Microbiological Data Program - Annual Summary, Calendar Year 2009

United States 

Department of 

Agriculture

Agricultural 

Marketing Service

Science & 

Technology 

Programs

Microbiological Data Program

Progress Update and 2009 Data Summary

Please Visit Our Website at www.ams.usda.gov/mdp

January 2011
Microbiological Data Program - Annual Summary, Calendar Year 2009

United States

Department of 

Agriculture

Marketing and

Regulatory

Programs

Agricultural

Marketing

Service

1400 Independence Ave.

Washington, DC

20250

AMS-Agricultural Marketing Service

An Equal Opportunity Provider and Employer

January 2011

To the Reader:

I am pleased to present the USDA Microbiological Data Program (MDP) 2009 

Data Summary. In 2009, MDP tested eight commodities (cantaloupe, cilantro, 

green onions, hot peppers, lettuce, spinach, sprouts, and tomatoes). MDP also 

performed a special survey of peanut butter to assist the Centers for Disease 

Control and Prevention and the U.S. Food and Drug Administration during the 

Salmonella typhimurium outbreak investigation. 

MDP is a partnership with cooperating State agencies that are responsible for 

sample collection and analysis. Eleven States participated in the program in 2009: 

California, Colorado, Florida, Maryland, Michigan, Minnesota, New York, Ohio, 

Texas, Washington, and Wisconsin. Because together these States represent all 

regions of the country and more than half the Nation’s population, MDP data can 

be used to develop inferences about the national food supply. With a sampling 

framework and testing laboratory capability in place, MDP has demonstrated its 

ability to quickly mobilize and respond to outbreak situations providing data 

rapidly during local and national outbreaks.

This summary is intended to provide the reader with an overview of data collected 

in 2009 and summarizes program refinements made during that year. MDP data 

are important in developing baseline levels of targeted pathogens in the domestic 

food supply. As a continuous data-gathering program, MDP data can be used to 

identify microbial trends and to develop risk models.

If you have comments or suggestions on how this summary can be improved, 

please send electronic-mail to amsmpo.data@ams.usda.gov or visit our Web site at 

www.ams.usda.gov/mdp.

Sincerely,

 

Rayne Pegg

Administrator
Microbiological Data Program - Annual Summary, Calendar Year 2009

Contents

Page No.

Acknowledgements ........................................................................................................................ vii

Executive Summary ........................................................................................................................ ix

Section I. Introduction..................................................................................................................... 1

Section II. Sampling........................................................................................................................ 4

Section III. Laboratory Operations................................................................................................ 11

Section IV. Database Management ............................................................................................... 13

Section V. Summary of 2009 Data................................................................................................ 15

References..................................................................................................................................... 21

Disclaimer ..................................................................................................................................... 21

Definitions..................................................................................................................................... 22

iii
Microbiological Data Program - Annual Summary, Calendar Year 2009

v

Figures and Tables

Figures Page No. 

 1 MDP Program Planning and Program Testing Operations............................................2

 2 Program Participants .....................................................................................................3

 3 Commodity Origin.......................................................................................................10 

4 MDP Data Pathway ....................................................................................................14

5 Salmonella Isolates PFGE Patterns..............................................................................21

Tables

1 Sample Sizes.................................................................................................................5

 

2 Sample Origin by State or Country ..............................................................................7

3 Samples Collected by State .........................................................................................9

4 Number of Samples Analyzed....................................................................................12

5 Number of Samples Tested for E. coli .......................................................................15

6 Summary of Sample Analysis for Pathogenic E. coli ................................................16

7 Characterizations of 2009 non-O157 Pathogenic E. coli Isolates..............................17

8 Summary of Analysis for Salmonella ........................................................................18

9 Characterization of 2009 Salmonella Isolates............................................................19

10 Salmonella Species Isolated From Commodities Implicated in Outbreaks ...............20
Microbiological Data Program - Annual Summary, Calendar Year 2009

vii

Data presented in this report were collected and processed through the efforts of the following 

organizations:

State Agencies

California Department of Pesticide Regulation

Colorado Department of Agriculture

Florida Department of Agriculture and Consumer Services

Maryland Department of Agriculture

Michigan Department of Agriculture

Minnesota Department of Agriculture

New York Department of Agriculture and Markets

Ohio Department of Agriculture

Texas Department of Agriculture

Washington State Department of Agriculture

Wisconsin Department of Agriculture, Trade and Consumer Protection

Laboratories

 

Colorado Department of Agriculture

Inspection & Consumer Services Division

Laboratory Section

2331 West 31st Ave.

Denver, CO 80211-3859

Florida Department of Agriculture and Consumer Services

Bureau of Food Laboratories, Bldg. 9

3125 Conner Blvd.

Tallahassee, FL 32399-1650

Michigan Department of Agriculture

Laboratory Division

1615 South Harrison Rd.

East Lansing, MI 48823-5224

Minnesota Department of Agriculture

Laboratory Services Division

601 Robert Street North

St. Paul, MN 55155-2531

New York Department of Agriculture and Markets

Food Laboratory

1220 Washington Ave.

State Office Campus, Bldg. 7

Albany, NY 12235

Acknowledgements
Microbiological Data Program - Annual Summary, Calendar Year 2009

Ohio Department of Agriculture

Consumer Analytical Laboratory Bldg. 3

8995 East Main St.

Reynoldsburg, OH 43068

U.S. Department of Agriculture

Agricultural Marketing Service

National Science Laboratory

801 Summit Crossing Pl.

Gastonia, NC 28054

Washington State Department of Agriculture

3939 Cleveland Ave., SE.

Olympia, WA 98501

Wisconsin Department of Agriculture, Trade 

 and Consumer Protection

Bureau of Laboratory Services

4702 University Ave.

Madison, WI 53705

Program Administration

U.S. Department of Agriculture

Agricultural Marketing Service

Deputy Administrator, Science and Technology Programs: 

Robert L. Epstein

1400 Independence Ave., SW., Room 1090-S

Washington, DC 20250

Director: 

Martha Lamont

Monitoring Programs Office

8609 Sudley Rd., Ste. 206

Manassas, VA 20110

(703) 330-2300 x 117, Facsimile (703) 369-0678

E-mail: amsmpo.data@ams.usda.gov

Web site: www.ams.usda.gov/mdp

viii
Microbiological Data Program - Annual Summary, Calendar Year 2009

ix

In 2001, the U.S. Department of Agriculture 

(USDA), Agricultural Marketing Service 

(AMS) was charged with implementing 

microbiological testing of fresh fruit and 

vegetables in the United States. The program’s 

mission is to provide statistically reliable 

information regarding targeted foodborne 

pathogens and indicator organisms on fresh fruit 

and vegetables. The Microbiological Data 

Program (MDP) is a voluntary data-gathering 

program, not a regulatory enforcement effort.

AMS coordinates MDP planning and program 

requirements on a continual basis with the 

Centers for Disease Control and Prevention 

(CDC), the U.S. Food and Drug Administration 

(FDA), and the USDA National Agricultural 

Statistics Service (NASS). The participating 

States play a prominent role in program 

planning, providing sampling and testing 

support, and technical advice on methods and 

quality assurance (QA) issues.

MDP collects produce samples from terminal 

markets and wholesale distribution centers on a 

year-round basis. The MDP sampling frame is 

designed to take into account population and 

consumption on a national scale. In 2009, 11 

States collected fruit and vegetable samples 

(California, Colorado, Florida, Maryland, 

Michigan, Minnesota, New York, Ohio, Texas, 

Washington, and Wisconsin).

The program tested eight commodities: 

cantaloupe, cilantro, green onions, hot peppers, 

lettuce (conventionally grown and organic), 

spinach, sprouts (alfalfa or clover), and 

tomatoes (round and Roma) for non-O157 

Escherichia coli (E. coli) carrying shiga toxin 

and enterotoxin genes (STEC/ETEC), E. coli

O157:H7, and Salmonella. These samples were 

also tested for generic E. coli, and this testing 

was discontinued to focus on foodborne 

pathogens. Per request of CDC, a special 

survey of peanut butter samples was conducted 

Executive Summary

between February and September in response 

to the peanut products-related outbreak. 

Peanut butter samples were screened for the 

presence of Salmonella.

MDP analyzed a total of 16,896 samples during 

12 months of sampling and analytical 

operations. Seventy-four percent of the samples 

were from domestic sources, 25 percent were 

imported, and 1 percent was of unspecified 

origin. MDP identified 51 samples with E. coli

carrying shiga toxins; however, pathogenic E. 

coli strains were isolated from only 24 samples. 

