15 

39:2 62:6 66:20 

152:15 202:19 282:13 

339:10,17 340:3 

352:7 395:14 

meeting 1:5 4:4 9:8,20 

9:20 15:21 27:19 

43:18 46:17 99:8 

143:5 195:16 201:4 

315:5 347:3 390:13 

394:13 

meetings 7:3 59:10 

346:19 

meets 16:12 239:16 

254:16 346:3 

melon 377:14 

member 27:17 83:10 

332:1 363:8 369:13 

members 2:1 8:4 17:11 

28:15 31:17 37:20 

43:7 72:13 93:11 

152:4 272:3,7,10,11 

341:9 346:17 361:1 

382:1,2 385:15 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
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389:16 

membership 93:21 

349:18 350:12 

memories 377:22 

memorized 240:22 

men 310:14 

mention 9:7 211:3 

290:16 364:1 367:21 

mentioned 9:9 10:5 

23:11 40:8 41:12 48:9 

53:15 54:12,13 65:22 

66:14 75:9 82:12 

182:6 195:13 221:9 

290:18 301:3,19 

331:7 349:20 361:11 

368:7 

mentioning 288:22 

menu 95:6 

merchandise 147:3 

message 140:4 280:6 

met 1:8 6:9 7:9 65:20 

66:4 139:17 354:4 

367:11 

metabolites 176:9 

185:13 

method 175:20,21 

176:10 182:6 269:3 

353:11,19 

methodologies 8:11 

methodology 22:12 

298:16 

methods 158:9 161:8 

166:6 176:1,2 178:2 

185:16 194:6 204:22 

353:13 

Metrc 2:10 12:21,22,22 

13:10 

metrc.com 13:11 

metric 145:11 357:9 

metrics 366:2 384:4,4 

metropolitan 38:11 

Mexican 64:1 78:2 

123:13 

Mexico 28:16 33:2 

35:17,19 36:18 37:22 

38:9 42:10,19 58:13 

59:2 60:21 63:14,15 

63:17 98:4 111:19 

114:11 115:2 117:9 

117:11 120:5 121:14 

123:5,15,21 133:21 

142:10,20 143:2 

147:8 

mic 93:11 250:16 

263:22 

MICHAEL 2:2 

Michigan 168:3 361:16 

microbial 189:18 

351:17,20 352:8 

microbiological 342:15 

343:1 

microbiologist 348:9 

353:15 

microorganism 364:20 

Microsoft 296:5 

Microsoft's 296:6 

mics 250:8,12 256:2 

mid 276:9 

middle 110:17,20 

118:17 120:3,15 

130:19 131:10 306:21 

Midwest 51:9 239:14,14 

migrant 301:18 338:1,8 

migrants 317:17 

migrating 266:7 301:21 

Mike 311:6 

mile 159:18 

miles 243:13 280:11 

milk 182:14,14 

million 29:21 69:6 

84:22 170:14,17 

214:5 232:13 234:20 

235:19 236:7 238:5 

261:8 265:3 266:5,5 

320:3,7 328:3 329:17 

345:17 361:18 

millions 19:2 347:4 

mind 43:20 72:6 107:14 

163:16 220:14 222:10 

256:6 295:10 316:4 

mindful 366:9 

mindset 349:19 

mine 193:8,11 

minimal 25:10 

minimize 238:18 

minimum 159:18 

197:17 287:2 290:3 

293:6,17,20 294:5,11 

294:14 381:1 383:7 

minimums 383:1,12 

Minnesota 253:18 

minute 99:7,10 230:18 

258:8 

minutes 14:15 152:1,2 

183:10 200:22 201:2 

234:12 250:20 267:8 

311:22,22 314:20 

347:18 390:3,5,12 

misconception 219:19 

misleading 218:3 

misrepresent 96:21 

missed 22:9 

misses 278:21 

missing 34:8 193:16 

380:6 

mission 165:21 166:22 

178:12 186:20 

misspeak 215:6 

misunderstanding

296:10 

mitigation 26:9 79:10 

80:10,16,22 81:5 

359:6 

mix 272:5 

mixed 96:18 

model 171:8 178:21 

195:14 262:9 272:8 

325:13 

models 238:8 

moderate 321:12 

modern 130:10 

modernization 281:15 

342:3 

modernize 256:21 

257:12 

modernizing 282:4 

modifications 393:2 

modify 5:5 

modulated 129:2 

modulating 116:17 

modules 344:18 

Molly 1:15 341:10 

moment 45:2 101:16 

Monday 11:13 

monetary 395:11,12 

money 31:15 70:19 

71:4 84:6 86:12,14 

89:1 102:11 109:14 

112:17 116:7 130:16 

156:14 191:18 298:6 

322:3 329:9,10 

330:10 336:2,4,5,14 

336:21 337:3,5,18 

379:21 395:15 

money's 332:2 

monies 326:15 329:14 

monitor 19:7 26:7 

179:13 205:15 

monitoring 19:19 23:8 

164:6,9,10,22 166:14 

167:7 169:8 179:21 

monitors 174:8 

month 173:9,10 174:22 

175:4,19 210:6 

229:13 230:9,9,9 

232:5,17 237:17 

264:5 265:19 306:1 

monthly 62:7 179:13 

months 72:2 118:2 

165:15 172:8,10 

183:20 204:19 211:8 

232:4 244:19 261:1 

264:9 275:18 276:6,6 

276:12,16 277:8,19 

323:14 325:3 347:17 

356:4 374:4 389:17 

Moore 2:14 28:2,3 

34:10 35:8,11,15 36:4 

37:11 43:3 

morning 4:3 5:3 6:7 

27:18 44:8 46:12,13 

57:14,15 99:18 317:9 

Morocco 112:19 

mortality 127:17 

motion 394:15 396:1,2 

motivation 368:22 

380:5 

move 11:7 27:2 48:17 

48:20 49:17 63:15 

83:5 91:19 92:7 99:11 

119:20 138:11 148:4 

158:8,9 159:14 160:9 

162:12 180:17 230:14 

255:21 261:17 264:14 

269:4 282:8,21 283:4 

306:4 392:16,18 

moved 235:7 280:9 

movement 31:8 33:10 

34:20 48:12 51:22 

160:4 161:2 350:8 

moves 185:20 258:17 

moving 21:10 45:4 

56:19 77:12,17 151:9 

205:2 258:13 305:15 

342:4 344:5 346:8 

MRLs 44:19 45:4 

189:16 

MSMA 320:17 

multi- 175:20 182:5 

multi-residue 176:10 

194:6 

multi-room 324:5 

multi-state 68:11 210:9 

211:19 

multi-year 346:1 

multifamily 316:11 

320:22 

multiple 170:6 175:22 

235:12 245:22 246:1 

248:5 250:8 272:4 

335:7 

multiply 253:7 

mushroom 274:13,19 

mushroomed 73:8 

mushrooms 274:16 

mustard 170:9 

muster 41:1 

myth 242:18 

N

NAFTA 57:18 74:9,13 

78:15 110:4 121:13 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
420 

121:20 122:1,4,7,10 

122:22 123:3,10,18 

124:22 142:18 

NAICS 230:3,5 

nail 18:7 236:9 

name 13:6 44:8 99:20 

107:19 202:13 338:19 

names 46:9 257:8 

NAP 88:15 157:10 

narrative 108:11 183:17 

246:21 

narrow 25:15,20 377:8 

narrowing 376:5 

NASS 171:7 207:2 

208:4,6,10 209:18 

213:13 215:2 218:7 

221:9 223:12 226:6 

254:4 287:7,11 

288:14 

NASS' 267:10 

nation 323:4 329:18 

341:21 

national 2:12 67:22 

68:12 72:14 75:13 

117:18,19 144:2,5,16 

145:1,14 170:22 

207:12 210:22 223:11 

228:22 240:19 241:13 

252:20 

nationally 165:22 171:1 

174:17 178:17 179:22 

243:16 

nationals 8:8 

nationwide 84:21 

NATO 108:22 

natural 147:18 278:7 

352:11 

nature 24:18 236:15 

275:15 276:16 277:11 

374:22 

nay 394:1 

near 46:19 84:12 

147:18 261:7,8 

283:15 292:4 317:16 

nearly 103:15,18 

necessarily 67:4 

215:18 263:6 331:15 

378:8 

necessary 19:9 26:10 

161:16 

needed 169:10 172:20 

175:17 178:15 268:5 

272:12 285:18 

needing 192:20 

needle 138:12 

needs 6:18 60:9 98:3 

98:12 135:13 141:4 

154:20 168:14 169:5 

195:19 239:16,18 

240:4 262:3 263:16 

263:17 308:1 349:3,8 

352:15 353:16 354:11 

360:9 387:12 389:5 

389:11 

negative 42:21 125:5 

156:7 

negotiate 136:22 142:2 

negotiated 120:5,6 

121:20 133:10 

negotiating 120:10 

132:4 166:18 

negotiation 35:13 54:7 

78:13 119:21 120:13 

120:16 121:7 130:20 

131:7 134:4 151:13 

negotiations 33:3 

58:11 59:1 74:18 

75:14 100:10,13 

136:16 151:2 

negotiators 60:7,12 

neonicotinoids 176:18 

nest 322:3 

net 104:1 126:9,13 

147:17 

never 54:2 80:1 122:22 

133:3 284:7 325:10 

Nevertheless 370:2 

new 20:14 38:15 52:18 

54:16 56:16 60:17,18 

63:15,16 72:5 83:8 

107:5 109:7 120:8 

132:16 133:21 135:2 

135:2 154:5,9,11 

155:9,14 158:5 

160:10 168:2 188:5,6 

205:2 216:20 219:6 

252:11 280:20 282:16 

299:3,13 306:19 

310:1,4 313:22 314:1 

327:1 329:19 371:18 

379:11 391:2 

newest 189:1,3 

news 111:15 117:12 

120:4 130:15 143:16 

newspaper 304:7,14 

nice 64:16,21 344:14 

nine 209:9 276:12 

no-cost 322:9 

Nogales 28:4 37:9,12 

noise 238:9 336:19 

376:19 

non- 279:10 

non-adulterated 185:8 

non-ag 114:9 

non-agriculture 278:13 

non-farm 227:1 

non-nationally 198:9 

non-policy 242:8 

non-regulatory 375:2 

non-tariff 55:15 

nonprofit 321:14,22 

325:14 326:10 327:18 

328:2,7 330:6,16 

331:15 337:9 338:3 

nonprofits 318:18 

321:19 323:7 325:13 

normal 129:5 131:8 

320:19 

North 28:20 168:3 

NOSA 319:13 329:20 

334:20 

not-for-profits 320:5 

notably 13:13 

note 304:4 

noted 155:5 156:16 

notes 10:15 153:2 

341:12 366:21 368:2 

notice 96:7 232:4 

254:19 284:8,21 

319:10 339:5 

noticeably 193:16 

noticed 17:17 211:10 

novel 54:18 

November 118:2 212:1 

nuanced 266:19 

number 32:21 50:19 

65:10 74:11 108:2 

122:17 125:18,19 

127:8,10,12 131:16 

160:5 161:3,14 

174:18 176:12 177:4 

178:11 181:17 187:13 

195:3 197:12 204:21 

205:20 206:9,18,20 

208:1 209:3,6,8 

210:14 220:8 227:22 

230:4,7,13 231:20 

233:22 234:19 235:3 

236:1 237:7 238:3 

239:6 242:22 245:11 

252:12,20 253:4,10 

254:2 255:7 266:4,11 

266:15 271:17 290:20 

324:7 352:1 363:22 

376:9 

numbers 188:8 225:9 

226:9 232:22 259:9 

259:10,18 268:11 

287:17 293:5 308:21 

322:14 353:2,9,14 

numerator 219:20 

nutrition 48:11 73:9 

82:12 85:16,22,22 

86:9,22 87:5,9 

nuts 105:7 133:2 

nutshell 323:10 

O

o'clock 5:8 

oats 170:9 

Obama 145:6 

objective 94:3,12 

130:19 135:22 153:8 

204:11 341:17 363:18 

observe 381:20 

observed 349:18 

obtain 318:12 333:14 

obvious 351:4 366:10 

obviously 4:20 29:14 

31:13 39:11 48:1 

65:20 72:20 73:2 76:5 

81:19 106:22 112:1 

130:17 185:12 186:5 

221:5 226:6 236:3 

307:4 348:13 389:12 

occupation 243:12 

247:21 

occupational 202:4 

211:1,21 248:2,9,10 

251:22 272:22 

occupations 205:5,11 

occupy 321:5 

occur 90:15 305:4 

occurring 374:15 

occurs 319:11 

Ocean 306:21 

October 35:22 58:2 

210:7 217:16 395:6 

odd 332:19 364:7 

off- 319:8 320:5 331:4 

off-farm 318:7,8 319:17 

319:20 320:8,15 

321:13,18 322:7,15 

322:18,21 323:2,7 

324:16 330:14,16 

off-site 331:9 

offense 288:7 

offer 37:7 230:15 

254:17 299:6,9 301:2 

310:3 322:9 347:19 

392:13 

offered 40:18 310:10 

offering 40:7 41:5 

296:5 341:13 

offers 97:21 246:1 

office 19:8 28:8 44:11 

100:7 177:14 194:20 

195:1 196:11 200:4 

227:17 238:17 256:10 

257:22 259:17 260:19 

285:15 287:12 345:4 

officer 13:10 16:2 90:12 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
421 