These isolates were sent to Pennsylvania State 

University for further characterization, 

including serotyping and testing for different 

virulence-specific genes associated with 13 

different categories of pathogenic E. coli, and 

the Ohio Department of Health conducted 

genomic fingerprinting on these isolates. MDP 

sample screening for Salmonella resulted in 90 

preliminary positive samples, and from these, 

32 Salmonella isolates were reported to the 

FDA and CDC.

In 2009, three MDP Salmonella isolates were 

matched with past outbreaks. Information from 

one of the isolates from green onions helped 

FDA to issue an import alert. In addition, a 

number of important benefits are being derived 

from MDP. Coordination with public health 

agencies has increased, allowing early 

intervention by regulatory agencies when 

problem areas are identified, and communication among State and Federal agencies for 

the reporting and sharing of data on foodborne 

outbreaks has improved. Microbiological data 

obtained from MDP’s fresh produce screening 

efforts can be used to enhance the understanding of potential pathogens in fresh fruit 

and vegetables in the U.S. food supply, permit 

the identification of long-term trends, and 

contribute significantly to a national produce 

microbiological pathogen prevalence baseline. 

MDP data, which in part reflect changes in 
Microbiological Data Program - Annual Summary, Calendar Year 2009

fresh produce group/packaging/shipping 

practices to meet changing consumer life styles 

and preferences, will help refine Good 

Agricultural Practices and Hazard Analysis and 

Critical Control Points plans used by growers, 

processors, and food handlers. Furthermore, 

MDP data, which include antimicrobial 

resistance, genomic fingerprints, serotypes, and 

virulence attributes, will assist collaborators 

such as CDC and FDA in planning public 

health initiatives and responding to producerelated foodborne outbreaks.

x
Microbiological Data Program - Annual Summary, Calendar Year 2009

1

I. Introduction 

Fresh produce is recognized as an important 

component of a healthy diet. Because most 

produce is grown in the environment, it may be 

vulnerable to contamination with pathogens. Produce is often consumed raw without 

any type of intervention that would reduce or 

eliminate pathogens prior to consumption, which 

contributes to its potential as a source of 

foodborne illness [Ref. 1, 2]. In 2001, Congress 

authorized funding for a microbiological 

monitoring program to collect data on fresh fruit 

and vegetables. The U.S. Department of Agriculture’s (USDA) Microbiological Data Program 

(MDP) plays a key role in support of the 

Secretary’s priority to promote a safe, sufficient, 

nutritious food supply and his call for a modern 

food safety system. Fresh produce is recognized 

as an essential component of everyday healthy 

eating and in fighting obesity, especially during 

childhood. It is essential that fresh produce be 

free from contamination in order to safeguard 

public health, particularly vulnerable segments of 

the population, including children and the elderly.

MDP’s mission is to collect information 

regarding the incidence and identification of 

targeted foodborne pathogens on fresh fruit and 

vegetables. This publication provides an overview of data collected in 2009 and summarizes 

program refinements made during that year. The 

Agricultural Marketing Service (AMS) Monitoring Programs Office (MPO) manages MDP and is 

responsible for the program’s administrative, 

sampling, technical, and database operations.

Figure 1 (a) illustrates MDP program planning 

participants. AMS coordinates MDP planning 

and program requirements with the Centers for 

Disease Control and Prevention (CDC), the U.S. 

Food and Drug Administration (FDA) and 

participating States and relies on their 

scientists’ expertise for technical direction. 

The USDA National Agricultural Statistics 

Service (NASS), in collaboration with AMS, 

designed the sampling frame taking into 

account per capita consumption, marketplace 

availability, and crop production statistics. 

Figure 1 (b) depicts MDP program testing 

operations. The participating State laboratories and AMS National Science Laboratory 

(NSL) analyze MDP samples collected by 

trained State sample collectors. Additional 

testing to characterize positive findings is 

performed by the Ohio Department of 

Agriculture (ODA), the Ohio Department of 

Health (ODH), and the Pennsylvania State 

University (PSU). Information on MDP data 

and isolates is shared with CDC and FDA.

Commodities tested were selected in 

consultation with CDC and FDA and were 

chosen because they are high-consumption 

fruit and vegetables in the U.S. diet, are often 

consumed raw, and have been implicated in 

foodborne outbreaks. Commodities tested in 

2009 included: cantaloupe, cilantro, green 

onions, hot peppers, lettuce (pre-bagged 

organic and Romaine), spinach, sprouts 

(alfalfa or clover), and tomatoes (round and 

Roma). Commodities were tested for generic 

Escherichia coli (E. coli), E. coli strains with 

human pathogenic potential including E. coli

O157:H7, and Salmonella. MDP laboratories 

also performed multiplex polymerase chain 

reaction (mPCR) screening for pathogenic E. 

coli on all samples. Isolates of these 

organisms were sent to specialized laboratories for further characterization including 

serotyping, testing for antimicrobial 

susceptibility and virulence attributes, and 

genomic fingerprinting.

Microbiological Data Program (MDP)

Annual Summary, Calendar Year 2009

This summary consists of the following sections: (I.) Introduction, (II.) Sampling, (III.) Laboratory 

Operations, (IV.) Database Management, (V.) Summary of 2009 Data
Microbiological Data Program - Annual Summary, Calendar Year 2009

2

Figure 1. MDP Program Planning and Program Testing Operations. This figure illustrates (a) agencies/

groups that support MDP program policy and planning activities, and (b) agencies/groups that analyze MDP 

samples, isolates, or results. 

U.S. Food and Drug 

Administration Participating 

States

(a) MDP Planning

(b) MDP Program 

National 

Agricultural 

Statistics Service

Centers for 

Disease Control 

and Prevention

Participating 

States National Science 

Laboratory

Pennsylvania 

State University

Centers for 

Disease Control 

and Prevention

Food and Drug 

Administration / Center 

for Food Safety and 

Applied Nutrition
Microbiological Data Program - Annual Summary, Calendar Year 2009

3

In addition, MDP conducted a special 9-month 

survey of peanut butter at the request of CDC as 

a follow up to the peanut paste-related S. 

typhimurium outbreak. Peanut butter samples 

were tested for Salmonella only.

Samples were collected in the 11 participating 

States through cooperative agreements with their 

respective agencies (Figure 2). Also shown in 

Figure 2 are the 13 neighboring States that are in 

the direct distribution networks for the MDP 

collection States: Alaska, Connecticut, Delaware, 

Hawaii, Idaho, Massachusetts, Nevada, New 

Jersey, New Mexico, Oklahoma, Vermont, 

Virginia, and Wyoming. Together, these States 

represent over 50 percent of the Nation’s 

population and all geographic regions of the 

country, with significant rural-to-urban variability. Therefore, MDP samples are a statistically 

defensible representation of the country as a 

whole.

Analytical services were provided by 

microbiology laboratories in eight States 

(Colorado, Florida, Michigan, Minnesota, New 

York, Ohio, Washington, and Wisconsin) and 

the AMS NSL. The States of California, 

Maryland and Texas did not provide testing 

services. Their samples were transshipped 

overnight to be analyzed by one or more State 

laboratories or the AMS NSL. 

MDP employed DNA-based screening for 

Salmonella and for pathogenic E. coli, 

including E. coli O157:H7. All produce 

samples were screened for the presence of 

pathogenic E. coli that carry shiga toxin 

(STEC) and/or enterotoxin (ETEC) genes, 

Nevada

Idaho

Wyoming

New

Mexico

Hawaii

Alaska

Virginia

Delaware

Connecticut

Massachusetts

Michigan Vermont

New Jersey

Figure 2. Program Participants. During 2009, AMS established cooperative agreements with 11 States 

to sample and/or test MDP commodities. Samples collected by California, Maryland and Texas were 

shipped to one or more MDP laboratories for analysis.

New

York

Texas

California

Oklahoma

Washington

Wisconsin

Florida

Participating State

Minnesota

States where produce is directly marketed from 

Participating States

Location of Participating State Laboratories (white stars) 

Federal Laboratory (black star) 

Maryland Colorado

Ohio
Microbiological Data Program - Annual Summary, Calendar Year 2009

4

safety decisions. MDP continues to adopt 

faster, more sensitive analytical tools for 

improved microbial detection and reporting. 

Working with FDA and FERN, MDP is 

harmonizing methodologies for testing foodborne pathogens among the agencies. MDP 

periodically upgrades data collection systems 

for better database management. 

II. Sampling 

The goal of the MDP sampling program is to 

obtain a statistical representation of selected 

commodities in the U.S. food supply by 

randomly selecting samples from the national 

food distribution system. The MDP sampling 

frame is designed to take into account regional 

diversity, marketplace availability, population, 

and consumption on a national scale [Ref. 3]. 

The samples include both domestic and 

imported fresh produce that are either 

conventionally or organically grown. The 

sampling rationale was developed by MPO in 

consultation with NASS, FDA, and CDC. 

Collecting data over time from a range of 

sources permits statistical statements to be 

made about the distribution of targeted 

pathogens within the target population. The 

target population is all units of a commodity 

available at the wholesale level in a 

participating State during a defined timeframe 

(e.g., 1 year). The extension of statistical 

statements to the distribution of microorganisms within the inferential population 

(the entire amount of the commodity actually 

consumed by the U.S. public during the same 

timeframe) requires that strong assumptions be 

made about the relationship between the 

participating States and the United States as a 

whole, and between the wholesale and pointof-consumption levels. Nevertheless, because 

the States that participate in MDP fully 

represent the U.S. inferential population, and 

many microorganisms may enter the food 

supply at or before the wholesale level, the 

MDP data are useful and defensible.

using mPCR technology. STEC and ETEC are 

two groups of E. coli that cause the majority of 

enteric diseases and therefore are important to 

human health. Additionally, samples were 

tested for generic E. coli using an automated 

assay system during the first quarter of the 

year. Generic E. coli testing was discontinued 

in April to focus on foodborne pathogens. 

MDP laboratories are members of the Food 

Emergency Response Network (FERN), a 

Government initiative that is co-managed by 

FDA and USDA’s Food Safety and Inspection 

Service (FSIS). FERN’s mission is to integrate 

the Nation’s food testing laboratories to detect, 

identify, respond, and recover from a bioterrorism or public health emergency/outbreak 

involving the food supply. MDP laboratories 

have taken a very active role in FERN 

activities, including participation in validation 

of realtime polymerase chain reaction (rt-PCR)

based detection methods for E. coli O157:H7 

and Salmonella, and in proficiency testing 

rounds. MDP laboratories have also responded 

to outbreak emergencies by sampling specific 

commodities and testing for the pathogens 

implicated in outbreaks.

USDA is a member of the interagency Task 

Force on Antimicrobial Resistance established 

in 1999 to address antimicrobial resistance, 

which has been identified as a priority food 

safety and public health issue. As such, isolates 

from positive MDP samples were sent to ODA 

for antimicrobial resistance testing. These data 

were added to the CDC National Antimicrobial 

Resistance Monitoring System (NARMS) database. Additionally, ODH performs genomic 

fingerprinting on MDP isolates by Pulsed Field 

Gel Electrophoresis (PFGE) for inclusion in 

the CDC PulseNet database. With the assistance of CDC, MDP isolates were matched to 

pathogens from past outbreaks and/or 

identified as unique to the database. 

As the program evolves, procedures and 

methods are being refined to provide information necessary for making science-based food 
Microbiological Data Program - Annual Summary, Calendar Year 2009

5

Cantaloupe, cilantro, green onions, hot peppers, 

lettuce (pre-bagged organic and Romaine), 

spinach, sprouts (alfalfa or clover), and 

tomatoes (round and Roma) were collected by 

the Program in 2009. Based on consultations 

with FDA, cilantro was reintroduced during 

2009, replacing green onions. These commodities were selected because they are often 

consumed raw and have been implicated in 

outbreaks. Peanut butter samples were also 

collected in 2009 to assure consumers that this 

product was not implicated on the peanut pasterelated Salmonella outbreak.

The peanut butter special survey lasted 8 

months (February to September), and during 

this timeframe, cantaloupe was replaced with 

peanut butter. MDP collected 1,542 peanut 

butter samples and tested them for presence of 

Salmonella. None of the samples tested 

positive for Salmonella; therefore, MDP 

resumed its normal sample collection schedule 

in October.

All samples in a State are collected on the same 

day or within a 2-day interval. Sample size is 

specific to each commodity and is based on the 

analytical method requirements. A description 

of sample sizes is given in Table 1. More 

detailed information on sample size is posted on 

the MDP website at www.ams.usda.gov/mdp. 

Inferences cannot reasonably be made from the 

sample units to the lots from which they 

originate because the units do not provide 

enough information to generate statistically 

reliable lot estimates. However, statistical 

methods can be applied to make whole-targetpopulation inferences from the data and to 

compare these inferences over time.

MDP benefited from the well established sampling framework of the Pesticide Data Program 

(PDP), a program administered by MPO since 

1991. States that were already providing 

sampling services for PDP also began 

collecting samples for MDP in 2001 and 

continue, to date, through annual cooperative 

agreements with AMS. All sample collectors 

receive training and are provided with 

factsheets on the commodities they collect. The 

information in each factsheet includes acceptable and unacceptable products, availability, 

sample size, and instructions for data entry, 

packaging, and shipping. 

The sampling of commodities is conducted at 

distribution centers and terminal (wholesale) 

markets from which food commodities are 

released to supermarkets and grocery stores, 

and include domestic and imported commodities. Samples are collected on a year-round 

basis. Sampling is apportioned according to 

Table 1. Sample Sizes. This tables shows sample quantities by commodity.

Commodity Code Sample Size

Number of Samples 

Collected per Lot

Alfalfa sprouts SR 3 oz./85 g 3

Cantaloupe CN 1 cantaloupe 3

Cilantro CL 8 oz./225 g 3

Green Onions GO 8 oz./225 g 3

Hot Peppers HP 8 oz./225 g 3

Lettuce, Organic LT 16 oz./450 g 3

Lettuce, Romaine LT 16 oz./450 g 3

Peanut Butter PB 14 oz./397 g 3

Spinach SP 16 oz./450 g 3

Tomatoes, Round TO 3 tomatoes 3

Tomatoes, Roma TR 5 tomatoes 3
Microbiological Data Program - Annual Summary, Calendar Year 2009

latex gloves and place samples in sterile sample 

bags). Once bagged, samples must be properly 

identified and tamper-proofed to ensure that 

chain-of-custody requirements are met. Sufficient frozen ice packs and packing materials for 

cushioning and insulation are required to 

maintain refrigerated temperatures during 

transport. The condition of each sample is 

checked and recorded upon receipt at each 

laboratory. If the integrity of a sample is in 

question, the laboratory will request that the 

particular commodity be sampled again. All 

samples are shipped on the same day as sample 

collection by overnight delivery so that laboratory analysis can begin the following day.

Unlike PDP operations, where specific commodities are sent to laboratories specializing in 

the analysis of a particular commodity, MDP 

laboratory analyses are performed in the same 

State from which the sample was collected. 

Exceptions to this are California, Maryland, and 

Texas. California samples were shipped to 

Colorado, Florida, Michigan, Ohio, Washington, and AMS NSL for analysis; Maryland 

samples were shipped to Ohio; and Texas 

samples were shipped to AMS NSL in 

Gastonia, North Carolina.

For bagged lettuce, all lettuce varieties were 

acceptable and included conventionally grown 

and organic samples. Bagged lettuce samples 

consisted of a single lettuce variety or mixtures 

of more than one variety. Bags containing 

lettuce mixed with spinach were not acceptable. 

These commodities are harvested primarily by 

hand, although some mechanical harvesting 

does occur. Alfalfa and clover sprouts are most 

often grown in drums and packaged in 

controlled environments. Other produce may be 

packaged in the field or taken to a packinghouse 

(e.g., tomatoes require classification for color 

and/or size). At the packing-house, the produce 

is cleaned, trimmed, sized, sorted, chopped into 

small pieces for ready-to-eat purposes, bagged, 

wrapped, and chilled for preservation until 

arrival at distribution centers and terminal 

markets. Cleaning is typically accomplished 

population of the participating State, therefore, 

the higher the population of the State, the 

greater the number of samples taken. The 

monthly population-based collection numbers 

are as follows: California, 14 (JanuarySeptember) and 13 (October-December); Colorado, 2; Florida, 7; Maryland, 4; Michigan, 6; 

Minnesota, 2; New York, 9; Ohio, 6; Texas, 8 

(January-September) and 9 (October-December); Washington, 4; and Wisconsin, 2. This 

schedule results in a monthly target of 64 sites 

sampled per commodity. At each site, 3 

samples are collected from the same lot in each 

facility for a total of 192 samples collected 

every month for each commodity.