Official 2:4 

officially 90:13 

offset 97:15 

Ohio 168:4 

oil 147:5,6,9,9,11,14,15 

147:22 148:1 

oils 14:1 

OLC 276:1 

old 78:8,9 123:2 154:10 

207:9 298:15 378:15 

older 176:1 326:17 

OMB 305:14 308:12 

on- 334:1 

on-farm 318:7,9 319:15 

319:21 320:9 321:7 

321:14,16 322:8,16 

322:19 323:1 328:4 

329:19 330:14,15,21 

331:4 333:10,21 

334:7 338:3 343:3 

371:8 

on-site 339:10 

onboard 292:9 

once 23:22 50:1 51:19 

53:12 55:18 137:18 

142:19 169:2 175:6 

232:16,17 259:5 

292:20 323:12 337:1 

375:19 

one's 394:21 

one-page 220:20 306:1 

308:11,17 

ones 26:5 83:21 182:22 

196:2 213:19 301:16 

310:1,1,2,4,4 331:9 

388:17 391:2 

ongoing 33:3 51:1 

85:11 101:9 210:11 

218:18 

onions 236:18 

online 343:6,13 355:13 

open 52:6,18 54:10 

94:17 109:2 113:7 

120:12 123:8 130:4 

130:14 155:8 392:11 

opens 51:20 

operate 273:17 321:20 

operates 289:3 

operating 13:9 325:22 

operation 222:16 

236:14 246:13 262:1 

273:10,15 290:1,1 

321:15 

operations 16:7,11 

26:11 28:18 37:9 

253:5 278:5 343:5 

354:16 

operators 234:21 248:5 

249:8 251:9 

opinion 30:20 35:11 

55:5,10 80:13 153:17 

199:12 276:1 349:14 

366:18 375:5 

opinions 391:14 

opportunities 54:15 

105:1 110:22 137:22 

150:18 280:19 

opportunity 13:5 14:7 

44:5 74:6 77:9 98:5 

111:3 150:22 165:16 

208:19 269:6 306:12 

317:11 319:16 328:4 

332:17 343:10 378:11 

379:12 385:6 

opposed 12:7 35:18 

275:8 290:14 300:19 

optimistic 140:17,17,18 

option 65:8 352:9 

options 67:17 96:5 

163:4 353:14 

oral 12:17,19,21 

oranges 169:15 175:2 

orchard 249:1,5 255:5 

order 3:2 4:4,10 298:21 

390:19 393:20 

orders 281:10 285:19 

386:8 

ordinance 335:15 

organic 12:1,8 44:15 

158:14,15 171:19 

173:14 

organism 351:19 

organization 19:1 

45:17 72:15 82:8 

209:21 216:5 242:8 

294:22 

organizations 75:14 

155:6,12 358:9 

363:14 385:3 

organize 101:22 107:12 

109:21 113:2 249:15 

249:16 278:14 

organized 105:18 

357:11 

organizing 101:17 

278:5 

organophosphates

176:17 

oriented 113:8 

original 78:7 

originally 79:22 99:22 

originations 24:7 

origins 24:22 25:9 

ought 68:14 69:2,3 

381:3 

outbreak 25:4,6,9,22 

346:13 354:5 355:2 

356:1,6,6 370:2,11 

377:12 

outbreaks 346:11 350:4 

358:15 374:16,19 

378:22 

outlines 142:1 

output 118:14 

outreach 154:14 345:10 

outside 11:1 14:12 48:3 

52:2 80:6 81:5 107:9 

108:14 133:19 206:1 

277:7 325:21 384:10 

385:17 

over-spray 153:13 

overall 30:8 61:22 84:4 

122:4 137:11 186:12 

186:14 187:16 199:15 

199:17 388:16 

overcome 370:18 

overhead 356:22 

364:10 

overlaps 151:19 

overlay 82:21 

overseas 101:15 

103:18 105:10,21 

110:12 

oversee 207:18,21 

overtime 205:6 219:2 

overview 3:7,13 100:15 

101:3 164:19 165:8 

166:22 208:4 315:6 

overviews 153:15 

overwhelming 160:5 

owe 71:9 

owner 63:21 249:5 

owners 11:20 234:21 

ownership 208:15 

333:6 

owns 288:17 

oyster 321:6 

P

P-R-O-C-E-E-D-I-N-G-S

4:1 

p.m 201:10,11 315:1,2 

396:7 

Pacific 306:21 

pack 63:12 206:2,7 

package 36:6 373:6 

packaging 249:9,9 

350:6 

packed 16:21 317:13 

346:6 

packer 341:19 

packers 342:1,22 

packet 4:14 

packing 153:13 206:4,5 

273:10 317:13 321:7 

346:20 349:7 

page 184:2 270:8 307:8 

pages 90:22 

paid 205:11 219:16 

231:1 232:3,4,7,21 

255:10 289:10 

painful 107:21 281:7 

painfully 227:2 244:17 

pairs 170:14 

PALMBY 2:2 

panel 143:4 

papayas 377:13 

paper 202:8 302:22 

303:4 305:19 

paperwork 281:22 

282:2 308:13 362:1 

par 157:17 

paradigm 332:6 

parity 157:11 239:22 

part 25:14 47:14,15 

57:6 58:18 60:5 62:19 

74:2 75:18 85:3 

108:19 118:15 122:11 

122:15,15 134:5 

146:11,12 150:11,22 

151:1 164:5 165:1 

166:10 182:5,11 

185:8 186:20 192:12 

220:17 221:11 222:5 

228:7 232:19 233:3,4 

239:10 244:18 257:4 

257:11 259:4,6 277:6 

281:2,14 300:21 

302:19 306:7 335:5 

335:11 349:11 354:9 

354:18 355:3,6 

358:11,11 360:9 

363:10 372:17 392:9 

part-time 222:18 

parte 257:7 

PARTICIPANT 395:9 

participate 85:1 167:3 

168:1 274:14 363:15 

participating 171:3 

263:7 

participation 96:16 

particular 36:18 73:18 

74:10 83:8 100:21 

153:15 156:8 158:7 

185:14 192:7 193:2 

203:21 218:8 233:3 

270:2 278:15 300:21 

341:9 376:1,6 382:20 

392:10 

particularly 45:21 

78:20 94:7 134:8 

157:3 163:5 191:6 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
422 

192:10 193:3 195:22 

278:8 334:14 366:6 

particulars 157:13 

partly 151:3 

partner 123:18 130:11 

180:18 326:10 

partnering 337:9 

partners 31:14,15 

32:18 36:15 37:3 54:8 

166:19 210:10 214:21 

224:5 225:16 

partnership 16:16 

56:18 65:17 132:13 

168:8 

partnerships 14:10 

parts 48:4 74:10 82:5 

118:7 119:19 177:7 

216:10 220:15 221:14 

226:2 236:16 239:12 

257:12 287:9 351:11 

373:22 

party 23:3,5 140:8 

pass 43:12 124:17 

179:15 180:10 294:1 

passed 35:19 121:21 

275:20,21 286:1 

297:14 340:1 354:5 

passing 123:9 

passionate 71:2 220:17 

Pasternak 2:15 202:17 

256:8,9 262:22 263:5 

263:8 265:9,11,18 

267:14,19 268:1,14 

270:1,6,19 271:14 

272:15 274:7,15,18 

275:1,6,9,13 277:21 

278:22 279:4,7 

280:16 281:9,12,21 

282:3 283:7,17,20,22 

284:3,22 285:3 

286:14 288:20 290:12 

291:1,4,11,16 293:4 

293:10,15 294:15,18 

295:9 297:22 300:12 

306:16 307:17 308:6 

309:6,9,15,20 310:18 

311:2,5,10,14 312:12 

312:16,21 313:4 

314:3,8,12,18 

Pasternak's 234:13 

patchwork 34:13 

patent 142:6 

path 127:2 140:12 

358:15 

patterns 36:17 146:9 

PAUL 2:2 

pause 349:11,15 

354:10 361:3 

pay 15:17 132:9 133:8 

148:19 232:7,8,9,11 

232:16,19 289:1,8 

293:18 294:4 296:14 

300:6,8 309:4,22 

Payback 319:5 

paying 71:5 122:2 

232:16 295:14 308:22 

310:20 350:13 

payment 223:10 

payments 52:13 79:11 

80:16 102:22 

payroll 209:11 219:1 

pays 25:6 

PDF 391:16 

PDP 165:20 166:8,9,16 

167:3 168:1,12 169:3 

169:22 170:12,15 

174:3,8 176:8,19 

177:10 178:7,10,16 

178:21 179:2,19 

180:21 181:11 183:7 

183:15 184:3,5 

186:15,17 198:7 

pea 321:8 

peace 109:1 

peach 182:21 

peaches 12:8 66:19 

73:21 74:12 79:16 

96:17 

peak-load 276:15 

pear 298:11 

pears 96:18 

peas 170:10 

peeling 175:12 

penalties 96:20 

pending 256:20 304:5,8 

penetration 268:4 

Pennsylvania 274:20 

pens 289:12,14 

people's 248:15 377:22 

pepper 170:8 

peppers 170:9 

percent 29:4,6 30:5,9 

63:13 69:20 72:10 

79:6 87:21 94:17 

105:7,8 106:14 107:8 

111:11 114:6,13 

119:9,11,12,17 

123:16,19,20 126:18 

126:20,21 127:9,9 

132:9,10,14 133:4,5 

133:12,14,18,21 

138:15,19 139:8 

145:19,20 179:2,8 

180:4 188:8,9 205:22 

240:15 241:13,14,17 

242:16,21 243:17,18 

244:3,13 260:6 

261:12,16,21 262:3 

262:18 265:4 267:15 

268:7,10 269:2 271:2 

284:17 291:3,6,9,14 

295:1,3 298:19 303:3 

319:4,5 320:4,5 

330:11 378:16 382:9 

382:11 385:21 386:9 

386:11 393:16,16 

percentage 186:11,14 

292:19 

perception 242:19 

367:1 

Perdue 40:12 

perfect 347:22 365:6 

395:7 

perfectly 99:6 262:8 

perform 105:1 175:21 

177:20 346:4,9 371:8 

performance 160:15 

178:1 

performed 258:6 

270:14 

performing 166:8 

273:14 

period 50:5 74:1 80:10 

91:6 107:17 211:12 

219:1 240:9 254:18 

294:3 305:6 

periods 172:16 232:8 

232:19 

perishability 373:2 

perishable 77:15 

permanent 86:9 273:4 

276:8,11,16 277:12 

301:17 321:10 

permit 345:15 

permits 271:6 

permitted 191:10 

326:18 

permitting 334:15 

Perot 121:21 

person 8:11 12:17 

62:21 128:5,6 206:7 

246:10 247:5 259:12 

310:9,13 313:16 

335:16 379:16 

person's 246:4 

personal 50:21 80:13 

149:3 

personnel 345:9 

perspective 8:3 100:18 

101:12 195:7 208:5 

238:4 349:17 

pertaining 8:22 

Peru 63:18 98:4 

pest 56:2 194:20 195:1 

196:11,17 200:4 

pest/disease 47:22 

pesticide 2:7 3:7 9:2,6 

160:19 161:17 164:17 

165:6,21 166:1,5 

170:14,17 174:9 

178:3,13,19 179:3,8 

180:19 184:7 190:16 

194:17 196:13 

pesticides 45:12 

169:16 175:22 176:9 

176:11,13,17 177:2 

182:3 189:17 

Petersen 345:4 

Peterson 345:22 

petition 306:4 

petroleum 147:7,18 

pew 159:10 

pharmaceutical 142:7 

pharmaceuticals

141:15 142:2,8,10 

Philippines 112:18 

phone 7:3 313:6 

physical 305:19 

physically 333:21 

phytosanitary 57:1 

pick 232:1 236:20 244:7 

291:17 300:8 335:9 

387:2 

picked 292:7 

picker 289:8 

pickers 211:5 

picking 204:8 211:3 

249:20 

picture 173:19 175:15 

196:12 260:17 313:1 

pie 33:20,21 155:21 

piece 26:22 33:20 

155:21 199:22 213:5 

220:11,16,19 238:4 

244:4 279:12 285:6 

286:20 298:4,19 

299:4,6,8,9 300:10,13 

300:18 302:22 334:2 

370:20,20 377:14 

384:8,11 

pieces 7:11 155:22 

373:13 

pills 87:19 

pilot 84:21 

pineapples 104:11 

pinpoint 388:17 

pipe 365:13 

place 19:17 25:7 74:9 

74:21 91:11 114:12 

114:16 115:1 127:6 

144:4 146:1 151:12 

178:6 250:9 283:5 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
423 

304:4 374:15 390:5,7 

places 105:15 150:12 

151:15 

plan 9:16 68:6 171:2 

214:12 

planet 101:18 110:16 

planning 166:13 179:20 

198:15 334:14 

plans 167:6 333:13 

plant 15:10 23:18,20 

24:15 157:1 159:18 

269:17 317:13 

planting 264:6 273:8 

364:18 365:14 

plants 12:4,6 13:18,19 

145:20 148:12 321:7 

321:8 

plate 93:19 

play 32:20 58:5 137:14 

225:15 293:5 356:18 

players 381:7 

playing 42:13,16 367:4 

383:6 

please 6:3 12:12 102:7 

105:2 107:11 152:7 

pleasure 201:13 256:18 

PLU 373:16,18 

plug 10:14,15 143:3 

plus 79:19 136:20 

345:5,10,18 358:5 

361:14 362:6,9 

PMA 370:6 

pocket 71:5 

pockets 109:15 

podium 27:16 315:10 

point 4:10 6:5 24:1 27:1 

34:8 40:11 47:9 60:9 

64:5 67:14 73:8 75:15 

78:4 81:8 89:18 91:17 

110:13 112:4 139:13 

144:14 148:4 162:6 

170:14,20 185:4 

211:14 224:21 251:13 

259:2 261:20 264:3 

270:17 281:2 282:14 

282:15 284:1 291:9 

296:21 297:12 299:17 

301:8 308:8 322:12 

323:1 326:19 341:18 

355:2 375:5 381:13 

386:7 

point's 370:19 

pointed 158:1 274:11 

pointedly 156:16 

157:18 

pointing 140:19 

points 4:9 15:9 24:5 

25:11 26:5 170:18 

349:1 366:16 382:22 

poisoning 11:19 

police 16:2 57:20 388:3 

policies 107:7 

policy 17:14,16 48:13 

61:19 73:9 87:5 100:9 

100:13,16 106:1 

107:13 125:19 126:22 

129:20 136:12,16 

194:20 195:2 196:12 

196:17 200:3,4 216:5 

216:6 271:16 275:17 

279:22 288:10 394:6 

political 51:3 316:22 

politics 141:19 143:12 

pollination 158:14 

pollinator 158:12 

pool 215:20 216:3 

222:2 235:19 266:13 

266:15 267:9 332:2 

pools 226:6 

poor 30:7 110:15 157:3 

374:20 

pop 38:11 

popular 122:10 123:1 

378:14 

populate 21:4 

populated 174:21 

populates 23:2 

population 107:16 

144:9 174:20 201:21 

213:22 215:1,3 216:8 

254:2 266:6 320:16 

320:21 378:3 381:17 

populations 138:3 

171:3 

pork 50:14 

portfolio 322:15 323:9 

portion 49:18 85:4 

187:11 227:1,5 229:5 

portions 175:18 

position 60:13 70:13 

74:19,19 97:7 388:16 

positions 163:18 

positive 31:8,20 45:3 

48:8,12 124:21 125:4 

140:9 268:20 304:3 

318:21 376:21 

positively 30:2 

possess 158:17 206:14 

possesses 265:6 

possibilities 376:16,18 

possible 26:13 64:9 

196:13 

possibly 269:6 380:13 

post 167:18 298:20 

post-harvest 174:7 

post-World 108:19 

posted 176:5 

potato 24:13 

potatoes 50:15 169:15 

potential 30:13 31:6 

110:12 153:19 156:7 

160:3 172:22 178:16 

208:14 235:11 236:10 

347:4 

potentially 26:8 81:22 

82:1 252:11 301:15 

343:19 372:2 

poultry 123:20 131:1 

pounds 29:6,7 171:13 

175:2 

poverty 108:3,3,6,13,15 

POWELL-MCIVER 1:18 

power 88:5 145:6 

276:18 

powerful 372:2 

PowerPoint 340:18 

PPTXs 392:1,3 

practical 338:16 

practice 151:14 259:16 

practices 12:4,6 18:15 

150:1 151:7,12 175:8 

175:11 208:16 347:19 

379:15,17 

pre 174:7 

pre-harvest 352:12 

pre-plant 160:2 

pre-season 160:2 

precautionary 45:10 

predictability 113:12 

predictable 113:7 

predominant 226:1 

predominantly 222:11 

262:7,10 268:17 

292:3 

predominately 36:11 

36:16 

prefect 326:11 

preferable 204:7 

preference 319:16 

330:4 

preferred 206:13 

premises 15:12 

preparation 175:12 

176:5 182:9 185:17 

prepare 79:18 

prepared 9:16 175:7 

preponderance 330:18 

prescient 134:3 

prescripted 353:12 

prescriptive 354:19 

presence 161:9 

present 1:11 2:3,5 36:9 

143:22 185:1,2 

341:13 388:21 393:3 

presentation 3:5,7,11 

3:13,19 4:13 92:5 

152:14 165:9,14 

166:20 183:12 184:11 

202:18 234:13 312:7 

392:9 

presentations 91:4,12 

215:11 391:20 

presented 184:22 364:3 

365:2 

presenter 92:5 164:4 

presenting 364:1 

President 97:8 117:17 

117:20 121:14 129:15 

144:20 145:6,10 

146:8 

president's 257:11 

presiding 1:10 

press 355:1 

pressure 48:6 64:7 

134:7 162:6,10 380:3 

pressures 172:13 

presumably 120:8 

presumed 190:8 

presumptive 179:15 

pretty 29:7 58:19 

111:17 117:9 156:16 

157:18 194:5 206:17 

234:8 241:19 243:22 

262:6 264:11 265:12 

267:19 280:2 305:22 

316:7 331:9 338:5 

341:17 348:18 351:1 

351:16,19 353:11 

354:18 361:10 378:22 

prevailing 286:19 298:3 

298:4 

prevalent 87:9 244:15 

prevent 367:22 369:17 

374:14 

prevented 191:9 

preventive 343:21 

344:1,7 368:3,7,12,13 

370:20 379:11 

previous 176:2 284:6 

311:19 335:22 347:15 

previously 158:4 205:8 

price 25:6 87:15 102:14 

102:21 105:17 129:2 

131:15 

priced 239:22 321:18 

prices 79:17 80:7 87:21 

103:7 107:6 115:7,13 

115:14,15,21 116:2 

116:11,16,20 142:11 

pricing 149:21 

primarily 63:11 170:2 

172:5,11 186:16 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
424 

342:9 

primary 76:9 228:2 

240:3 248:19 

print 93:8 304:7,14 

305:19 306:3 307:7 

printed 373:6 

printout 46:8 340:16 

prior 194:1 233:15,17 

259:19 292:1 346:21 

358:14 

priorities 124:12 

prioritized 82:18 

prioritizes 86:19 

priority 120:12 123:4 

134:12 169:19 176:14 

181:22 182:3 185:20 

344:22 

private 62:12 100:7 

155:5 191:15,16 

337:18 338:16 

privately 155:10 191:1 

pro-competitive 137:13 

pro-trade 122:13 

probability 171:7 

probably 25:17 27:20 

58:17 62:15 63:12 

68:5 74:11 83:12 

85:12 86:3 121:4 

186:6 188:21 191:5 

192:22 200:20 222:3 

227:2 254:12 261:8 

265:3 267:12,19 

281:5 311:16 313:4 

323:15 328:2 360:21 

385:1 

problem 29:17 41:5 

52:19 71:11,12 74:15 

78:15 105:12 132:3 

132:18 140:18 142:17 

152:11 188:5,6 

269:21 281:13 283:9 

293:17 362:22 

problems 25:2 113:11 

130:21 162:5 

proceed 192:8 

process 14:18 15:15 

17:1 18:20 33:12 

62:15 63:1 76:8,11,12 

76:13 77:12,16 80:18 

103:13 140:16 143:4 

160:7 161:19 166:11 

177:19 178:14 205:15 

206:16 259:2,3 

263:21 268:10 269:11 

269:16 278:21 280:3 

280:17 301:8 302:20 

322:6,10 330:1,7 

343:15 346:3 347:14 

363:15 375:14 378:8 

processed 172:14 

276:8 346:6 

processes 16:18 18:2 

330:17 346:21 362:20 

processing 139:5,14 

228:9,10,14 264:11 

264:12,18 268:16 

269:9,16 294:10 

321:7 349:7 352:15 

processor 21:10 

341:20 

processors 13:22 

175:17 342:1 

Procure 344:6 

procurement 69:14 

382:13 

produce 2:6,13,14 6:17 

12:15 23:12 28:3,15 

28:21,22 30:8 31:11 

31:16,22 37:6 40:22 

46:14 69:14 70:13 

104:11 118:14 136:5 

138:6 171:13 183:14 

211:4 218:8,17 

239:14 269:17 278:3 

343:6,21 345:17 

346:11,14 348:6,13 

349:4,5,11 351:10,11 

352:15 355:9 359:7,8 

366:3 367:11,14,15 

368:14 371:1,4,5,9,16 

372:22 383:7 

produced 25:21 96:9 

144:11 

producer 57:19 58:3 

63:11 102:17 115:11 

156:22 163:6 215:3 

223:20 226:6 255:9 

341:19 

producer-driven

209:19 

producers 41:22 65:9 

101:20 102:1 103:15 

104:7,14,21 105:20 

106:3 111:1,2 115:12 

124:4,5 135:3 137:9 

146:2 155:1 158:15 

160:22 199:2 210:1 

212:9 213:3,22 216:7 

224:2,15 244:1,22 

245:3 290:9 342:1,21 

350:16 367:9,9 

380:13 

producing 64:3 147:14 

372:20 

product 21:9 24:1,7 

25:21 27:2 34:17 37:8 

37:12,15,19 38:3,22 

42:4,4 51:21 56:4 

57:4 63:13,14 64:2,3 

64:10,10 66:7,18 

69:10 71:5,17 73:3 

88:11 96:8 103:11 

105:15 129:12 132:21 

134:11,18 135:3,15 

143:1 144:9 158:21 

161:12 171:11 172:6 

172:11 175:11 186:11 

204:8 205:22 206:5,8 

216:10 224:8 242:10 

269:21 280:13,15 

362:6,7,19 363:2,4 

365:21 366:14 371:2 

371:2,17,19 372:20 

373:2 377:21 378:21 

384:14 385:11 386:9 

386:10,11,13 

production 3:6 7:8 8:20 

36:17 42:18 52:1 64:8 

79:7 82:17 86:19 

94:14 99:11 109:8 

116:6,8 118:5,6,13 

125:14 146:3,13 

149:18 152:22 153:9 

153:10,22 154:17,20 

157:4 158:14 171:5 

208:16 228:7,13 

239:21 277:4 280:9 

317:6 351:9,11 

357:16 362:19 367:2 

367:8 382:9,10 

productive 119:1 

productivity 118:21 

126:2,9 154:2 

products 11:18 14:1 

25:16 32:11 41:22 

45:14 95:7 96:22,22 

97:1 104:8,10 105:9,9 

106:7 107:4 109:16 

110:2 113:20 114:5 

114:14 115:4 117:5 

120:18 123:7,14 

124:7 125:22 126:3,9 

126:13,18,19 128:13 

129:1,4 131:14 132:2 

134:20 136:5,9,10 

137:8 138:5,14 139:6 

160:11,15 162:16,17 

174:7 180:5,8 204:6 

365:19 378:14 

Proficiency 178:6 

profile 351:21 

profit 157:1 321:17 

328:20,21 

profligate 148:13 

programmers 296:6 

programs 6:17 9:11 

22:19 30:15,22 31:6,9 

31:12 32:3,7 39:1 

41:13,20 48:11 54:14 

67:7,21 72:9,22 75:21 

80:12 81:6 83:5,20 

85:5 86:18 88:15 

97:10,14 154:14 

157:12 164:10 165:1 

168:1 229:13 256:14 

256:18 306:18 363:1 

progress 20:3 143:19 

163:21 369:3,4 372:9 

progressive 66:6 

prohibited 161:7 

prohibiting 70:4 

prohibitive 96:6 

project 184:18 238:6 

250:12 319:4 329:21 

334:6,7 

projected 93:12 

projects 68:21 198:16 

319:18,21 320:15 

322:14,16 329:21 

334:22 338:12 343:4 

prolific 329:18 

promise 133:3 

promote 68:17 

promotes 71:19 

promoting 68:9 

promotion 8:15 31:8 

97:2,10 

promotional 97:21 

proper 135:16 

properties 318:15 

322:4,20 323:1,2,3 

property 129:21 327:4 

334:2,4 

proportion 262:2 

proportional 171:7 

proportioned 174:19 

proposal 60:17 304:15 

305:13,15,21 370:7 

proposals 48:19 359:10 

360:1 

propose 285:10 304:16 

proposed 33:10 53:18 

62:9 257:5,10 282:4 

284:12 304:6 339:3,4 

339:15 

proposing 313:22 

proprietary 19:16 

protect 35:7 94:10 

113:2 129:20 295:6 

342:21 385:15 

protected 155:14 

protecting 8:16 64:12 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
425 

98:11 131:20 311:4 

protection 98:8,14 

126:17 142:6 166:2 

195:9 349:6 381:4 

protectionism 129:22 

135:20 

protectionist 32:10 

protective 365:4 

protects 71:21 

protein 135:14 

prove 160:21 337:11 

351:8 

proven 23:16 158:8 

provide 8:2 27:18 73:4 

100:14 157:5 164:19 

165:22 166:4,12 

167:13 195:22 196:3 

196:5 197:13 203:12 

212:20 225:3 239:16 

257:8 258:12 270:20 

282:7 287:9 294:21 

301:15 318:6,13 

321:17 322:3 329:4 

331:10 332:9,10 

333:15 382:14 393:9 

394:10 

provided 39:17 92:16 

96:2 

provides 84:18 166:9 

178:17 

providing 248:13,16 

336:9 

provinces 37:1 

provision 58:6,8,14 

59:12 60:8 73:5,7,13 

73:18 77:15 95:18 

277:15 286:6 352:7 

provisions 33:11 41:19 

57:1 72:21 78:6 82:5 

87:8 120:22 191:7 

309:22 

prudent 336:17 365:8 

Prune 55:5 

public 3:3 11:3,7,14,15 

12:11,12 17:8,14 24:3 

27:17 43:5,8 62:11 

90:3,4 93:11 96:7 

154:12 155:11 184:5 

192:19 199:6 217:21 

218:14 226:15 254:17 

285:6 287:16 308:9 

339:7,16 340:8 

344:22 366:13 

Public's 11:15 

public-private 14:10 

16:16 

publication 287:16 

publicly 62:14 155:6 

183:13 186:21 187:21 

199:6 

publish 198:21 205:10 

208:19 210:8 211:20 

217:5,6 299:22,22 

published 210:17 212:2 

212:18 217:21 240:7 

240:8 277:2 300:1,10 

319:12 

publishing 210:22 

212:22 

pull 124:22 143:3 

186:18,22 245:6 

380:9 387:12,20 

388:5,6 

pulldown 246:18 

pulled 56:20,21 57:9 

61:2 192:1 351:4 

purchase 95:14 96:8,11 

172:9 382:3,5 

purchasers 107:10 

purchases 24:2 52:13 

80:16 383:11 

purchasing 174:13 

382:4 384:11 

purple 133:8 

purpose 6:13 

purposes 260:16 273:3 

push 58:17 60:14 77:2 

85:1 286:10 323:6 

pushback 154:8 334:13 

pushed 129:2 

pushing 56:17 355:3 

put 8:13 9:21 20:20 

32:10 33:16 42:15 

44:7 48:18,19 49:19 

60:13,17 66:11 71:3 

79:9 81:6 88:11 90:21 

92:14 93:7 101:12 

113:22 114:13 121:18 

128:15 146:1 173:2 

191:18 198:20 203:22 

220:22 226:8,14,22 

228:16,22 229:1 

242:10 243:11 246:11 

247:22 254:18 256:2 

264:12 308:9 309:22 

310:14 321:22 325:5 

328:16 330:19 331:19 

338:1,3 339:8,12,21 

340:2,9 353:11 

358:16 360:17 374:7 

382:1 389:2 391:1 

puts 268:11 

putting 4:7 34:16 41:22 

64:7 120:17,18 

148:17 153:2 228:17 

229:14 335:20 

pyrethroids 176:18 

Q

QA 187:22 

QA/QC 177:17 

QCEW 201:19 215:7 

229:2 

qualified 336:16 

qualifies 258:6 

qualify 273:20 289:12 

332:20 333:20 

quality 38:21 88:2 

165:22 166:2 176:19 

177:17 189:18 195:9 

199:16 247:1 349:9 

351:6,21 359:4 360:8 

quantification 177:1 

178:4 

quarter 228:18,21 

229:13,14,17 230:11 

230:12 231:8,11,21 

232:7,8 233:15 234:7 

235:5,6 261:7 

quarterly 177:21 

201:15 210:16 226:12 

226:17 227:3,6,8 

230:1 231:7 232:22 

235:20 240:22 

quarters 212:19 217:13 

219:8 243:18 

queen 339:12 

queries 180:15 181:3 

query 180:10 

question 34:3 59:7 63:7 

70:6,22 79:1 82:12,20 

87:12 92:9 100:21 

116:11 122:4 141:2 

142:3,15 143:20,21 

146:12,19 150:8 

152:4 180:2 185:10 

186:3 192:22 194:4 

200:8 223:13,15 

225:11 235:2 238:11 

238:12 240:5 243:15 

245:9,19 247:17 

252:8 254:5,11 255:2 

257:14 259:17 274:5 

275:10 277:9 279:8 

290:19 292:10 293:1 

294:13 314:13 323:12 

327:7 329:7 330:3 

334:9 335:6,19 

353:16,20 357:17 

372:6 375:6 377:2,11 

387:22 394:18 

questioned 283:11 

questionnaire 219:13 

220:19,21 238:3,16 

239:11 

questions 4:20 6:4 

20:10 21:17 27:5 34:1 

41:7 45:15 49:6 71:1 

91:16,19,20 92:2 93:1 

98:16,20 139:2 

152:12 184:13,14 

203:12 207:7 213:10 

213:12,16 215:10 

226:18 234:14 237:6 

250:22 312:2,9 

313:21 317:22 318:3 

323:11 361:9 372:5 

380:10 

quick 11:5 26:19 43:10 

76:17 98:18 152:20 

163:13 203:15 213:8 

241:4 272:16 286:9 

298:1 332:4 335:19 

394:18 

quickly 36:3 250:6 

298:1 306:5,8 

quilt 34:13 

quite 62:14 70:20 

135:10,11 146:10 

181:8 191:5 261:4 

263:11 316:15 341:7 

345:3 355:11 364:11 

372:2 379:11 

quota 98:8 

quotas 98:14 120:6 

quote 107:19 345:19,20 

quote-unquote 56:4 

quotients 233:2 

R

R 1:10,12 

radar 193:4 

radio 15:13 

radiological 189:20 

radish 170:10 

raise 81:12 82:7 89:1 

277:9 293:13 

raises 277:9 

raising 293:6 

ramifications 94:8 

ramp 146:2 

rampant 11:22 

ranch 262:1 

ranchers 208:18 

ranches 239:13 

ranching 262:1 

random 327:18 

randomly 171:10 

range 8:5 132:1 177:7 

241:9 277:4 353:3 

ranged 7:19 

ranges 241:4 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
426 

Ranking 83:10 

rate 39:14 209:12,13 

212:3,7,18,20,22 

213:1,5 218:8 219:3 

219:17,18 220:2,16 

220:19 221:2 231:5 

237:9 239:20 241:3 

242:14 244:10 245:5 

251:4 261:12,13 

268:4 286:20 288:18 

289:1 295:5 299:7 

300:6,9 303:6 309:5,6 

310:15 318:12,22 

319:6 364:2,3 

rated 171:11 

rates 149:3 210:18 

212:13,15 217:7 

241:2 243:3,6,11 

251:3 298:4,19 299:4 

299:8,9 300:3,10,13 

300:18 319:3 364:17 

ratio 219:16 262:21 

RD 315:17 329:20,21 

re-contact 247:7 

re-evaluate 349:22 

re-evaluation 343:16 

reach 5:11 90:12 91:17 

172:22 173:4 238:19 

394:19,22 

reached 120:21 212:9 

244:8 

reaching 173:22 363:11 

react 76:17 

reaction 282:11 

read 4:15,16,18 11:11 

22:4,5 27:22 49:19 

92:11,15 95:11 99:8 

157:13 197:16 204:12 

204:20 277:1 355:21 

393:3 

READE 1:18 

readily 345:13 

ready 6:3 11:3 49:17 

51:2 176:8 183:19 

327:11 396:5 

Reagan 287:22 

real 11:5 19:10,11 20:2 

54:20 76:17 105:11 

127:16 138:4 140:18 

158:13 159:6,7 162:6 

235:3 272:16 286:8 

298:1,1 368:22 

369:20 

realistic 267:20 

reality 87:20 297:8 

realized 18:8 

reallocate 331:3 

realm 192:17 

reason 14:3 33:7 81:11 

88:4 131:1,3 135:6 

142:22 188:22 193:3 

208:22 239:19 259:6 

269:12 281:14 342:8 

369:18 372:18 

reasonable 159:16 

322:4 333:15 335:3 

336:21 376:16 382:14 

reasonably 321:17 

381:17 

reasons 65:10 104:18 

115:11 260:7 271:16 

349:14 354:9 374:11 

reauthorization 73:9 

82:13 83:16 86:9,22 

87:9 

reauthorized 83:1 

recall 346:14 372:12 

recap 7:4 

receipts 102:10 

receive 12:12 27:20 

37:8 238:2 

received 11:14 21:13 

27:17 189:3 

receiving 221:15 

recess 83:19,19 396:2 

recession 118:8,10 

122:12 149:11 316:17 

316:18 

reckon 280:6 

reclassify 156:12 

recognize 96:4 126:1 

159:14 215:4 223:20 

356:15 358:21 370:16 

recognized 234:20 

318:19 345:12 362:10 

362:15,16 

recognizes 94:5 153:9 

354:7 359:18 

recognizing 65:4 352:4 

360:20 

recommend 25:18 52:4 

156:5 160:10,14,18 

161:9,15 

recommendation 10:2 

40:10 92:16 95:12,21 

97:3 98:7,10,13 161:3 

196:7,15 204:13,21 

205:20 206:9,18,20 

208:1 211:10 212:7 

342:5 389:5,11 

recommendation's

49:3 

recommendations 4:8 

5:6 6:15,21 7:22 8:14 

8:21 10:12,18 73:14 

91:6,9 94:13,19 

153:15 155:4 156:2 

157:14 159:12 163:14 

163:17,21 164:3,20 

165:7 181:7 196:20 

196:21 271:2 274:10 

342:11 348:17 382:1 

382:3 383:19 388:15 

388:22 389:10 

recommended 379:6 

recommends 97:4,17 

156:12 

reconsidered 349:16 

record 12:11 99:15 

201:10 250:14 290:14 

290:17 297:10 315:1 

315:11 396:7 

recording 166:6 

records 232:12 306:14 

371:3 373:3,8 376:12 

376:19 

recourse 282:4 

recovery 122:12 

recruiters 258:19 

recruiting 301:8 

recruitment 268:10,21 

290:22 291:14 303:17 

303:18 304:3 

recurring 276:14,14 

red 108:2 115:8 126:5 

146:21 

redirect 75:21 

redirected 221:13 

reduce 55:15 136:22 

137:1,7 138:10 160:3 

222:7 340:2 

reducing 57:3 268:8 

reduction 110:6 

reenter 22:15 172:17,19 

196:1 

reestablish 51:19 

refer 209:21 

reference 210:5,5 

225:19 240:12 260:15 

296:21 299:17 

referring 223:18 

refine 91:8 

refined 205:17 

refining 388:15 

reflect 171:11 

reflective 221:2 242:11 

245:5 

reform 215:17 

reforms 48:20 130:10 

refreshing 247:15 

refurbished 326:19 

refurbishing 326:16 

refused 58:14 

regarding 169:4 198:19 

regardless 18:9 

regards 192:9 284:8 

Regency 1:9 

region 25:13,13 138:14 

240:20 241:10,18 

242:2,3 354:3 359:11 

359:12 

regional 34:16 67:22 

68:12 74:16,20 77:13 

78:16 222:12 347:11 

347:12 363:3 369:10 

369:11 

regions 171:6 210:9 

211:19 212:4 241:15 

354:15 359:10 

register 246:13 254:18 

283:1 319:12 368:1,5 

368:6 

registered 43:5 196:22 

registration 160:13,18 

160:20 161:17 162:4 

166:11 178:14,20 

195:20 196:22 

registrations 160:10 

regular 230:15 308:4 

regulated 13:16,17 

15:19,20 16:7,13,17 

17:11,19 18:14 20:4,6 

25:8 26:4 307:1 344:4 

368:10 

regulating 16:9 17:18 

18:8 19:12 

regulation 3:20 44:13 

59:5 64:15 276:2 

288:21 306:22 324:11 

324:12,15 364:5 

regulations 7:21 24:18 

24:19 42:17 45:10 

288:6 324:10 348:19 

regulator 16:1,3,4,17 

17:7,10 18:1,6,17 

23:8 25:7 26:6,16 

regulatorily 275:7 

regulators 20:4 

regulatory 15:6,18 

20:16 44:10 136:3 

161:12 256:21 271:9 

274:12 275:8 277:14 

304:5,9,11 308:3 

349:10 350:22 379:7 

379:17 383:22 

rehab 329:21 

rehabbed 329:22 

reintroduced 58:16 

reiterate 95:8 

reiterating 41:5 

reject 33:13 258:11 

280:1 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
427 

rejected 33:12 35:13 

rejoining 150:14 

relate 23:13 104:3 

related 52:21 56:2 

114:3 116:19 146:17 

193:5 205:22 342:22 

371:16,17 

relates 22:6 

relating 192:9 193:14 

relation 239:6 343:20 

relationship 116:22 

163:19 190:15 194:14 

195:18 

relationships 369:21 

relative 115:7 

relatively 115:12,22 

131:22 326:4 

relativity 199:1 

release 241:1 

released 167:18 187:21 

339:4 

reliable 122:19 214:17 

reliant 51:8 

rely 206:6 373:2 

relying 113:9 254:7 

365:5 377:22 

remain 200:2 

remaining 5:20 

remains 139:13 

remarkable 88:13 

remarks 12:17,21 101:6 

remember 6:10 7:9 

29:10 54:4 119:8,9 

137:12 209:17 248:17 

285:21 344:11 366:21 

remembered 345:2 

remind 106:1 

reminded 144:1 

reminder 114:22 

163:14 

reminding 279:17 

remiss 341:8 

remodel 327:3 

remodeling 326:22 

remove 204:14,19 

removed 74:17 115:1 

removing 175:13 

renew 305:8 

renewed 83:7 160:12 

160:20 

rent 318:14 

rental 321:18 323:18 

338:4 

rep 60:7 

repacking 37:9,13,14 

37:18,18 

repair 273:17 320:11 

332:18 

repeat 179:5 

replace 178:21 366:3 

replaces 195:14 

replacing 89:11 

replicate 306:18 

reply 254:8 

report 3:4,6,9,16 15:4 

17:20 18:11 21:2 

22:12 26:15 28:6 

102:17 117:17 118:1 

185:21 206:22 212:1 

214:13 251:10 291:14 

305:5 355:21 376:7 

reported 177:12 182:4 

231:1 234:5 236:5 

245:1,5 246:3,9 

reporting 15:20,22 

16:13 18:16 205:8 

213:7 228:3,21 236:1 

251:16 336:2 

reports 160:6 177:22 

182:11 188:21 227:9 

240:22 

represent 39:11 171:5 

194:11 325:15 

representative 12:20 

43:8 71:20 165:22 

171:2 174:12,17 

178:18 179:22 198:9 

Representative's 100:7 

representatives 215:16 

representing 28:10 

202:7 238:3 

represents 381:22 

Republic 106:19 

reputable 380:4 

request 156:3 204:13 

204:21 205:14,20 

206:9 257:1 258:15 

requested 176:14 360:2 

requesting 330:10,11 

requests 95:16 97:7 

181:2 204:1 

require 96:7 161:15 

182:8 251:3 302:16 

required 57:2 191:1 

291:13 354:20 368:1 

368:4,6 

requirement 5:19 15:19 

257:6 320:21,22 

326:21 350:22 358:6 

383:2,21,22 

requirements 15:6,22 

16:13 18:16 20:16,17 

95:3 163:7 342:3,19 

343:1,17 349:10,13 

351:16,17 354:4 

358:7 379:6 382:21 

384:2 

requires 185:17 301:14 

requiring 96:10 359:11 

research 8:22 47:22 

153:12,16,17,21 

155:5,7,14,19 156:5,9 

156:11 160:21 186:18 

192:21 204:22 212:8 

213:2 220:13 224:6 

255:14 343:4 359:9,9 

365:3 

researching 224:6 

resembles 174:13 

reservoir 356:8,8 

residence 301:17 

resident 321:10 

resides 334:6 

residue 158:17,19 

159:1,16 161:6 166:1 

166:15 167:12 175:21 

177:6 179:14 182:6 

190:5,19 195:4,7 

residues 165:21 166:5 

177:4 179:3,9,17 

180:19 184:20 190:16 

191:8 194:18 

resolve 180:22 

resort 336:17 

resource 138:4 344:16 

resources 372:11 

respondency 221:21 

respondent 219:5 

239:15 243:10,10 

respondent's 219:12 

respondents 209:20 

212:11 221:4,7 

238:19 239:3 242:16 

responses 11:16 

responsibility 341:20 

365:18 

rest 106:15 113:4,6 

117:12 123:17 135:12 

350:12 357:22 365:12 

restaurant 387:4 

restrict 32:9 145:2 

restricted 96:20 

restricting 116:2 

149:13 

restrictions 33:14 

97:16 113:17 114:18 

131:5 135:8 

restricts 33:9 

result 213:2 

Resulted 275:19 

resulting 161:18 170:13 

177:11,18 

results 167:16 174:3 

resumed 99:15 201:10 

315:1 

retail 38:4 39:6 62:4 

68:1 174:2,15 228:10 

252:4 380:8 382:2 

387:2 

retailer 379:5 383:4,21 

retailers 64:8 71:17 

72:9 77:1 191:12 

361:14,21 362:5,10 

380:2,11,12 381:2,22 

382:20 

retained 266:8 

retaliated 114:1 

retaliation 114:3 117:4 

retaliatory 32:18 

113:20 115:3 

retired 321:2,8 

retiring 83:13 

retool 91:8 

returning 291:22 

309:22 310:2,3,9 

returns 153:20 

revenue 125:1 271:1,5 

325:14 

review 49:4 156:6 

166:11 168:14 178:14 

195:21 226:14 346:6 

347:20,21 360:14 

reviewed 167:14 

177:13 

reviewing 276:20 

reviews 161:16 

revisions 95:21 

Revolution 108:7 

RFID 23:11,15 24:9,17 

25:17 

rice 105:6 126:12 

170:10 

rich 110:17 128:3 149:1 

149:1 

Richard 1:13 42:6 75:4 

richer 130:8 

Richmond 1:9 

rid 133:15 269:14 

292:13 

ridiculous 363:6 

rigor 363:16 

ripple 79:21 81:14 

risk 26:9 132:15 156:17 

158:3,15 159:6 

166:10 169:5 174:9 

177:9 178:16,18 

195:8,12,19 358:10 

358:17 365:20 366:5 

366:12 

risk- 360:19 

risk-based 359:3 

riskier 356:16 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
428 

risky 366:8 

road 249:9 280:12 

341:11 

Robert 2:6 46:3,5,13 

53:15 55:5 90:2,6 

Roberts 83:9,13 393:20 

Robison 2:16 201:17 

201:17 

robust 177:17 183:17 

192:21 193:19 205:1 

355:14 

role 225:15 287:8 

341:19 

rolling 200:14 

romaine 350:15 365:7 

375:22 376:1 377:13 

386:17 

roof 332:19 

room 1:9 72:3 138:17 

191:6 199:3 214:22 

324:8 328:17 339:11 

339:13 340:10 

root 165:3 

roots 100:11 