Distribution centers and terminal markets in 

each State are selected at random based on 

probability proportional to the site’s distribution volume (i.e., the amount of produce that 

moves through the site). Therefore, the larger 

the site, the greater the chance it will be 

sampled. If the commodity of interest is not 

available at the designated primary site, an 

alternate site may be chosen. MDP does not 

allow samples to be taken from public markets 

or retail stores because of the potential for 

contamination by the consumer and because 

commodity handling practices at this level in 

the distribution chain may vary widely. During 

2009, 16,896 samples were collected from over 

390 sites across the country and analyzed by 

MDP laboratories. Table 2 shows the distribution of Sample Origin by State or Country. 

Approximately 74 percent of all MDP samples 

were grown in the United States, 25 percent 

were imports, and 1 percent was of mixed 

national origin and unknown origin. The 

largest number of samples came from 

California (30%) and Mexico (20%). Figure 3 

illustrates the proportion of samples that were 

domestic, imported, and of unknown origin for 

each commodity. Table 3 shows the number of 

samples collected by commodity by collection 

State. 

All samples are collected using aseptic 

techniques (i.e., sample collectors wear sterile 

6
Microbiological Data Program - Annual Summary, Calendar Year 2009

7

Commodity Codes # of % of

States CL CN GO HP LT-C LT-O PB SP SR TO TR Samples Total

Alabama 2 3 9 14 0.1

Arizona 42 3 3 6 27 6 87 0.5

Arkansas 39 15 6 60 0.4

California 165 294 120 201 896 799 74 1634 420 329 147 5,079 30.1

Colorado 3 6 6 6 27 57 6 111 0.7

Connecticut 3 3 57 3 66 0.4

Delaware 3 3 <0.1

Florida 105 36 240 42 6 27 27 261 584 246 1,574 9.3

Georgia 45 6 6 57 0.3

Idaho 16 36 52 0.3

Illinois 12 15 94 6 27 6 160 0.9

Indiana 3 6 9 0.1

Iowa 1 1 <0.1

Kansas 6 6 <0.1

Kentucky 3 3 1 18 18 3 46 0.3

Maine 12 9 21 0.1

Maryland 6 12 33 45 6 13 57 216 42 33 463 2.7

Massachusetts 3 21 5 90 48 167 1.0

Michigan 3 18 33 57 72 198 30 60 471 2.8

Minnesota 6 3 15 12 21 61 4 27 9 158 0.9

Mississippi 6 6 <0.1

Missouri 13 3 12 28 0.2

Nebraska 134 9 143 0.8

New Hampshire 2 2 <0.1

New Jersey 30 15 30 285 15 9 15 399 2.4

New York 3 39 3 6 58 18 189 18 9 343 2.0

North Carolina 144 3 3 9 9 9 27 204 1.2

Ohio 48 6 39 54 12 30 418 15 84 36 27 769 4.6

Oregon 3 6 21 8 3 41 0.2

Pennsylvania 3 12 18 9 48 30 57 18 195 1.2

South Carolina 3 12 3 21 6 45 0.3

Tennessee 2 16 12 30 0.2

Texas 18 57 15 78 45 27 19 63 258 84 45 709 4.2

Vermont 7 7 <0.1

Virginia 3 6 1 24 105 39 21 199 1.2

Washington 12 15 15 3 3 27 45 3 123 0.7

Wisconsin 3 3 8 15 105 3 137 0.8

Unknown State 12 33 12 126 21 12 2 44 51 75 60 448 2.7

No. of Domestic 402 489 258 1,098 1,127 970 1,447 2,212 2,271 1,409 750 12,433

% of Total 49.3 84.2 22.1 62.9 95.8 83.7 93.8 95.0 99.7 60.0 42.7 73.6

Part 1. Domestic Samples
Microbiological Data Program - Annual Summary, Calendar Year 2009

8

Table 2. Sample Origin by State or Country. This table shows the number of samples per State or 

Country of origin as determined by the reported grower, packer, or distributor information.

Part 2. Imported Samples

Commodity Codes # of % of

Country CL CN GO HP LT-C LT-O PB SP SR TO TR Samples Total

Argentina 3 3 <0.1

Canada 6 30 15 92 21 162 27 353 2.1

Chile 6 6 <0.1

Dominican Republic 3 3 <0.1

Ecuador 6 6 <0.1

Guatemala 327 18 345 2.0

Honduras 51 51 0.3

Mexico 24 74 845 575 21 108 66 728 954 3,395 20.1

No. of Imports 402 80 899 584 36 108 95 87 0 890 981 4,162

% of Total 49.3 13.8 77.1 33.5 3.1 9.3 6.2 3.7 0 37.9 55.9 24.6

Part 3. Mixed National Origin Samples

Commodity Codes # of % of

Countries CL CN GO HP LT-C LT-O PB SP SR TO TR Samples Total

Canada / USA 3 3 <0.1

Mexico / USA 6 78 26 3 6 119 0.7

No. of Mixed Origin 9 78 26 3 6 122

% of Total 0.8 6.7 1.1 0.1 0.3 0.7

Part 4. Unknown Origin Samples

Commodity Codes # of % of

CL CN GO HP LT-C LT-O PB SP SR TO TR Samples Total

Unknown Origin 12 12 9 63 5 3 3 6 48 18 179

% of Total 1.5 2.1 0.8 3.6 0.4 0.3 0.1 0.3 2.0 1.0 1.1

Sample Totals: 816 581 1,166 1,745 1,177 1,159 1,542 2,328 2,277 2,350 1,755 16,896

Commodity Legend

CL = Cilantro PB = Peanut Butter

CN = Cantaloupe SP = Spinach

GO = Green Onions SR = Sprouts (Alfalfa)

HP = Hot Peppers TO = Tomatoes, Round

LT-C = Lettuce, Conventional TR = Tomatoes, Roma/Plum

LT-O = Lettuce, Organic
Microbiological Data Program - Annual Summary, Calendar Year 2009

with chlorinated water, although other 

disinfecting agents, such as ozone, may be used. 

Some commodities may have a food-grade wax 

applied to replace natural waxes removed during 

washing to help prevent water loss. Fungicides 

may be added to the wax or applied separately to 

retard spoilage. Chilling may be accomplished 

by various means such as vacuum cooling, 

hydrovac cooling, room-chilling, or forced air 

cooling. After initial chilling, the produce is 

stored under chilled conditions (avoiding freezing) and, depending on the commodity, under 

low-oxygen atmospheric conditions (primarily 

carbon dioxide). Except for leafy greens and 

sprouts, the produce is often harvested before 

reaching full ripeness to minimize spoilage and 

bruising. Prior to shipment to distribution centers 

and terminal markets, some commodities are 

often artificially ripened using techniques such 

as ethylene oxide gassing. Some shipping 

companies transport produce in refrigerated 

trucks or rail cars; others use ice; still others use 

no method of cooling, depending on the 

commodity. Therefore, MDP data reflect not 

only agricultural practices but also handling 

practices occurring during harvesting, storage 

(including postharvest treatment), bagging, and 

shipping operations. 

MDP uses electronic Sample Information 

Forms (e-SIFs) to capture information needed 

to characterize the sample. Sample collectors 

use laptop or handheld computers in the field to 

record sample identification information such 

as: (1) State of sample collection, (2) collection 

date, (3) sampling site code, (4) commodity 

code, and (5) testing laboratory code. Other 

available information about the sample is also 

recorded, such as the country of origin, any 

production claims (such as organic), and any 

postharvest treatments. The e-SIFs are electronically mailed the same day as sample 

collection or, at the latest, by the following 

morning after collection to ensure that sample 

information is received at each laboratory by 

the time the samples arrive for analysis.

Table 3. Samples Collected by State. This table shows the number of samples collected by each State 

by commodity. 

State Total

California 159 117 243 360 168 318 327 486 486 502 360 3,526

Colorado 24 18 36 54 33 39 48 72 69 72 54 519

Florida 93 69 143 216 177 108 186 281 279 279 216 2,047

Maryland 60 36 72 108 51 90 84 144 141 143 108 1,037

Michigan 72 54 108 162 120 96 144 216 207 216 162 1,557

Minnesota 27 18 36 54 24 48 48 72 72 72 54 525

New York 108 81 162 243 144 180 216 324 324 324 243 2,349

Ohio 72 54 108 162 168 48 144 216 213 216 162 1,563

Texas 129 80 153 227 157 151 201 301 285 310 234 2,228

Washington 48 36 69 105 87 57 96 144 132 144 108 1026

Wisconsin 24 18 36 54 48 24 48 72 69 72 54 519

Totals 816 581 1,166 1,745 1,177 1,159 1,542 2,328 2,277 2,350 1,755 16,896

Cantaloupe

Cilantro

Green OnionsHot Peppers

Lettuce (Conventional)

Lettuce (Organic)Peanut Butter

SpinachSprouts (Alfalfa)

Tomatoes (Round)

Tomatoes (Roma)

9
Microbiological Data Program - Annual Summary, Calendar Year 2009

Hot Peppers (1,745 Samples)

Green Onions (1,166 Samples)

Figure 3. Commodity Origin. The proportion of domestic, imported or unknown origin for 

each commodity is depicted for samples tested in 2009.

Domestic 49.3%

Unknown 1.4%

Imported 49.3%

Cantaloupe (816 Samples)

Domestic 83.6%

Unknown 2.1%

Imported 13.8%

Cilantro (581 Samples)

Domestic 22.1%

Unknown 0.8%

Imported 77.1%

Domestic 62.9%

Unknown 3.6%

Domestic 95.8%

Unknown 0.4%

Imported 3.8%

Lettuce (1,177 Samples)

(Conventional)

Imported 33.5%

Domestic 83.7%

Imported 16.0%

Peanut Butter (1,542 Samples)

Domestic 93.8% Domestic 95.0%

Unknown 0.1%

Spinach (2,328 Samples)

Imported 6.2%

Sprouts, Alfalfa (2,277 Samples)

Domestic 99.7%

Imported 0.3%

Lettuce (1,159 Samples)

(Organic)

Unknown 0.3%

Imported 4.9%

Tomatoes, Round (2,350 Samples)

Domestic 60.0%

Domestic 42.7%

Unknown 1.0%

Tomatoes, Roma (1,755 Samples)

Imported 38.0% Imported 56.3%

Unknown 2.0%

10
Microbiological Data Program - Annual Summary, Calendar Year 2009

MDP sampling operations are conducted following Standard Operating Procedures (SOPs) 

designed to provide consistency across the 

program and ensure the integrity of the analytical 

data. SOPs also contain specific instructions for 

sample selection, shipping and handling, and 

chain-of-custody. SOPs are updated as needed 

and serve as a technical reference for conducting 

program sampling reviews to ensure that 

program goals and objectives are met. All 

program SOPs are available on the Internet at 

www.ams.usda.gov/mdp.

III. Laboratory Operations

Participating microbiology laboratories tested 

MDP samples for generic E. coli and screened 

MDP samples for Salmonella and E. coli strains 

carrying shiga toxins and enterotoxins (STECs 

and ETECs, respectively), including E. coli

O157:H7. Laboratories used mPCR technology 

to screen all samples for pathogenic E. coli

(STEC and ETEC), based on the presence of 

gene sequences that code for shiga toxins and 

enterotoxins. From January through March 

2009, MDP laboratories also performed generic 

E. coli testing for all commodities.

For all pathogenic E. coli isolates, the 

Gastroenteric Disease Center at PSU performed 

serotyping using specific antisera and tested for 

additional virulence-related genes using 

polymerase chain reaction (PCR). The ODA 

laboratory performed antimicrobial susceptibility 

testing for all pathogenic isolates. The ODH 

laboratory performed serotyping on Salmonella

isolates and genomic fingerprinting using PFGE 

on all pathogenic isolates from Colorado, 

Florida, Michigan, Ohio, Washington, and the 

AMS NSL. MDP laboratories in New York, 

Minnesota, and Wisconsin performed PFGE on 

all pathogenic isolates obtained by their 

laboratories. 

Upon arrival at the testing facility, samples were 

logged, visually examined for acceptability, and 

discarded if determined to be damaged (decayed, 

extensively bruised, or spoiled). Samples were 

refrigerated until analysis commenced. 

Laboratories were permitted to refrigerate 

commodities for up to 48 hours to allow for 

different sample arrival times from the various 

collection sites. 

Prior to the analytical tests, all samples were 

washed in Universal Pre-enrichment Broth 

(UPB) in order to streamline the screening 

process for all target bacteria. Peanut butter 

and alfalfa sprouts were blended. To improve 

pathogen detection, washing was followed by 

a soaking step for all commodities except 

green onions and sprouts. For green onions 

and sprouts, the plant materials were removed 

prior to incubation. Genomic DNA was 

extracted from each enriched sample using an 

automated system. Next, the extracted DNA 

was cleaned for use in detecting pathogens by 

PCR. The BAX®automated PCR system was 

used for screening samples for the presence of

Salmonella and enterohemorrhagic E. coli

O157:H7. Similarly, an appropriate aliquot of 

extracted DNA for each sample was used in 

screening for the presence of non-O157 

pathogenic E. coli strains by mPCR. Table 4 

shows the number of samples tested for each 

organism by commodity.

MDP laboratories tested 2,531 samples for the 

presence of generic E. coli using an automated 

assay system. This assay uses the presence of 

a unique enzyme in E. coli for detection. It 

enumerates the number of E. coli cells per 

gram of sample using Most Probable Number 

(MPN) based statistical analysis. Generic E. 

coli testing was discontinued in April to focus 

on foodborne pathogens.

In order to improve pathogen detection, 

cantaloupe, cilantro, hot peppers, lettuce, 

peanut butter, spinach, and tomato samples 

were soaked overnight. For green onions and 

sprouts, any debris/plant material was 

removed from the wash prior to overnight 

incubation.

11
Microbiological Data Program - Annual Summary, Calendar Year 2009

12

The main objectives of the Quality Assurance/

Quality Control (QA/QC) program were to 

ensure the reliability of MDP data and to ensure 

performance equivalency of participating 

laboratories. Direction for the MDP QA program was provided through written SOPs based 

on FDA’s 8th edition Bacterial Analytical 

Methods (BAM) [Ref. 4], AOAC® methods, the 

USDA FSIS Microbiological Laboratory Guide, 

and the U.S. Environmental Protection 

Agency’s Good Laboratory Practices. SOPs 

provide uniform administrative, sampling, and 

laboratory procedures. MDP analytical methods 

are published at www.ams.usda.gov/mdp. 

Several MDP laboratories have been accredited 

or are in the process of International 

Organization for Standardization (ISO) accreditation. MDP laboratories participate in an 

annual proficiency testing round, administered 

by MPO, for selected target organisms in 

produce samples. Several MDP laboratories 

also participated in microbiological proficiency 

testing for foods, including produce, 

administered by FERN.

MDP laboratories utilized automated systems for 

the extraction and purification of genomic DNA

from enriched bacterial cultures in order to 

streamline the labor intensive preparation of 

DNA samples for PCR assays. MDP laboratories 

used automated PCR systems for the detection of 

Salmonella and enterohemorrhagic E. coli

O157:H7 in samples, with the exception of 

peanut butter samples, which were analyzed only 

for Salmonella using the VIDAS system.

All samples (except peanut butter) were screened 

by mPCR procedures for STECs and ETECs. 

Cultural methods involving selective growth 

media to permit the enrichment of pathogens 

were used in isolation procedures. When 

necessary, pathogenic cells were concentrated 

from mixed cultures using an Immunomagnetic 

Separation (IMS) technique, which isolates 

target bacteria using specific antigen-antibody 

reactions. In addition to cultural methods, 

identification based on automated biochemical 

tests and serotyping of surface antigens was used 

in the verification of isolates for the target 

pathogens. 

Table 4. Number of Samples Analyzed. This table shows the number of samples tested for each 

organism.

Commodity E. coli

Pathogenic 

E. coli E.coli O157:H7 Salmonella

Total Number 

of Tests

Cantaloupe 231 816 231 816 2,094

Cilantro 581 581 581 1,743

Green Onions 1,166 1,166 1,166 3,498

Hot Peppers 1,745 1,745 3,490

Lettuce, Conventional 261 1,177 1,177 1,177 3,792

Lettuce, Organic 315 1,159 1,159 1,159 3,792

Peanut Butter 1,542 1,542

Spinach 575 2,328 2,328 2,328 7,559

Sprouts (Alfalfa) 573 2,277 2,277 2,277 7,404

Tomatoes, Round 576 2,350 576 2,350 5,852

Tomatoes, Roma 1,755 1,755 3,510

Total 2,531 15,354 9,495 16,896 44,276
Microbiological Data Program - Annual Summary, Calendar Year 2009

Positive and negative controls and a sterile 

media blank were required for each sample set. 

MDP laboratories use positive control strains of 

E. coli O157:H7 and S. typhimurium that carry a 

gene coding for Green Fluorescent Protein 

(GFP). Expression of the GFP, detected by 

exposing the cultures to ultraviolet light, 

indicates the presence of the control cultures 

without the need for performing lengthy 

biochemical tests. All controls and blanks were 

processed in conjunction with sample cultures 

from the pre-enrichment step to isolation and 

identification of target isolates using cultural, 

immunological, biochemical, and serological 

methods. 