Ross 121:21 

rotated 169:6 170:5 

171:22 193:20 

rotating 171:22 

rotation 169:9 173:2 

rotten 12:9,10 

rough 373:20 

roughly 5:13 238:5 

242:15 

round 63:20 67:11,12 

67:13 81:2,5 98:6 

172:15 237:2 308:21 

322:9 

route 23:12 

routinely 166:16 182:4 

182:10 

row 124:6 153:18 

157:17 

rub 351:14 

rule 204:15,20 205:22 

218:9,12 257:5,10 

269:2 276:18 277:2,3 

284:12 301:14 313:22 

339:3,4,9,15,22 343:7 

343:21 344:7 349:12 

351:3,15 352:18 

353:11 354:10,18,19 

354:20 355:4,6 

360:12,18 361:2 

367:22 368:4,8,15 

371:5 383:7 

rules 90:14 113:8 

282:16,17 335:8 

336:13 340:12 344:10 

385:14 388:2 393:20 

rules-based 130:5 

run 68:15 85:18 132:15 

148:14 180:9 203:14 

250:1 314:13 338:8 

rundown 213:8 

running 175:9 237:3 

248:14 249:17 254:9 

255:4 256:13 317:3 

390:8 

runs 177:18 

rural 2:6,11 30:6,10 

102:18 312:4 315:12 

315:13,14,15,16 

316:10,10,12 321:4 

S

S.B 58:6 

Sacramento 73:22 

sacrifice 41:2 

sad 254:15 

safe 120:9 226:15 351:5 

362:7 384:6 

safety 3:17 7:7,14 24:3 

135:8 160:16 341:5 

341:21 342:3 343:7 

343:21 344:6,21 

347:11 348:7,12,19 

349:11 355:9 356:14 

359:8,8 360:15 

368:15 369:10 371:5 

379:6 381:1,10 

382:15,18 383:7 

392:15 

safety-related 56:6 

sake 16:20 308:21 

sakes 297:15 

Salad 31:18 

salads 32:1 

salary 252:22 

sales 102:14 111:18 

112:3,12 113:1,13 

208:13,14 361:18 

Saluda 243:8 

Sam 250:7 

sample 168:9 173:13 

175:2,10,11 176:4,12 

177:19 187:12 211:14 

211:15 217:12 222:2 

222:6 238:1 245:2,3 

291:18,19 

sampled 167:8 171:16 

171:21 172:21 242:16 

samples 161:6 167:11 

170:13,16,21 171:8 

171:18 173:8,10,11 

173:16,21 174:18,21 

175:3,6,16 176:7 

179:3,8 181:13 

182:14 183:3,4,6 

187:15 188:8,12 

189:22 190:19 197:12 

197:16 222:8 

sampling 166:6 167:10 

168:5,11,12,13 169:4 

170:4 171:2,10 172:1 

172:2,16,18 173:7,7 

173:20 174:12,18 

175:1 198:10,12,13 

198:15 209:22 343:3 

346:5 

sand 159:15 

sanitary 55:17 57:1 

78:6 351:6 

sat 267:8 

satellite 355:14 

satisfying 331:3 

saturated 357:5 

Saudi 147:7 

save 149:2 385:17 

savings 149:3,9 

saw 13:8 116:1 123:5 

181:7 200:13 212:6 

241:16 264:8 340:6 

saying 69:18 81:9 

89:16 93:7 117:17 

122:7,17 133:14 

143:7 145:6 146:17 

227:13 241:11 242:18 

243:17 247:8 250:2,3 

267:7 268:12 278:2 

308:9 309:21 317:14 

341:3 364:13 378:15 

386:6 392:15 

says 59:5 144:20 

158:20 235:18 236:6 

295:11 298:22 339:9 

345:19 355:1 389:4 

392:16 

SBA 336:7,18 

SBA's 336:12 

scalable 18:19,21 

scale 24:16 272:9 

scan 241:5 302:21 

schedule 91:15 99:3 

151:21 314:21 390:9 

school 31:13 41:13,20 

67:6,7,8,21 72:22 

73:17,22 85:4,8 86:20 

87:7 95:6,6,13 159:8 

207:9 253:15,16 

267:2 317:7,8 

schools 31:18 32:1 

73:17 84:7,8 86:15 

96:2,7,10 

science 44:10 164:6,11 

165:3 348:11 354:11 

354:13 360:4,5,21 

363:17 364:3 

science-based 342:14 

360:20 

scientific 351:2 

scientifically 57:3 

scope 81:6 234:4 246:5 

270:12 

screaming 241:19 

242:2 

screen 92:14 200:14 

screw 111:12 

SCRI 156:9,13 

seafood 294:10 

seamlessly 16:10 19:17 

search 184:6 

searches 184:5 

season 64:13 71:18 

160:16 185:2 236:17 

264:6 271:15 292:1 

365:15 

seasonal 34:15 35:2,3 

35:8 77:15 98:7,14 

124:9 236:14 237:3 

272:20,22 276:15 

278:9 318:8 

seasonality 33:10,14 

34:6,11 35:14,16,18 

36:16 37:4 58:6,14 

59:11 60:8 70:7 

seasons 64:12 

seat 222:13 366:21 

seats 315:5 

second 12:13 46:17 

86:7 101:9 146:12 

182:17 217:15 225:7 

234:10 268:16 274:2 

286:21 301:3 325:7 

386:20,21 394:15 

second- 39:20 294:16 

secret 62:13 

secretary 6:16 40:12 

46:22 49:4 60:4 95:17 

95:19 97:6,7,19 99:21 

100:8 144:22 156:3,6 

157:14 166:3 205:14 

205:16 206:10 271:7 

358:3 

Secretary's 204:13 

section 11:7 84:13 

95:14 144:18 157:19 

320:14 

sector 14:13 100:7 

131:20 150:3 227:19 

240:2 253:1 254:22 

268:5 337:18 

sectors 100:12 103:15 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
429 

105:3 129:8 149:16 

security 108:21 117:18 

117:19 144:2,16 

145:1 286:2 301:6 

341:21 

sediment 356:7 

seed 161:22 162:3,7 

seeing 32:20 38:11 

69:21 80:4 89:15 

116:5 140:19 242:13 

263:9 370:14 

seek 32:7 161:16 

seeking 87:17 

seen 31:7 48:12 79:17 

93:18 110:4 112:3 

114:3 186:14 282:12 

291:20 334:12,16 

347:6,14 350:8 375:4 

379:8 

sees 231:14 

segue 236:2 

selected 171:10 

selection 169:10 

181:22 

selects 169:3 

self- 125:13 246:22 

self-employed 252:21 

self-explanatory

206:17 

self-identify 246:15 

self-introduce 256:7 

sell 64:9 102:15 111:10 

112:13,14,15 124:8 

127:20 131:17 135:9 

135:10 137:18 147:9 

316:18 

selling 102:22 373:20 

sells 345:16 

semiconductors

128:14 

Senate 83:8,9 

Senate's 49:17 

Senator 83:8,12 

send 52:9 88:11 114:8 

124:6,7 183:20 

302:19 305:21 309:20 

313:1 375:13,19 

senior 140:7 

sense 128:4 134:22 

135:1 236:7 237:12 

355:7 378:12 389:8 

sensitive 159:18 

sent 141:1 376:14 

391:17 

separate 26:14 87:19 

220:11 282:19 334:2 

separated 175:17 

separately 249:16 

separating 205:6,9 

September 50:3 58:1 

73:11 83:18 110:14 

228:19 334:21 395:4 

395:15,19 

series 61:17 

serious 141:8 

serve 59:19 99:20 

100:8 168:12 288:7 

serves 215:5 

service 2:6,11,12 10:6 

10:7 90:15 100:6 

165:2 171:1 180:20 

207:13 224:6 248:13 

248:16 249:13 271:1 

271:5 315:15,17 

386:19 387:1 

services 9:18 10:4,8 

147:2 202:9 270:10 

270:12 278:1,4 338:1 

servicing 263:11 330:5 

331:13 

serving 321:2 

servings 84:1 

session 46:18 

set 26:14,22 48:19 90:8 

90:13 108:20 109:3 

141:14 177:20 212:12 

212:16 237:16 270:20 

271:22 287:17 298:16 

333:6 337:10 

settle 53:10 

settlement 141:16 

142:14 

seven 122:9 232:8 

269:13 303:12,13 

343:10 

Seventy-two 114:13 

share 16:22 49:10 

62:14 105:4 123:14 

138:13,16,19 146:13 

196:10 197:22 198:5 

272:11 299:20 330:11 

330:12 341:4 357:14 

377:19 391:14 

shared 9:12 340:22 

347:18 348:17 

sharing 152:14 181:9 

198:3 360:10 

she'll 348:2 

sheep 277:4 

sheer 236:15 

shelves 388:5,6 

shift 52:1 349:18 

shifting 234:13 

shifts 258:16 

shiga 356:2 

ship 63:12 175:4 206:7 

shipped 167:11 173:16 

shipper 63:11 

shirttail 128:3 

shoe's 53:21 

shop 66:18 

shopper 373:14 

short 80:11 107:20 

134:9 199:5 

shortage 339:6 

shortened 57:22 

149:17 

shorter 172:16 

shortly 9:20 53:5 

shot 193:4,11 

show 17:20 81:8 179:2 

180:16 195:15 

showed 263:14 376:22 

showing 161:6,9 

244:13 281:14 

shown 24:10 167:21 

168:7 175:14 

shows 102:9 106:9 

108:1 110:19 111:6 

113:19 114:4 115:6 

118:4 119:7 121:19 

122:3 123:13 124:20 

126:5,22 127:7 128:9 

129:4 133:1,9 136:6 

136:18 146:21 247:6 

262:13 365:3 

shrinks 149:10 

shut 128:17,18 

shutdown 285:12,13,21 

286:4 

sick 374:6 387:19 

sicknesses 386:18 

side 15:1,2 18:6 66:17 

129:19 140:14 150:13 

150:15 151:5 181:19 

228:14 311:13 352:12 

362:15 374:14 378:20 

379:18,20 

sides 77:21 150:17 

331:4 

SIEVERT 1:18 372:6,8 

375:8 384:10,13,19 

385:9 386:2,5 387:7 

sight-unseen 55:17 

sign 103:20 110:7 

143:18 

signal 304:21 376:20 

signed 58:12 

significant 50:19 85:4 

88:18 95:22 153:22 

241:19 

significantly 96:3 

similar 34:17 117:15 

125:11 318:15 333:12 

356:5 359:3 

similarly 295:13 

simple 229:9 254:15 

325:3 384:3 393:22 

394:2 

simplistic 189:8 

simply 179:19 197:22 

365:7 

simultaneous 44:6 

177:1 191:22 255:11 

308:5 309:12 311:9 

311:11,17 312:11,15 

313:14,19 314:11 

326:8 327:10 333:1,3 

334:17 337:6,13 

338:10 348:21 380:17 

384:18 386:1,4 

387:15 393:5,18 

394:9 

simultaneously 58:19 

161:18 

single 134:11 316:11 

354:14 376:17 

sir 57:14 187:9 235:1 

235:21 269:14 274:7 

308:18 329:15 

sit 136:21 159:8 343:10 

site 171:12 173:16 

176:5 180:14 184:1,3 

226:3 251:8 282:17 

299:2,2 

sites 159:17 171:9,10 

171:17 173:20 174:14 

283:3 333:22 334:1 

335:9 359:12 

sits 105:16 

sitting 10:13 143:18 

159:9 295:18 

situation 129:17 161:22 

289:6 364:7 369:16 

370:12 374:17 376:3 

381:8 

situational 369:8 

situations 79:3 110:18 

280:7 

six 111:9 118:2 119:7,8 

119:14,19 122:9 

232:9 244:19 256:16 

284:5 323:1 340:9 

six-digit 230:5 

size 18:19 171:8 175:2 

175:10 211:14,15 

216:3 222:6 227:20 

243:14 265:1 

sizes 6:21 

Skeleton 341:12 

skeptical 278:11 

skewing 191:15 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
430 

skilled 296:17 297:1 

skip 302:9 

skipped 112:9 364:9 

slice 128:6 

slide 102:7 103:13 

104:18 105:2,22 

107:11 109:22 110:10 

110:19 111:4 112:8,9 

113:14 114:21 116:12 

117:2,14 119:6,6 

123:12 124:12,13 

125:7 127:5,16,16 

128:9,22 129:4,12 

131:12 132:3 133:1 

135:9 136:14 143:20 

143:22 146:18 148:14 

166:19,22 167:21 

168:15 170:19 175:5 

180:8,17 181:9,17 

182:12,17 183:1 

184:12 207:10 261:11 

287:5 315:22 342:4 

344:5 346:8 364:9 

slides 146:15 169:21 

183:11 260:14,14 

281:15 

slightly 111:20 241:5 

slipping 141:7 

sliver 127:13 254:21 

slowly 133:11 

slows 116:4 

slug 88:12 

small 15:10 18:21 33:20 

80:22 85:6 124:21 

149:4,4,4 186:11,13 

187:11 234:8 316:16 

317:4 332:17 343:4,5 

363:2 

smaller 155:1,22 

171:17 253:11 320:9 

361:17 362:1 

smart 71:8 277:17 

smarter 88:18 

smelled 317:9 

SMITH 1:19 139:4,11,17 

152:19 180:2,4 

187:18 188:1,6,16 

194:13,21 196:3,18 

198:17 269:15 270:5 

270:16 271:11 272:14 

282:14 393:15 

smokable 13:22 

snack 84:19 

snap 132:11 

snapshot 263:13 

300:20 

Snickers 30:18 

snippet 351:4 

societies 348:11 

SODs 176:5 

softly 121:16 

software 20:12,17 

21:22 22:4,19 

soil 11:19 

sold 138:14,18 191:13 

316:16 

Solicitation 319:10 

soliciting 359:9 

solid 206:14 244:21 

389:11 

solution 15:18 39:17 

40:5,7,13,18,21 41:5 

41:6 53:18 54:16 70:3 

70:8 71:7,10,14 75:1 

80:9 81:2 89:5,10,22 

90:1 355:18 

solutions 47:9,13 53:16 

55:8,11 57:22 60:9 

71:9 87:17 94:1 

solve 113:10 130:20 

somebody 54:12 92:10 

144:14 190:17,20 

204:2 224:18 231:14 

235:5 236:17 237:1 

246:1,2 284:13 

315:20 331:16 353:7 

380:1 382:11 384:14 

385:12,18 

somewhat 14:20 

114:15 183:8 

Sonia 2:4 6:6 

soon 360:1 

sorry 21:19 44:2 112:8 

127:9 129:13 150:20 

152:10 164:5 168:15 

168:22 197:15 219:6 

225:11 244:7 264:2 

272:16 274:7,8 

297:19,22 311:10 

395:1 

sort 26:18 28:19 86:10 

87:19 91:2 100:15,18 

101:5,11 102:3 117:8 

120:5,14 133:2 136:8 

136:11,14 149:20 

190:18 192:20 207:11 

211:7 213:8 228:12 

246:15,19 247:2 

260:3 261:9,14 

264:21 265:19 271:21 

277:6,7 287:18 289:6 

291:16 298:13 302:14 

304:8 305:8 328:5 

337:16 356:5 369:17 

370:11 381:11 382:18 

382:22 383:20 

sorters 211:5 212:4 

216:22 251:9 

sorts 336:13 

sought 96:15 

sound 121:21 

sounds 191:20 225:1 

source 68:1 96:8,22 

102:10 226:2 229:10 

287:21 288:9 308:3 

325:16 353:5,7,18 

356:19 379:2 380:22 

sources 96:14 319:18 

336:22 356:16,17 

357:20 

sourcing 65:8 

South 243:8 282:18 

283:21 

southeast 25:14 74:11 

311:15 

Southeastern 237:1 

southern 78:21 

soy 105:6 116:21 

123:19 129:8,9 

135:10,14 154:3 

160:11 

soybean 193:6 

space 19:8 48:13 55:19 

86:1 163:22 

Spanish 343:8,14,15 

speak 4:19 6:3 27:15 

45:20 46:14 76:12 

92:1 93:1 152:5 

194:16 203:6 218:6 

218:12 221:21 244:5 

250:16 262:17 288:17 

345:6 

speaker 9:3,4 12:19 

27:15 43:5 49:19 

92:22 93:2 99:3 140:7 

140:16 141:3 312:3 

324:21 

speakers 4:18,21 5:22 

6:3 11:8 46:8,16 

91:14,16,18,22 203:5 

203:15 

speaking 44:6 87:4 

191:22 225:19 250:11 

250:16 255:11 308:5 

309:12 311:9,11,17 

312:11,15 313:14,19 

314:11 326:8 327:10 

333:1,3 334:17 337:6 

337:13 338:10 348:21 

380:17 384:18 386:1 

386:4 387:15 393:5 

393:18 394:9 

speaks 157:18 

special 17:12 45:9 

140:1 242:14,22 

specialized 181:3 

220:18 222:16 

specialty 6:15 28:14 

52:12 68:6 153:20 

154:7,22 155:13,16 

155:18,20 156:4,8,20 

160:7,22 165:2 

specific 143:17 145:3 

169:9,17 191:5,7 

215:10 216:11 250:3 

351:17 352:3 

specifically 37:17 

155:4,15,16 162:18 

187:17 202:5 210:12 

213:12 244:5 348:15 

350:9 

specification 383:14 

specifications 324:9 

specifics 101:4 102:5 

specified 167:12 

253:20 

spectrometers 176:22 

spectrum 6:14 223:22 

speed 211:9 

spend 47:20,21 68:14 

86:8 88:2 89:1 106:12 

106:20 112:5 130:16 

152:2 191:18 374:4 

395:14 

spent 39:8 41:21 44:18 

244:18 345:3 

spike 116:1 

spiked 129:2 

spikes 177:19,20 

232:22 

spillover 121:11 

spinach 170:10 

spirit 26:3 

split 207:18 219:9 

spoil 89:13 

spoke 98:13 313:8,17 

345:5 

sponsor 326:13 

spot 44:8 65:16 207:5 

spray 157:21 159:5 

spraying 9:1 

square 171:14 339:14 

339:14 

Stabenow 83:10 

staff 2:3 168:12 177:13 

217:13 264:10 287:7 

288:15 299:1 309:21 

314:14 371:7 

stakeholder 8:1 343:20 

347:12 

stakeholders 172:22 

staking 147:2 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
431 

stamped 175:10 

stand 58:3 73:4 106:8 

376:5 

standard 185:15 211:1 

338:17 353:17,21 

358:4,4,5 363:17 

367:9 385:3 

standardized 166:5 

standards 141:21 145:4 

270:22 337:11 339:11 

339:17,20 340:3 

342:15 346:4 381:1 

382:6,7 383:8 

standing 207:15 395:6 

standpoint 66:3 266:21 

270:18 376:14 379:8 

383:16 395:11,12,13 

stands 383:2 

standup 250:12 

start 5:2 14:5 41:13,14 

81:16 83:20 92:8 

108:8 119:3 140:19 

152:21 157:4 170:21 

192:6 223:8 259:5,8 

271:12 280:3 292:4 

301:7,10 302:14 

305:2 312:5 332:10 

355:19 

started 6:11 56:11 76:2 

84:20 129:3 152:13 

153:2 251:14 267:6 

350:1 358:15 

starting 5:8 116:3 

251:13 360:1 373:13 

starts 108:7 155:19 

225:18 

state 13:7,8,15,17 15:6 

31:6,15 68:11,21,21 

75:7 80:6 92:19 164:2 

167:4,12 173:15 

174:19 177:12 182:11 

189:4 209:2 223:12 

227:14 229:1,5 233:6 

236:20 246:13,14 

253:13 256:17 257:2 

279:18 280:8 283:20 

284:21 287:2 289:9 

293:17,20 294:1,11 

294:13,14,17 298:5,7 

298:8,15,22 299:21 

300:9,19 301:4 

302:11 303:21 305:4 

305:11 318:18 339:11 

339:20 357:12 376:14 

state's 174:20 

stated 35:12 40:10 

statement 37:10 40:5,6 

40:13,14 87:13 90:5 

94:3 98:7 153:8 

204:11 289:5 328:10 

333:17 341:17 394:6 

statements 4:17 21:18 

22:3 45:16 388:16 

states 1:1 50:14 56:20 

68:16 69:4,17 72:17 

78:21 79:16 80:6 

84:21 98:2 109:1 

115:19 144:10,11 

148:7,10 159:22 

160:1 167:2,2,10,11 

167:13,21 168:6,9,9 

168:10,13 171:3,5,10 

174:21 179:7 199:16 

227:9 233:22 239:7 

246:20 253:10,10 

262:13,16 293:6 

294:4 299:12,14 

346:12,15 348:12 

351:10 359:11 367:12 

371:10 

states' 167:7 

statistic 207:12 262:18 

statistical 186:15 216:5 

229:12 238:8 242:8 

352:4,21 

statisticians 186:10 

statistics 2:12 8:10 

171:1 201:14,18 

202:5 208:4 225:16 

226:21 

stats 261:19 

status 3:4,6,9,16 

215:22 258:2 280:20 

388:21 

statute 268:17 270:20 

271:6 290:15,15 

296:13 

statutes 270:11 

Statutorily 303:11 

statutory 270:21 271:5 

274:12 

stay 100:3 324:2 368:14 

staying 78:3 266:8 

314:20 

steel 113:22 114:12,16 

114:22 115:6,8,11,18 

116:2,6,9,15,18,20 

117:21 139:6,10 

144:1 145:11,13,15 

145:16,20,22 

STEM 267:5 

step 34:12 36:7 101:15 

231:3 257:20 282:9 

301:1,3 306:8 349:22 

381:2 

stepping 341:10 

Steve 1:19 74:2 82:19 

84:15 85:9 

Steve's 186:2 

stick 122:18 

sticker 373:7 

stickiest 85:12 

sticks 371:14 

stinky 104:7 

stipulations 324:13 

stitch 373:12 

stocks 148:13 

stomachs 207:6 

stool 257:19,19 

stop 66:18 118:9 139:2 

255:20 266:14 361:8 

374:8 

stopped 279:6 

store 12:9 13:21 67:18 

246:8,9 252:3,4 

368:10 373:14,19 

stored 356:19 358:22 

stores 252:1,7 380:9 

story 108:16 109:17 

112:1 117:3 118:16 

127:22 

straight 154:4 219:3 

224:7 240:17 

strain 354:6 356:7 

strategic 68:6 

strategy 54:6,7,19,20 

strawberries 67:10 

89:12 170:11 

strawberry 24:15 

strayed 263:22 

stream 24:5 25:11 27:2 

221:12 228:11 229:20 

233:12 

streamline 282:5 

streamlined 206:15 

streams 208:5,6 221:10 

236:9 

street 271:10 

strength 149:7,8 215:2 

strengthen 73:13 

102:19 143:6 

strengthened 73:16 

stretch 283:10 

strict 278:6 

strictly 277:8 

stride 18:14 26:13 

strike 18:2 95:22 

striking 118:12 

strive 385:5 

strong 18:10 57:1 

102:17,18 143:15 

145:13,14,16,21 

266:2 288:4 

strongly 16:15 19:20 

35:17 160:9 

structure 62:21 223:10 

357:11 362:12 370:8 

structures 36:21 

struggled 226:8 

struggling 39:21 

stuck 376:21 

study 30:3 36:19 

244:18 

stuff 48:8 56:11 64:12 

104:10 121:22 131:6 

135:12,18 149:4,15 

155:10 188:17 203:15 

203:18 215:16 251:22 

271:3 281:16 302:10 

325:22 332:20 335:7 

340:18 390:14 

subcommittee 93:10 

341:9 342:7,8 385:2 

389:13 392:6,16 

subcommittees 82:14 

subgroup 22:7 383:17 

383:17 387:11 

subject 7:16 95:4 98:11 

121:2 161:12 340:11 

348:18 

subjects 342:5 

submit 5:16 347:20 

submitted 4:14 11:10 

117:17 

Subpart 354:10 

subsequently 210:8 

subset 251:5 

subsidized 42:9,18 

subsidizing 94:21 95:5 

subsistence 302:3 

substandard 379:15,17 

substantial 120:7 

substitutions 96:16 

succeed 88:8,13 

success 110:8 150:5 

240:1 

successful 23:16 30:22 

47:3 255:19 353:12 

successfully 97:12 

suck 148:8 

sucking 69:22 121:21 

sudden 108:8 122:10 

155:22 281:6 317:19 

sue 143:1 

sued 288:1 

suffering 79:17 

sufficient 125:14 

sugar 104:14 126:10 

suggest 354:12 

suggestions 82:16 

318:1,4 323:10 

392:13 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
432 

suit 77:14 350:18 

357:18 

summary 167:17,17 

181:10 183:5,15,19 

183:21 193:19 257:8 

301:12 

summer 4:7 141:6 

172:8 253:16 

summit 355:11 

Supermarkets 69:14 

supervised 310:14 

supervisor 309:2 

supervisors 289:9,10 

supplement 220:20 

supplemented 221:17 

233:22 

supplier 7:20 63:20 

66:18 96:14,20 

119:16 344:8,17 

346:10 379:9 

suppliers 119:14 

128:19 380:4 382:14 

supplies 32:7 98:6 

supply 28:20 32:9 35:5 

37:2 38:5 39:8 76:18 

76:22 107:5 116:2 

149:17 179:12 243:5 

277:20 325:10 379:10 

379:21 380:1 385:4 

387:6 

supplying 249:8 

support 31:17 49:18 

60:6 64:8,14,16 65:4 

65:5 68:19 72:8,22 

73:6 74:4,19 97:22 

118:17 122:18 154:13 

156:4 203:13 205:17 

248:16 287:10 341:22 

345:8 351:2 355:10 

supporters 122:20 

supporting 65:18 69:9 

75:12 273:9 

supportive 78:12 

199:15 

supports 95:13 217:20 

367:16 377:20 

Suppose 332:16 

supposed 12:5 20:20 

68:8,9 82:22 92:11 

98:21 121:6 239:12 

278:9 302:15 330:5 

surface 356:12 364:21 

366:7 

surge 132:11 

surgically 25:12 

surplus 101:20 105:20 

111:1 

surprise 137:17 

surprised 9:8 354:19 

367:21 

surprises 87:14 

surprising 123:22 

137:6 

surrounding 7:20 

survey 8:10 201:21 

202:10 205:1,2 

207:22 208:8 209:14 

209:19,20,21 211:12 

213:17,22 214:5,6,8 

215:2,6 216:7,14,15 

216:20 218:17,18,21 

220:7,14 221:11,11 

222:10,12 236:5 

237:6 239:17 242:17 

242:20 248:11 252:19 

253:2 254:2,8 268:12 

287:8,10,19 288:6,12 

298:10 300:20 

surveys 213:17 

survive 98:6 

surviving 127:17 

suspect 200:18 207:22 

364:15 

sustain 63:14 

sustainable 34:4,22 

sustained 97:20 265:12 

sustaining 52:15 

swap 312:13 391:7 

sweet 79:7 

switched 247:13 

syrup 142:21 

system 13:13 14:20,21 

14:22 15:5,17,21 16:9 

16:12 18:13 19:5,6,19 

20:19 21:1,1,3,3,4,6 

21:12,13,15,21,22 

22:16,20,22 23:1,4,5 

23:17 25:7,10 26:3,7 

26:22 45:4,11 108:20 

227:10,20 230:3 

234:3 247:6 258:16 

258:18 259:7,9,11 

302:20 306:7,14,15 

307:11,21 338:4 

373:10,11 

systemically 237:17 

systems 19:16 20:3,13 

22:15 176:22 373:8 

T

T-Bills 148:17,21 

tab 242:22 

table 59:10,17 123:11 

131:6 174:22 181:20 

187:1 189:2 194:10 

209:18 250:9 359:6 

tables 183:17 193:20 

tabulation 242:14 

tackle 348:18 

tagging 15:14 23:18 

tags 25:17 

tahini 371:17 

tail 112:12 

tailor 6:17 

Taiwan 45:5,7,21 

150:12 

taken 74:18 117:11 

159:2 169:1 198:22 

234:1 

takes 34:12 118:13 

178:6 208:15 237:17 

304:20 354:20 

Talan 2:17 201:12,13 

226:16 

TALBOTT 1:19 337:22 

338:13 

talk 8:12,18 9:5 11:9 

21:20 23:22 27:11 

51:16,17 53:4 61:7 

62:22 65:3 81:13 87:6 

101:13 102:5,8 

109:20 112:9 113:15 

115:6 116:14 125:7 

134:14 137:21 146:18 

147:17 153:12 165:9 

200:21 208:1 215:16 

215:17 216:17 218:18 

219:7,8 254:13 257:1 

257:10 258:7 274:1 

276:17 277:20 282:16 

286:20 306:14 323:20 

331:22 339:2 348:14 

348:19 350:21 375:10 

383:13 387:12,13 

388:13 390:4 

talked 7:18 20:12 33:11 

90:6 141:13 146:16 

146:19 155:16 178:12 

203:18 271:20 286:15 

286:15 300:22 325:17 

talking 6:1 17:16 47:7,7 

50:13 58:1 121:6 

140:8 143:18 182:7 

214:1,12 215:18 

223:19 243:11 253:9 

264:22 287:4 307:22 

311:5 328:6 349:4,5 

352:13 356:22 360:16 

361:10 367:7 373:5,6 

373:7 382:19,21 

383:5,20 

talks 255:19 340:17 

tandem 176:21 

tap 370:1 

target 114:21 157:22 

158:8 159:10,14 

160:3,9 161:1 333:14 

targeted 114:12,17 

116:21 120:1 153:11 

198:12,13,14 346:9 

targeting 241:14 326:3 

targets 9:1 151:4 

208:13 

tariff 56:10 71:3,4,6 

126:17,20 132:10,12 

132:14,17 133:10,13 

133:14,18,22 134:2 

136:1 139:7,9,10,12 

tariffs 52:21 55:16,19 

76:21 110:1,6,8 

113:21,22 114:2,3,6,9 

114:10,11,13,16,19 

115:1 116:1 117:1,22 

120:8,17,19 124:2 

125:18 126:21 129:16 

131:8,18,21,22 132:6 

132:20,21 135:7 

136:2,22 138:21 

145:2 146:1 

Task 375:22 

tax 71:16 72:10 94:22 

133:6 227:17 251:16 

taxes 110:1 

team 87:4 285:1 328:7 

363:9 

tease 387:9 

tech 164:6 165:17 

207:9 

technical 56:9 57:11 

61:17 90:7 92:22 

322:10 342:18 347:11 

362:15 369:11 

technically 162:19 

345:11 

technologies 16:18 

20:5 38:15 109:7 

154:9,10,11 155:9 

technology 20:14 23:11 

23:15 24:9,17 27:4 

38:17 129:21 154:5 

164:12 165:4 

teeth 59:3,4 

telephone 5:14 222:11 

tell 9:14 28:8 45:22 

62:22 64:18 88:7 

180:13 185:6 191:11 

197:18 200:11 216:6 

223:15 224:10,13,15 

225:9 240:21 244:20 

245:15 252:10 253:6 

261:14 283:19 285:11 

336:5 348:2 387:3 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
433 

telling 232:15 237:18 

242:11 255:15 

tells 214:18 229:20 

255:22 

temper 239:15 

temperate 138:8 

temperature 159:20 

temporary 204:18 

272:20 273:3 275:15 

275:22 276:20 277:11 

ten 76:1 106:14 112:21 

115:7 167:2,21 171:3 

204:18 233:15 262:14 

267:16,17 276:12,16 

277:8 

ten-month 204:15,19 

274:11 275:12 276:7 

276:17 277:3,13 

tenants 318:13 322:5 

337:20 

tend 260:1 272:7 

283:10 291:21 319:20 

319:21 

tendency 160:9 

tends 318:10 322:21 

365:12 

tension 300:17 

term 54:6 80:11 134:10 

terminal 174:2 347:5 

terms 28:20 66:7,11,17 

68:18 75:13 76:18 

77:9 83:20 106:1 

113:17 126:7 141:4 

141:18 147:1 189:9 

189:16,21 220:6 

228:6 253:15 360:3 

test 76:5 77:3 172:1 

187:6,7 258:10 

268:15 295:21 296:7 

296:8,14 297:5 353:1 

353:8 356:13 361:4 

371:21 

testament 179:6 

tested 169:16 170:1 

176:9,11,12 179:3,8 

188:12 191:1 192:11 

354:3 

testing 170:4,7 178:6 

342:15 343:1,17 

349:21 350:1 353:5 

356:13 366:10 376:20 

tests 296:12 297:2 

353:18 360:8 

Texas 39:18 40:15 

63:15 69:15 168:4 

253:17 

textile 128:1 

texts 368:21 

thank 10:9,17,20 13:4 

26:17 27:6,13 34:9 

36:9 39:3 43:1,3,22 

46:1 90:2 94:2 139:22 

152:17 163:13 164:21 

165:11 184:10 200:10 

202:13 203:10,20 

255:17,17 288:21 

314:9,16,18 324:22 

332:22 338:18,21 

341:8 363:20,22 

368:2 372:4 388:8,9 

388:10 396:3 

thanking 152:21 

thanks 27:11 99:17 

Thanksgiving 356:5 

that'd 284:13 

theme 102:4 

theoretically 222:6 

289:8 

they'd 317:9 

things 5:18 7:4 10:11 

14:2,6 17:13 24:12,21 

30:12 47:14 49:1,2 

50:13 55:11,13 56:8 

63:5,9 70:16 71:19 

81:10,20 83:14 85:8 

86:3 88:17 95:1,9 

101:14 104:11 106:3 

106:15 116:17 125:4 

128:15 129:14 138:9 

139:4 150:2 151:17 

151:18 153:3,5,12 

156:3 158:16 161:20 

162:9 163:5 181:5 

185:12 191:20 200:5 

205:7 213:4 238:8 

250:3 273:18 284:11 

285:11 290:18 292:2 

295:22 301:12,14 

302:4 304:15 341:15 

343:18 369:1 370:3 

370:14 

thinks 193:6 389:10 

third 23:3,5 81:2,5 86:7 

88:13 132:22 235:6 

third-generation 39:20 

Thomas 107:19 

thought 56:19 75:21 

80:1 100:3,14 104:17 

163:1,1 164:16 

168:15 169:1 269:15 

285:14,15 375:14 

389:20 

thoughts 93:4 144:8 

threat 123:10 144:2,6 

144:16 145:1 

threats 111:21 113:10 

three 7:14 8:13 54:4 

62:6 81:6 86:3 158:4 

161:3 178:6 193:21 

230:10 232:4 235:9 

237:22 244:9 247:8 

247:16 249:11 250:3 

272:1 285:13 311:22 

313:9,17 323:2 328:5 

348:8 

three-legged 257:18 

three-year 244:6,12 

247:7 

threshold 144:13 146:5 

277:13,14 352:4,21 

393:17 

threw 356:10 

thrive 75:17 

throw 21:3,7 22:10 

throwing 140:20 

thrown 21:12 222:3 

379:4 387:17 

ticks 381:9 

tier 70:15 

ties 124:1,1 

tight 244:22 

tighten 253:10 

tighter 234:2 

timeframe 365:8 373:21 

timeline 36:5 58:1 

195:21 

timelines 282:13 

timely 195:22 342:15 

times 14:18 25:2,5 35:1 

35:4 36:20 62:6 

105:14 170:6 172:4 

178:7,14 193:21 

210:4 212:18 220:7 

221:22 228:16 232:5 

235:9 341:10 

timing 347:22 

TINA 1:14 

tinctures 14:1 

tip 73:20 

TISON 1:20 46:7,11 

293:5,12 396:1 

tit-for-tat 34:13 

title 44:9 

today 4:18 5:18,18 8:3 

8:11,19 9:4,16 10:19 

13:6 14:3,4 27:7 

28:10 35:14 44:20 

91:5,12,21 92:20 

93:18,19 141:1 

147:13 165:21 203:18 

207:10,15 208:2,22 

216:13 219:7 220:16 

239:19 242:7 257:10 

257:13 262:15,16 

271:10 304:13 314:10 

360:16 371:11 378:12 

386:12 388:20 394:19 

394:22,22 

today's 94:6 

told 204:2 283:12 

303:18 309:3,19 

tolerance 158:18,19 

159:1,16 166:15 

179:4,15 182:13,19 

185:19,20 190:3,7,8 

tolerances 44:19 179:9 

181:21 182:1,21 

195:17 196:4 

TOM 1:17 

tomato 77:16 78:1 

157:3 377:5,16 

tomatoes 29:5 30:3 

33:2 37:16 67:13,14 

74:12 76:6,21 269:18 

269:18 377:4 

Tommy 1:21 47:9 49:11 

79:2 92:4 93:16 

387:10 

Tommy's 60:9 

tomorrow 5:1,3,18 28:1 

40:20 41:19 69:12 

81:12 91:8,21 93:5 

98:20 206:21 338:12 

366:18 388:14 389:21 

394:11,13 395:2,2 

ton 128:14 135:12 

Tony 75:4 

tool 54:16 156:17 184:8 

tools 18:10 68:4,18 

301:22 

top 48:15 111:8,9 119:7 

119:8,14 123:6 

124:12 126:10,11,11 

131:13,16 132:1 

134:14 160:12 197:15 

197:20 262:13 264:2 

394:13 

topic 17:5 34:7 63:8 

93:1,19 164:19 

203:17 361:9 390:17 

topics 4:19 6:1 7:19 8:5 

11:9 

total 30:6,9 111:6,11 

119:13 128:22 209:6 

209:11 219:1,15,15 

229:16,18 230:1,1,4,8 

230:12 231:7,9,12 

238:22,22 264:22 

267:13 322:17 323:3 

totally 12:7,9,10 43:9 

263:12 

touch 27:10 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
434 

touched 75:6 

touching 357:4 

tough 17:19 63:8 64:17 

65:11 89:9 244:3 

318:3 336:4 

towel 356:11 

town 246:2,7 317:5 

346:19 

toxic 11:17 

toxin-producing 356:2 

TPP 56:18 133:14,17,19 

150:11,15,22 151:1,3 

trace 23:22 24:4,6,12 

24:13,21 372:19 

387:1 

trace-back 376:22 

traceability 346:21 

372:21 373:1,3,5 

374:20 376:13,19 

tracing 27:1 

track 13:16 24:15,20 

25:12 368:14 

tracking 13:13 18:20 

23:19 24:17 163:20 

tracks 13:18 

traction 121:8 346:2 

tractor 237:3 

traded 78:19 143:1 

trading 32:18 36:15 

37:3 130:10,12 

traditional 48:3 236:22 

319:7 

trained 266:10 267:3 

training 343:7 

Trans-Pacific 56:18 

132:13 

transcribe 250:7 

transfer 129:22 272:12 

280:19 282:22 283:6 

307:2,15 

transferring 280:7 

transform 305:16 

transition 19:18 21:21 

250:20 251:7 254:11 

332:7 361:16 

transparency 23:14,22 

26:2,3,12,21 27:16 

transparent 57:2 310:5 

transportation 106:16 

302:2 

transported 13:20 

15:11 

travel 280:11 

traveling 4:5 17:15 

treat 310:6 

treated 131:3 

treating 359:15,20 

361:6 

treatment 359:14 

tree 105:7 

trees 344:9 

tremendous 39:19 

64:11 95:10 

trend 110:20 243:16 

244:6 262:12 

trending 243:16 

triazoles 176:18 

tribes 318:19 

trickier 142:3 

tricky 136:1 

tried 200:2 338:5 

triggered 143:21 

triggers 50:5 144:3,4 

145:4 

trillion 192:13 

tropical 104:10 124:7 

138:7 

truck 252:1 

true 78:17 225:9 362:14 

395:12 

truly 41:3 244:22 

267:12 362:11 

Trump 50:8 122:20 

try 27:21 54:10 56:4 

65:17 67:2 72:15 

87:18 101:3 112:6 

116:14 143:9 152:7 

152:20 220:10 226:15 

226:18 246:19 282:4 

282:13 294:2 363:12 

388:1,17 

trying 22:6 39:8 43:14 

55:18 121:15 131:6 

214:15 216:19 238:6 

238:17 267:9 276:11 

284:15 295:6,8,10,14 

309:13 317:19 333:13 

358:16 373:12,21 

374:4 378:1 387:9 

turn 6:6 121:12 199:22 

213:10 257:16 315:5 

323:12 324:3 

turning 43:6 

turns 231:9 258:17 

Twenty 79:6 

Twenty-two 114:6 

twice 210:4,9,17 211:15 

211:17 264:19 

twisted 46:15 198:22 

two 12:9 25:21 37:3 

52:9,9 54:4 62:6 

85:16 90:22 123:6 

150:17 160:5 161:19 

162:1 171:21 182:20 

191:7 194:15 203:7,8 

207:18 208:5,6 209:9 

211:12 213:16 217:13 

219:8 221:10,22 

226:5,9 230:9 232:3 

232:21 236:9 237:22 

239:18 240:3 242:15 

243:17 244:8 246:10 

250:20 256:20 261:1 

262:11 270:11,21 

284:5 308:8 319:22 

322:19 323:13 328:5 

330:16 339:12 340:2 

346:16 372:9 384:1 

two-thirds 393:22 

type 52:16 162:20 

175:11 236:19 241:2 

246:20 251:19,21 

324:6 371:18 376:2,3 

381:8 

types 6:22 8:13 14:6 

17:13 155:2,11 190:9 

219:10 298:12 354:16 

354:17 356:15,16 

367:11 369:21 

typically 282:12 288:13 

302:12 329:19 

typo 182:20 

U

U 30:3 

ultimately 88:19 288:2 

356:21 385:5 

uncertainty 111:17 

unclear 58:17 

undergoing 195:20 

underground 274:15 

274:19 

underlying 102:4 107:6 

238:8 

underneath 158:20 

understand 4:11 6:19 

26:5 36:12 53:21 59:7 

62:20 68:16 70:14 

74:22 81:17 91:17 

178:22 212:10 216:2 

218:19 225:13 275:14 

278:1,17 284:11 

313:20 317:5,7 331:6 

331:21 335:18 339:5 

344:1 375:9 377:2 

understanding 58:11 

163:10 198:11 205:1 

215:19 218:7 346:20 

358:10 

understood 256:22 

353:18 

underwater 122:6 

undue 342:22 

unemployment 227:8 

227:10,16,19 233:10 

234:3 246:14 

unfair 130:1 150:1 

151:7,11,14 367:2 

unfairly 143:1 

unfortunately 9:15 57:9 

78:19 79:14 384:1,5 

unhappy 80:17 151:16 

unified 392:20 

uniform 163:4 

unintended 359:19 

Union 45:12 

unique 14:20 274:3 

286:16 372:22 376:1 

uniquely 296:2 

unit 164:18 319:22 

323:17,18 324:2,4,5 

united 1:1 2:6,13 8:2 

31:18 46:3,4,14,18 

50:14 53:17 56:20 

59:9 64:17 69:14,16 

72:17 73:4 74:18 

79:16 85:20 98:2 

108:22 115:19 144:10 

144:11 148:7,10 

179:7 199:16 227:9 

342:17 346:12,15 

348:1,5,7,7,13 351:10 

358:3 359:11 360:16 

367:12 368:19 371:9 

United's 366:18 

units 319:22 320:9 

322:16,17,17,19 

323:20 324:17 328:13 

328:17 

universal 254:1 

universe 215:1 

universities 154:12,15 

university 36:19 154:21 

155:11 

unjustified 135:7 

142:21 

unknown 163:22 326:5 

unlimited 271:17 

unmet 154:20 

unpredictable 54:1 

unsafe 385:16 

unsatisfied 199:19 

unused 326:4 

unusual 232:19 

up-front 369:15 

upcoming 169:20 

195:21 

update 101:11 363:15 

389:14 392:4 

updated 378:9 

updates 294:4 

upload 302:21 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
435 

upper 239:14 

urban 40:1 321:3 

urge 157:14 367:5 

USA 106:11 

USCIS 258:13 280:22 

281:18 307:2 308:11 

USCIS' 276:2 

USDA 2:6,7,8,11,12 

29:17,18 30:22 44:21 

48:4 51:4 59:20 61:17 

61:20 73:15 78:4 79:9 

81:8 98:3,11,12 

159:13 160:18 161:15 

161:16 163:2,7,16 

167:4,13 168:2,12 

177:13 194:22 196:8 

196:16 204:22 205:21 

206:11 208:19 209:17 

218:7 287:18 288:12 

298:17,18 320:19 

330:5 336:8,19 

338:18 341:7 345:4,5 

345:10,18,22 346:18 

347:9 358:5 361:14 

362:5,9 363:13 

368:10 

USDA's 61:11 164:4 

USDA-USTR 62:8 

use 15:13,13 19:21 21:1 

23:7 25:18 63:17 

82:16 130:20 141:21 

160:17 162:7 163:10 

163:11 167:20 175:19 

176:19 184:4 191:10 

191:13 192:20 199:13 

199:14 205:4 208:15 

217:11 229:12 251:5 

261:15 262:7,7 

263:10 269:19 271:11 

271:22 276:11 287:18 

288:2,2 304:7 305:20 

308:21 313:22 325:4 

325:6 327:2 329:13 

349:4 351:6 356:21 

357:19 359:2,5 361:5 

364:11 365:9 373:15 

useful 75:22 157:6 

uses 131:20 171:7 

178:9 180:21 181:1 

354:17 

USG 310:16 

USMCA 33:12 35:13,17 

49:9 58:15 59:12 75:7 

75:10,12 101:11 