A technical advisory group, comprised of 

microbiologists from each MDP-participating 

laboratory, provided technical feedback on 

program SOP revisions and addressed technical 

and QA issues. Additionally, MDP consulted 

with scientists from other Federal agencies 

(FDA, CDC, USDA Agricultural Research 

Service, and FSIS) and academia on technical 

issues. For day-to-day QA oversight, each 

participating facility was required to have a 

Quality Assurance Unit (QAU) that operated 

independently from the laboratory staff. 

Preliminary QA/QC review procedures were 

performed onsite by each laboratory’s QAU. 

Final review procedures were performed by 

MDP staff responsible for collating and 

reviewing data for conformance with SOPs. 

Laboratory performance was monitored through 

onsite reviews by MDP staff to determine 

compliance with MDP SOPs. Corrective 

actions, if necessary, were performed as a result 

of onsite reviews. 

IV. Database Management

 

MDP maintains an electronic database that 

serves as a central data repository. The central 

database resides at MPO in Manassas, Virginia. 

The data captured and stored in the MDP 

database include product information and 

analytical findings for each sample collected 

13

along with QA/QC results for each set of 

samples. The MDP data pathway is depicted in 

Figure 4.

MDP uses a Web-based Remote Data Entry 

(RDE) system to capture and report MDP data. 

The RDE system is centralized, with all user 

interface software and database files residing 

in Washington, DC. The laboratory users need 

only a Web browser to interface with the RDE 

system. Access to the RDE system is controlled through separate user login/password 

accounts and user access rights for the various 

system functions based on position requirements. The RDE system utilizes Secure 

Sockets Layer (SSL) technology to encrypt all 

data passed between users’ computers and the 

central Web server. 

A separate Windows®-based system allows 

sample collectors to electronically capture the 

standardized Sample Information Form (SIF) 

on handheld or laptop computers. The e-SIF 

system generates formatted text files 

containing sample information that are emailed to MDP headquarters and then 

imported into the Web-based RDE system.

The RDE data entry screens have extensive 

edits and cross-checks built in to ensure that 

acceptable values are entered for all critical 

data elements. This task is made easier by the 

practice of capturing and storing standardized 

codes for all critical alphanumeric data 

elements rather than their complete names, 

meanings, or descriptions. This coding scheme 

allows for faster and more accurate data entry, 

saves disk storage space, and makes it easy to 

perform queries on the database. The data 

entry screens also perform edits on numeric 

fields, dates, and other character fields to 

ensure that entries are within prescribed 

boundaries. 

At MDP headquarters, the RDE system allows 

scientists to review and approve the data for 

inclusion in the central database. The central 

MDP database is maintained using Microsoft® 
Microbiological Data Program - Annual Summary, Calendar Year 2009

14

Figure 4. MDP Data Pathway. An illustration of MDP data path from sample collection, through 

laboratory analysis and reporting.

-8 State labs + 1 Federal lab for sample testing

-State Public Health Laboratories

-FDA/CVM Laboratory

-Pennsylvania State University E. coli Reference 

Laboratory

-Standardized sample preparation

-Test for specific foodborne pathogens

-Confirmation and serology of isolated pathogen

-Genomic fingerprints

-Antimicrobial susceptibility

Laboratory Analysis

Sample Collection

- Collection in 11 States

- Samples taken close to consumer

- Standardized Sample Information Form

- Data entry on handheld/laptop computers

- Web-based data entry software

- Import data from other systems

- Access controlled by user login

- Extensive data cross-checks

Laboratory Remote Data Entry (RDE)

Data Review at HQ

- Scientists review data on-screen

- Upload data to central database

Year-end Review

- Data reconciliation

Internet

Internet

- Standard & ad hoc reporting

- Annual Summary

- eLEXNET

- PulseNet

- NARMS

Data Reporting
Microbiological Data Program - Annual Summary, Calendar Year 2009

15

Access and SQL Server database tools. Access 

to the central MDP database is limited to MDP 

headquarters personnel and is controlled through 

password protection and user access rights.

V. Summary of 2009 Data

MDP collected a total of 16,896 samples. In 

addition, MDP tested 1,542 peanut butter 

samples as a special survey conducted from 

February through September 2009. This survey 

was initiated at CDC’s request to assure 

consumers that peanut butter for retail sale was 

not implicated in a Salmonella outbreak traced 

to other peanut products. Peanut butter samples 

were tested only for Salmonella.

The 2009 MDP testing program was streamlined 

to target priority organism-commodity combinations. Consequently, all commodities were 

screened for Salmonella; all commodities, 

except peanut butter, were screened for nonO157 STEC and ETEC; and only eight 

commodities were screened for E. coli O157:H7. 

Peanut butter, hot peppers, and tomatoes (both 

round and Roma) were not tested for E. coli

O157:H7. 

Enumeration of E. coli: Testing of generic E. 

coli was performed on a total of 2,531 fresh 

produce commodities using an automated 

detection and enumeration system on samples 

collected from January through March. Table 5 

shows that MPN values of 1,000 E. coli cells/

gram of sample were found in 6 samples and 5 

of those samples were alfalfa sprouts. 

Pathogenic E. coli: A total of 15,354 samples 

were screened for STECs and ETECs using an 

mPCR assay developed by FDA. Table 6 shows 

that 51 samples were identified as positive 

pathogenic E. coli by mPCR. The laboratories 

were successful in isolating 24 pathogenic E. 

coli (13 STECs and 11 ETECs). This represents 

a 47-percent rate of successful isolation, higher 

than the 30 percent reported in 2008. In addition 

to the technological differences between detection by PCR and isolation by cultural means, 

several other factors influence the rate of 

successful isolation. The overwhelming 

amount of background microflora when 

compared to the small number of target 

bacterial cells and the diverse physiology of 

bacteria present in produce wash cultures pose 

a challenge in identification and isolation by 

selective enrichment of targets. 

The 24 isolates were sent to other laboratories 

for further characterization. PSU conducted 

tests that included 13 virulence-specific genes 

associated with different classes of pathogenic 

E. coli and serotyping for somatic O antigens 

and flagellar H antigens. ODA conducted tests 

on antimicrobial resistance for 15 different 

antibiotics for all isolates. ODH and selected 

State laboratories performed genomic fingerprinting by PFGE for isolates. The PFGE gel 

images were loaded onto the PulseNet database 

by the laboratories. All PFGE information on 

MDP isolates was sent to CDC and FDA. 

Table 7 shows results of additional testing on 

isolates of non-O157 pathogenic E. coli. NonO157 pathogenic E. coli was isolated from 23 

samples, 16 of which were spinach. A single 

spinach sample was found to contain one 

isolate each of STEC and ETEC. All but one 

of the STEC isolates contained the shiga toxin 

2 (Stx-2) gene. The other STEC isolate is 

under further investigation. Seven out of 13 

STEC isolates contained an additional 

virulence factor for the gene coding for 

MPN Range Number of Samples

< 10 2,442

10 - 99 73

100 - 999 10

1,000 - 10,000 4

> 10,000 2

Total Number of 

Samples Tested 2,531

Table 5. Number of Samples Tested for E. coli. 

This table shows the results of E. coli enumeration 

by Most Probable Number (MPN).
Microbiological Data Program - Annual Summary, Calendar Year 2009

16

enterohemolysin (hlyA), which causes lysis of 

erythrocytes. None of the isolates contained 

the eae gene coding intimin, a virulencerelated gene required for attachment to 

epithelial cells. All of the ETEC isolates 

contained either the heat-labile or heat-stable 

toxins or both. Results from antimicrobial 

resistance testing revealed that an ETEC 

isolate from a spinach sample was resistant to 

the antibiotic kanamycin and a STEC isolate 

also from spinach was resistant to tetracycline. 

Based on PulseNet information provided by 

CDC, three STEC isolates from spinach 

matched isolates from humans and one STEC 

isolate from spinach was shown to be a new 

strain with O172 and H2 antigens. To 

characterize a non-O157 pathogenic E. coli

isolate as a human pathogen capable of 

causing disease, there must be interactions 

among several proteins including toxins, 

encoded by respective genes. MDP only 

identified toxin genes; the additional testing 

required for determining the disease-causing 

potential of these isolates is beyond the scope 

of MDP. 