121:13,16,16,17 

123:2,10 124:11,16 

124:17,22 125:4 

139:21 

USTR 36:5 44:21 49:20 

60:7 61:17,20 100:6 

usually 122:13 190:2 

227:16 236:4 299:12 

377:11,19 379:22,22 

381:7 

utilization 145:18,19 

146:5 

utilize 19:15 

utilized 144:4 198:20 

utilizing 206:12 

utterly 308:14 

UV 364:19 

V

valid 262:8 298:19,20 

validated 178:2 308:3 

359:17 

value 131:15 213:9 

215:5 225:13 352:4 

352:21 

variables 390:18 

variance 218:3 

variances 222:3,5 

244:21 

variation 232:6 358:12 

variations 217:18 

varieties 300:2,15 

variety 172:1 

various 115:11 192:19 

202:1 205:5,11 

vary 177:5 

vast 127:11 

veg 37:2 

vegetable 1:3 45:8 47:1 

52:12 59:20,21 60:3 

62:2 84:15,18 86:16 

94:4,7 96:4 97:5,18 

98:8,14 154:22 

157:16 158:6,11,13 

162:20 170:3 171:4 

183:6 200:13,17 

225:22 236:13 346:22 

347:10 369:10 

vegetables 12:4,7 25:3 

32:5 48:10 66:7 68:10 

72:17 84:1,9 94:16 

96:11 98:9,15 104:16 

105:9 124:8 156:18 

158:3 162:17 169:14 

199:18 317:13 344:3 

346:7 

vehicles 118:7 

Veneman 46:22 

Venezuela 147:8 

verge 151:13 

Verification 7:20 344:8 

344:18 346:10 379:10 

verify 351:7 

verifying 367:10 

vernacular 382:19 

version 98:18 

versus 47:10 144:11 

185:8 236:18 240:9 

243:9 248:5,6 263:19 

326:22 327:17 330:6 

330:12,14,15 335:22 

367:2 372:12 383:22 

vessel 69:8 

viable 156:17 

Vice 1:12 

Vietnam 112:19 149:14 

151:9,9,11 

view 53:7 77:4 

violation 179:15 190:8 

violations 180:7 198:7 

Virginia 1:10 38:12 

visa 258:2,15 259:1 

260:18 265:6 268:4 

269:11 289:13 296:3 

296:7,19,20 306:18 

306:19 321:10 

visas 273:13 274:22 

visible 14:22 15:2 

visiting 72:1 

visitors 99:18 

visual 265:15 

Vito 276:9 

vocabulary 40:9 

voice 208:17 

volatilization 160:6 

Volpe 276:9 

volume 102:14 144:9 

171:11 250:10 261:2 

264:8 265:19 281:15 

282:11 297:13 328:6 

331:1 363:3 

volumes 118:14 

voluntary 357:12,13 

382:8 

volunteer 49:5 

vote 50:6 390:5 

votes 140:22 

voting 293:13 

VP 348:6 

vulnerable 110:16 

159:6 

W

wag 64:19 

wage 205:10,12 209:12 

209:13,16 210:18 

212:3,7,13,15,18,20 

212:22 213:1 218:8 

219:3,16,17,18 220:2 

220:19 221:2 230:1,4 

230:6,9,11 231:1,4,4 

231:7,7,9,13,15,16 

232:22 239:20 240:13 

241:2,3 242:14 243:3 

243:6,11 244:10 

245:5 251:3,4,10 

252:22 286:17 288:18 

289:3,5,15,18,19 

290:3 293:17,20 

294:11 295:5,10 

298:3,10 299:4,10 

300:3,6,9,13 301:2 

309:7,9 310:15 314:1 

wages 30:9 201:16,20 

205:5,6,7,8,11 217:5 

217:7,9 218:20 220:8 

220:11 226:13,17 

227:4,6 229:16,19,19 

230:8,12 231:12 

233:14,14 234:6 

238:22 239:1 249:10 

274:1,4 286:15,16,20 

287:1,2 290:8 293:6 

294:5,14 295:12 

298:4 299:14 300:22 

309:18 310:3 

wait 51:2 360:4 

waiting 49:12 245:6 

305:4,11,11,14 

waits 223:5 

Wal-Mart 345:15 

walk 39:18 166:20 

walked 10:22 

wall 21:4,8,12 

wanted 9:7 75:10 81:12 

139:12 153:12 164:1 

182:19 192:3 193:1 

231:20 253:22 299:16 

316:20 340:14 375:8 

wanting 31:16 295:7 

341:5 

wants 67:10,12,13 

83:15 90:10 152:15 

167:20 200:9 249:16 

392:21 

war 51:13 91:2 107:17 

108:11,19 112:2 

115:19 116:15 128:10 

warehouse 252:5,7 

373:10 

Warehousers 252:6 

warehousing 228:7 

warning 371:13,15 

warranted 387:18 

wars 82:3 111:21 

113:10,10 

wash 148:22 

washed 175:8 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
436 

washing 349:7 352:15 

Washington 44:11 80:6 

100:2 121:19 141:18 

168:4 236:20 247:10 

253:13 285:18 289:9 

294:13 298:22 299:2 

299:3,3,13,21 301:6 

Washington's 301:5 

wasn't 46:14 188:2 

192:2 193:7 221:6 

313:17 371:16 379:12 

waste 106:15 176:3 

391:8 

watching 77:19 

water 3:19 7:21 8:3 

11:19 39:22 126:8 

175:9 183:3 192:10 

192:12 342:14 343:3 

343:17 348:15 349:3 

349:6,8,19,21 350:5,6 

350:11 351:5,20 

352:7,13,15 353:5,7 

353:18 354:3,4,8,17 

355:2,11 356:3,8,12 

356:15,17,19,20,21 

357:4,5,5,9,20,20 

358:6,7,10,18 359:2,4 

359:13,14,16,20 

360:8 361:4,5,6,9 

364:10 366:2,5,7,7,12 

367:7 

watermelon 193:15,17 

193:20 

watermelons 31:9 

193:2 

way 10:1 15:14 19:22 

20:18 22:10 24:1,7 

26:20,22 35:1,9 41:13 

42:21 52:16 64:17,21 

65:16 67:3 71:2 73:16 

80:14,17,20 88:14 

92:7 101:16 102:20 

107:11,14 120:1 

123:12 124:14 128:8 

131:21 135:15 136:5 

140:10 143:9 150:20 

151:16 190:15 195:14 

199:13,14 200:11 

203:2 204:5 208:20 

220:4 223:14 232:9 

244:11 258:22 271:13 

271:15 287:20 307:21 

311:16 316:3 318:22 

330:14 348:8 350:10 

355:7 356:14 359:16 

365:12 366:11 367:10 

370:14 371:21,22 

376:18 385:13 

ways 24:16 33:18,19 

38:14 39:14 48:3 

65:18 67:7,20,21 

75:16 102:19 103:7 

105:18 116:5 121:5 

124:9 156:9 192:19 

238:14 272:1,7 

350:19 356:10 

wealth 110:21 

wealthy 137:17 

web 176:5 180:14 

183:22 184:1,3,4 

222:11 340:16 

website 13:11 167:6,19 

246:18 

WEDNESDAY 1:7 

weeds 220:4 

week 210:6 229:11 

230:21 232:17 237:16 

267:10 

weekly 62:7 230:6,11 

231:3,9,13,15 235:15 

weeks 210:5,5 230:12 

230:20 231:2 232:4 

232:21 233:16 240:12 

253:17,18,18 285:14 

308:8 347:16 360:14 

374:4 

weigh 199:11 

weighing 117:20 

weight 199:12 

weighted 212:19 220:1 

288:22 330:7 

welcome 6:20 46:17 

47:5 99:18,19 

well-rounded 37:10 

went 59:1 92:10 99:15 

116:16 133:14 152:9 

201:10 207:8 255:13 

285:22 286:3 290:17 

291:6 315:1 317:7 

355:16 396:7 

weren't 326:7 336:15 

336:15 

west 239:13 

whatnot 392:22 

wheat 71:22 105:5 

123:15 126:11 

WHEELER 1:20 

Where'd 352:2 

Whitaker 370:5 

white 356:10 

whoever's 227:12 

wholeheartedly 341:22 

wholesale 228:9,10 

wholesalers 344:19 

wholesome 158:21 

wide 172:1 286:17 

376:15 

wife 67:10 

wife's 51:15 

wildly 259:19 

Wilkins 1:21 35:12,21 

36:2 39:4 49:8 50:8 

52:3 69:11 90:16,21 

92:9 93:16,17 98:21 

139:20 141:10 377:1 

377:7 379:1 380:6,19 

380:21 384:7 385:20 

387:16,22 388:8 

391:16,21 

Williams 370:8 

willing 88:2 239:3 

255:16 374:3 383:18 

win 84:4 362:6 

window 38:6 241:8 

278:7,16 339:14 

windows 279:8,11 

wine 104:4,5,6 136:7 

WINGARD 1:21 53:15 

187:3,10 188:7,11,15 

189:13 223:13 224:10 

224:17,20 225:8,12 

225:18 238:10 252:9 

254:4 277:16 278:17 

279:1,5 280:5 281:1 

281:10,20 282:1 

308:19 309:8,11,13 

309:16 310:12,19 

311:3 332:16,22 

333:8 

winter 104:15 172:10 

Wisconsin 317:5 

322:22 

wise 204:2 

wish 92:10 342:21 

witnessed 241:13 

witnessing 79:3 

woefully 156:19,19 

wondering 82:15 

170:19 196:19 350:14 

word 52:5 53:17 95:11 

95:11 214:14 290:16 

words 46:16 225:1 

wordsmithing 367:18 

workable 239:12 

worked 46:21 93:13 

100:5,12 152:22 

210:15,15 219:2,15 

235:12 245:16 254:5 

266:9 316:19 337:22 

338:5 348:10 358:9 

370:6 

worker 205:19 209:9 

210:16 235:4,4,8,8 

241:2 251:19 252:12 

268:21 276:12 292:16 

295:6,12 296:15 

310:7,11,16,22 311:4 

334:6 

worker-based 258:18 

workers 11:20 118:14 

209:6,8,9 210:14,19 

210:19,20 214:18 

215:22 216:21,21 

218:22 219:11 223:16 

223:18 224:11,14 

226:10 228:1 233:16 

236:1,5,14 237:7,19 

241:4 251:4 252:10 

254:5,6 255:8 258:2 

258:10,15,19 259:4 

260:6,10 262:11 

268:13 269:5,5,16,19 

269:22 271:17 272:2 

279:13 280:8,10,14 

280:14,20 282:21 

283:5 290:8,9,10,11 

291:10,21,22 292:3,7 

292:14,19 293:19 

294:8 295:13,15,16 

296:18,22 301:15,16 

301:19,22 302:3,13 

304:3,21 305:6 

306:10 310:20 318:17 

325:4,6 331:19 

333:16 334:3 339:8 

workforce 60:10 224:4 

227:14,21 249:17 

279:18 300:10 303:21 

workgroup 91:3 97:4 

152:22 153:9 181:18 

workgroups 91:8 

working 4:12 5:2,4 7:6 

10:11 17:6 38:1 44:18 

48:14 49:20 50:2 81:9 

81:16 92:19,21 93:5 

136:12 140:11,15 

141:5,14 145:20 

172:22 173:1 187:22 

192:7 246:4,7 253:15 

256:1 258:19 287:11 

310:8 317:10 334:3 

335:7 348:12 349:17 

353:12 357:21 360:19 

368:17 369:5 370:21 

378:9 390:3,13 

391:15 

workload 263:14,16 

264:17 282:6 284:10 

works 9:15 28:8,9 63:1 

80:14,18 94:9 232:1 

237:1 244:11 246:2,2 

304:17 334:6 354:14 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
437 

390:21 

worksite 228:3 280:21 

worksites 283:10,13 

world 17:16 39:12,14 

51:17 52:1 55:19 66:7 

76:3 81:1 94:18 

107:16,17 108:11 

115:13 126:6,10,14 

127:6 148:8 158:6,11 

193:5 216:7 351:12 

371:8 

world's 107:8 

worry 39:16 40:6,9,13 

worse 82:4 268:3 

340:13 

worth 29:22 351:21 

would've 334:16 378:4 

378:6 

wouldn't 130:7 188:17 

248:11 276:4 286:4 

290:9 295:20 336:14 

344:14 354:19 390:21 

wow 200:14 

wrap 5:18 150:13 152:6 

wrapped 217:18 

wraps 136:15 

write 163:3 220:14 

318:3 

writing 5:16 11:10 

written 11:14 12:13 

27:17,20 83:6,6 

186:18 352:19 364:4 

wrong 35:9 150:20 

377:17 

wrote 202:8 

WTO 109:3 110:3 

125:17 126:16 133:2 

136:20 

Wyoming 244:1 

X

X 237:7 238:3 

XYZ 386:3,6 389:4 

Y

yay 394:1 

year 29:22 35:4 51:3 

58:12 62:6 63:20 

67:10,12,13,19 69:6 

78:8,9 79:18 86:12 

96:15 98:6 100:3 

119:16 120:20 123:16 

129:5,6,7 135:11 

137:5 140:13 141:9 

167:16,19 170:12 

171:21 172:4,15 

173:12 178:7 180:1 

183:14,17 184:7 

187:12,18 197:17 

204:20 210:4,9,18 

211:15,17 212:19 

228:16 233:15,17 

236:3,11 237:2 240:6 

240:7,9,11,11 241:1 

241:12,20 243:16 

259:22 260:20 261:1 

261:2,3,3,9 262:15 

263:17,19 264:4,8,9 

264:19 265:9,12 

276:3,13 280:9 284:5 

285:21 288:9 291:8 

296:15 300:11,21 

320:3 329:10 335:22 

336:5 339:22 355:10 

361:15 

year's 117:7 244:15 

336:4 

year- 322:8 

year-round 38:20 275:4 

318:7 319:15 386:14 

year-to-year 263:15 

years 6:12 28:22 39:6 

44:12,17 47:3 54:3,4 

67:15 69:13 76:1,4 

78:14 85:13,16 100:2 

103:2 107:16 115:7 

122:10 125:9,17 

137:4 158:4 161:5 

162:2 172:18 183:7 

189:3 191:7 201:22 

202:10 208:11,12 

211:12 242:15 244:8 

244:9 247:8,16 

256:15,16 262:14 

267:16,17 283:16 

284:5 289:2 302:5 

316:15 317:20 319:5 

328:14 329:8 336:1 

338:2 348:8,11 

years' 351:21 

yell 29:17 

yellow 168:7 

yesterday 50:10 129:15 

Yiannas 370:7 

yield 318:21,22 

yields 173:8 

York 168:2 299:13 

young 41:15 

Yuma 354:2 356:1 

376:6 

Z

Z 250:1 

Zea 1:22 55:4,4 57:7,13 

87:13 139:10 186:1,5 

186:9 334:10 335:2 

Zealand 132:16 133:21 

135:2,2 

zero 158:22 

0

06 316:16 

07 377:3 

08 260:18 377:3 

09 377:3 

1

1,000 264:4 

1.25 127:12 

1.4 267:12 268:3 

1.6 138:15 

1:25 201:8 

1:30 201:5,6,7 

1:31 201:11 

10 127:8,11 129:4,6 

232:13 276:6 332:14 

10-1/2 276:5 

10,000 170:13 332:12 

10:10 99:15 

10:25 99:13,16 

100 69:20 72:10 87:21 

94:17 112:14 114:5 

385:21 386:10 393:16 

100,000 187:12 

1000 208:13 210:1 

234:7 

101 34:5 40:8 58:6 

340:17 

106,000 228:20 232:12 

11 3:3 144:1 183:2 

275:18 276:6 308:22 

11,000 260:20 291:8 

11.9 138:19 

113 126:18 

11th-hour 59:11 

12 29:6 241:6 253:7 

309:1 310:15 

12,000 187:16 260:22 

12,905 181:14 183:3 

12:16 201:10 

126 170:1 352:2,3 

12th 210:6 229:11 

237:16 245:16 

13 13:15 14:18 115:7 

168:6 175:3 230:12 

230:20 231:2,8,19 

232:1 262:19 310:16 

138 29:16,20 

14 1:7 83:2 170:7 194:8 

194:11 

14,000 211:15 221:4 

14.71 240:14 

140 119:13 

1400 221:4 

15 76:1 83:2 99:7,9 

112:21 115:7 119:12 

126:21 150:2 210:9 

211:19 212:4 234:12 

243:12 256:15 265:4 

267:8 269:10 293:7 

293:14 294:2 300:5 

309:2 314:20 

15-minute 286:9 

15.03 289:9,10 

150 209:4,4 235:12 

328:12 

16 58:6 119:17 143:20 

16,467 322:17 

16.40 300:3 

164 3:8 

17 241:7 

178 29:19 

18 211:8 325:3 

18-plus 47:3 

1800s 128:1 

1875 182:14 

19 35:22 

1924(a) 324:12 326:20 

1945 110:3 

1948 126:16 

1986 287:20 

1991 121:19 165:20 

169:22 

1994 78:7 

1996 166:3 

1997 208:11 

1B 296:19 

1st 395:6 

2

2 123:18 125:1 132:8 

135:10 170:13 204:21 

208:1,12 253:7 

345:16 361:17 

2.04 238:5 

2.4 214:5 234:19 235:18 

236:7 265:2 266:5 

268:2 

2/3 261:21 

20 28:22 29:6 30:5 

105:8 112:21 114:8 

125:9,17 133:12,13 

233:16 253:17,18,18 

265:4 269:10 338:2 

348:10 

20-plus 54:3 

20,000 233:14,14 

2000s 46:22 

2001 125:18 

2002 146:22 

2004 79:17 

2005 36:19 

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2008 263:19 378:16 

201 3:9 

2010 83:6 

2011 147:12 202:10 

2012 262:19 

2013 285:13 

2014 83:1 210:21 

2015 193:22 277:2 

2016 122:16 316:16 

2017 29:16 56:21 

120:21 138:13 183:20 

187:21 188:3 214:10 

236:11 

2018 95:15 110:14 

129:7 144:1 183:18 

187:22 240:15 265:10 

2019 1:7 228:18 229:15 

240:14 265:7,16 

2020 160:17 242:5 

395:14 

205 3:11 

21 69:13 364:11,14 

365:6 

214 322:16 

22 241:16 280:10 

22nd 11:13 

23 183:7 189:3 284:17 

300:4 

232 116:1 117:11,15 

134:6 144:18 

24 30:8 

25 78:14 127:9 138:19 

139:7 281:5,5 320:5 

338:2 

250,000 181:13 

265,000 170:16 187:15 

270,000 261:8 265:2 

268:2,3 

2799 1:9 

28 133:11 

2B 264:15 307:19 

3

3 127:11 205:20 253:17 

266:5 320:6 328:3 

3/4 302:7,8 

3:13 315:1 

3:15 286:10,11 

3:30 314:20 

3:31 315:2 

30 44:12 78:8 100:2 

105:8 112:15 161:5 

281:5 292:4,20 305:1 

306:9 320:3 328:16 

329:16 

300 31:2 126:19 280:11 

3000 222:17 

30s 262:22 

310 322:15 

315 3:14 

317 29:21 

33 319:5 

33,000 30:4 

332 119:18 

34 170:17 

34,000 211:16 

341 3:17 

35 281:5 320:20,20 

35,000 320:18 

359 3:20 

365 67:18 

38 304:20 

38.5 132:9 133:5,8,13 

133:22 

39,000 211:17 221:5 

238:2,7 

396 3:22 

4

4 3:2 188:8 206:9 

243:11 253:18 

4.5 188:8 

4:58 396:7 

40 78:9 122:7 161:5 

317:20 320:3 329:16 

330:11 

40-hour 230:21 

40-something 286:3 

40s 266:6 302:6 

42 262:3 

4207 95:14 

43 262:18 

432 322:19 

44 39:7 

45 5:13 292:20 302:14 

304:19 390:3,5,12 

4th 228:19 

5

5 70:18 175:2 206:18,20 

242:16,21 253:17 

295:1 

5-10 152:2 

5-pound 175:3 

5,000 332:12,13 

50 39:6 132:10 133:4,4 

269:2 291:6,9,14 

302:5,13 317:20 

500 146:22 176:9 

50s 302:6 

51 205:22 271:2 

514 320:14 325:4,6 

52 36:20 

53 119:17 322:17 

57 123:16 

59 173:8 

6

6 119:11 138:15 243:17 

243:19 

6.2 241:13 

60 76:4 111:11 119:9 

300:13 301:9,10 

328:16 

60,000 262:20 296:14 

600 29:4 

62 261:21 

65 57:5 

66 393:22 

67 378:16 

69 323:3 

7

7 208:12 240:14 241:14 

243:18,19 244:3 

304:19 

70 76:4 301:9 

700 173:11 

70s 275:16,20 276:19 

297:16 

75 107:16 200:22 201:2 

260:5 301:10 320:4 

330:12 

79 114:9 123:20 

8

8 332:14 

8:00 396:4 

8:30 1:10 4:2 

8:40 27:18 

80 29:5 105:7 107:16 

127:9 145:18,20 

260:6 

800 147:1 173:9 197:16 

222:14 

800,000 236:5 

80s 297:16 

812,000 267:10 

817,000 235:20 

83 119:13,20 

85 63:12 69:6 159:22 

86 275:20,20 290:6,18 

297:9,15 

87 287:20 

9

9 5:8 132:14 133:18,21 

90 50:7 267:15 303:3 

319:4 393:16 

90s 29:5 276:9 

93 3:4 

94 123:19 

95 107:8 386:9 

97 261:12,16 

99 3:5 179:2,7 180:4 

298:19 382:9 

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439

C E R T I F I C A T E 

This is to certify that the foregoing transcript 

In the matter of: Fruit and Vegetable Industry

Advisory Committee Meeting

Before: USDA

Date: 08-14-19

Place: Arlington, VA

was duly recorded and accurately transcribed under 

my direction; further, that said transcript is a 

true and accurate record of the proceedings. 

 ----------------------- Court Reporter 

NEAL R. GROSS 

COURT REPORTERS AND TRANSCRIBERS 

1323 RHODE ISLAND AVE., N.W. 

(202) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com 
1

 UNITED STATES DEPARTMENT OF AGRICULTURE

 + + + + +

 FRUIT AND VEGETABLE INDUSTRY

 ADVISORY COMMITTEE

 + + + + +

 MEETING

 + + + + +

 THURSDAY, AUGUST 15, 2019

 The Advisory Committee met in the

Fairfax Room of the Hyatt Regency Crystal City

Hotel, 2799 Richmond Highway, Arlington, VA, at

8:00 a.m., Chalmers R. Carr, III, Chair,

presiding. 

PRESENT 

CHALMERS R. CARR, III, Chair

KILEY HARPER-LARSEN, Vice Chair

RICHARD E. BOWMAN 

JOHN CHANDLER 

TINA ELLOR 

K.C. ELY 

BRET ERICKSON 

MOLLY GLEASON 

JULIE L. GORDON 

JEFF HUCKABY 

BRIAN KIRSCHENMANN 

TOM LIPETZKY 

KELLY POWELL-MCIVER 

READE SIEVERT 

STEVE SMITH 

BRUCE TALBOTT 

GREG TISON 

DERRIN WHEELER 

TOMMY WILKINS 

CHARLES A. WINGARD 

DONN ZEA 

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2 

MEMBERS NOT IN ATTENDANCE 

DAVID K. BELL 

MICHAEL JANIS 

PAUL PALMBY 

STAFF PRESENT 

DARRELL HUGHES, Designated Federal Official

LEANNE SKELTON, AMS, USDA 

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 (7:59 a.m.) 

 CHAIR CARR: Welcome everybody back 

this morning. I'll call the meeting officially 

to order. As we said yesterday, we are going to 

break up with our working groups from 8:00 to 

9:00. And then we will come back and start 

discussion on each working group's 

recommendations. We have tables back there. 

 MR. HUGHES: Before everyone splits 

up, I pulled open the policies and administrative 

procedures for completing the recommendations. 

So I said yesterday that I was going to go over 

the process for approving recommendations. 

 And so first, let me read the section 

that is about completing workgroup 

recommendations. Developing workgroup 

recommendations follow these broad steps. 

 One, the workgroup prepares the 

recommendation or discussion document. Two, 

during the committee meeting, the workgroup 

presents its recommendation for discussion by the 

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full committee. 

 Three, at any point in the process 

prior to the committee's vote on the status of 

the recommendation, the presenting workgroup may 

convene and vote to withdraw this recommendation 

based on approval of this action by the majority 

of the members of the workgroup. Once presented, 

that -- number four, once presented, that 

committee votes on the workgroup recommendation. 

 The committee, which is the full 

committee, may take the following actions for 

each workgroup recommendation. One, adopt the 

recommendation as presented by the workgroup. 

Two, amend and adopt the amended recommendation. 

Three, reject the recommendation, or four, refer 

the recommendation back to the workgroup for 

further development. 

 And so the process for voting under 

the Conducting Business Section, which is on page 

7 of the policies and procedures, the second 

bullet decides the vote. Two-thirds of the votes 

cast at the meeting of the committee, at which a 

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quorum is present, shall be decisive of any 

motion. 

 Following Robert's Rules of Order, all 

abstentions will be recorded as such and will not 

be included as part of the total vote cast. 

Similarly, all committee members who recuse 

themselves due to conflict of interest or absent 

shall be recorded as such, and their votes will 

not be counted toward the number of votes cast. 

 Votes, both abstentions and recusals 

will be considered in order to establish a 

quorum. And so, based on that, I would say that 

the voting mechanism for the recommendations is 

two-thirds, and it would be two-thirds within --

I guess, no, within the workgroup, I don't know 

that you all need to vote to bring forward. 

 I think you just bring it forward 

because you develop the work. You guys have 

worked on it already, and so I think you just 

bring it forward to the committee. And then twothirds of the committee has to vote to approve 

it. Right? 

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 CHAIR CARR: Yes. 

 MR. HUGHES: All right. Was that in 

there already? 

 CHAIR CARR: No, you just read it, and 

that's what I said. 

 MR. HUGHES: Okay. 

 CHAIR CARR: All right. That's it. 

 MR. HUGHES: All right. So the 

committee leads will find a table, and I guess if 

anybody wants to go out. 

 MR. WILKINS: Trade group is coming 

right here. 

 (Whereupon, the above-entitled matter 

went off the record at 8:03 a.m. and resumed at 

9:34 a.m.) 

 CHAIR CARR: Okay. So since we are 

starting back a little bit late, if this is okay, 

and I'll ask you for a consensus on this. We 

will go, and now we will cut everybody to 30 

minutes, which will still keep us on time. 

 But at the end, if we feel that we 

still need more time, we could always stay, but 

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to try to keep us on task to be done by 12:00. 

So we will go in the same order we presented in 

yesterday, and each group will have 30 minutes of 

discussion. 

 If it takes less than that, then 

great, we'll move on. If it takes longer than 

that, we'll table that until the end, and we have 

time to come back. So the first group -- who 

went first yesterday? 

 MR. WILKINS: Trade did. 

 CHAIR CARR: Trade went first 

yesterday. They will start, and we'll break 

after that or break at 10:00 o'clock and come 

back. 

 MR. WILKINS: You're going to put this 

on the screen, Darrell? 

 MR. HUGHES: Yes. It's coming on 

there. It's coming. All right. 

 MR. WILKINS: All right. My name is 

Tommy Wilkins, and I'm going to discuss the Trade 

workgroup, trade promotion. We have a couple of 

things we want to talk about. 

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 Our first recommendation comes in the 

form of the Trade workgroup recommends that the 

Fruit and Vegetable Industry Advisory Committee, 

that it should inform the Secretary of its 

concerns, and request that the Secretary make our 

position known to the President and Congress. 

 The critical importance of ensuring 

that export market promotion programs continue to 

be made available for the United States 

agriculture to successfully compete against 

foreign competition and export markets and that 

available funding for these programs be increased 

to offset the balance of trade restrictions and 

impacts of trade disputes. 

 The Trade group recommends that the 

Fruit and Vegetable -- are we going to do these 

one at a time or as a group? 

 MR. HUGHES: I think you would, based 

on the buckets that you were going through, you 

would read each one and then talk about the trade 

promotion recommendations as a whole, right? 

 CHAIR CARR: Well, it's a part of the 

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group. While we're here, if they're -- provided 

we vote the whole package, but let's just go with 

each one. So does anybody have a problem with 

the number one statement on the board? 

 MR. WILKINS: Do we vote now? 

 CHAIR CARR: No. We'll come back and 

do it all together. 

 MR. WILKINS: Our second bullet point 

is the Trade workgroup recommends to the Fruit 

and Vegetable Industry Advisory Committee that it 

should inform the Secretary of its interest in 

developing a sustaining U.S. grown food program 

that offers additional promotional support for 

helping qualify agricultural competitors to 

compete against foreign competition within the 

United States. 

 CHAIR CARR: Questions or concerns? 

 MR. WILKINS: Number three. 

 MR. HUGHES: There isn't a number 

three for trade promotion. Is there? There's 

only these two. Do you want me to go back to Buy 

American? 

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 MR. WILKINS: We had three categories. 

This is the first category that we're discussing. 

 CHAIR CARR: So let's move on to the 

second category. 

 MR. HUGHES: Okay. 

 MR. WILKINS: So the next category. 

 MR. HUGHES: Okay. It's Buy American. 

 MR. WILKINS: All right. In talking 

about Buy American, the committee supports the 

Buy American requirements for school food 

purchase, enhanced by Section 4207 of the 

Agricultural Improvement Act of 2018. 

 The committee requests that the 

Secretary consider meaningful improvements in the 

guidance for and enforcement of this provision 

and ask the Secretary to keep the committee 

advised of his actions. 

 Recommendation revisions include the 

following. Strike the significant cost different 

language from the Buy American exception provided 

to schools. This exemption is significantly too 

ambiguous and does not recognize the myriad of 

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fruits and vegetable options that are available 

should the desired first choice be costprohibitive. 

 Require that public notice when 

schools elect to purchase foreign-sourced food 

products instead of domestically produced, 

including and required that school maintain 

documentation to justify foreign purchase of 

fruits and vegetables over domestic. 

 For instance, whether alternative 

supply sources were considered, whether bids were 

sought at the best time of the year to allow for 

domestic participation, whether substitutions 

were considered, for example, applesauce instead 

of peaches, pears instead of mixed fruit 

cocktail, et cetera. 

 MR. HUGHES: And there's a third one 

here. 

 MR. WILKINS: Establish financial or 

commercial, which restrict from supplying schools 

penalties for food distributors that misrepresent 

their food products or who switched foreign 

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source product for contracted domestic food 

products. 

 CHAIR CARR: Go back to the other 

page. Any questions or concerns with this page? 

Next page? Any concerns with the last part? 

Moving on. 

 MR. WILKINS: So we're addressing 

protecting U.S. growers, and our recommendation 

is remedies for domestic product growers need to 

be strengthened. A resolution process should be 

added to take into account domestic regional 

production of horticultural products that allows 

for sustainable market access to foreign 

suppliers. 

 CHAIR CARR: Is this in regard to 

USMCA or -- is that the intent? You're trying to 

address that. 

 MR. WILKINS: Yes. 

 CHAIR CARR: If there's no comments or 

concern, then we will take a motion. These are 

now I guess admitted in the form of a motion to 

be accepted by the committee. 

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 MR. BOWMAN: At the committee level, 

there's a lot of debate. And this is the closest 

compromise we could come up with that addresses 

the seasonality issue that we thought could get 

past the committee. 

 CHAIR CARR: My only concern is it 

doesn't address trade agreements. Could you add 

under current and proposed trade agreements, 

remedies for domestic producer growers? Maybe 

strike that, but I don't know. 

 MR. WILKINS: So maybe --

 MS. HARPER-LARSEN: I have a 

discussion point, too. Where did we stand when 

we had the discussion point relating to H.R. 101 

and Senate Bill 16, the improving domestic 

production, strengthening domestic production? 

Would that be separate? 

 MR. BOWMAN: When we thought that it 

was two-thirds of the committee to get it past, 

we didn't. We didn't want to bring up something 

that was going die on the floor, but if somebody 

wants to make a motion, we can vote on it I 

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guess. 

 MR. WILKINS: So there's two things. 

If you have something to say, go ahead. 

 MR. WINGARD: I make a motion that we 

insert the words in front of remedies in all 

trade agreements called. Then it would read in 

all trade agreements call out remedies for 

domestic produce, so and so on. 

 MR. WILKINS: I don't have a problem 

with that, and addresses some of what you're 

saying. But it does not address what you're 

saying. 

 MS. HARPER-LARSEN: I'll make a second 

motion. I'll second Charles' motion to add the 

verbiage in front. I second the motion. 

 CHAIR CARR: Darrell, can you put it 

back up there? 

 MR. HUGHES: Yeah. I'm pulling it up 

here. 

 CHAIR CARR: So will the working group 

accept that as a friendly amendment, or do we 

need to vote on this and have a discussion? 

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 MR. WILKINS: I believe that's a 

friendly --

 MR. WINGARD: It was meant to be 

friendly. 

 (Laughter.) 

 CHAIR CARR: The Chair recognizes 

that. Darrell, you going to type that in up 

there? I think that was a simple change, so 

outside of that, is there any other discussion? 

 MS. GLEASON: I'm just curious what 

the resolution process looks like or what the 

trade group envisions that will do. 

 MR. WILKINS: The whole intention is 

to prohibit any product from any country coming 

in below cost, which is sometimes referred to as 

dumping. So there has to be a process that would 

identify and address that. 

 CHAIR CARR: So to be clear, I'm going 

to vote, but the resolution process already 

exists, but currently right now the resolution 

process means that you must be -- you must have 

25 percent of the production within a 365 day 

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calendar period to be able to bring it forward. 

 So this is addressing a regional area, 

like Florida strawberries who has 75 percent of 

domestic production in February and March in the 

country and can then bring a resolution, but 

right now they cannot do that because they don't 

have enough production in 365 days. So this is 

to address regional and seasonality issues within 

current trade agreements. 

 MS. HARPER-LARSEN: Thank you. 

 MR. WILKINS: Yes. So in all trade 

agreements there would be remedy for domestic 

produce growers. When you get to the strength, 

and then that's what we're addressing is the fact 

that the instance that the chairman just 

mentioned. 

 CHAIR CARR: So should you say that we 

recommend that the Secretary works with the 

Administration, because there's really not a 

recommendation here. 

 MS. GLEASON: It seems like the 

resolution process needs to be strengthened if 

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that already exists. 

 MR. WILKINS: I like where we're going 

with this. We just have to get this in a form 

that we can put up on the board. And the team 

can jump in and either add or correct me as I go, 

but we may recommend to Secretary Perdue that he 

addresses the resolution process. 

 CHAIR CARR: You could do that, or you 

could leave it as a statement and just say the 

Fruit and Vegetable Advisory Committee believes 

that all trade agreements, remedies for the 

growers -- the resolution process should allow 

for reasonable production. 

 MR. WILKINS: So that would be another 

line in the bottom. So let's address that one 

more time. 

 CHAIR CARR: So the question is, does 

this group want this to be a recommendation to 

the Secretary, which a recommendation, if I 

understand right, a recommendation gives him --

what we were asking him to do, and he has to 

report back on what he's done with that 

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recommendation. 

 Or you could simply have a statement 

that says that this committee believes that all 

trade agreements should have the ability for 

regional industries to be able to bring 

complaints for dumping through the resolution 

process that already exists. 

 But the problem is it doesn't allow 

for regional areas to bring those complaints. So 

the first question is do you want this as a 

recommendation, which means you're asking the 

Secretary to do something. 

 We could ask the Secretary to -- that 

he should work diligently with the Administration 

that all trade agreements included. That would 

be a recommendation. Or you could simply state a 

statement that this committee believes that in 

what all trade agreements should have. What's 

the pleasure of the group and your working group? 

 Recommendations/statements, you can 

choose either one. 

 MR. WILKINS: Can we erase the word 

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statement then? 

 CHAIR CARR: So if you're going to do 

that, then we recommend that the Secretary of 

Agriculture work with the Administration that in 

all trade agreements --

 MR. HUGHES: The Admin and what? 

 CHAIR CARR: The Administration --

 MR. WILKINS: -- works with all trade 

groups. 

 CHAIR CARR: Works with the 

Administration to incorporate -- in all trade 

agreements incorporate the following. 

 MR. HUGHES: With all trade groups. 