Salmonella: As depicted in Table 8, a total of 

16,896 samples were screened for Salmonella

by BAX® PCR. Of these samples, 90 were 

reported as presumptive positives via the 

preliminary screening method and 32 were 

successfully isolated and confirmed: 8 from 

cilantro, 2 from cantaloupes, 4 from green 

onions, 4 from hot peppers, 1 from lettuce, 6 

from spinach, 6 from alfalfa sprouts and 1 from 

tomato (Roma). These isolates were sent to 

ODH or to State health department laboratories 

for serotyping and genomic fingerprinting by 

PFGE and to ODA for antimicrobial resistance. 

Results were uploaded onto the CDC PulseNet 

database. 

Table 9 provides the compiled information on 

characteristics of MDP Salmonella isolates. 

About one-third of the isolates (10) belonged to 

serogroup C. Six of the S. arizonae or 

diarizonae demonstrated variable serogroups. 

S. litchfield isolates from Florida cilantro 

samples were identified as having a unique 

PFGE pattern not previously reported in 1,285 

Litchfield PFGE patterns already in the 

PulseNet database.

Commodity

Number of 

Samples 

Screened by 

mPCR

Number of 

Pathogenic E. coliPositive Samples

Number of 

Positive Isolates 

Obtained

Cantaloupe 816 1 0

Cilantro 581 9 4

Green Onions 1,166 3 0

Hot Peppers 1,745 1 1

Lettuce, Conventional 1,177 2 1

Lettuce, Organic 1,159 3 2

Spinach 2,328 29 16

Sprouts (Alfalfa) 2,277 2 0

Tomatoes, Round 2,350 1 0

Tomatoes, Roma 1,755 0 0

Total 15,354 51 24

Table 6. Summary of Sample Analysis for Pathogenic E. coli. This table summarizes the 

number of samples initially screened for E. coli and further tested for pathogenic E. coli and 

the number of samples that tested positive for pathogenic E. coli.
Microbiological Data Program - Annual Summary, Calendar Year 2009

17

Table 7. Characterization of 2009 non-O157 Pathogenic E. coli Isolates. This table provides data 

obtained from additional testing of pathogenic E. coli isolates initially screened by MDP laboratories.

STa and STb - heat-stable toxins A and B, respectively

HlyA = hemolysin A

LT = heat-labile toxin

Stx-1 and Stx-2 - shiga toxins 1 and 2, respectively

Under heading of E. coli Class, numbers with ( ) denote multiple isolates.

Collection 

State Commodity

E. coli 

Class Toxin Genes

O 

Antigen

H 

Antigen

Antimicrobial 

Resistance

Comments Based on 

PulseNet/CDC

Maryland Spinach STEC Stx-2, Hy1A X25 -

New York Spinach ETEC STa 61w 34

Florida Spinach ETEC STa 153 21

Wisconsin Spinach STEC Stx-2 - 2

New Strain; O172:H2 in E. coli 

Reference Center and 

PulseNet per CDC.

Colorado Spinach ETEC STa, STb - 10 Kanamycin

California Lettuce ETEC (2) LT, STb 83w 15 Organic Lettuce

Michigan Spinach STEC Stx-2 73 18

California Spinach STEC Stx-2, Hy1A 116 21 Tetracycline

California Spinach STEC Stx-2 116 21

Florida Spinach STEC Stx-2, Hy1A 113 36 All other sources for this 

organism are human per CDC.

Texas Spinach STEC Stx-2, Hy1A 8 -

All other sources for this 

organism are human per CDC

Michigan Spinach STEC Stx-2, Hy1A - 19

Michigan Cilantro ETEC LT, STb 175 15

Florida Spinach ETEC STa - 36

Florida Spinach STEC Stx-2, Hy1A 168 8

Michigan Cilantro ETEC LT, STb 83w 15

New York Spinach STEC Stx-2 - 21

Maryland Spinach STEC Stx-2 113w 21 All other sources for this 

organism are human per CDC.

Michigan Lettuce STEC STa, Stx-2, 

Hy1A 168 - Conventionally grown lettuce.

California Cilantro ETEC (2) LT, STb 175w 15

California Hot Pepper ETEC STa - 5

Minnesota Spinach STEC Stx 11 15

TOTAL 24

Isolated from the same } sample.
Microbiological Data Program - Annual Summary, Calendar Year 2009

Three Salmonella isolates demonstrated 

resistance to antimicrobial compounds tested: 

S. kentucky isolated from a Wisconsin lettuce 

sample was resistant to streptomycin and 

tetracycline; S. oranienberg isolated from a 

California cantaloupe sample carried resistance 

to chloramphenicol; and a S. havana isolated 

from a Texas hot pepper sample was found 

resistant to trimethoprim and sulfamethoxazole. Information on Salmonella antimicrobial resistance has been provided to the 

CDC NARMS. MDP data, including the 

characteristics of pathogenic isolates, were 

provided to FDA and CDC. 

E. coli 0157:H7: No enterohemorrhagic E. 

coli O157:H7 strain was isolated from the 

9,495 samples screened, although there were 

16 presumptive PCR positives reported. These 

presumptive positives suggested that the target 

bacteria might be present in extremely low 

numbers. As with pathogenic E. coli analysis, 

several factors contribute to successful 

detection and isolation, including the level of 

naturally occurring background microflora 

present in produce compared to the small 

number of target bacterial cells, and the 

diverse physiology of the complex mixtures of 

bacteria, which can pose a challenge in 

selective enrichment of targets. 

Foodborne Outbreaks: Tables 9 and 10 

show results of testing done by MDP in 

support of FDA and CDC outbreak 

investigations. MDP initiated a special survey 

in response to an outbreak investigation 

implicating peanut paste and peanut paste 

byproducts. Although peanut butter for retail 

sale was not implicated in the outbreak, 

consumers’ fears led to a decline in 

consumption of this product. The MDP peanut 

butter special survey was implemented to 

provide data to reassure consumers that this 

product was not implicated in the outbreak. 

MDP tested 1,542 samples of peanut butter for 

Salmonella using the VIDAS method. In the 

course of screening, 14 samples were found to 

be positive by VIDAS. Although selective 

media were used in Salmonella isolation 

procedures, no Salmonella was isolated from 

18

Table 8. Summary of Analysis for Salmonella. This table shows the number of samples 

tested for Salmonella and the number of presumptive positives and isolates obtained.

Commodity

Number of 

Samples Tested 

Number of 

Presumptive 

Positive Samples

Number of 

Positive Isolates 

Obtained

Cantaloupe 816 2 2

Cilantro 581 9 8

Green Onions 1,166 4 4

Hot Peppers 1,745 7 4

Lettuce, Conventional 1,177 1 1

Lettuce, Organic 1,159 0 0

Peanut Butter 1,542 14 0

Spinach 2,328 15 6

Sprouts (Alfalfa) 2,277 23 6

Tomatoes, Round 2,350 14 0

Tomatoes, Roma 1,755 1 1

TOTALS 16,896 90 32
Microbiological Data Program - Annual Summary, Calendar Year 2009

Table 9. Characterization of 2009 Salmonella Isolates. This table provides data obtained from 

additional testing of Salmonella isolates initially screened by MDP laboratories.

Collection 

State Commodity Species

SerogroupAntigenic 

Formula

Antimicrobial 

Resistance

Comments Provided 

by FDA or CDC

Minnesota Sprouts S. diarizonae (2) Z S(IIIa) 50:z4,z23:-

California Sprouts S. oranienberg (2) C1 SI 7:m,t:- Outbreak associated per CDC

Wisconsin Spinach S. mbandaka C1 SI 6,7:z10,e,n,z15

Texas Plum 

Tomatoes S. bareilly C1 SI 6,7,14:y:1,5

Michigan Spinach S. anatum E1 SI 3,10:e,h:1,6

California Sprouts S. poona (2) G1 SI 22:z:1,6

New York Hot Peppers S. saintpaul B SI,4,5],12:e,h:1,2 Outbreak associated per CDC

Wisconsin Lettuce S. kentucky C3 SI 8,20:i:z6 Streptomycin, 

Tetracycline

Michigan Green 

Onions S. javiana (3) D1 SI 9,12:l,z28:1,5 Outbreak associated per CDC– Import Alert per FDA

Florida Hot Peppers S. arizonae Z S(IIIa) 50:z4,z23:-

New York Green 

Onions S. javiana D1 SI 9,12:l,z28:1,5

Michigan Spinach S. paratyphi B B SI 4,5,12:b:1,2

California Cantaloupe S. oranienburg C1 SI 7:m,t:- Chloramphenicol

Texas Cantaloupe S. newport C2 SI 6,8,20:e,h:1,2

Texas Hot Peppers S. havana G SI 13,23:f,g:-

Florida Cilantro S. saintpaul (3) B SI 1,4,[5],12:e,h:1,2

California Spinach S. arizonae (2) L S(IIIa) 21:g,z51:-

California Spinach S. arizonae Y S(IIIa) 48:z29:-

Maryland Cilantro S. assen L SI 21:a:5

Florida Cilantro S. lomalinda D1 SI 1,9,12:a:e,n,x

Texas Hot Peppers S.havana G SI 1,13,23:f,g:-

Trimethoprim, 

Sulfamethoxazole

Texas Cilantro S. montevideo C1 SI 6,7,14:g,m,s:-

Florida Cilantro S. litchfield (2) C2 SI 6,8:l,v:1,2

Unique out of 1,285 litchfields 

already in PulseNet database 

per CDC

TOTALS 32

19
Microbiological Data Program - Annual Summary, Calendar Year 2009

any sample. However, four of the samples 

yielded Enterobacter sakazakii, which is 

considered a pathogen, especially for children. 