 MR. WILKINS: I think we're going to 

abort the trade groups. We're saying that the 

Secretary work with the Administration that in 

all trade agreements. All right. Can you just 

get that as one screen instead of the bullets to 

the left? There you go. 

 MR. HUGHES: You can use shorthand 

too, because I update everything. 

 MR. WILKINS: So we recommend the 

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Secretary work with the Administration in all 

trade agreements. Any help here is fine. 

 CHAIR CARR: That all trade agreements 

contain remedies for domestic produce. How about 

that? 

 MR. WILKINS: And that all trade 

agreements --

 CHAIR CARR: Contain. 

 MR. WILKINS: -- remedies. Does that 

answer that? So then in all trade agreements. 

All right. So I'm going to read this again. We 

recommend that the Secretary work with the 

Administration so that all trade agreements --

 MR. WINGARD: So within all trade 

agreements. 

 MR. WILKINS: So that within all trade 

agreements, remedies for domestic produce growers 

need to be strengthened. The resolution process 

should be added to take into account domestic 

regional production of horticulture products that 

allows for sustainable market access to foreign 

suppliers. 

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 CHAIR CARR: So the resolution process 

already exists, so it doesn't need to be added. 

The resolution process should include. It's 

already there. The resolution process is already 

there, so it's not to be added. It's got to --

 MR. WILKINS: It should be --

 MS. GLEASON: Domestic regional 

production of horticulture products should be 

added to the resolution process. It should be 

reversed. 

 MR. WILKINS: So not taken but can be 

added to. 

 MR. HUGHES: So you're saying domestic 

regional production of horticulture products that 

allows for sustainable market access to foreign 

suppliers should be added to the resolution 

process. Did I hear that --

 MR. WILKINS: No I think that's in the 

wrong place. 

 MS. GLEASON: Domestic regional 

production of horticulture products should be 

added to the resolution process to allow for 

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sustainable market access to foreign suppliers. 

Is that -- no? 

 CHAIR CARR: I think we're going in a 

different direction. Can we cut and paste the 

original back up there since we chopped this one 

up so much? It's really the resolution process 

should allow for regional. 

 MR. HUGHES: Oh. All right. 

 MS. GORDON: I have it queued up on my 

laptop if you guys want me to read it quick, the 

original. 

 MR. HUGHES: No, that's fine. I'm 

just going to save this as a V2 real quick and 

then open up both. 

 MS. GORDON: The original statement 

read remedies for domestic produce growers need 

to be strengthened. A resolution process should 

be added to take into account the domestic 

regional production horticultural products that 

allows for sustainable market access to foreign 

supplies -- suppliers. 

 MR. ZEA: In my opinion, and I'm a 

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member of the subcommittee, I still believe that 

the way that it is written places influence on 

foreign suppliers rather than domestic producers. 

 CHAIR CARR: Yes, I don't understand 

the last sentence with the foreign suppliers. 

 MR. ZEA: It's a way of suggesting 

that we are not trying to regulate the provision 

of foreign supply in the United States any more 

fully than it is currently done, but we're 

emphasizing that domestic production should 

receive more attention. 

 MR. WILKINS: So a supplier that 

covers a retailer 365 days a year has got to have 

the ability to source from wherever that is. 

What we're wanting to do is we give an American 

farmer a chance without changing any of the trade 

particulars that we have right now. 

 So what we're wanting or what our 

intent was to put a little different spin on the 

word seasonality with the -- to protect the 

regional farmer. And I just believe that we, you 

know, a majority of the people that are taking 

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care of retailers 365 days a year have -- have 

got to have access to other supplies other than 

domestic. We just need to protect them from any 

 CHAIR CARR: So let me ask you this 

question to that. So in that situation where 

you're supplying 365 days a year, and you're 

actually able to buy products at below production 

cost in the U.S. But you have products available. 

On a regional basis, wouldn't have -- would you 

allow for that regional producer, that regional 

industry to then make a claim against that --

Mexico allowing products to come up here at that 

cheap rate during a period of time. 

 MR. SIEVERT: Doesn't the original 

piece go back to that, basically anti-dumping, 

right? I mean that's really what you're trying 

to protect. You're trying to protect against 

Florida berries being $8.00 and Mexico berries 

coming across at $4.00, right? 

 I mean that's -- you're looking at the 

dumping not -- I mean whoever's supplying that 

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retailer year round is going to do the best job 

they can to stay competitive, right? You're 

protecting against dumping. That's what you're 

looking for. 

 CHAIR CARR: So the southeast is 

asking that the ability to make a regional claim 

on dumping be included in the trade agreements. 

That's what's really happening here. They note 

in certain industries they don't have the ability 

to do that in certain timeframes. 

 So basically just asking that the 

resolution process take into account regional 

production is what we're asking for. Where you 

go with the foreign supply down below that, I'm 

not sure how that ties in. It's just making a 

request that that be -- the resolution process 

right now precludes a regional industry from 

bringing a challenge. 

 MR. SIEVERT: Because of the 

percentage of year they provide supply. 

 CHAIR CARR: Right. 

 MR. SIEVERT: Okay. So that's 

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probably where that needs to go then, right? 

 MS. GLEASON: So take out the last 

part about the last part about sustainable market 

access for foreign suppliers? 

 MR. WILKINS: I'm going to battle that 

one a little bit because I don't want to lose the 

sight that companies in the United States support 

a retailer for 365 days a year, we have to 

maintain that we have access to alternate 

suppliers, and that's important. 

 Okay. But I do think that we could 

work on some verbiage around what you're saying 

there. How do we -- so the remedies for domestic 

produce needs to be strengthened. I think right 

there is where we're looking for maybe a little 

change in verbiage there. 

 CHAIR CARR: So let me do this. It's 

time for break. We'll take a break. Hopefully, 

during this break somebody can come up with some 

language that we can come back and discuss. 

 If not, we're going to need to go on 

to the next group, and then we will come back and 

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discuss this then. Again, we've got to give 

consideration to all the groups. So if that's 

okay with everybody, we'll be back in 10, 15. 

 (Whereupon, the above-entitled matter 

went off the record at 10:02 a.m. and resumed at 

10:15 a.m.) 

 CHAIR CARR: Okay. I think we have 

language here that addresses both parties 

concerns. If we can come to a real quick 

consensus on this, we're going to do this. If we 

can't, we're going to punch it back. So Tommy, 

why don't you read it? 

 MR. WILKINS: On the recommendation of 

attending U.S. growers, we recommend that the 

Secretary work with the Administration so that 

within all trade agreements, remedies for 

domestic produce growers need to be strengthened. 

 A resolution process should be added 

to take into account seasonal domestic production 

of horticultural products in regards to antidumping. This provision should not preclude for 

affairs sustainable market access to foreign 

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suppliers. 

 MS. HARPER-LARSEN: I make a motion 

that we accept this as written. 

 CHAIR CARR: The way we've been 

handling this is if there is a consensus on this, 

which we already have consensus on everything 

else they put forward, then the group is putting 

this forward as a recommendation. We vote on it 

as one. Let's be clear. Do we have consensus on 

this language as written? Is there any further 

work to be done? 

 MR. ZEA: I'd just suggest a technical 

amendment. Take out the word for between 

conclude and fair. 

 CHAIR CARR: Okay. That's done. Make 

that happen please. I know we've broke it up on 

this, but we have gone through each one of their 

recommendations. And Tommy, is it your intent 

for your sub working group to put this forward as 

one big package, and you would accept a motion to 

be approved? 

 MR. WILKINS: Yes, I would. 

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 CHAIR CARR: Do I have a motion? 

 MS. HARPER-LARSEN: You do. 

 CHAIR CARR: Do I have a second? 

 MR. WINGARD: Second. 

 CHAIR CARR: Any discussion? All 

those in favor of passing the Trade group 

recommendations, please say aye. 

 (Chorus of ayes.) 

 CHAIR CARR: Any opposed? Good. One 

down. So who's next? 

 MR. WILKINS: All right, Steve. Show 

them how it's done. 

 MR. SMITH: Thank you. I hope ours 

goes maybe a little quicker and smoother, but you 

never know. 

 MR. WILKINS: I will not take that 

personally. 

 (Laughter.) 

 MR. SMITH: While Darrell's putting 

this up, we made a few editorial changes, not 

substantive changes. We did a little 

wordsmithing to some of the paragraphs. 

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 MR. HUGHES: Can I go directly to the 

research recommendation? 

 MR. SMITH: Yes. So from what we had 

yesterday --

 MR. HUGHES: One second. I notice 

that the text on this slide changed, and I don't 

know. Is this for background? 

 MR. SMITH: Yes. 

 MR. HUGHES: Okay. Got it. So we can 

skip over that. 

 MR. SMITH: I didn't get the font 

change. Okay. 

 From what we had yesterday, we believe 

that all specialty crops should be protected from 

new and emerging crops that are specifically 

listed as specialty crops in the Farm Bill. 

 Do you want to do both bullet points? 

Okay. And the Fruit and Vegetable Industry 

Advisory Committee is very concerned about the 

impact on the specialty crops from the recent 

decision by the USDA to define hemp as a 

specialty crop. 

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 CHAIR CARR: Any questions on that 

before we move on? All right. 

 MR. SMITH: All right. Here's our 

recommendations. We request that the Secretary 

support additional base funding for applied 

specialty crop agricultural research at land 

grant universities and experiment stations and 

cooperative extension that can be used to address 

regional and local priorities driven by user 

needs. 

 And number two, we recommend that the 

Secretary review this decision, including hemp as 

a specialty crop, looking into potential native 

impacts to the existing specialty crops; in 

particular, the impacts on federal funds for 

research initiative grants. 

 If in any way it's determined that 

hemp will dilute the limited research funds, the 

Fruit and Vegetable Industry Advisory Committee 

recommends that the Secretary reclassify hemp or 

limit the crop from access to SCRI funds until 

additional money is appropriated. 

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 Is there a third one there, three and 

four? The committee recommends that the 

Secretary review research grant eligibility 

criteria and process with the goal of increasing 

the opportunity for private organization. 

 We project -- project funding in 

public and private projects. Increase outreach 

and involvement of potential industry applicants 

to determine how future grants can be available 

for emerging technology, development and 

agriculture. 

 And number four, the committee 

recommends the Secretary increase grant funding 

available dedicated to the development of new 

labor saving technology and equipment development 

with the goal of recruiting agriculture, labor 

efficiency and demand. 

 CHAIR CARR: I have a question on 

number four. 

 MR. SMITH: Okay. 

 CHAIR CARR: So when you say increase 

grant funding available for, is that new funding, 

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or are you asking the Secretary to mandate a 

portion of the current SCRI funding to go to 

labor funding? 

 MR. SMITH: John. 

 MR. CHANDLER: Yeah, I think the 

intent is not to be that specific, to allow the 

discretion of the Secretary depending on funds 

available or how it would best fit in with 

existing programs. But the report is really 

driven as addressing some of the labor concerns 

by increasing some technology solutions. 

 CHAIR CARR: So my concern and serving 

on the Dairy board where we reviewed these grants 

and the process for the grants, it could be 

interpreted by the Secretary that you're saying 

that he should be dedicating a portion of these 

funds. 

 That's my only concern. If you're 

giving him a recommendation that he increases 

funding, and the only funding for this research 

right now is coming out of these SCRI grants, 

then a response could be he says 10 percent of 

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these funds have to go to this technology. 

 That would be my concern. I don't 

disagree with the overall concept, but dedicating 

those funds or mandating those funds go to 

certain areas are a concern. 

 MR. CHANDLER: With that concern, 

would you have a suggested amendment that you 

think might keep the intent of allowing 

flexibility for the Secretary because I wouldn't 

want to preclude him from taking an action would 

benefit the entire industry? 

 MR. WINGARD: We could put it into 

that sentence, into that. We prefer that this 

funding be new funds. 

 MR. CHANDLER: Explore additional 

funding, if possible, or if available. 

 (Off-microphone comments.) 

 MR. CHANDLER: So what was it you 

said? 

 MR. WINGARD: We're prefer that this 

funding be -- we prefer that this be new funding. 

 MR. SIEVERT: How about provide new 

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funding? 

 MR. CHANDLER: What's that? 

 MR. SIEVERT: What about provide new 

funding, instead of increase funding? How about 

we recommend that new funding is available? 

 MR. CHANDLER: I'd hate for him to not 

be able to -- I mean, my goal would be to keep it 

as broad, allow him as much freedom of action as 

possible, but if you want to limit him to just 

new funding. 

 CHAIR CARR: Let me ask. Would you 

take out the word increase and just say 

prioritize? 

 MR. CHANDLER: Okay. 

 CHAIR CARR: Because increase means 

you should be going up. Prioritize just means 

they could make that -- so right now with the 

SCRI fundings, there's already a huge portion of 

that funding that goes to citrus right off the 

top that was mandated. 

 Okay. So now you're left with all the 

other commodities to feed for what's left after 

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you remove the citrus budget, which is $45 

million. So at that point, the pot is only about 

60 or 70. I don't remember the exact number. So 

after you do that. So mandating you increase 

funding to it but if you prioritize it, then at 

least that's what -- they'd go back and do that. 

 MS. HARPER-LARSEN: And each of these 

grants does already have established priorities. 

And when you apply, so we recommend 

prioritization. That will give a definitive to 

the Secretary and his office to just move this 

stuff up the chain. 

 MR. CHANDLER: That's fine. So you're 

happy? 

 CHAIR CARR: Yes. 

 MR. CHANDLER: Happy with that then? 

Okay. The committee recommends that the 

Secretary prioritize grant funding available 

dedicated to the development of new labor saving 

technology. 

 CHAIR CARR: Any other -- so this --

 MR. LIPETZKY: Can we go back to 

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number 2? And this might be just making it more 

of a point of clarification. It looks like 

you've got the SCRI grant. So is there any 

consideration or discussion around the specialty 

crop block grant program component of this that 

involves specialty crops? 

 MS. HARPER-LARSEN: That's a good 

consideration. 

 MR. SMITH: We did talk a little bit 

about specialty crop block grants. And our 

thought was to leave the states alone in doing 

what they wanted to do with those rather than 

coming from a national perspective. 

 MR. LIPETZKY: And that helps because 

somebody who does administer that side of it, I 

was kind of wondering where that fine line would 

be for states dealing with hemp as well as that 

hemp direction coming from USDA. 

 MS. HARPER-LARSEN: But you guys do 

get prioritization directly from USDA. You can 

include that type of verbiage in this same thing 

as well for specialty block grant as well as SCRI 

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to prioritize. 

 MR. SMITH: We intentionally left out 

the state specialty crop block grants. 

 CHAIR CARR: So this is the full 

recommendations on research. If there's not any 

further discussion, we'll move to your next 

topic. 

 MR. SMITH: All right. On crop 

insurance, we make a recommendation that we urge 

the Secretary to make it a goal to ensure that 

fruit and vegetable farmers have access to 

coverage options that are with crop farmers for 

crop insurance generally works well, both in 

terms of effectiveness in addressing the perils 

unique to the crop and affordable premiums. A 

lot of this was your language, wasn't it? 

 CHAIR CARR: Any discussion on this? 

Next topic. 

 MR. SMITH: The overspending off 

target. Recommendation one is that they should 

recognize that they can and will be off target. 

And therefore, reasonable tolerance should be 

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established, but first round application should 

be available for mild and coast sensitive plant. 

 That application should be limited to 

more desirable circumstances, such as lower 

temperature of humidity, pre-plant, preseason and 

other factors that would reduce the potential for 

moving off target. You want to do these 

individual? 

 CHAIR CARR: Well, yeah. We'll do 

this. So my only thing there is you're saying 

USDA, EPA. So again, a recommendation -- for us 

to put a recommendation for a motion is it needs 

to be a recommendation to the Secretary. 

 So my suggestion would be you should 

say the Secretary of Agriculture should work with 

EPA and FDA to recognize. 

 MR. SMITH: I don't have any problems 

with that. 

 CHAIR CARR: Again, it's going to come 

back because I think we're going to probably --

this is pretty shaky as well. A recommendation 

from this group is often -- Darrell, you correct 

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me if I'm wrong, but a recommendation from this 

committee has got to go to the Secretary. 

 And a recommendation means he's got to 

come back and report to us what he's done with 

that recommendation. By simply saying that, we 

have no purview to recommend the EPA or FDA do 

anything, so --

 MR. SMITH: That's correct. 

 CHAIR CARR: If your intent here is to 

start the conversation, then your request or your 

recommendation should be to the Secretary of 

Agriculture should do. 

 MR. SMITH: Should -- what word? 

 CHAIR CARR: Should work with EPA and 

FDA to recognize -- remember, your preamble 

before that talks about the science and all that. 

You're assuming that he buys into that. 

 MS. HARPER-LARSEN: And I'm sort of 

wondering why you're not asking for a mandated 

demand or sync or technology or something like 

that to be included into this pesticide 

manufacturer, like make it a way your molecules 

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don't drift. 

 (Simultaneous speaking.) 

 MR. SMITH: I don't think we want to 

get into label instructions about additives and 

all. 

 MR. WINGARD: I think that would be 

covered under desirable circumstances or more 

desirable circumstances. 

 CHAIR CARR: So are we good there? 

 MR. HUGHES: Yes. I was just adding 

-- it's a separate recommendation from the first 

one? 

 MR. SMITH: No. 

 MR. HUGHES: Okay. So then we add it 

back to --

 MR. SMITH: All right. Yes. 

 MR. HUGHES: There we go. 

 MR. SMITH: All right. So we probably 

need to add language that we strongly recommend. 

 MR. WINGARD: Go back to that one. 

Something's changed. Something's not right. We 

started out with remedies for domestic produce 

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grown --

 MR. SMITH: That's still two things. 

 MR. WINGARD: Yeah, but that's from 

trade. 

 (Off-microphone comments.) 

 MR. SMITH: All right. Back to number 

two. Sorry. I'm assuming we need to get the 

same language in here under the recommendation, 

that the Secretary recommend the Administration 

for extending the max of gene effects obtained or 

any new formulations for in crop use on soybeans 

and cotton not be renewed when the current 

registration expires. 

 In addition, we recommend that the EPA 

evaluate the performance of these products after 

the 2019 season and make an appropriate judgment 

about their use in 2020, even before the 

registration expires. 

 We also recommend that the USDA 

pesticide data program work with EPA to ensure 

that the dicamba registration is not renewed 

until such time when research can prove with 

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certainty that specialty crop producers would not 

be adversely affected by any form of off target 

movement, including volatility. 

 CHAIR CARR: So back up to number one. 

Two things. Where does the bio come from, and 

could that just be a question that determines, 

say this is good now. But most in turn by 

sensitive plant versus sensitive crop production 

because a sensitive plant could be anything. But 

if your concern is about protecting the other 

crop production, I get that. 

 MS. GORDON: Non labeled plants and 

non labeled crops. 

 MR. SMITH: I'll give you an example. 

I lost all my trees in my home farm. That's not 

a crop. So I would prefer to keep plant because 

it's not a crop. 

 (Off-microphone comments.) 

 MR. SMITH: The more mild kind of 

comes on Florida label language, also out of 

Washington and Oregon on some of these products, 

and certain counties in Michigan also have that. 

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 CHAIR CARR: Any other questions? Do 

you have another recommendation under this one? 

 MR. SMITH: Yes. 

 CHAIR CARR: Any on this page before 

we move over to page 2? 

 MR. HUGHES: Well, yes. There's 

something that I want to make sure that you guys 

take into consideration, and that's Brenda Foos's 

comment yesterday about the pesticide program and 

that maybe that should be USDA should because of 

the Office of Pesticide -- Pest Management. 

 MS. GLEASON: Pest policy. 

 MR. HUGHES: Pest policy or something, 

and that was the first time I heard about that 

office. And I just wanted to make sure that you 

guys take that into consideration because that 

program may not achieve --

 (Simultaneous speaking.) 

 MS. HARPER-LARSEN: That was the 

appropriate agency --

 MR. SMITH: Right. 

 MS. HARPER-LARSEN: -- to use hard 

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data to work with the EPA. 

 MR. HUGHES: But as far as policy, but 

our program is data based. It's not policy 

based. And it seems like this is a policy 

recommendation. 

 MS. GLEASON: Can we add the OPP, the 

other office to that as well as USDA, PDP and 

OPP, Office of Pesticide Policy, or whatever the 

other office is called. 

 MR. HUGHES: You can do as you please. 

I would just say that my suggestion would be to 

make it broad so that if we are identifying the 

wrong sub entity, the Secretary is able to send 

it to a different USDA organization say like do 

XYZ if he has the ability or whoever has the 

ability to do that. 

 MR. SMITH: Well, her group actually 

doesn't make the tolerances. That is EPA that 

does that. 

 MS. GLEASON: So I think he's 

suggesting that we just say that USDA should work 

with the EPA. 

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 MR. HUGHES: That is what Brenda's 

recommendation was, yes. 

 CHAIR CARR: It says the Secretary? 

 MS. GLEASON: No OPP, instead of 

naming a specific agency, just --

 CHAIR CARR: Again, I would recommend 

you go with say the Secretary of Agriculture 

should do this and remove all the rest of that. 

Just make it consistent. Your recommendations 

are to the Secretary. 

 So that last sentence as of right now 

you say recommend that USDA Pesticide Data 

Program. It should be you recommend the 

Secretary of Agriculture could work with EPA to 

ensure. 

 MS. GLEASON: Right. 

 CHAIR CARR: Yes. That's all you're 

doing is inserting that. 

 MR. TISON: I had one thing on the 

word sensitive up there. Is that too broad or 

not explain enough in that you have something 

that's a plant that distinguished by the state of 

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the federal government by being an essential 

plant. Is that going to end up with somebody in 

a lawsuit or something? I know what you're 

trying to say, but are we being too broad there 

on that one? 

 MR. SMITH: I'm not sure how you would 

make that any different particular meaning. 

 MS. GLEASON: Non-target? 

 MS. GORDON: Yes, non-target type 

language. 

 MR. SMITH: I'd be okay with nontarget for that in number one. 

 MR. HUGHES: Where is --

 MR. WINGARD: That would be the tree 

on the side of the field then. 

 MR. SMITH: That's technically -- by 

label, that is -- it does matter. We can say 

sensitive, non-target plant. 

 MR. WINGARD: That might be the best 

yet. 

 MR. HUGHES: I would put a comma after 

sensitive. Any further on this page? 

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 MS. GORDON: It doesn't read right. 

 MR. HUGHES: What did you say, Julie? 

 MS. GORDON: It does not read right, 

number two doesn't where you added that. 

 MR. HUGHES: This goes away. 

 MS. GORDON: If you're going to add 

that, don't we want to just take off the 

beginning that says the Secretary should because 

we're saying he should, then he shouldn't. 

 MR. HUGHES: Right. So I added that 

because I didn't know who --

 MS. GORDON: Oh, okay. All right. 

There you go. 

 MR. HUGHES: Give me one second. That 

needs a comma. Get rid of this red. 

 CHAIR CARR: All right. Next page. 

 MR. SMITH: This is switching gears a 

little bit. USDA, EPA, FDA and we may have to do 

the same language again -- to recognize the 

latest legacy materials that have long been 

prohibited and not been applied to fruit and 

vegetable crop are now being detected in very 

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small levels. 

 The presence of a legacy material 

should not be considered an adulterated product, 

nor should the producer be subject to regulatory 

action. So how do we need to start that out 

different, Darrell? 

 (Off-microphone comments.) 

 MR. SMITH: Okay. And then number 

four, we recommend the USDA use the same 

language, require biotech developers to seek the 

necessary reviews by USDA for seed genetics and 

EPA for the corresponding pesticide registration 

simultaneously resulting in a joint approval 

process and the two agencies increase 

collaboration for seed genetics and corresponding 

pesticides are approved. 

 We hope that a simultaneous and joint 

approval process will serve to facilitate 

discussion between the two agencies and prevent 

confusion among farmers. 

 And again, this originated from the 

situation where the seed was registered or was 

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approved two years before the product was 

registered and kind of forced -- sort of forced 

EPA's hands and farmers were using the product 

before it was actually registered. 

 CHAIR CARR: So is the one agency EPA, 

so it should be the Secretary should work with 

EPA to require? Is that cleaner language now? 

 MR. SMITH: Maybe get rid of this. 

This that was highlighted there. There you go. 

 CHAIR CARR: Everybody good with this? 

All right, next one. 

 MR. SMITH: Okay. Again, this is 

about label language. The USDA should work with 

EPA -- again, we'll leave that other language in 

there -- to encourage chemical manufacturers to 

write their chemical labels in a uniform manner 

so that producers can easily determine the 

correct requirements of the final material. 

 And even the Secretary should work 

together to establish crop groups that are 

consistent with each other with industry 

standards, terminology, and other accepted 

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practices. 

 And this comes from the problem of how 

crops are grouped together in different -- the 

same active ingredients are accrued on one label 

but not another label. Yeah. 

 MS. HARPER-LARSEN: So on Number 1, 

instead of word, encourage, I think it's 

appropriate to say require. There is --

 MR. SMITH: I'd agree with that. 

 MS. HARPER-LARSEN: -- precedent 

already in workplace safety requirements under 

hazard communication for global harmonized 

symbols that mandated specific mandatory label 

writing to an extent. This would further 

strengthen the uniformality. 

 MR. SMITH: Yeah. I agree with that. 

 CHAIR CARR: Any other? And this is 

your last recommendation? 

 MR. SMITH: No, we've got --

 CHAIR CARR: You only have one more? 

 MR. HUGHES: No, that's it. 

 MR. SMITH: That's it. 

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 CHAIR CARR: All right. 

 MR. SMITH: So there's the four. 

 CHAIR CARR: So your intent is, as all 

the changes are made, you want to put this 

forward to this group for approval as 

recommendations from your working group on 

production? 

 MR. SMITH: I move we approve these 

from our working group. 

 MR. WINGARD: And I second. 

 CHAIR CARR: We have a motion and a 

second. Any discussion? 

 (No audible response.) 

 CHAIR CARR: All those in favor of 

approving these recommendations please say aye? 

 (Chorus of ayes.) 

 CHAIR CARR: Any opposed? 

 (No audible response.) 

 CHAIR CARR: Very good. Well, we're 

on time, correct? Going to Labor next. 

 (Off-microphone comments.) 

 MR. ERICKSON: Okay. I'm not going to 

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read through all the extra stuff. I'm going to 

go straight to our recommendations which are here 

in bold. Number 1, the fruit and vegetable 

industry has identified that access to labor --

 MR. WINGARD: Can you zoom in just a 

little bit? Right there, a little bit better. 

Thank you. 

 MR. ERICKSON: There's something wrong 

with this thing. 

 (Off-microphone comments.) 

 MR. ERICKSON: All right. Number 1, 

the fruit and vegetable industry has identified 

that access to labor is our most critical need. 

And we recognize the Secretary's commitment to 

solving the agricultural labor crisis. 

 We recommend that the Secretary work 

with Congress and the administration for 

legislative agricultural immigration reforms. 

These reforms should allow the industry to retain 

the current workforce in light of their ongoing 

critical contributions to the supply chain as 

well as creating a new future flow of labor that 

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makes our workforce affordable, predictable, and 

sustainable. 

 Number 2, we request the Secretary 

form a multi-agency task force including, but not 

limited to, USDA and Department of Labor, as well 

as a nationwide cross section of industry 

stakeholders with the primary charge of studying 

the methodology behind and impact of AEWR and to 

seek alternative solutions for wage 

determination. 

 Number 3, considering that Congress 

has been unable to pass agricultural labor 

reforms, combined with the expedient rate at 

which the agricultural workforce is dwindling, we 

request collaboration between the Secretary of 

Agriculture and the Administration, in particular 

the Secretary of Labor, to broaden the 

interpretation of temporary work to less than one 

year, thereby allowing more agriculture companies 

to participate in the program. 

 Number 4, we recommend that USDA 

research methods to make the farm labor survey 

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more robust and to work with the Secretary of 

Labor to ensure that the refined data which is 

collected is utilized by DOL to support 

agricultural employers and workers. 

 Number 5, we request that USDA work 

with necessary agencies to amend the rule related 

to 51 percent or more of product coming from 

outside the H-2A farm applicant with the 

understanding that the industry has undergone 

significant changes, and that many growers also 

package shipped product for other growers in 

their region. 

 MS. HARPER-LARSEN: Before you go on -

-

 MR. ERICKSON: Yes? 

 MS. HARPER-LARSEN: Can you remove in 

their region? Because we have to recognize that 

these are packed for people, and that regionality 

is ---

 MR. ERICKSON: Loosely defined. 

 MS. HARPER-LARSEN: Yes. 

 MR. ERICKSON: Okay. Number 6, we 

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request the Secretary collaborate with the 

Secretary of Labor to create meaningful impact 

for employers utilizing the H-2A program by 

developing a program to identify preferred 

employers who possess solid history in the 

program for an expedited and more streamlined 

application process. 

 And finally, this Committee commends 

the Secretary of Agriculture and his team for 

their involvement in the development of DOL's 

proposed H-2A modernization rule, July 26, 2019, 

which offers significant reform to the 

application process and, if enacted, should 

benefit all employers. 

 Furthermore, we request the 

Secretary's continued engagement in this process, 

compelling stakeholders to submit comments and 

ensure these new rules are published as soon as 

possible. 

 CHAIR CARR: Very good. Much to 

approve. 

 (Laughter.) 

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 CHAIR CARR: So when we say AEWR, 

let's go ahead and define that a little bit 

better. 

 MR. ERICKSON: Okay. 

 CHAIR CARR: So it's the methodology 

behind the current H-2A program wage rate. 

 MR. ERICKSON: Current H-2A wage rate? 

 CHAIR CARR: And then go ahead and 

type out adverse effect wage rate -- adverse wage 

effect rate. 

 MS. GORDON: And its impact. 

 (Off-microphone comments.) 

 MS. GORDON: Can you go back up to the 

one where you --

 MR. ERICKSON: Well, we're not through 

here. 

 (Off-microphone comments.) 

 CHAIR CARR: So, Bret, one thing, it 

was supposed to look at the effect of that wage 

rate and the ability -- or, really the 

sustainability of agriculture. 

 The whole premise was is for them to 

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study the wage rate and look at the effect that 

it is having, or will have, on the industry, 

based on the current inflationary period we're 

in, and then seek alternatives there. 

 So I don't know how you want to say 

that, but that's your -- and its impact to ---

you're missing after it, and I thought you had it 

before. 

 MR. ERICKSON: I probably did. 

 CHAIR CARR: You could just say to the 

sustainability of production agriculture. 

 MR. CHANDLER: At the very end, right? 

 CHAIR CARR: What? 

 MR. CHANDLER: At the very end after 

wage determination. 

 MR. ERICKSON: Okay. Is that right? 

 CHAIR CARR: So when you're saying ---

back up here a second. You're asking him for 

with the primary charge, to study the rate and 

methodology and --

 MR. ERICKSON: Hold on, hold on, I'm 

not moving that fast. 

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 CHAIR CARR: I was just saying what 

you had up there. To study the methodology on 

the current H-2A adverse wage rate and its impact 

to the sustainability of production agriculture. 

 MR. ERICKSON: And to seek alternative 

solutions for wage determination? 

 CHAIR CARR: That are clear and 

predictable. They are clear and predictable. 

 (Off-microphone comments.) 

 CHAIR CARR: Somebody want to go back 

to Number 1? I think that was Kelly. 

 (Off-microphone comments.) 

 MS. GORDON: It was me. The very 

first sentence says, it says that these are our 

most critical needs. The fruit and vegetable 

industry has identified that labor is our most 

critical need. 

 It sounds like out of all the things 

we're doing here, this is our most critical need, 

to me. So are we identifying that labor is the 

one --- can we say, like, it's a priority, 

instead the most critical need? 

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 MR. HUGHES: Or among our most 

critical needs? 

 MS. GORDON: Yes. 

 PARTICIPANT: I don't have a problem 

with that. 

 MR. ERICKSON: I would say labor is --

I mean, a lot of us, our highest priority because 

the fact --

 CHAIR CARR: Well, if we don't solve 

our labor problem, we're not going to have an 

industry. 

 MS. GORDON: All right, if that's the 

consensus. 

 MS. GLEASON: I mean, it's not a 

problem for my small farmers. But I see where 

it's a problem for the industry. 

 MR. ERICKSON: Must have just 

happened. 

 (Laughter.) 

 MR. HUGHES: Can we go to the very 

last one. I want to read that to see if I've got 

the right insights. 

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 MR. ERICKSON: Which? 

 MR. HUGHES: The very last one, the 

last one above the ---

 (Off-microphone comments.) 

 MR. HUGHES: And so my only comment 

is, I don't know what that recommendation is for, 

because the Secretary will always do that. I 

mean, when you post rules and ask for public 

comment, and then there are regulations that 

require comments to be published, then there are 

rules you have to follow. And so that's the 

only thing that I would say about that. And I 

don't know if that says you were asking him 

something. 

 CHAIR CARR: Yes, we're asking him to 

work with industries like United and compelling 

them to get stakeholders to make a --

 There were only 61 comments filed in 

the last rotation. This one is going to be a lot 

more controversial. So we need the Secretary to 

engage with stakeholders, encouraging their 

membership to supply comments. 

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 PARTICIPANT: Is encouraging a better 

word than compelling? 

 CHAIR CARR: I'm fine with that. 

 PARTICIPANT: Compelling a little 

mandatory. 

 MR. BOWMAN: Mr. Chair, another 

comment, it's a little --- you know, there's a 

push by some people in Congress right now to bring 

in the pool of undocumented workers that are 

currently in the U.S. into the H-2A program, which 

I think is a very, very bad idea. 

 And I don't know, if -- since it's not 

a bill yet, if we would consider making a 

statement on that. Substituting the H-2A 

workforce with undocumented domestic workers for 

five years at a time is not the solution to our 

labor needs. 

 CHAIR CARR: It's come to me that the 

Secretary supported that the last two years 

already. 

 MR. BOWMAN: I have a different opinion 

now. I don't need to feel like I'm at fault 

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there. 

 MS. HARPER-LARSEN: What about 

verbalizing a more streamlined process to take 

undocumented agricultural workers forward with 

citizenship? 

 CHAIR CARR: We already have that one 

in. We have that. I understand what you're 

saying. And I would like to discuss that probably 

offline. 

 MR. BOWMAN: I agree. 

 (Laughter.) 

 PARTICIPANT: I'm okay with that. 

 CHAIR CARR: I don't think the 

industry's going to support that. 

 PARTICIPANT: I don't support that one 

either. But I do support their ability to return 

home and come back later if they so choose. 

 MR. BOWMAN: I think the Congressman 

from Florida is bringing a bill up right now. 

 CHAIR CARR: Yeah. 

 MR. WINGARD: I think that's one of the 

most -- that is one part of the issue that has 

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prohibited us from moving forward on any solution. 

So it's a very divisive issue. And I understand 

what you're saying and agree with you, but I think 

we don't even need to get into that, just because 

of the --- it's a lightning rod. 

 I want to go to five if we could. This 

is Charles Wingard, by the way. Don't we want to 

not say we request the USDA, but we recommend to 

the Secretary? 

 PARTICIPANT: Same language. 

 MR. WINGARD: Well, whatever the 

similar language is to use with the Secretary. 

 CHAIR CARR: Darrell, you've got to 

clean all that up if we missed that somewhere 

where we've said the USDA should or something. 

 MR. HUGHES: Do you want to change it 

all to we request the Secretary? 

 CHAIR CARR: Or we recommend to the 

Secretary. 

 MR. HUGHES: As long as you guys will 

give me that blanket authority to update, 

streamline --

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 MS. HARPER-LARSEN: Do you need a 

motion on that? 

 MR. HUGHES: I don't think so. 

 CHAIR CARR: No, consensus. We're 

voting to approve these, but since we're --- he's 

going to take these and ---

 PARTICIPANT: And fine tune them. 

 (Simultaneous speaking.) 

 MR. HUGHES: Yeah, exactly. 

 CHAIR CARR: We have 30 to 60 days, for 

the record, to clear up our minutes from today. 

So those changes need to go ---

 MR. HUGHES: It's 90 days. 

 CHAIR CARR: Up to 90 days. 

 MR. TISON: I remember seeing the word 

we. I thought I said Chairman of the group. 

 (Laughter.) 

 CHAIR CARR: Chairman of the group is 

the only one who participates. 

 MR. HUGHES: And since we're talking 

about that, one of the things that I will have to 

work with the leads on, does the Chairman want to 

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know? Like, all of you in the findings will have 

to retool or refine that language. So, I mean, 

we're approving the recommendations for this bill, 

like the little finishing touches that need to be 

executed. 

 MS. GLEASON: Can you go back to three? 

I am not sure how this works, because I don't --

I mean, it's not an issue with our small scale 

producers. 

 But if it's expanding temporary work to 

almost a year, and folks then have back to back 

contracts where they are in the country 

indefinitely, then I have a small issue with not 

providing a path to citizenship for those folks. 

 CHAIR CARR: So first of all, being in 

the H-2A program, they have to have no intent to 

immigrate. So you have to take that off. 

 Then the second part of it is mandated 

by current law, they have to serve so many days 

out of the country. Even if the employer does a 

back to back contract, that worker, at some point, 

will have to take a break. It's usually 60 days 

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out of every year --

 MS. GLEASON: Okay. 

 CHAIR CARR: -- that they can't come 

back. So the worker wouldn't be back to back, but 

you allow the employer to have a group of workers. 

We started using this language in the industry now 

called pooling of workers. 

 And so one way Gary -- one way Gary 

could get around this is Gary would have to accept 

that they would not have a continual worker for 

three years, but they could take a workforce and 

work them for nine months, and then bring in 

another workforce. And most of the industry did 

the same thing. 

 And, you know, then they could have --

they would be able to have employees, they just 

wouldn't be the same employees. But at least 

they'd have access to workers. Now that's broad 

strokes. 

 MS. GLEASON: Okay. 

 CHAIR CARR: But in this program, no 

worker coming in can ever have the ability to get 

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in the line for citizenship. They can go through 

the regular process, but it wouldn't be an 

entitlement group, being in this program. 

 MS. GLEASON: Okay. 

 (Off-microphone comments.) 

 CHAIR CARR: A lot of times, people get 

caught up in current workforce versus a guest 

worker. But then guest workers, when they leave 

their families, their wives, their children, they 

don't come in and stay home. They've reached 

their home. It's just the worker coming here 

because of the work. 

 MS. GLEASON: Thank you. 

 CHAIR CARR: Any other questions? I 

know there's a lot of language up there. You read 

the ones with -- do you want to move those forward 

as --

 MR. ERICKSON: Yeah, so do we have a 

motion to approve these? 

 MS. ELLOR: I'll make that motion. 

 MR. TALBOTT: Second. 

 CHAIR CARR: Any discussion? 

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 (No audible response.) 

 CHAIR CARR: All those in favor please 

say aye. 

 (Chorus of ayes.) 

 CHAIR CARR: Opposed? 

 (No audible response.) 

 CHAIR CARR: Very good. Moving on to 

the last group. 

 (Off-microphone comments.) 

 MS. HARPER-LARSEN: Is that good? Do 

you want me to bring it up more? 

 CHAIR CARR: Please. 

 MS. HARPER-LARSEN: All right. Here's 

an issue with our workgroup objective statement. 

This was not modified at all during our last subgroup meeting. Okay, moving forward, I'm going to 

skip over the members of the group. 

 MR. ERICKSON: I have a quick question. 

 MS. HARPER-LARSEN: Yes? 

 MR. ERICKSON: Before you start, did 

you guys address all of the items that Jennifer 

had suggested yesterday? 

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 MS. HARPER-LARSEN: We did. 

 MR. ERICKSON: Very well. 

 MS. HARPER-LARSEN: And with the 

inclusion of an additional item that you guys will 

see at the very bottom. 

 MR. ERICKSON: Wonderful. 

 MS. HARPER-LARSEN: Thank you very 

much. That's why it took us a bit longer, because 

we had that dialogue with her. 

 MR. ERICKSON: Yeah, great. 

 MS. HARPER-LARSEN: And we also had two 

of our tech experts at our table as well. 

 MR. ERICKSON: Perfect. 

 MS. HARPER-LARSEN: Okay. So you will 

see that we have combined some based on that 

dialogue. We wish to protect producers and 

packers from undue economic burden related to 

increased microbiological testing requirements. 

 We would like the USDA to collaborate 

with the FDA to obtain funding for -- on farm 

water sampling education outreach, research 

projects, financial assistance for small and very 

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small operations, a development of online produce 

safety rule grower training programs in English 

and Spanish to meet FSMA requirements. 

 But we encourage the FDA to continue to 

work with growers to develop science-based water 

microbiological testing standards in a timely 

manner. We encourage the re-evaluation of these 

agricultural water testing requirements annually. 

 So we basically took everything that 

relates to water, slapped it into one bullet 

point. 

 MR. HUGHES: So here's a quick question 

for you. With the current setup of this type of 

recommendation, it wouldn't allow me to use the --

- we request the Secretary of Agriculture, blah, 

blah, blah. And so it seems like it fits better 

at the start of the second sentence. And so I 

just want to highlight that so maybe something 

gets ---

 CHAIR CARR: In regards to the second 

bullet point, we ask the Secretary --- can we just 

always say instead of USDA, so it says we'd like 

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USDA, and then data you suggested. Can we just 

say we recommend or we request the Secretary of 

Agriculture ---

 MR. HUGHES: Protect producers, blah, 

blah, blah, okay. 

 MS. HARPER-LARSEN: Okay. So you would 

like --

 (Simultaneous speaking.) 

 CHAIR CARR: -- words to fit that 

later. You give him the ---

 MR. HUGHES: I just wanted to make sure 

that was okay to change back, yeah. 

 MS. HARPER-LARSEN: Yes. 

 CHAIR CARR: That is our tip. 

 MS. HARPER-LARSEN: We want to keep 

that consistency flowing. All right, are we good 

to move on to the next one? 

 (No audible response.) 

 MS. HARPER-LARSEN: All right. We ask 

that Secretary Purdue work with the FDA to 

establish a FSMA produce safety rule and 

preventive controls for human food, fruit, and 

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vegetable-mixed type use operation -- that was the 

inclusion from Jennifer, Regional Grower 

Stakeholder Advisory Boards for collaboration, and 

to seek in programs. 

 MR. SMITH: I think we should take 

Purdue out of that and just ---

 CHAIR CARR: We would change all of 

that to read always the Secretary ---

 (Off-microphone comments.) 

 MS. HARPER-LARSEN: Are we good there? 

 PARTICIPANT: There was difference for 

a second --

 MR. HUGHES: I'll fix all that. You 

don't have ---

 MS. HARPER-LARSEN: Okay. Next, we 

encourage development of a FSMA produce safety 

rule, preventive controls for human food as 

warrants our verification program, interactive 

decision tree to assist entities in determining 

which rules they must comply with and when. Yes? 

 CHAIR CARR: So again, do you say we 

encourage, but we've got ---

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 MS. HARPER-LARSEN: We ask the 

Secretary to. 

 CHAIR CARR: Okay. 

 MS. HARPER-LARSEN: Blanket statement. 

Again, the next --

 CHAIR CARR: So let me just, because 

now he doesn't see any of the language to that. 

And you don't have USDA up there. So can we also 

--- the way I understand it, if we say we 

encourage, that you're going to say we recommend 

that the Secretary of Agriculture? 

 MR. HUGHES: So whenever there's 

encourage? 

 CHAIR CARR: So right now, there is no 

mention of USDA in either one of those two bullet 

points. 

 MR. HUGHES: Right. 

 CHAIR CARR: But that is the intent. 

 MR. HUGHES: Right. So I will put 

there we encourage the Secretary ---

 CHAIR CARR: No, we recommend. 

 MR. HUGHES: We recommend the Secretary 

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develop --

 CHAIR CARR: Yes. 

 MR. HUGHES: Yeah. 

 MS. HARPER-LARSEN: And you can 

wordsmith it. 

 MS. SKELTON: Can I interrupt? You may 

want to encourage the Secretary to work with FDA 

to develop. 

 CHAIR CARR: Yeah. 

 MS. SKELTON: It's their regs. 

 CHAIR CARR: Thank you. Would that be 

the same below two. 

 MS. SKELTON: Same verbiage, yes. 

 MS. HARPER-LARSEN: Same verbiage, we 

encourage development of FSMA, foreign supplier 

verification program information modules, and this 

is a new addition in multiple languages, that are 

prioritized on import volume. 

 So basically we saw, beyond English and 

Spanish, we also had China and Vietnam on the top 

importers list. And that needs to be developed. 

 These modules should focus on educating 

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distributors, wholesalers, cross-docking 

facilities and aggregation entities. 

 CHAIR CARR: Any discussion? 

 (No audible response.) 

 CHAIR CARR: Next page. 

 MS. HARPER-LARSEN: Okay. We support 

providing increased funding on an annual basis for 

personnel marketing and education outreach for the 

USDA Harmonized GAP Plus audit program in an 

effort to more successfully market GFSI technical 

equivalents and FSMA recognition with producers 

and packers. 

 New language -- so we sort of split up 

this, we strongly encourage the Secretary's office 

to engage members of the buying community, 

including retailers, food service entities, and 

consumer brands in discussions relating to GFSI 

technical equivalents. Any discussion? 

 (No audible response.) 

 MS. HARPER-LARSEN: Next, we encourage 

 MR. WILKINS: I've got a question. 

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 MS. HARPER-LARSEN: Oh. 

 MR. WILKINS: I don't like the word 

buying. 

 PARTICIPANT: Call it procurement? 

 MS. HARPER-LARSEN: Okay. Procurement 

community, procurers? 

 MR. WILKINS: I think you could take 

out the buying community, and just say including 

retailers and food service. 

 MS. HARPER-LARSEN: Engage retailers, 

food service entities, and consumer brands in 

discussions for writing the GFSI technical 

equivalents? Charles? 

 MR. WINGARD: I agree with that. 

 MR. SIEVERT: How about distribution 

chain, something like that, and then offer some 

examples? 

 CHAIR CARR: Would it be on farm supply 

chain -- beyond the farm supply chain? 

 MR. SIEVERT: Well, that whole bottom 

part is about the farm. 

 CHAIR CARR: I mean, that's --

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 MR. SIEVERT: That's why the buying 

part was in there. Something about buying food, 

something about the purchasers. 

 MR. WILKINS: But we're trying to get 

retailers and food service to understand Gap 

Plus+. 

 MS. HARPER-LARSEN: Yes. 

 MR. WILKINS: And so it is retailers 

and food service that needs to understand that. 

 MS. HARPER-LARSEN: It's major 

procurement decision makers. 

 CHAIR CARR: But that's beyond 

retailers. 

 MR. WILKINS: Well, it should be ---

 CHAIR CARR: Right. I mean, you have 

wholesalers out there that don't ---

 MR. WINGARD: But shouldn't it be the 

whole supply chain? Shouldn't it be those that 

transport it too? Don't we want them to 

understand this? Anybody who's got control or 

custody of the product so they ---

 MS. HARPER-LARSEN: Not for the audit 

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purposes. You can't audit GFSI. You can't audit 

harmonized Gap Plus truckers. You can't audit. 

That's not applicable to that audit. 

 CHAIR CARR: Yeah, this is not what 

this is saying. This is saying that you want the 

supply chain or the procurement chain part of it 

to recognize this program as being --

 MS. HARPER-LARSEN: Like this? We 

strongly encourage the Secretary's office to 

engage all foreign procurers, like retailers, food 

service entities, and consumer brands in 

discussions related to GFSI technical equivalence? 

 CHAIR CARR: Is that okay? 

 MR. WILKINS: So the retailers are 

talking about if they don't buy nothing they have 

to go to a market to replenish. And I think 

that's a very strong part of it. I don't 

understand the consumer brands. 

 MS. HARPER-LARSEN: You have recognized 

consumer brands that are major fresh fruit and 

produce brands, Dole, Dandy, Fresh Express, that 

are known consumer identifiable, Green Giant, 

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brands who currently have provisions not to accept 

USDA Harmonized Gap, because it's not benchmarked. 

And the reason for that is simply semantics. 

 MR. WINGARD: So to his point, what 

makes Dole, which is what you listed as a brand, 

what makes them not a procurer? 

 MR. WILKINS: They're a source, not a 

procurer. 

 MS. HARPER-LARSEN: They are also a 

procurer, straight up. 

 CHAIR CARR: Procurer, yeah, they are. 

 MS. HARPER-LARSEN: They're a source as 

well, sometimes. 

 MR. WINGARD: Okay, I get that. 

 MR. ZEA: If you said supply chain, 

you're going to have to really -- to make clear 

what you're talking about ---

 MS. HARPER-LARSEN: If we just say 

supply chain, and we give them directive to say, 

go to the major retailers, go to your major food 

service entities, and go to your major consumer 

brands, you're not going to ---

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 MR. ZEA: But say that then in parens 

and offer some examples, right? 

 MS. HARPER-LARSEN: So to engage major 

retailers, to take out all foreign procurers or --

-

 CHAIR CARR: How about try it this way. 

Just say encourage the supply chain, like 

retailers, food service entities and --- we want 

the whole supply chain to recognize this 

equivalent. 

 MR. WILKINS: And these are such as? 

 MS. HARPER-LARSEN: So go back up to 

the previous statement? 

 CHAIR CARR: No, just right there in 

front of your cursor. 

 MS. HARPER-LARSEN: Okay. 

 CHAIR CARR: Take out of farm produce, 

and just say encourage the supply chain, i.e. 

retailers, food service ---

 MR. WILKINS: Such as? 

 MS. HARPER-LARSEN: Anybody else that 

I'm missing there? 

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 CHAIR CARR: So supply chain 

incorporates it all. You've highlighted these 

three segments. 

 MR. WILKINS: I think that's pretty 

good. 

 CHAIR CARR: Kiley, would that be your 

intent? 

 MS. HARPER-LARSEN: Yes. 

 CHAIR CARR: Okay. 

 MS. HARPER-LARSEN: But what we need is 

we need leadership from the Secretary's office to 

open dialogue with these entities. We're not just 

asking for additional funding towards the 

harmonized program for education throughout our 

stakeholders. We need that dialogue. 

 MR. WINGARD: So you think you should 

take out such as and put to include. That points 

the finger. 

 MR. WILKINS: Good point. 

 MS. HARPER-LARSEN: Shall I read it 

again? 

 CHAIR CARR: Not right now. 

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 MS. HARPER-LARSEN: Okay. Are we good? 

 (No audible response.) 

 MS. HARPER-LARSEN: Excellent. All 

right. We encourage the USDA's regular 

collaboration with the FDA to share technical 

expertise and data so as to inform FDA's 

implementation plan -- that's specific verbiage, 

by the way -- to ensure that foreign supply is 

held to the same standards as domestic supply in 

regards to all aspects for FSMA compliance when we 

are giving specific examples of surveying 

Hepatitis A, contaminated Egyptian strawberries, 

and Chinese peaches and squashes. We just 

basically strengthened our original bullet point 

to give some additional examples. And it lends 

credence to your trade. 

 CHAIR CARR: Comment? 

 MS. SKELTON: Yeah, now that I see that 

on the screen -- this is Leanne Skelton, now that 

I see that on the screen, I think we're mixing 

things up here. 

 I've got FSMA compliance. That's what 

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you're angling for, is that everybody is uniformly 

protected by compliance. That's what you want, I 

think. And I don't mind the examples, but the 

examples aren't, because of FSMA compliance, or 

non-compliance. That's USDA's purchasing 

programs. You can do what you want, but you might 

be mixing things up a little bit. 

 MR. WILKINS: So should that be USDA 

instead of FSMA? 

 MS. SKELTON: Well, I think what, if I 

remember how the group was talking about this, 

they wanted to ensure that, regardless of the 

source of product, it was to have equal, uniform, 

consistent compliance activity related to those 

models. 

 MR. WILKINS: So we might say FSMA and 

USDA compliance and give an example. 

 CHAIR CARR: I'm sorry, I don't even 

understand how the two examples work into that. 

 MS. HARPER-LARSEN: Okay, all right. 

So I can get in with the Chinese peaches in school 

lunches, because that was just against USDA 

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procurement issues. 

 But when we talk about FSMA compliance, 

those growers and the importers did not meet what 

we currently have for FSMA compliance. And they 

brought in adulterated products. 

 MS. SKELTON: Did they have to meet it? 

Were they of the size that had to meet it yet? 

 MS. HARPER-LARSEN: I don't think they 

were under the requirement --

 MS. SKELTON: Yeah. 

 MS. HARPER-LARSEN: -- currently. It 

was all due to the date. 

 MS. SKELTON: Might you be as well 

served to just strike the examples? 

 (Off-microphone comments.) 

 MS. HARPER-LARSEN: As it reads now? 

We spent some time trying to come up with an 

accurate flow that would represent a very robust 

segment. 

 (Off-microphone comments.) 

 MR. WILKINS: I think that's what 

you're trying to say. 

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 MS. HARPER-LARSEN: And so the FDA does 

have a specific implementation plan. And we need 

USDA's technical experts and our data to have a 

seat at the table for that, okay? And it brings 

in our objective to make sure that foreign supply 

and domestic supply are held to the same 

standards. 

 All right. Our next one is, we 

encourage the USDA to engage with the FDA 

regarding prioritization of FSBP inspections 

related to produce that have caused outbreaks in 

the United States. 

 You will notice yesterday that Jennifer 

said the inspections are not on the produce, it's 

on the importer and the documentation. So what we 

tried to do was take that information and craft it 

into something that was palatable. 

 So prioritization of documentation 

inspections are people who are having trouble with 

the produce causing outbreaks. Are we good there? 

 (No audible response.) 

 MS. HARPER-LARSEN: Okay. We encourage 

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the USDA to work with the FDA and CDC to hold town 

hall-style meetings to improve agency 

understanding. Agency was changed from 

regulatory. 

 A growing, harvesting, packing, and 

traceability process is prior to issuing 

additional fruit and vegetable consumer 

advisories. Previous consumer advisories have 

temporarily and sometimes permanently disrupted 

the market for some fresh fruit and vegetables. 

And we gave examples that we have documented 

economic evidence of market disruption, at 

consumer request. 

 We did remove all of those bullet 

points. The seeking input, commentary, although 

several of us maybe were not involved in that, 

Leanne did confirm that there was input sought. 

Maybe it just wasn't broad enough as it should 

have been. 

 MR. HUGHES: I have a question for you. 

So the other three workgroups have some type of 

overview or finding statement that will accompany 

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a recommendation or a position statement so that 

it informs various leadership up the chain. 

 Do you plan to, which it doesn't have 

to be robust, but do you plan to include some type 

of background workgroup finding that adds some 

meat that explains why you've reached that 

recommendation? 

 MS. HARPER-LARSEN: I don't see any 

reason why we can't -- I can't provide that to the 

group for review. 

 CHAIR CARR: But in that particular 

one, you actually have it at the bottom. It's 

just where it's at. But you discuss at the end 

why previous consumer advisors have temporarily 

altered markets, so you're ---

 MR. WILKINS: But not only the market. 

 MR. HUGHES: I'm not just specifically 

talking about that one. I'm just talking about in 

general, that some of them, it's just a 

recommendation. And, I mean, I can easily see 

certain leaders saying, well, where is this coming 

from? Did they say anything else? 

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 MS. HARPER-LARSEN: Because we're not 

there to convey it. 

 MR. HUGHES: Right. 

 MR. WILKINS: So I would like for us to 

somehow incorporate the pain that a restaurant, or 

retailer, or anyone that has the product in their 

supply chain, from PC to stores, or distribution 

to restaurants, they say, well you have to dump 

that product. So it's not just the market, but 

it's everything in the supply chain is damaged in 

some sense. 

 MS. HARPER-LARSEN: Consumer supply 

chain? 

 MR. WILKINS: Well, it just doesn't 

address the fact that, if we have any of those 

examples in our supply chain, and there's an 

advisory ---

 MR. SIEVERT: Should it be up on the 

report, where it says previous consumer 

advisories? 

 MR. WILKINS: Yeah. 

 MR. SIEVERT: The financial? 

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 MR. WILKINS: Yeah, I may do that. 

There may be something there that I tried that 

that causes financial strain on customers that 

have advised -- I don't know. We just have ate 

millions of dollars -- ate's a bad word. We've 

lost millions of dollars on these advisories. 

 MS. HARPER-LARSEN: When they haven't 

been found or when they have been found? 

 MR. WILKINS: Both. 

 MR. WINGARD: Well, to Tommy's point, 

when the Romaine advisory came out from major 

retailers that kale listed in their computer 

system in the same category as Romaine. 

 So we had to pick up the kale that we 

already had in their warehouse. And we had to eat 

it. And it was bag of kale salad that was their 

label. So it's not like I can sell it down the 

street. But we lost, like, 10,000 cases. 

 MR. ELY: So what if -- after we had, 

you know, we had created an economic hardship in 

this industry. 

 PARTICIPANT: Yeah, there you go, and 

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temporarily. 

 (Off-microphone comments.) 

 MR. ELY: That is the ---

 MS. HARPER-LARSEN: All right. So 

previous consumer advisories have created economic 

hardships and temporarily and sometimes 

permanently disrupted the market and consumer 

supply. 

 It's actually not just the consumer 

supply chain, it's consumer demand. 

 MR. SIEVERT: And maybe that's ---

 MS. HARPER-LARSEN: Consumer supply 

chain incompetence? 

 MR. SIEVERT: How about consumer 

confidence? 

 PARTICIPANT: Right, confidence is a 

good --

 PARTICIPANT: I like confidence. 

 MR. WILKINS: I'd take supply chain out 

and put confidence. 

 MS. HARPER-LARSEN: And consumer 

confidence for consumption of some fresh fruit and 

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vegetables. 

 Is there another example that needs to 

be listed there? I just looked at majors and 

discussed it with my workgroup committee. Is 

there something else? I mean, should we stick in 

some kale in there, since you lost 10,000 cases? 

 MR. WINGARD: No, because the kale ---

 (Simultaneous speaking.) 

 MR. SMITH: Those will resonate. It's 

not just fresh. We lost tomato sales with the 

bogus tomato problem in 2008 in canned. 

 PARTICIPANT: So fresh and processed. 

 MR. SMITH: Fresh and processed. 

 MR. WINGARD: I'd put canned up beside 

the fresh, fresh and canned. 

 MR. HUGHES: For those who haven't 

checked out, it's 11:30. But don't all leave. 

Keep working. Just a reminder. 

 MS. HARPER-LARSEN: All right, how does 

this read now? 

 MS. SKELTON: Change your first canned 

to processed. 

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 PARTICIPANT: Yeah, I'd say that the 

process ---

 (Off-microphone comments.) 

 MS. HARPER-LARSEN: All right. Are we 

good to move forward? 

 (No audible response.) 

 MS. HARPER-LARSEN: All right. We 

encourage the USDA to work with the FDA and CDC to 

coordinate a fresh fruit and vegetable 

stakeholder-driven workgroup focused on improving 

communication and advising during the consumer 

advisory process and other related activities. 

 So we took out a lot of wordiness, made 

it more broad, and we also referenced what had 

been provided by United and PMA in direct 

discussion under Appendix D that has been 

submitted for review to the FDA in relation to 

developing a more robust collaborative effort. 

 What was lacking from United and PMA's 

Appendix D document was the fact that USDA and 

smaller stakeholders did not have a seat at the 

table. And so in our bullet point we wanted to 

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make sure that USDA was recognized for their 

contribution in that process and that we had a 

more robust, broad, stakeholder group represented, 

rather than just larger membership organizations. 

 Last, and this is a new bullet point, 

we ask that the Secretary's office seek 

appropriate annual funding streams for FSMArelated training initiatives, in specific, the 

Produce Safety Alliance, which is the produce 

safety rural grower training, which is federally 

mandated for all entities that are not applicable 

to the Tester Amendment that grow, harvest, and 

sometimes pack their own product. 

 We don't have appropriate annual 

funding streams. It's specifically, right now, on 

a time-limited grant. So we have a law, and we 

don't have the education outreach to enact it. We 

essentially have a defunct domestic supply 

initiative. So therefore, that's the new bullet 

point. 

 MR. WINGARD: Are you trying to get 

money, you want money every year here? You're 

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saying recurring funding streams. 

 MS. HARPER-LARSEN: What I think we 

need to look at is, like, a line item specific, 

that when we say recurring funding streams, right 

now what we would be dealing with is grant, versus 

a line item on the budget. So is it recurring, or 

is it an annual line item? 

 MR. HUGHES: Yes. 

 MS. HARPER-LARSEN: It's an annual line 

item, correct? 

 MR. HUGHES: It is an appropriations --

and appropriations line item, right? 

 MS. SKELTON: It would end up as an 

appropriation, yes. 

 MS. HARPER-LARSEN: So that's the, I 

mean, it's super important when we're considering 

this verbiage that we ask for recurring. They're 

going to take additional -- just keep funding that 

grant. And then when they decide to slice that 

grant up, well, bye-bye. 

 CHAIR CARR: Technically they can't 

count your grant as recurring funding. But if you 

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say the word recurring, that may speak line item 

funding. 

 MS. HARPER-LARSEN: Because it's not --

no, because it's not the original funding source? 

You can't recur something that hasn't happened 

yet. 

 MS. GLEASON: Can you just add 

recurring line item funding? 

 MS. HARPER-LARSEN: Or appropriations? 

 CHAIR CARR: And take out funding. 

 MS. SKELTON: Change your first 

appropriate to adequate. 

 MS. HARPER-LARSEN: We've got really 

good technical assistance for our committee, don't 

we? Yes, uh-huh. 

 MS. HARPER-LARSEN: So we ask that the 

Secretary's office seek adequate, recurring, line 

item appropriations for FSMA-related training 

initiatives. All right, do we have it? 

 CHAIR CARR: Any other questions or ---

so you're ready to put this forward? 

 MS. HARPER-LARSEN: Yes. 

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 CHAIR CARR: May I have a motion? 

 MR. SIEVERT: Motion. 

 CHAIR CARR: Have a second? 

 MR. ELY: Second. 

 CHAIR CARR: Any discussion? 

 (No audible response.) 

 CHAIR CARR: All those in favor, please 

say aye. 

 (Chorus of ayes.) 

 CHAIR CARR: Those opposed? 

 (No audible response.) 

 CHAIR CARR: Well, very good. So our 

work on recommendations at this level is done. 

Darrell, for housekeeping, you're going to type 

these up, send them out to the whole group, one 

last time to the specific committee leads to look 

at it. 

 And then, again, we're going to ask 

everybody to review these one more time and come 

back. But how they have to handle that process? 

Do we just have their acknowledgment? 

 MR. HUGHES: Yeah, similar to how we do 

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the minutes, since you guys have already approved 

them at a high level here, just going through and 

looking at the two versions to make sure they're 

consistent, and there has been nothing deleted, or 

so on and so forth. 

 CHAIR CARR: And let me also go and add 

that so, beyond that, if there's something else 

that needs to come up during this next -- after 

the end of September, we can make further -- you 

can work within your working groups and bring 

something else forward. We'll get it to Darrell, 

and get it out to all of us. And we can bring 

other recommendations. This doesn't have to be 

the end of the process -- 

 MR. HUGHES: Right. 

 CHAIR CARR: -- is what I'm saying. 

Things may emerge in that time period. 

 MR. HUGHES: Yeah. And, I mean, we 

won't be able to meet in person again, but we will 

be able to revise which, I think, most of you are 

comfortable doing at this point. 

 CHAIR CARR: Well, before we leave, I 

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want to thank all the committee leads again for 

taking the charge of working with the your groups 

over the summer, getting these done, fantastic 

process today. Everybody's gone through it, 

everybody's gotten their input, so again ---

 (Simultaneous speaking.) 

 MR. HUGHES: When I read through the 

actual recommendations in the position statements, 

it's the expectation that the overviews, the 

workgroup findings, paragraphs, that also needs to 

finalized by then. And I'm looking for a 

complete, refined, package. 

 MR. WILKINS: I'm sorry, so ---

 (Simultaneous speaking.) 

 MR. WILKINS: -- there will be more in 

there that I think might be changing a little bit. 

You said you might change a little bit of your ---

 MS. HARPER-LARSEN: The reason why we 

arrived at that recommendation. 

 MR. HUGHES: Straight to that whole 

section on protecting the farmer, that background 

section needs to be 100 percent revamped. 

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 PARTICIPANT: Right. 

 (Simultaneous speaking.) 

 MR. HUGHES: And so, I mean, I don't 

mind moving for the refined recommendations in 

position statements for clearing. But then the 

same thing will have to happen for the meat that 

supports those recommendations. 

 So it's up to you. Do you want the 

workgroup leads to get their refined workgroup 

finding statements that -- the background 

statement's completed? 

 CHAIR CARR: Yes, I want to get -- let 

me get those completed so that one time, one final 

package can go back out to everybody. 

 MR. HUGHES: All right. So can we --

what timeframe would you like those refined 

paragraphs to be submitted to me? 

 CHAIR CARR: Is two weeks good enough 

for the working group leads? 

 (Off-microphone comments.) 

 MR. WILKINS: Well, that's two weeks. 

 MS. HARPER-LARSEN: I want to do that 

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in September. 

 PARTICIPANT: Let's do two weeks. 

 MR. WILKINS: August 30th is Friday, 

that's two weeks and a day. 

 CHAIR CARR: Kiley, you're a working 

group leader. If you can't do that timeframe, 

tell us what you can do. 

 MS. HARPER-LARSEN: I can do the 

following Friday. 

 CHAIR CARR: So the goal would be to 

have all the findings to you within two weeks and 

you to have those back to us in a week or ---

 MR. HUGHES: Yeah. 

 CHAIR CARR: -- after that? 

 MR. HUGHES: Yeah, within a week after 

that. 

 CHAIR CARR: So sometime after Labor 

Day we should all see a final product. And again, 

if there are substantive changes to that product, 

then if there's a wordsmith or something like 

that, you can work with Darrell directly on that. 

But subsequently, we have to come back together as 

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a group to make any changes to that. 

 All right, so we've gone through the 

committee leads, and we've gone through all this. 

Are there any other topics that need to come up to 

be discussed? 

 MR. HUGHES: I had on the agenda to 

schedule follow-up meetings. But I think I'll 

table that until we get all the material in. 

That's it, yeah. Thank you all. 

 CHAIR CARR: So what else? 

 MS. HARPER-LARSEN: I do have one 

thing. Based on the discussion that we made a 

unanimous vote in the trade section for 

recommendations as it relates to defending 

domestic production in the United States, there 

are both a House and a Senate Bill, H.R. 101 and 

Senate Bill 16, that are currently looking to take 

our policy recommendation into law. 

 And I wanted to know if it would be the 

pleasure of the committee to make a formalized 

vote on the support of H.R. 101 and Senate Bill 

16, which is the Domestic Protection Act, to lend 

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further credence to our policy recommendation. 

 MR. SIEVERT: Could we have copies of 

those bills before we ---

 MR. HUGHES: Wait, let me ask this 

question first. Are we amending the approved 

trade or this is just an additional? 

 MS. HARPER-LARSEN: Just an additional, 

I don't know, separate. 

 MR. HUGHES: Yeah, you can do what you 

want. Then you have to put it in writing and then 

approve. Or, I mean, it's on the record here in 

minutes. But if someone wants minutes it's --

we're, like, almost out of time here today. 

 CHAIR CARR: Well, I mean --

 (Simultaneous speaking.) 

 CHAIR CARR: Let me have the chair, 

Darrell. So we've already adopted the language 

that supports those bills, but remember, our job 

is to recommend to the Secretary or to make a 

statement. 

 So this is legislation. So is your 

recommendation that this committee recommends that 

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the U.S. Secretary of Agriculture should support 

and work for the passage of those bills? 

 MS. HARPER-LARSEN: Yes. 

 CHAIR CARR: Okay. Since nobody has 

seen those bills, I would have to say that -- I'd 

recommend that we circulate those bills. And then 

we can come back together via email and vote on 

them. 

 MR. ZEA: So bills by review of the 

Senate. 

 CHAIR CARR: So have I agreed to work 

with you on this? 

 MS. HARPER-LARSEN: But they are 

supported by a multi --- it's a bilateral support, 

multi-state. 

 MR. WILKINS: But there is bilateral 

multi-state objection to that. And I think that 

-- I hate to overstep what we agreed on today. If 

you do that, then it weakens the stance we made 

today. It changes the stance we did today. And 

I think you're taking one step back to come back 

to doing something we didn't agree to today. I 

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strongly disagree with that. 

 CHAIR CARR: Yes, Charles? 

 MR. WINGARD: I'm not sure exactly what 

our charter says. I don't have it right in front 

of me. But I think we were charged to make 

recommendations to the Secretary of Agriculture on 

how he can lead his agency forward to help our 

industry. And Kiley understands that would be one 

way to do it. But I don't think we should --

 CHAIR CARR: I don't think that was our 

charge. 

 MR. WINGARD: No. I just don't think 

we should get into lobbying for passage of this or 

that. I mean, I do think we have to protect the 

industry. I get that completely. But that's for 

people on Capitol Hill to figure out, not for this 

group. 

 We may have all got in here and in two 

hours be lobbying for individuals, but as a group 

I think we're charged to recommend to the 

Secretary what we think he needs to do to help our 

industry. 

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 CHAIR CARR: And, Charles, just 

following that -- serving on another USDA 

committee, you are not allowed to take a position 

on legislation. You can go up there on the Hill 

as yourself, or represent your company. But you 

can never, ever go up and say as a member of the 

USDA Food Advisory Committee, I recommend you 

support this. You cannot do that. 

 I mean, I probably should have done 

that from the opening. So I would say that, 

Kiley, I understand your position. So if you want 

to move forward with it, then I'm going to say 

that we have submit the bills to everybody, and 

then everybody can think about it. Otherwise, 

would you accept the language as it's adopted 

today that covers the very same things you're 

trying to say? 

 MS. HARPER-LARSEN: So I would just 

make the commentary that I put a motion on the 

floor. If I don't see a second to it, then it's 

going to fall flat according to Robert's Rules of 

Order which dictates our committee's standing. 

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 But what I think is very important to 

note is that the policy recommendation that we put 

forward does not say the same thing as both of 

those bills, and it does not have the teeth. 

 MR. WILKINS: We are not in legislative 

recommendations. 

 MR. TALBOTT: The other problem we've 

got is legislation is a moving target. And to say 

I support X, by the time it goes through 

legislative meat grinding --

 PARTICIPANT: It'll be amended. 

 MR. TALBOTT: It can be ugly. And it 

may not say anything close to --

 CHAIR CARR: There is a motion on the 

floor. Is there a second for that motion? 

 (No audible response.) 

 CHAIR CARR: Hearing no second --

 MS. HARPER-LARSEN: It dies. 

 CHAIR CARR: -- it dies. 

 MS. HARPER-LARSEN: Thank you though 

for the consideration. 

 CHAIR CARR: We put it on the record. 

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And we have all discussed it. So is there 

anything else to come before this Committee? 

 MR. WINGARD: Mr. Chairman, I'd like to 

commend everybody here for their commitment to the 

industry. It's been great getting to know you 

all. I hope it was great, I hope it was someone 

goes on getting the ---

 (Laughter.) 

 MR. WINGARD: But thank you to 

everybody for --- I think that everybody should be 

commended for the giving of their time and their 

talent to this process, and to the USDA staff, and 

to those visitors in the room. And with that, and 

thank you, Mr. Chairman, for leading us. And with 

that, I make a motion we adjourn. 

 PARTICIPANT: Second. 

 CHAIR CARR: Motion to adjourn, 

seconded, so admitted. Thanks everybody, travel 

safe home. 

 (Whereupon, the above-entitled matter 

went off the record at 11:45 a.m.) 

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72:12 81:12 97:20 

100:14 101:12,22 

104:7,21,21 

background 30:7 88:5 

99:21 100:10 

bad 62:11 90:5 

bag 90:16 

balance 8:13 

base 31:5 

based 4:6 5:12 8:18 

45:3,4 58:3 70:15 

102:12 

basically 24:16 25:11 

71:9 75:19 83:14 

basis 24:10 76:7 

battle 26:5 

beginning 48:8 

believe 15:1 23:1,21 

30:13 

believes 17:10 18:3,17 

BELL 2:2 

benchmarked 80:2 

benefit 34:11 56:14 

berries 24:19,19 

best 11:12 25:1 33:8 

47:19 

Neal R. Gross and Co., Inc. Neal R. Gross and Co., Inc. 

(202) 234-4433 (202) 234-4433 Washington DC Washington DC www.nealrgross.com www.nealrgross.com 
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better 53:6 57:3 62:1 

71:16 

beyond 75:19 77:19 

78:12 98:7 

bids 11:11 

big 28:20 

bilateral 104:14,16 

bill 13:15 30:16 62:13 

63:19 66:3 102:16,17 

102:21 

bills 103:3,18 104:2,5,6 

104:9 106:13 107:4 

bio 43:5 

biotech 49:10 

bit 6:17 26:6 37:9 48:18 

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99:16,17 

blah 71:15,16,16 72:4,5 

72:5 

blanket 64:21 74:4 

block 37:5,10,22 38:3 

board 9:4 17:4 33:13 

Boards 73:3 

bogus 92:11 

bold 53:3 

bottom 17:15 70:5 

77:20 88:12 

BOWMAN 1:13 13:1,18 

62:6,21 63:10,18 

brand 80:5 

brands 76:17 77:11 

79:11,18,20,21 80:1 

80:22 

break 3:6 7:12,13 26:18 

26:18,19 66:22 

Brenda 44:8 

Brenda's 46:1 

Bret 1:15 57:18 

BRIAN 1:17 

bring 5:16,17,20 13:20 

16:1,5 18:5,9 62:8 

67:12 69:11 98:10,12 

bringing 25:18 63:19 

brings 86:4 

broad 3:18 35:8 45:12 

46:20 47:4 67:18 

87:18 93:14 94:3 

broaden 54:17 

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BRUCE 1:19 

buckets 8:19 

budget 36:1 95:6 

bullet 4:21 9:8 30:17 

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87:14 93:22 94:5,19 

bullets 19:18 

burden 70:17 

Business 4:19 

buy 9:21 10:7,9,10,20 

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buying 76:15 77:3,8 

78:1,2 

buys 40:17 

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C

calendar 16:1 

call 3:4 14:7 77:4 

called 14:6 45:9 67:7 

canned 92:11,14,15,21 

Capitol 105:16 

care 24:1 

cases 90:18 92:6 

cast 4:22 5:5,9 

categories 10:1 

category 10:2,4,6 90:13 

caught 68:7 

caused 86:11 

causes 90:3 

causing 86:20 

CDC 87:1 93:8 

certain 25:9,10 34:5 

43:22 88:21 

certainty 43:1 

cetera 11:16 

chain 36:12 53:21 

77:16,19,19 78:18 

79:6,6 80:15,19 81:7 

81:9,18 82:1 88:2 

89:7,10,13,16 91:10 

91:13,19 

chairman 16:15 65:16 

65:18,22 108:3,14 

challenge 25:18 

Chalmers 1:10,12 

chance 23:16 

CHANDLER 1:13 33:5 

34:6,15,18 35:2,6,14 

36:13,16 58:12,14 

change 15:8 26:16 

30:12 64:16 72:12 

73:7 92:21 96:11 

99:17 

changed 30:6 41:21 

87:3 

changes 29:20,21 52:4 

55:10 65:12 101:19 

102:1 104:20 

changing 23:16 99:16 

charge 54:7 58:19 99:2 

105:11 

charged 105:5,20 

Charles 1:21 64:7 77:13 

105:2 106:1 

Charles' 14:14 

charter 105:4 

cheap 24:14 

checked 92:17 

chemical 50:15,16 

children 68:9 

China 75:20 

Chinese 83:13 84:21 

choice 11:2 

choose 18:21 63:17 

chopped 22:5 

Chorus 29:8 52:16 69:4 

97:9 

circulate 104:6 

circumstances 39:4 

41:7,8 

citizenship 63:5 66:14 

68:1 

citrus 35:19 36:1 

City 1:9 

claim 24:12 25:6 

clarification 37:2 

clean 64:14 

cleaner 50:7 

clear 15:18 28:9 59:7,8 

65:11 80:16 

clearing 100:5 

close 107:13 

closest 13:2 

coast 39:2 

cocktail 11:16 

collaborate 56:1 70:19 

collaboration 49:15 

54:15 73:3 83:5 

collaborative 93:18 

collected 55:3 

combined 54:13 70:15 

come 3:7 7:8,13 9:6 

13:3 24:13 26:19,20 

26:22 27:9 39:19 40:4 

43:5 62:18 63:17 67:3 

68:10 85:17 97:19 

98:8 101:22 102:4 

104:7,21 108:2 

comes 8:1 43:20 51:2 

comfortable 98:21 

coming 6:11 7:17,18 

15:14 24:20 33:21 

37:13,18 55:7 67:22 

68:11 88:21 

comma 47:21 48:15 

commend 108:4 

commended 108:11 

commends 56:8 

comment 44:9 61:5,9 

62:7 83:17 

commentary 87:15 

106:19 

comments 12:19 34:17 

42:5 43:18 49:7 52:21 

53:10 56:17 57:12,17 

59:9,12 61:4,10,18,22 

68:5 69:9 73:9 85:15 

85:20 91:2 93:3 

100:20 

commercial 11:20 

commitment 53:14 

108:4 

committee 1:3,8 3:21 

4:1,9,10,11,22 5:6,20 

5:21 6:9 8:3 9:10 10:9 

10:13,16 12:22 13:1,5 

13:19 17:10 18:3,17 

30:19 31:19 32:2,12 

36:17 40:2 56:8 92:4 

96:14 97:16 99:1 

102:3,20 103:22 

106:3,7 108:2 

committee's 4:3 106:22 

commodities 35:22 

communication 51:12 

93:11 

community 76:15 77:6 

77:8 

companies 26:7 54:19 

company 106:5 

compelling 56:17 61:16 

62:2,4 

compete 8:10 9:15 

competition 8:11 9:15 

competitive 25:2 

competitors 9:14 

complaints 18:6,9 

complete 99:12 

completed 100:11,13 

completely 105:15 

completing 3:12,16 

compliance 83:10,22 

84:2,4,14,17 85:2,4 

comply 73:20 

component 37:5 

compromise 13:3 

computer 90:12 

concept 34:3 

concern 12:20 13:6 

33:12,18 34:2,5,6 

43:10 

concerned 30:19 

concerns 8:5 9:17 12:4 

12:5 27:9 33:10 

conclude 28:14 

Conducting 4:19 

confidence 91:15,16,18 

91:20,22 

confirm 87:17 

conflict 5:7 

confusion 49:20 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
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Congress 8:6 53:17 

54:11 62:8 

Congressman 63:18 

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consider 10:14 62:13 

consideration 27:2 

37:4,8 44:8,16 107:21 

considered 5:11 11:11 

11:14 49:3 

considering 54:11 

95:16 

consistency 72:16 

consistent 46:9 50:21 

84:14 98:4 

consumer 76:17 77:11 

79:11,18,20,22 80:21 

87:7,8,13 88:14 89:12 

89:19 91:5,7,9,10,12 

91:14,21 93:11 

consumption 91:22 

contain 20:4,8 

contaminated 83:12 

continual 67:10 

continue 8:8 71:4 

continued 56:16 

contract 66:21 

contracted 12:1 

contracts 66:12 

contribution 94:2 

contributions 53:21 

control 78:20 

controls 72:22 73:17 

controversial 61:20 

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coordinate 93:9 

copies 103:2 

correct 17:5 39:22 40:8 

50:18 52:20 95:10 

corresponding 49:12 

49:15 

cost 10:19 15:15 24:9 

cost- 11:2 

cotton 42:12 

count 95:22 

counted 5:9 

counties 43:22 

country 15:14 16:5 

66:12,20 

couple 7:21 

coverage 38:12 

covered 41:7 

covers 23:13 106:16 

craft 86:16 

create 56:2 

created 90:20 91:5 

creating 53:22 

credence 83:16 103:1 

crisis 53:15 

criteria 32:4 

critical 8:7 53:13,21 

59:15,17,19,22 60:2 

crop 30:22 31:6,13,21 

37:5,10 38:3,8,12,13 

38:15 42:11 43:1,8,11 

43:16,17 48:22 50:20 

crops 30:14,15,16,20 

31:14 37:6 43:13 51:3 

cross 54:6 

cross-docking 76:1 

Crystal 1:9 

curious 15:10 

current 13:8 16:9 33:2 

42:12 53:20 57:6,7 

58:3 59:3 66:19 68:7 

71:13 

currently 15:20 23:9 

62:10 80:1 85:4,11 

102:17 

cursor 81:15 

custody 78:21 

customers 90:3 

cut 6:19 22:4 

D

D 93:16,20 

Dairy 33:13 

damaged 89:10 

Dandy 79:21 

Darrell 2:5 7:16 14:16 

15:7 39:22 49:6 64:13 

97:14 98:11 101:21 

103:17 

Darrell's 29:19 

data 42:20 45:1,3 46:12 

55:2 72:1 83:6 86:3 

date 85:12 

DAVID 2:2 

day 15:22 101:4,18 

days 16:7 23:13 24:1,7 

26:8 65:10,13,14 

66:19,22 

dealing 37:17 95:5 

debate 13:2 

decide 95:19 

decides 4:21 

decision 30:21 31:12 

73:19 78:11 

decisive 5:1 

dedicated 32:14 36:19 

dedicating 33:16 34:3 

defending 102:14 

define 30:21 57:2 

defined 55:20 

definitive 36:10 

defunct 94:18 

deleted 98:4 

demand 32:17 40:20 

91:10 

Department 1:1 54:5 

depending 33:7 

DERRIN 1:20 

Designated 2:5 

desirable 39:4 41:7,8 

desired 11:2 

detected 48:22 

determination 54:10 

58:15 59:6 

determine 32:9 50:17 

determined 31:17 

determines 43:6 

determining 73:19 

develop 5:18 71:5 75:1 

75:8 

developed 75:21 

developers 49:10 

developing 3:17 9:12 

56:4 93:18 

development 4:17 

32:10,14,15 36:19 

56:10 71:1 73:16 

75:15 

dialogue 70:9,16 82:12 

82:15 

dicamba 42:21 

dictates 106:22 

die 13:21 

dies 107:18,19 

difference 73:11 

different 10:19 22:4 

23:19 45:14 47:7 49:6 

51:3 62:21 

diligently 18:14 

dilute 31:18 

direct 93:15 

direction 22:4 37:18 

directive 80:19 

directly 30:1 37:20 

101:21 

disagree 34:3 105:1 

discretion 33:7 

discuss 7:20 26:20 

27:1 63:8 88:13 

discussed 92:4 102:5 

108:1 

discussing 10:2 

discussion 3:8,20,22 

7:4 13:13,14 14:22 

15:9 29:5 37:4 38:6 

38:17 49:19 52:12 

68:22 76:3,18 93:16 

97:5 102:12 

discussions 76:17 

77:12 79:12 

disputes 8:14 

disrupted 87:9 91:7 

disruption 87:12 

distinguished 46:22 

distribution 77:15 89:7 

distributors 11:21 76:1 

divisive 64:2 

document 3:20 93:20 

documentation 11:8 

86:15,18 

documented 87:11 

doing 37:11 46:18 

59:19 98:21 104:22 

DOL 55:3 

DOL's 56:10 

Dole 79:21 80:5 

dollars 90:5,6 

domestic 11:9,13 12:1 

12:9,11 13:9,15,16 

14:8 16:4,12 20:4,17 

20:19 21:7,13,20 

22:16,18 23:3,10 24:3 

26:13 27:17,19 41:22 

62:15 83:9 86:6 94:18 

102:15,22 

domestically 11:6 

DONN 1:22 

drift 41:1 

driven 31:9 33:10 

due 5:7 85:12 

dump 89:8 

dumping 15:16 18:6 

24:22 25:3,7 27:21 

dwindling 54:14 

E

E 1:13 

easily 50:17 88:20 

eat 90:15 

economic 70:17 87:12 

90:20 91:5 

editorial 29:20 

educating 75:22 

education 70:21 76:8 

82:14 94:17 

effect 57:9,10,19 58:1 

effectiveness 38:14 

effects 42:10 

efficiency 32:17 

effort 76:10 93:18 

Egyptian 83:12 

either 17:5 18:21 63:16 

74:15 

elect 11:5 

eligibility 32:3 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
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ELLOR 1:14 68:20 

ELY 1:14 90:19 91:3 

97:4 

email 104:7 

emerge 98:17 

emerging 30:15 32:10 

emphasizing 23:10 

employees 67:16,17 

employer 66:20 67:5 

employers 55:4 56:3,5 

56:14 

enact 94:17 

enacted 56:13 

encourage 50:15 51:7 

71:4,7 73:16,22 74:10 

74:13,20 75:7,15 

76:14,20 79:9 81:7,18 

83:4 86:9,22 93:8 

encouraging 61:21 

62:1 

enforcement 10:15 

engage 61:21 76:15 

77:10 79:10 81:3 86:9 

engagement 56:16 

English 71:2 75:19 

enhanced 10:11 

ensure 38:10 42:20 

46:15 55:2 56:18 83:8 

84:12 

ensuring 8:7 

entire 34:11 

entities 73:19 76:2,16 

77:11 79:11 80:21 

81:8 82:12 94:11 

entitlement 68:3 

entity 45:13 

envisions 15:12 

EPA 39:11,16 40:6,14 

42:14,20 45:1,18,22 

46:14 48:18 49:12 

50:5,7,14 

EPA's 50:3 

equal 84:13 

equipment 32:15 

equivalence 79:12 

equivalent 81:10 

equivalents 76:11,18 

77:13 

erase 18:22 

ERICKSON 1:15 52:22 

53:8,11 55:15,20,22 

57:4,7,15 58:9,16,21 

59:5 60:6,17 61:1 

68:18 69:18,20 70:2,6 

70:10,13 

essential 47:1 

essentially 94:18 

establish 5:11 11:19 

50:20 72:21 

established 36:8 39:1 

et 11:16 

evaluate 42:15 

everybody 3:3 6:19 

27:3 50:10 84:1 97:19 

100:14 106:13,14 

108:4,10,10,18 

everybody's 99:4,5 

evidence 87:12 

exact 36:3 

exactly 65:9 105:3 

example 11:14 43:14 

84:17 92:2 

examples 77:17 81:2 

83:11,15 84:3,4,19 

85:14 87:11 89:16 

Excellent 83:3 

exception 10:20 

executed 66:5 

exemption 10:21 

existing 31:14 33:9 

exists 15:20 17:1 18:7 

21:2 

expanding 66:10 

expectation 99:9 

expedient 54:13 

expedited 56:6 

experiment 31:7 

expertise 83:6 

experts 70:12 86:3 

expires 42:13,18 

explain 46:21 

explains 88:6 

Explore 34:15 

export 8:8,11 

Express 79:21 

extending 42:10 

extension 31:8 

extent 51:14 

extra 53:1 

F

facilitate 49:18 

facilities 76:2 

fact 16:14 60:8 89:15 

93:20 

factors 39:6 

fair 28:14 

Fairfax 1:9 

fall 106:21 

families 68:9 

fantastic 99:3 

far 45:2 

farm 30:16 43:15 54:22 

55:8 70:20 77:18,19 

77:21 81:17 

farmer 23:16,21 99:21 

farmers 38:11,12 49:20 

50:3 60:15 

fast 58:22 

fault 62:22 

favor 29:6 52:14 69:2 

97:7 

FDA 39:16 40:6,15 

48:18 70:20 71:4 

72:20 75:7 83:5 86:1 

86:9 87:1 93:8,17 

FDA's 83:6 

February 16:4 

federal 2:5 31:15 47:1 

federally 94:10 

feed 35:22 

feel 6:21 62:22 

field 47:15 

figure 105:16 

filed 61:18 

final 50:18 100:13 

101:18 

finalized 99:11 

finally 56:8 

financial 11:19 70:22 

89:22 90:3 

find 6:9 

finding 87:22 88:5 

100:10 

findings 66:1 99:10 

101:11 

fine 20:2 22:12 36:13 

37:16 62:3 65:7 

finger 82:18 

finishing 66:4 

first 3:15 7:8,9,11 8:1 

10:2 11:2 18:10 39:1 

41:11 44:14 59:14 

66:15 92:21 96:11 

103:5 

fit 33:8 72:9 

fits 71:16 

five 62:16 64:6 

fix 73:13 

flat 106:21 

flexibility 34:9 

floor 13:21 106:20 

107:15 

Florida 16:3 24:19 

43:20 63:19 

flow 53:22 85:18 

flowing 72:16 

focus 75:22 

focused 93:10 

folks 66:11,14 

follow 3:18 61:11 

follow-up 102:7 

following 4:11 5:3 

10:19 19:12 101:9 

106:2 

font 30:11 

food 9:12 10:10 11:5,21 

11:22 12:1 72:22 

73:17 76:16 77:9,11 

78:2,5,9 79:10 80:20 

81:8,19 106:7 

Foos's 44:8 

force 54:4 

forced 50:2,2 

foreign 8:11 9:15 11:8 

11:22 12:13 20:21 

21:15 22:1,20 23:3,5 

23:8 25:14 26:4 27:22 

75:15 79:10 81:4 83:8 

86:5 

foreign-sourced 11:5 

form 8:2 12:21 17:3 

43:2 54:4 

formalized 102:20 

formulations 42:11 

forth 98:5 

forward 5:16,17,20 16:1 

28:7,8,19 52:5 63:4 

64:1 68:16 69:16 93:5 

96:21 98:11 105:7 

106:12 107:3 

found 90:8,8 

four 4:8,15 32:2,12,19 

49:9 52:2 

freedom 35:8 

fresh 79:20,21 87:10 

91:22 92:10,12,13,15 

92:15 93:9 

Friday 101:3,9 

friendly 14:21 15:2,4 

front 14:5,15 81:15 

105:4 

fruit 1:3 8:3,16 9:9 

11:15 17:10 30:18 

31:19 38:11 48:21 

53:3,12 59:15 72:22 

79:20 87:7,10 91:22 

93:9 

fruits 11:1,9 

FSBP 86:10 

FSMA 71:3 72:21 73:16 

75:15 76:11 83:10,22 

84:4,9,16 85:2,4 

FSMA- 94:7 

FSMA-related 96:18 

full 4:1,10 38:4 

fully 23:9 

funding 8:12 31:5 32:6 

32:13,22,22 33:2,3,20 

33:20 34:14,16,21,21 

35:1,4,4,5,10,19 36:5 

36:18 70:20 76:7 

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(202) 234-4433 Washington DC www.nealrgross.com 
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82:13 94:7,15 95:1,4 

95:18,22 96:2,4,8,10 

fundings 35:18 

funds 31:15,18,21 33:7 

33:17 34:1,4,4,14 

further 4:17 28:10 38:6 

47:22 51:14 98:9 

103:1 

Furthermore 56:15 

future 32:9 53:22 

G

Gap 76:9 78:5 79:2 80:2 

Gary 67:8,8,9 

gears 48:17 

gene 42:10 

general 88:19 

generally 38:13 

genetics 49:11,15 

getting 99:3 108:5,7 

GFSI 76:10,17 77:12 

79:1,12 

Giant 79:22 

give 23:15 27:1 36:10 

43:14 48:14 64:21 

72:10 80:19 83:15 

84:17 

gives 17:20 

giving 33:19 83:11 

108:11 

GLEASON 1:15 15:10 

16:21 21:7,20 26:2 

44:12 45:6,20 46:4,16 

47:8 60:14 66:6 67:2 

67:20 68:4,13 96:7 

global 51:12 

goal 32:4,16 35:7 38:10 

101:10 

GORDON 1:16 22:9,15 

43:12 47:9 48:1,3,6 

48:12 57:11,13 59:13 

60:3,12 

gotten 99:5 

government 47:1 

grant 31:7 32:3,13,22 

36:18 37:3,5,22 94:16 

95:5,19,20,22 

grants 31:16 32:9 33:13 

33:14,21 36:8 37:10 

38:3 

Green 79:22 

GREG 1:20 

grinding 107:10 

group 6:11 7:3,8 8:15 

8:17 9:1 14:20 15:12 

17:18 18:19,19 26:22 

28:7,19 29:6 39:22 

45:17 52:5,6,9 65:16 

65:18 67:5 68:3 69:8 

69:16,17 84:11 88:10 

94:3 97:15 100:19 

101:6 102:1 105:17 

105:19 

group's 3:8 

grouped 51:3 

groups 3:6 19:9,13,15 

27:2 50:20 98:10 99:2 

grow 94:12 

grower 71:2 73:2 94:10 

growers 12:8,9 13:9 

16:13 17:12 20:17 

22:16 27:14,17 55:10 

55:11 71:5 85:3 

growing 87:5 

grown 9:12 42:1 

guess 5:15 6:9 12:21 

14:1 

guest 68:7,8 

guidance 10:15 

H

H-2A 55:8 56:3,11 57:6 

57:7 59:3 62:10,14 

66:16 

H.R 13:14 102:16,21 

hall-style 87:2 

handle 97:20 

handling 28:5 

hands 50:3 

happen 28:16 100:6 

happened 60:18 96:5 

happening 25:8 

happy 36:14,16 

hard 44:22 

hardship 90:20 

hardships 91:6 

harmonized 51:12 76:9 

79:2 80:2 82:14 

HARPER-LARSEN 1:12 

13:12 14:13 16:10 

28:2 29:2 36:7 37:7 

37:19 40:18 44:19,22 

51:6,10 55:13,16,21 

63:2 65:1 69:10,13,19 

70:1,3,7,11,14 72:6 

72:13,15,19 73:10,15 

74:1,4 75:4,14 76:6 

76:20 77:1,5,10 78:7 

78:10,22 79:8,19 80:9 

80:12,18 81:3,12,16 

81:21 82:8,10,20 83:1 

83:3 84:20 85:8,11,16 

86:1,22 88:8 89:1,12 

90:7 91:4,12,21 92:19 

93:4,7 95:2,9,15 96:3 

96:9,13,16,22 99:18 

100:22 101:8 102:11 

103:7 104:3,13 

106:18 107:18,20 

harvest 94:12 

harvesting 87:5 

hate 35:6 104:18 

hazard 51:12 

hear 21:17 

heard 44:14 

Hearing 107:17 

held 83:9 86:6 

help 20:2 105:7,21 

helping 9:14 

helps 37:14 

hemp 30:21 31:12,18 

31:20 37:17,18 

Hepatitis 83:12 

high 98:2 

highest 60:7 

highlight 71:18 

highlighted 50:9 82:2 

Highway 1:9 

Hill 105:16 106:4 

history 56:5 

hold 58:21,21 87:1 

home 43:15 63:17 

68:10,11 108:19 

hope 29:13 49:17 108:6 

108:6 

Hopefully 26:18 

horticultural 12:12 

22:19 27:20 

horticulture 20:20 21:8 

21:14,21 

Hotel 1:9 

hours 105:19 

House 102:16 

housekeeping 97:14 

HUCKABY 1:16 

huge 35:18 

HUGHES 2:5 3:10 6:2,6 

6:8 7:17 8:18 9:19 

10:5,7 11:17 14:18 

19:6,13,20 21:13 22:8 

22:12 30:1,5,9 41:10 

41:14,17 44:6,13 45:2 

45:10 46:1 47:13,21 

48:2,5,10,14 51:21 

60:1,20 61:2,5 64:16 

64:20 65:3,9,13,20 

71:12 72:4,11 73:13 

74:12,17,19,22 75:3 

87:20 88:17 89:3 

92:16 95:8,11 97:22 

98:15,18 99:7,20 

100:3,15 101:13,15 

102:6 103:4,9 

human 72:22 73:17 

humidity 39:5 

Hyatt 1:9 

I

i.e 81:18 

idea 62:11 

identifiable 79:22 

identified 53:4,12 59:16 

identify 15:17 56:4 

identifying 45:12 59:20 

III 1:10,12 

immigrate 66:17 

immigration 53:18 

impact 30:20 54:8 56:2 

57:11 58:6 59:3 

impacts 8:14 31:14,15 

implementation 83:7 

86:2 

import 75:18 

importance 8:7 

important 26:10 95:16 

107:1 

importer 86:15 

importers 75:21 85:3 

improve 87:2 

Improvement 10:12 

improvements 10:14 

improving 13:15 93:10 

include 10:18 21:3 

37:21 82:17 88:4 

included 5:5 18:15 25:7 

40:21 

including 11:7 31:12 

43:3 54:4 76:16 77:8 

inclusion 70:4 73:2 

incompetence 91:13 

incorporate 19:11,12 

89:5 

incorporates 82:2 

increase 32:7,13,21 

35:4,12,15 36:4 49:14 

increased 8:12 70:18 

76:7 

increases 33:19 

increasing 32:4 33:11 

indefinitely 66:13 

individual 39:8 

individuals 105:19 

industries 18:5 25:9 

61:16 

industry 1:3 8:3 9:10 

24:12 25:17 30:18 

31:19 32:8 34:11 

50:21 53:4,12,19 54:6 

55:9 58:2 59:16 60:11 

60:16 67:6,13 90:21 

105:8,15,22 108:5 

industry's 63:14 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
114 

inflationary 58:3 

influence 23:2 

inform 8:4 9:11 83:6 

information 75:16 

86:16 

informs 88:2 

ingredients 51:4 

initiative 31:16 94:19 

initiatives 94:8 96:19 

input 87:15,17 99:5 

insert 14:5 

inserting 46:18 

insights 60:22 

inspections 86:10,14 

86:19 

instance 11:10 16:15 

instructions 41:4 

insurance 38:9,13 

intent 12:16 23:19 

28:18 33:6 34:8 40:9 

52:3 66:16 74:18 82:7 

intention 15:13 

intentionally 38:2 

interactive 73:18 

interest 5:7 9:11 

interpretation 54:18 

interpreted 33:15 

interrupt 75:6 

involved 87:16 

involvement 32:8 56:10 

involves 37:6 

issue 13:4 63:22 64:2 

66:8,13 69:14 

issues 16:8 85:1 

issuing 87:6 

It'll 107:11 

item 70:4 95:3,6,7,10 

95:12 96:1,8,18 

items 69:21 

J

JANIS 2:2 

JEFF 1:16 

Jennifer 69:21 73:2 

86:13 

job 25:1 103:18 

John 1:13 33:4 

joint 49:13,17 

judgment 42:16 

Julie 1:16 48:2 

July 56:11 

jump 17:5 

justify 11:8 

K

K 2:2 

K.C 1:14 

kale 90:12,14,16 92:6,7 

keep 6:20 7:1 10:16 

34:8 35:7 43:16 72:15 

92:18 95:18 

Kelly 1:18 59:11 

Kiley 1:12 82:6 101:5 

105:8 106:11 

KIRSCHENMANN 1:17 

known 8:6 79:22 

L

L 1:16 

label 41:4 43:20 47:17 

50:13 51:4,5,13 90:17 

labeled 43:12,13 

labels 50:16 

labor 32:15,16 33:3,10 

36:19 52:20 53:4,13 

53:15,22 54:5,12,17 

54:22 55:2 56:2 59:16 

59:20 60:6,10 62:17 

101:17 

lacking 93:19 

land 31:6 

language 10:20 26:20 

27:8 28:10 38:16 

41:19 42:8 43:20 

47:10 48:19 49:10 

50:7,13,14 64:10,12 

66:2 67:6 68:15 74:7 

76:13 103:17 106:15 

languages 75:17 

laptop 22:10 

larger 94:4 

late 6:17 

latest 48:20 

Laughter 15:5 29:18 

56:22 60:19 63:11 

65:17 108:8 

law 66:19 94:16 102:18 

lawsuit 47:3 

lead 105:7 

leader 101:6 

leaders 88:21 

leadership 82:11 88:2 

leading 108:14 

leads 6:9 65:22 97:16 

99:1 100:9,19 102:3 

Leanne 2:5 83:19 87:17 

leave 17:9 37:11 50:14 

68:8 92:17 98:22 

left 19:19 35:21,22 38:2 

legacy 48:20 49:2 

legislation 103:21 

106:4 107:8 

legislative 53:18 107:5 

107:10 

lend 102:22 

lends 83:15 

let's 9:2 10:3 17:15 28:9 

57:2 101:2 

level 13:1 97:13 98:2 

levels 49:1 

light 53:20 

lightning 64:5 

limit 31:21 35:9 

limited 31:18 39:3 54:5 

line 17:15 37:16 68:1 

95:3,6,7,9,12 96:1,8 

96:17 

LIPETZKY 1:17 36:22 

37:14 

list 75:21 

listed 30:16 80:5 90:12 

92:3 

little 6:17 23:19 26:6,15 

29:14,21 37:9 48:18 

53:6,6 57:2 62:4,7 

66:4 84:7 99:16,17 

lobbying 105:13,19 

local 31:9 

long 48:20 64:20 

longer 7:6 70:8 

look 57:19 58:1 95:3 

97:16 

looked 92:3 

looking 24:21 25:4 

26:15 31:13 98:3 

99:11 102:17 

looks 15:11 37:2 

Loosely 55:20 

lose 26:6 

lost 43:15 90:6,18 92:6 

92:10 

lot 13:2 38:16 60:7 

61:19 68:6,15 93:13 

lower 39:4 

lunches 84:22 

M

maintain 11:7 26:9 

major 78:10 79:20 

80:20,20,21 81:3 

90:11 

majority 4:6 23:22 

majors 92:3 

makers 78:11 

making 25:15 37:1 

62:13 

Management 44:11 

mandate 33:1 

mandated 35:20 40:19 

51:13 66:18 94:11 

mandating 34:4 36:4 

mandatory 51:13 62:5 

manner 50:16 71:7 

manufacturer 40:22 

manufacturers 50:15 

March 16:4 

market 8:8 12:13 20:21 

21:15 22:1,20 26:3 

27:22 76:10 79:16 

87:10,12 88:16 89:9 

91:7 

marketing 76:8 

markets 8:11 88:15 

material 49:2 50:18 

102:8 

materials 48:20 

matter 6:13 27:4 47:17 

108:20 

max 42:10 

mean 24:17,21,22 35:7 

60:7,14 61:8 66:2,8 

77:22 78:15 88:20 

92:5 95:16 98:18 

100:3 103:11,14 

105:14 106:9 

meaning 47:7 

meaningful 10:14 56:2 

means 15:21 18:11 

35:15,16 40:3 

meant 15:3 

meat 88:6 100:6 107:10 

mechanism 5:13 

meet 71:3 85:3,6,7 

98:19 

meeting 1:5 3:4,21 4:22 

69:16 

meetings 87:2 102:7 

member 23:1 106:6 

members 2:1 4:7 5:6 

69:17 76:15 

membership 61:22 

94:4 

mention 74:15 

mentioned 16:16 

met 1:8 

methodology 54:8 57:5 

58:20 59:2 

methods 54:22 

Mexico 24:13,19 

MICHAEL 2:2 

Michigan 43:22 

microbiological 70:18 

71:6 

mild 39:2 43:19 

million 36:2 

millions 90:5,6 

mind 84:3 100:4 

minutes 6:20 7:3 65:11 

98:1 103:12,12 

misrepresent 11:21 

missed 64:14 

missing 58:7 81:22 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
115 

mixed 11:15 

mixing 83:20 84:7 

models 84:15 

modernization 56:11 

modified 69:15 

modules 75:16,22 

molecules 40:22 

MOLLY 1:15 

money 31:22 94:22,22 

months 67:12 

morning 3:4 

motion 5:2 12:20,21 

13:22 14:4,14,14,15 

28:2,20 29:1 39:12 

52:11 65:2 68:19,20 

97:1,2 106:19 107:14 

107:15 108:15,17 

move 7:6 10:3 31:2 

36:11 38:6 44:5 52:8 

68:16 72:17 93:5 

106:12 

movement 43:3 

moving 12:6 39:7 58:22 

64:1 69:7,16 100:4 

107:8 

multi 104:14 

multi-agency 54:4 

multi-state 104:15,17 

multiple 75:17 

myriad 10:22 

N

name 7:19 

naming 46:5 

national 37:13 

nationwide 54:6 

native 31:13 

necessary 49:11 55:6 

need 5:16 6:22 12:9 

14:22 20:18 21:2 

22:16 24:3 26:21 

27:17 41:19 42:7 49:5 

53:13 59:17,19,22 

61:20 62:22 64:4 65:1 

65:12 66:4 82:10,11 

82:15 86:2 95:3 102:4 

needs 16:22 26:1,14 

31:10 39:12 48:15 

59:15 60:2 62:17 

75:21 78:9 92:2 98:8 

99:10,22 105:21 

never 29:15 106:6 

new 30:15 32:14,22 

34:14,21,22 35:3,5,10 

36:19 42:11 53:22 

56:18 75:17 76:13 

94:5,19 

nine 67:12 

non 43:12,13 

non- 47:11 

non-compliance 84:5 

non-target 47:8,9,18 

note 25:8 107:2 

notice 11:4 30:5 86:13 

number 4:8 5:9 9:4,18 

9:19 31:11 32:12,19 

36:3 37:1 42:6 43:4 

47:12 48:4 49:8 51:6 

53:3,11 54:3,11,21 

55:5,22 59:11 

O

o'clock 7:13 

objection 104:17 

objective 69:14 86:5 

obtain 70:20 

obtained 42:10 

Off-microphone 34:17 

42:5 43:18 49:7 52:21 

53:10 57:12,17 59:9 

59:12 61:4 68:5 69:9 

73:9 85:15,20 91:2 

93:3 100:20 

offer 77:16 81:2 

offers 9:13 56:12 

office 36:11 44:11,15 

45:7,8,9 76:14 79:9 

82:11 94:6 96:17 

Official 2:5 

officially 3:4 

offline 63:9 

offset 8:13 

once 4:7,8 

ones 68:16 

ongoing 53:20 

online 71:1 

open 3:11 22:14 82:12 

opening 106:10 

operation 73:1 

operations 71:1 

opinion 22:22 62:21 

OPP 45:6,8 46:4 

opportunity 32:5 

opposed 29:9 52:17 

69:5 97:10 

options 11:1 38:12 

order 3:5 5:3,11 7:2 

106:22 

Oregon 43:21 

organization 32:5 

45:14 

organizations 94:4 

original 22:5,11,15 

24:15 83:14 96:4 

originated 49:21 

outbreaks 86:11,20 

outreach 32:7 70:21 

76:8 94:17 

outside 15:9 55:8 

overall 34:3 

overspending 38:19 

overstep 104:18 

overview 87:22 

overviews 99:9 

P

P-R-O-C-E-E-D-I-N-G-S

3:1 

pack 94:13 

package 9:2 28:20 

55:11 99:12 100:14 

packed 55:18 

packers 70:17 76:12 

packing 87:5 

page 4:19 12:4,4,5 44:4 

44:5 47:22 48:16 76:5 

pain 89:5 

palatable 86:17 

PALMBY 2:3 

paragraphs 29:22 

99:10 100:17 

parens 81:1 

part 5:5 8:22 12:5 26:3 

26:3 63:22 66:18 

77:21 78:2 79:6,17 

PARTICIPANT 60:4 

62:1,4 63:12,15 64:10 

65:7 73:11 77:4 90:22 

91:16,18 92:12 93:1 

100:1 101:2 107:11 

108:16 

participate 54:20 

participates 65:19 

participation 11:13 

particular 31:15 47:7 

54:16 88:11 

particulars 23:17 

parties 27:8 

pass 54:12 

passage 104:2 105:13 

passing 29:6 

paste 22:4 

path 66:14 

PAUL 2:3 

PC 89:7 

PDP 45:7 

peaches 11:15 83:13 

84:21 

pears 11:15 

penalties 11:21 

people 23:22 55:18 

62:8 68:6 86:19 

105:16 

percent 15:22 16:3 

33:22 55:7 99:22 

percentage 25:20 

Perdue 17:6 

Perfect 70:13 

performance 42:15 

perils 38:14 

period 16:1 24:14 58:3 

98:17 

permanently 87:9 91:7 

person 98:19 

personally 29:17 

personnel 76:8 

perspective 37:13 

Pest 44:11,12,13 

pesticide 40:21 42:20 

44:9,11 45:8 46:12 

49:12 

pesticides 49:16 

pick 90:14 

piece 24:16 

place 21:19 

places 23:2 

plan 83:7 86:2 88:3,4 

plant 39:2 43:8,9,16 

46:22 47:2,18 

plants 43:12 

please 28:16 29:7 45:10 

52:15 69:2,12 97:7 

pleasure 18:19 102:20 

Plus 76:9 78:6 79:2 

PMA 93:15 

PMA's 93:19 

point 4:2 9:8 13:13,14 

36:2 37:2 66:21 71:11 

71:21 80:4 82:19 

83:14 90:10 93:22 

94:5,20 98:21 

points 30:17 74:16 

82:17 87:15 

policies 3:11 4:20 

policy 44:12,13 45:2,3 

45:4,8 102:18 103:1 

107:2 

pool 62:9 

pooling 67:7 

portion 33:2,16 35:18 

position 8:6 88:1 99:8 

100:5 106:3,11 

possess 56:5 

possible 34:16 35:9 

56:19 

post 61:8 

pot 36:2 

potential 31:13 32:8 

39:6 

POWELL-MCIVER 1:18 

practices 51:1 

pre-plant 39:5 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
116 

preamble 40:15 

precedent 51:10 

preclude 27:21 34:10 

precludes 25:17 

predictable 54:1 59:8,8 

prefer 34:13,20,21 

43:16 

preferred 56:4 

premise 57:22 

premiums 38:15 

prepares 3:19 

preseason 39:5 

presence 49:2 

present 1:11 2:4 5:1 

presented 4:7,8,13 7:2 

presenting 4:4 

presents 3:22 

President 8:6 

presiding 1:10 

pretty 39:21 82:4 

prevent 49:19 

preventive 72:22 73:17 

previous 81:13 87:8 

88:14 89:19 91:5 

primary 54:7 58:19 

prior 4:3 87:6 

priorities 31:9 36:8 

prioritization 36:10 

37:20 86:10,18 

prioritize 35:13,16 36:5 

36:18 38:1 

prioritized 75:18 

priority 59:21 60:7 

private 32:5,7 

probably 26:1 39:20 

41:18 58:9 63:8 106:9 

problem 9:3 14:9 18:8 

51:2 60:4,10,15,16 

92:11 107:7 

problems 39:17 

procedures 3:12 4:20 

process 3:14 4:2,18 

12:10 15:11,16,19,21 

16:22 17:7,12 18:7 

20:18 21:1,3,4,9,17 

21:22 22:6,17 25:12 

25:16 27:18 32:4 

33:14 49:14,18 56:7 

56:13,16 63:3 68:2 

87:6 93:2,12 94:2 

97:20 98:14 99:4 

108:12 

processed 92:12,13,22 

procurement 77:4,5 

78:11 79:6 85:1 

procurer 80:6,8,10,11 

procurers 77:6 79:10 

81:4 

produce 14:8 16:13 

20:4,17 22:16 26:14 

27:17 41:22 71:1 

72:21 73:16 79:21 

81:17 86:11,14,20 

94:9,9 

produced 11:6 

producer 13:9 24:11 

49:4 

producers 23:3 43:1 

50:17 66:9 70:16 72:4 

76:11 

product 12:1,9 15:14 

49:3 50:1,3 55:7,11 

78:21 84:13 89:6,9 

94:13 101:18,19 

production 12:12 13:16 

13:16 15:22 16:4,7 

17:13 20:20 21:8,14 

21:21 22:19 23:10 

24:8 25:13 27:19 43:8 

43:11 52:7 58:11 59:4 

102:15 

products 11:6,22 12:2 

12:12 20:20 21:8,14 

21:21 22:19 24:8,9,13 

27:20 42:15 43:21 

85:5 

program 9:12 37:5 

42:20 44:9,17 45:3 

46:13 54:20 56:3,4,6 

57:6 62:10 66:16 

67:21 68:3 73:18 

75:16 76:9 79:7 82:14 

programs 8:8,12 33:9 

71:2 73:4 84:6 

prohibit 15:14 

prohibited 48:21 64:1 

prohibitive 11:3 

project 32:6,6 

projects 32:7 70:22 

promotion 7:21 8:8,21 

9:20 

promotional 9:13 

proposed 13:8 56:11 

protect 23:20 24:3,18 

24:18 70:16 72:4 

105:14 

protected 30:14 84:2 

protecting 12:8 25:3 

43:10 99:21 

Protection 102:22 

prove 42:22 

provide 25:20 34:22 

35:3 88:9 

provided 9:1 10:20 

93:15 

providing 66:14 76:7 

provision 10:15 23:7 

27:21 

provisions 80:1 

public 11:4 32:7 61:8 

published 56:18 61:10 

pulled 3:11 

pulling 14:18 

punch 27:11 

purchase 10:11 11:5,8 

purchasers 78:3 

purchasing 84:5 

Purdue 72:20 73:6 

purposes 79:1 

purview 40:6 

push 62:8 

put 7:15 14:16 17:4 

23:19 28:7,19 34:12 

39:12 47:21 52:4 

74:19 82:17 91:20 

92:14 96:21 103:10 

106:19 107:2,22 

putting 28:7 29:19 

Q

qualify 9:14 

question 17:17 18:10 

24:6 32:18 43:6 69:18 

71:12 76:22 87:20 

103:5 

questions 9:17 12:4 

31:1 44:1 68:14 96:20 

queued 22:9 

quick 22:10,13 27:9 

69:18 71:12 

quicker 29:14 

quorum 5:1,12 

R

R 1:10,12 

rate 24:14 54:13 57:6,7 

57:9,10,20 58:1,19 

59:3 

re-evaluation 71:7 

reached 68:10 88:6 

read 3:15 6:4 8:20 14:6 

20:11 22:10,16 27:12 

48:1,3 53:1 60:21 

68:15 73:8 82:20 

92:20 99:7 

READE 1:18 

reads 85:16 

ready 96:21 

real 22:13 27:9 

reason 80:3 88:9 99:18 

reasonable 17:13 38:22 

receive 23:11 

reclassify 31:20 

recognition 76:11 

recognize 10:22 38:21 

39:16 40:15 48:19 

53:14 55:17 79:7 81:9 

recognized 79:19 94:1 

recognizes 15:6 

recommend 16:18 17:6 

19:3,22 20:12 27:14 

31:11 35:5 36:9 40:6 

41:19 42:9,14,19 46:6 

46:12,13 49:9 53:16 

54:21 64:8,18 72:2 

74:10,21,22 103:19 

104:6 105:20 106:7 

recommendation 3:20 

3:22 4:4,5,9,12,13,14 

4:15,16 8:1 10:18 

12:8 16:20 17:18,19 

17:20 18:1,11,16 

27:13 28:8 30:2 33:19 

38:9,20 39:11,12,13 

39:21 40:1,3,5,11 

41:11 42:8 44:2 45:5 

46:2 51:18 61:6 71:14 

88:1,7,20 99:19 

102:18 103:1,22 

107:2 

recommendations 3:9 

3:12,14,17,18 5:13 

8:21 28:18 29:7 31:4 

38:5 46:9 52:6,15 

53:2 66:3 97:13 98:13 

99:8 100:4,7 102:14 

105:6 107:6 

Recommendations/s...

18:20 

recommends 8:2,15 

9:9 31:20 32:2,13 

36:17 103:22 

record 6:14 27:5 65:11 

103:11 107:22 108:21 

recorded 5:4,8 

recruiting 32:16 

recur 96:5 

recurring 95:1,4,6,17 

95:22 96:1,8,17 

recusals 5:10 

recuse 5:6 

red 48:15 

reduce 39:6 

refer 4:15 

referenced 93:14 

referred 15:15 

refine 66:2 

refined 55:2 99:12 

100:4,9,16 

reform 56:12 

reforms 53:18,19 54:13 

regard 12:15 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
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regarding 86:10 

regardless 84:12 

regards 27:20 71:20 

83:10 

Regency 1:9 

region 55:12,17 

regional 12:11 16:2,8 

18:5,9 20:20 21:7,14 

21:20 22:7,19 23:21 

24:10,11,11 25:6,12 

25:17 31:9 73:2 

regionality 55:18 

registered 49:22 50:2,4 

registration 42:13,18 

42:21 49:12 

regs 75:10 

regular 68:2 83:4 

regulate 23:7 

regulations 61:9 

regulatory 49:4 87:4 

reject 4:15 

related 55:6 70:17 

79:12 84:14 86:11 

93:12 94:8 

relates 71:10 102:14 

relating 13:14 76:17 

relation 93:17 

remedies 12:9 13:9 

14:5,7 17:11 20:4,9 

20:17 22:16 26:13 

27:16 41:22 

remedy 16:12 

remember 36:3 40:15 

65:15 84:11 103:18 

reminder 92:18 

remove 36:1 46:8 55:16 

87:14 

renewed 42:12,21 

replenish 79:16 

report 17:22 33:9 40:4 

89:19 

represent 85:18 106:5 

represented 94:3 

request 8:5 25:16 31:4 

40:10 54:3,15 55:5 

56:1,15 64:8,17 71:15 

72:2 87:13 

requests 10:13 

require 11:4 49:10 50:7 

51:8 61:10 

required 11:7 

requirement 85:9 

requirements 10:10 

50:18 51:11 70:18 

71:3,8 

research 30:2 31:6,16 

31:18 32:3 33:20 38:5 

42:22 54:22 70:21 

resolution 12:10 15:11 

15:19,20 16:5,22 17:7 

17:12 18:6 20:18 21:1 

21:3,4,9,16,22 22:6 

22:17 25:12,16 27:18 

resonate 92:9 

response 33:22 52:13 

52:18 69:1,6 72:18 

76:4,19 83:2 86:21 

93:6 97:6,11 107:16 

rest 46:8 

restaurant 89:5 

restaurants 89:8 

restrict 11:20 

restrictions 8:13 

resulting 49:13 

resumed 6:14 27:5 

retailer 23:13 25:1 26:8 

89:6 

retailers 24:1 76:16 

77:9,10 78:5,8,13 

79:10,14 80:20 81:4,8 

81:19 90:12 

retain 53:19 

retool 66:2 

return 63:16 

revamped 99:22 

reversed 21:10 

review 31:12 32:3 88:10 

93:17 97:19 104:9 

reviewed 33:13 

reviews 49:11 

revise 98:20 

revisions 10:18 

RICHARD 1:13 

Richmond 1:9 

rid 48:15 50:8 

Robert's 5:3 106:21 

robust 55:1 85:18 88:4 

93:18 94:3 

rod 64:5 

Romaine 90:11,13 

room 1:9 108:13 

rotation 61:19 

round 25:1 39:1 

rule 55:6 56:11 71:2 

72:21 73:17 

rules 5:3 56:18 61:8,11 

73:20 106:21 

rural 94:10 

S

safe 108:19 

safety 51:11 71:2 72:21 

73:16 94:9,10 

salad 90:16 

sales 92:10 

sampling 70:21 

save 22:13 

saving 32:15 36:19 

saw 75:19 

saying 14:11,12 19:15 

21:13 26:12 33:15 

39:10 40:5 48:9 58:17 

59:1 63:8 64:3 79:5,5 

88:21 95:1 98:16 

says 18:3 33:22 46:3 

48:8 59:14,14 61:13 

71:22 89:19 105:4 

scale 66:8 

schedule 102:7 

school 10:10 11:7 

84:21 

schools 10:21 11:5,20 

science 40:16 

science-based 71:5 

screen 7:16 19:18 

83:19,20 

SCRI 31:21 33:2,21 

35:18 37:3,22 

season 42:16 

seasonal 27:19 

seasonality 13:4 16:8 

23:20 

seat 86:4 93:21 

second 4:20 9:8 10:4 

14:13,14,15 29:3,4 

30:5 48:14 52:10,12 

58:18 66:18 68:21 

71:17,20 73:12 97:3,4 

106:20 107:15,17 

108:16 

seconded 108:18 

Secretary 8:4,5 9:11 

10:14,16 16:18 17:6 

17:19 18:12,13 19:3 

19:16 20:1,12 27:15 

31:4,12,20 32:3,13 

33:1,7,15 34:9 36:11 

36:18 38:10 39:13,15 

40:2,11 42:9 45:13 

46:3,7,10,14 48:8 

50:6,19 53:16 54:3,15 

54:17 55:1 56:1,2,9 

61:7,20 62:19 64:9,12 

64:17,19 71:15,21 

72:2,20 73:8 74:2,11 

74:20,22 75:7 103:19 

104:1 105:6,21 

Secretary's 53:14 56:16 

76:14 79:9 82:11 94:6 

96:17 

section 3:15 4:19 10:11 

54:6 99:21,22 102:13 

seed 49:11,15,22 

seeing 65:15 

seek 49:10 54:9 58:4 

59:5 73:4 94:6 96:17 

seeking 87:15 

seen 104:5 

segment 85:19 

segments 82:3 

sell 90:17 

semantics 80:3 

Senate 13:15 102:16,17 

102:21 104:10 

send 45:13 97:15 

sense 89:11 

sensitive 39:2 43:8,8,9 

46:20 47:18,22 

sentence 23:5 34:13 

46:11 59:14 71:17 

separate 13:17 41:11 

103:8 

September 98:9 101:1 

serve 49:18 66:19 

served 85:14 

service 76:16 77:9,11 

78:5,9 79:11 80:21 

81:8,19 

serving 33:12 106:2 

setup 71:13 

shaky 39:21 

share 83:5 

shipped 55:11 

shorthand 19:20 

Show 29:11 

side 37:15 47:15 

SIEVERT 1:18 24:15 

25:19,22 34:22 35:3 

77:15,20 78:1 89:18 

89:22 91:11,14 97:2 

103:2 

sight 26:7 

significant 10:19 55:10 

56:12 

significantly 10:21 

similar 64:12 97:22 

Similarly 5:6 

simple 15:8 

simply 18:2,16 40:5 

80:3 

simultaneous 41:2 

44:18 49:17 65:8 72:8 

92:8 99:6,14 100:2 

103:15 

simultaneously 49:13 

situation 24:6 49:22 

size 85:7 

Skelton 2:5 75:6,10,13 

83:18,19 84:10 85:6 

85:10,13 92:21 95:13 

96:11 

skip 30:10 69:17 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
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slapped 71:10 

slice 95:19 

slide 30:6 

small 49:1 60:15 66:8 

66:13 70:22 71:1 

smaller 93:21 

SMITH 1:19 29:13,19 

30:3,8,11 31:3 32:20 

33:4 37:9 38:2,8,19 

39:17 40:8,13 41:3,13 

41:16,18 42:2,6 43:14 

43:19 44:3,21 45:17 

47:6,11,16 48:17 49:8 

50:8,12 51:9,16,19,22 

52:2,8 73:5 92:9,13 

smoother 29:14 

solid 56:5 

solution 62:16 64:1 

solutions 33:11 54:9 

59:6 

solve 60:9 

solving 53:15 

somebody 13:21 26:19 

37:15 47:2 59:10 

Something's 41:21,21 

soon 56:18 

sorry 42:7 84:18 99:13 

sort 40:18 50:2 76:13 

sought 11:12 87:17 

sounds 59:18 

source 12:1 23:14 80:7 

80:12 84:13 96:4 

sources 11:11 

southeast 25:5 

soybeans 42:11 

Spanish 71:3 75:20 

speak 96:1 

speaking 41:2 44:18 

65:8 72:8 92:8 99:6 

99:14 100:2 103:15 

specialty 30:14,16,20 

30:22 31:6,13,14 37:4 

37:6,10,22 38:3 43:1 

specific 33:6 46:5 

51:13 83:7,11 86:2 

94:8 95:3 97:16 

specifically 30:15 

88:17 94:15 

spent 85:17 

spin 23:19 

split 76:13 

splits 3:10 

squashes 83:13 

staff 2:4 108:12 

stakeholder 73:3 94:3 

stakeholder-driven

93:10 

stakeholders 54:7 

56:17 61:17,21 82:15 

93:21 

stance 104:19,20 

stand 13:13 

standards 50:22 71:6 

83:9 86:7 

standing 106:22 

start 3:7 7:12 40:10 

49:5 69:20 71:17 

started 41:22 67:6 

starting 6:17 

state 18:16 38:3 46:22 

statement 9:4 17:9 18:2 

18:17 19:1 22:15 

62:14 69:14 74:4 

81:13 87:22 88:1 

103:20 

statement's 100:11 

statements 99:8 100:5 

100:10 

states 1:1 8:9 9:16 23:8 

26:7 37:11,17 86:12 

102:15 

stations 31:7 

status 4:3 

stay 6:22 25:2 68:10 

step 104:21 

steps 3:18 

Steve 1:19 29:11 

stick 92:5 

stores 89:7 

straight 53:2 80:10 

99:20 

strain 90:3 

strawberries 16:3 

83:12 

streamline 64:22 

streamlined 56:6 63:3 

streams 94:7,15 95:1,4 

street 90:18 

strength 16:13 

strengthen 51:15 

strengthened 12:10 

16:22 20:18 22:17 

26:14 27:17 83:14 

strengthening 13:16 

strike 10:19 13:10 

85:14 

strokes 67:19 

strong 79:17 

strongly 41:19 76:14 

79:9 105:1 

study 58:1,19 59:2 

studying 54:7 

stuff 36:12 53:1 

sub 28:19 45:13 

sub- 69:15 

subcommittee 23:1 

subject 49:4 

submit 56:17 106:13 

submitted 93:17 100:17 

subsequently 101:22 

substantive 29:21 

101:19 

Substituting 62:14 

substitutions 11:13 

successfully 8:10 

76:10 

suggest 28:12 

suggested 34:7 69:22 

72:1 

suggesting 23:6 45:21 

suggestion 39:14 45:11 

summer 99:3 

super 95:16 

supplier 23:12 75:15 

suppliers 12:14 20:22 

21:16 22:1,21 23:3,5 

26:4,10 28:1 

supplies 22:21 24:2 

supply 11:11 23:8 

25:14,20 53:21 61:22 

77:18,19 78:18 79:6 

80:15,19 81:7,9,18 

82:1 83:8,9 86:5,6 

89:7,10,12,16 91:8,10 

91:12,19 94:18 

supplying 11:20 24:7 

24:22 

support 9:13 26:7 31:5 

55:3 63:14,15,16 76:6 

102:21 104:1,14 

106:8 107:9 

supported 62:19 

104:14 

supports 10:9 100:7 

103:18 

supposed 57:19 

survey 54:22 

surveying 83:11 

sustainability 57:21 

58:11 59:4 

sustainable 12:13 

20:21 21:15 22:1,20 

26:3 27:22 54:2 

sustaining 9:12 

switched 11:22 

switching 48:17 

symbols 51:13 

sync 40:20 

system 90:13 

T

table 6:9 7:7 70:12 86:4 

93:22 102:8 

tables 3:9 

taken 21:11 

takes 7:5,6 

TALBOTT 1:19 68:21 

107:7,12 

talent 108:12 

talk 7:22 8:20 37:9 85:2 

talking 10:8 65:20 

79:15 80:17 84:11 

88:18,18 

talks 40:16 

target 38:20,21 39:7 

43:2 47:12 107:8 

task 7:1 54:4 

team 17:4 56:9 

tech 70:12 

technical 28:12 76:10 

76:18 77:12 79:12 

83:5 86:3 96:14 

technically 47:16 95:21 

technology 32:10,15 

33:11 34:1 36:20 

40:20 

teeth 107:4 

tell 101:7 

temperature 39:5 

temporarily 87:9 88:14 

91:1,6 

temporary 54:18 66:10 

terminology 50:22 

terms 38:14 

Tester 94:12 

testing 70:18 71:6,8 

text 30:6 

thank 16:10 29:13 53:7 

68:13 70:7 75:11 99:1 

102:9 107:20 108:9 

108:14 

Thanks 108:18 

they'd 36:6 67:18 

things 7:22 14:2 42:2 

43:5 59:18 65:21 

83:21 84:7 98:17 

106:16 

third 11:17 32:1 

thirds 5:21 

thought 13:4,18 37:11 

58:7 65:16 

three 4:2,15 9:18,20 

10:1 32:1 66:6 67:11 

82:3 87:21 

THURSDAY 1:7 

ties 25:15 

time-limited 94:16 

timeframe 100:16 101:6 

timeframes 25:10 

timely 71:6 

times 68:6 

TINA 1:14 

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(202) 234-4433 Washington DC www.nealrgross.com 
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tip 72:14 

TISON 1:20 46:19 65:15 

today 65:11 99:4 

103:13 104:18,20,20 

104:22 106:16 

tolerance 38:22 

tolerances 45:18 

TOM 1:17 

tomato 92:10,11 

Tommy 1:21 7:20 27:11 

28:18 

Tommy's 90:10 

top 35:20 75:20 

topic 38:7,18 

topics 102:4 

total 5:5 

touches 66:4 

town 87:1 

traceability 87:6 

trade 6:11 7:10,11,20 

7:21 8:2,13,14,15,20 

9:9,20 13:7,8 14:6,7 

15:12 16:9,11 17:11 

18:4,15,18 19:5,8,11 

19:13,15,17 20:2,3,6 

20:10,13,14,16 23:16 

25:7 27:16 29:6 42:4 

83:16 102:13 103:6 

training 71:2 94:8,10 

96:18 

transport 78:19 

travel 108:18 

tree 47:14 73:19 

trees 43:15 

tried 86:16 90:2 

trouble 86:19 

truckers 79:2 

try 7:1 81:6 

trying 12:16 23:7 24:17 

24:18 47:4 78:4 85:17 

85:22 94:21 106:17 

tune 65:7 

turn 43:7 

two 3:20 4:14 9:21 14:2 

31:11 42:2,7 43:5 

48:4 49:14,19 50:1 

62:19 70:11 74:15 

75:12 84:19 98:3 

100:18,21 101:2,4,11 

105:18 

two- 5:20 

two-thirds 4:21 5:14,14 

13:19 

type 15:7 37:21 47:9 

57:9 71:13 73:1 87:21 

88:4 97:14 

U

U.S 9:12 12:8 24:9 

27:14 62:10 104:1 

ugly 107:12 

unable 54:12 

unanimous 102:13 

undergone 55:9 

understand 17:20 23:4 

63:7 64:2 74:9 78:5,9 

78:20 79:18 84:19 

106:11 

understanding 55:9 

87:3 

understands 105:8 

undocumented 62:9,15 

63:4 

undue 70:17 

uniform 50:16 84:13 

uniformality 51:15 

uniformly 84:1 

unique 38:15 

United 1:1 8:9 9:16 23:8 

26:7 61:16 86:12 

93:15,19 102:15 

universities 31:7 

update 19:21 64:21 

urge 38:9 

USDA 2:5 30:21 37:18 

37:20 39:11 42:19 

44:10 45:7,14,21 

46:12 48:18 49:9,11 

50:13 54:5,21 55:5 

64:8,15 70:19 71:22 

72:1 74:8,15 76:9 

80:2 84:8,17,22 86:9 

87:1 93:8,20 94:1 

106:2,7 108:12 

USDA's 83:4 84:5 86:3 

use 19:20 42:11,17 

44:22 49:9 64:12 

71:14 73:1 

user 31:9 

USMCA 12:16 

usually 66:22 

utilized 55:3 

utilizing 56:3 

V

V2 22:13 

VA 1:9 

various 88:2 

vegetable 1:3 8:3,16 

9:10 11:1 17:10 30:18 

31:19 38:11 48:22 

53:3,12 59:15 87:7 

93:9 

vegetable-mixed 73:1 

vegetables 11:9 87:10 

92:1 

verbalizing 63:3 

verbiage 14:15 26:12 

26:16 37:21 75:13,14 

83:7 95:17 

verification 73:18 75:16 

versions 98:3 

versus 43:8 68:7 95:5 

Vice 1:12 

Vietnam 75:20 

visitors 108:13 

volatility 43:3 

volume 75:18 

vote 4:3,5,21 5:5,16,21 

9:2,5 13:22 14:22 

15:19 28:8 102:13,21 

104:7 

votes 4:9,21 5:8,9,10 

voting 4:18 5:13 65:5 

W

wage 54:9 57:6,7,9,9,19 

58:1,15 59:3,6 

Wait 103:4 

wanted 37:12 44:15 

72:11 84:12 93:22 

102:19 

wanting 23:15,18 

wants 6:10 13:22 

103:12 

warehouse 90:15 

warrants 73:18 

Washington 43:21 

wasn't 38:16 87:18 

water 70:21 71:5,8,10 

way 23:2,6 28:4 31:17 

40:22 64:7 67:8,8 

74:9 81:6 83:8 105:9 

weakens 104:19 

week 101:12,15 

weeks 100:18,21 101:2 

101:4,11 

Welcome 3:3 

went 6:14 7:9,11 27:5 

108:21 

WHEELER 1:20 

whoever's 24:22 

wholesalers 76:1 78:16 

Wilkins 1:21 6:11 7:10 

7:15,19,20 9:5,8,18 

10:1,6,8 11:19 12:7 

12:18 13:11 14:2,9 

15:1,13 16:11 17:2,14 

18:22 19:8,14,22 20:6 

20:9,16 21:6,11,18 

23:12 26:5 27:13 

28:22 29:11,16 76:22 

77:2,7 78:4,8,14 

79:14 80:7 81:11,20 

82:4,19 84:8,16 85:21 

88:16 89:4,14,21 90:1 

90:9 91:19 99:13,15 

100:21 101:3 104:16 

107:5 

Wingard 1:21 14:4 15:3 

20:14 29:4 34:12,20 

41:6,20 42:3 47:14,19 

52:10 53:5 63:21 64:7 

64:11 77:14 78:17 

80:4,14 82:16 90:10 

92:7,14 94:21 105:3 

105:12 108:3,9 

wish 70:16 

withdraw 4:5 

wives 68:9 

Wonderful 70:6 

wondering 37:16 40:19 

word 18:22 23:20 28:13 

35:12 40:13 46:20 

51:7 62:2 65:15 77:2 

90:5 96:1 

wordiness 93:13 

words 14:5 72:9 

wordsmith 75:5 101:20 

wordsmithing 29:22 

work 5:18 18:14 19:4 

19:16 20:1,12 26:12 

27:15 28:11 39:15 

40:14 42:20 45:1,21 

46:14 50:6,13,19 

53:16 54:18 55:1,5 

61:16 65:22 66:10 

67:12 68:12 71:5 

72:20 75:7 84:19 87:1 

93:8 97:13 98:10 

101:21 104:2,11 

worked 5:19 

worker 66:21 67:4,10 

67:22 68:8,11 

workers 55:4 62:9,15 

63:4 67:5,7,18 68:8 

workforce 53:20 54:1 

54:14 62:15 67:11,13 

68:7 

workgroup 3:16,17,19 

3:21 4:4,7,9,12,13,16 

5:15 7:21 8:2 9:9 

69:14 88:5 92:4 93:10 

99:10 100:9,9 

workgroups 87:21 

working 3:6,8 14:20 

18:19 28:19 52:6,9 

92:18 98:10 99:2 

100:19 101:5 

workplace 51:11 

works 16:18 19:8,10 

38:13 66:7 

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(202) 234-4433 Washington DC www.nealrgross.com 
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wouldn't 24:10 34:9 

67:4,17 68:2 71:14 

write 50:16 

writing 51:14 77:12 

103:10 

written 23:2 28:3,10 

wrong 21:19 40:1 45:13 

53:8 

X

X 107:9 

XYZ 45:15 

Y

year 11:12 23:13 24:1,7 

25:1,20 26:8 54:19 

66:11 67:1 94:22 

years 50:1 62:16,19 

67:11 

yesterday 3:5,13 7:3,9 

7:12 30:4,13 44:9 

69:22 86:13 

Z

ZEA 1:22 22:22 23:6 

28:12 80:15 81:1 

104:9 

zoom 53:5 

0

1

10 27:3 33:22 

10,000 90:18 92:6 

10:00 7:13 

10:02 27:5 

10:15 27:6 

100 99:22 

101 13:14 102:16,21 

11:30 92:17 

11:45 108:21 

12:00 7:1 

15 1:7 27:3 

16 13:15 102:17,22 

2

2 37:1 44:5 54:3 

2008 92:11 

2018 10:12 

2019 1:7 42:16 56:11 

2020 42:17 

25 15:22 

26 56:11 

2799 1:9 

3

3 54:11 

30 6:19 7:3 65:10 

30th 101:3 

365 15:22 16:7 23:13 

24:1,7 26:8 

4

4 54:21 

4.00 24:20 

4207 10:11 

45 36:1 

5

5 55:5 

51 55:7 

6

6 55:22 

60 36:3 65:10 66:22 

61 61:18 

7

7 4:20 

7:59 3:2 

70 36:3 

75 16:3 

8

8.00 24:19 

8:00 1:10 3:6 

8:03 6:14 

9

9:00 3:7 

9:34 6:15 

90 65:13,14 

Neal R. Gross and Co., Inc. 

(202) 234-4433 Washington DC www.nealrgross.com 
 

121

C E R T I F I C A T E 

This is to certify that the foregoing transcript 

In the matter of: Fruit and Vegetable Industry

Advisory Committee Meeting

Before: USDA

Date: 08-15-19

Place: Arlington, VA

was duly recorded and accurately transcribed under 

my direction; further, that said transcript is a 

true and accurate record of the proceedings. 

 ----------------------- Court Reporter 

NEAL R. GROSS 

COURT REPORTERS AND TRANSCRIBERS 

1323 RHODE ISLAND AVE., N.W. 

(202) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com 
  

  

     

  

       

            

                     

                       

               

     

  

                               

     

  

  

  

                           

                           

                                   

                            

   

   

Hughes, Darrell A - AMS 

From: Chalmers Carr <chalmers@titanfarms.com> 

Sent: Tuesday, September 10, 2019 3:52 PM 

To: AMS - SCP FVIAC 

Cc: Hillary Barrow; Tommy Wilkins; Kiley Harper-Larsen 

Subject: Re: Please Approve - FVIAC August 2019 Meeting Minutes 

I approve

Chalmers Carr

803 480 0545

Titan Farms

Sent from my iPad

Please excuse any typos or grammatical errors

On Sep 10, 2019, at 8:35 AM, AMS ‐ SCP FVIAC <SCPFVIAC@usda.gov> wrote:

CAUTION: This email originated from outside your organization. Exercise caution when opening

attachments or clicking links, especially from unknown senders.

Good morning Chalmers:

I’ve attached the meeting minutes for the August 14‐15 FVIAC session. Please respond to this email

approving the minutes.

Thanks,

Darrell

<image003.jpg> Darrell A. Hughes | Designated Federal Officer 

Fruit & Vegetable Industry Advisory Committee 

U.S. Department of Agriculture | Agricultural Marketing Service 

Desk: (202) 378-2576 | Mobile: (202) 336-2016 

SCPFVIAC@ams.usda.gov 

This electronic message contains information generated by the USDA solely for the intended recipients.

Any unauthorized interception of this message or the use or disclosure of the information it contains

may violate the law and subject the violator to civil or criminal penalties. If you believe you have

received this message in error, please notify the sender and delete the email immediately.

<0814USDA FVIAC.pdf>

<0815USDA FVIAC.pdf>

1