It is of interest to note that due to antigenic 

cross-reactivity, other organisms may yield 

positive results on the VIDAS screening 

method. Testing of this large number of peanut 

butter samples expanded CDC and FDA’s 

investigation capabilities during the outbreak.

S. javiana was isolated by the Michigan 

laboratory in green onions and was also found 

by FDA in a follow up sample collected after 

MDP notification. In August of 2009, FDA 

detected S. javiana in green onions on the 

Southwestern Import District border. In 

addition, a second positive sample finding was 

detected by FDA's Detroit District office. These 

positive sample findings were further 

strengthened by a Salmonella positive sample 

finding reported by MDP. The overwhelming 

strength of these three sample findings from the 

same lot of product spurred FDA into action by 

placing the firm on import alert to cease entry 

of the violative product until corrective action 

was taken by the firm. MDP's positive sample 

finding supported FDA's ability to take 

regulatory action quickly to ensure protection 

of the public's health. Further investigation by 

CDC linked this S. javiana isolate to a 

previous outbreak. The PFGE pattern for S. 

javiana isolate reveals that it matches nine 

human cases of Salmonellosis linked to green 

onions imported from Mexico in an outbreak 

investigation that included seven States (Figure 

5A). 

S. saintpaul was isolated from a New York hot 

pepper sample. This information was shared 

with CDC during the Salmonella-hot pepper 

outbreak, and CDC matched this isolate with a 

multi-State outbreak of 30 cases of human 

Salmonellosis (Figure 5B). 

S. oranienberg was isolated from a California 

alfalfa sprout sample and was matched by 

CDC to another multi-State outbreak of 

Salmonellosis involving 26 cases of illness. In 

addition, the PFGE pattern of the MDP isolate 

is shown to be identical to Salmonella isolated 

from spent irrigation water samples collected 

in Arizona (Figure 5C).

Commodity Species

Serogroup Antigenic Formulae PulseNet NumberPulseNet Match-Up 

Comment

Anitmicrobial 

Resistance to 15 

Antibiotics Tested

Peanut Butter None

Green Onions S. javiana D1 SI 9,12:1,z28:1,5 MDP-09-00018 Associated with 

outbreak 0908MIJGG-1

None

Hot Peppers S. saintpaul B SI 1,4,[5],12:e,h:1,2 MDP-09-00013 Associated with 

outbreak 0905MIJN6-1

None

Sprouts (Alfalfa) S. oranienberg C1 SI17:m,t:-

MDP-09-00003

MDP-09-00004

Associated with 

outbreak 0904MLIJX-1

None

Table 10. Salmonella Species Isolated from Commodities Implicated in Outbreaks. This table illustrates 

additional test results that provide further characterization of MDP isolates.

20
Microbiological Data Program - Annual Summary, Calendar Year 2009

References:

1. Produce Safety from Production to Consumption: 2004 Action Plan to Minimize Foodborne Illness 

Associated with Fresh Produce Consumption (October 2004). U.S. Food and Drug Administration, 

Center for Food Safety and Applied Nutrition, Office of Plant and Dairy Foods, 

http://www.fda.gov/Food/FoodSafety/Product-SpecificInformation/FruitsVegetablesJuices/

FDAProduceSafetyActivities/ProduceSafetyActionPlan/ucm129487.htm 

2. E. coli O157:H7 Outbreaks (September 2006, December 2006). U.S. Food and Drug 

Administration, Center for Food Safety and Applied Nutrition, Office of Plant and Dairy Foods, 

http://www.cfsan.fda.gov/list.html

3. USDA, Agricultural Marketing Service, Science and Technology Programs, AMS Microbiological 

Data Program Sampling Rationale and Principles, February 2002 (rev. 2), 

http://www.ams.usda.gov/science/MPO/SamplingOverview.pdf

4. Bacteriological Analytical Manual (BAM) (2001). U.S. Food and Drug Administration, 

http://www.cfsan.fda.gov/~ebam/bam-toc.html 

Disclaimer:

The use of trade, firm, or corporation names, references to published work, and analytical methodology 

referred to in this 2009 Microbiological Data Program Summary is for the information and convenience 

of the reader. Such use does not constitute an official endorsement or approval by the U.S. Department 

of Agriculture of any product, service, or analytical method to the exclusion of others that may be 

suitable.

21

Food MDP-09-00018

Human 

5A. S. javiana

5B. S. saintpaul

Human 

Food MDP-09-00013

5C. S. oranienburg

Human 

Food MDP-09-00003

Environment

Environment

Figure 5. Salmonella Isolates PFGE Patterns. This figure compares PFGE patterns of MDP food 

isolates to human or environmental isolates submitted by other agencies to the PusleNet Database. 

Matching PFGE patterns helps epidemiological investigators trace the source of foodborne illnesses.
Microbiological Data Program - Annual Summary, Calendar Year 2009

Definitions:

Antimicrobial susceptibility: The result of microbes changing in ways that reduce or eliminate the 

effectiveness of drugs, chemicals, or other agents to cure or prevent infections.

AOAC®INTERNATIONAL: An internationally recognized organization that validates and approves 

analytical methods for foods and agriculture.

Aseptic: Free of microbial contamination.

Cultural Methods: Use of rich or selective media for the growth and identification of target bacteria.

Deoxyribonucleic acid (DNA): The molecule that encodes genetic information required to constitute a 

living and reproducing organism. DNA-based technologies exploit the uniqueness in the DNA 

sequences of a given organism in detection and identification methods.

eLEXNET: The electronic laboratory exchange network (eLEXNET) is an electronic system 

administered by the Food Emergency Response Network (FERN) that allows the exchange of 

laboratory analytical data among over 100 public health laboratories at the Federal, State and local 

levels. eLEXNET is FERN’s data capture mechanism.

Enterohemorrhagic E. coli (EHEC): Strains of E. coli that are the primary cause of hemorrhagic colitis 

or bloody diarrhea, which can progress to the potentially fatal hemolytic uremic syndrome. EHEC are 

typified by the production of verotoxin or Shiga toxins (Stx). E. coli O157:H7 is the prototypic EHEC.

 

Enterotoxigenic E. coli (ETEC): Strains of E. coli that are the causative agent of travelers’ diarrhea 

and illness characterized by watery diarrhea with little or no fever. Pathogenesis of ETEC is due to the 

production of any of several enterotoxins, including heat-labile enterotoxin and heat-stable toxin.

Genomic fingerprinting: Techniques used in the identification and/or classification of organisms 

exploiting the differences in the DNA sequence.

Green Fluorescent Protein (GFP): Expression of the gene from jellyfish in bacterial control cultures is 

used as a marker.

Indicator organism: A microorganism or group of microorganisms whose presence indicates 

unsanitary condition or fecal contamination.

Isolate: Target bacterial strain isolated as a pure culture and identified.

Most Probable Number (MPN): Most Probable Number (MPN) is a statistical expression for 

estimating the microbial density in a culture or per unit volume of water.

National Antimicrobial Resistance Monitoring System (NARMS): A collaborative effort among the 

Centers for Disease Control and Prevention, the Food and Drug Administration, and the U.S. 

Department of Agriculture to monitor antimicrobial resistance of human enteric bacteria, including 

Campylobacter, Salmonella, Escherichia coli O157:H7, and Shigella.

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Microbiological Data Program - Annual Summary, Calendar Year 2009

23

Pathogen: Specific causative agent (e.g., a bacterium or virus) of disease.

Polymerase Chain Reaction (PCR): A technique used to amplify a specific region of DNA into a large 

number of copies in order to produce enough DNA to be adequately tested. PCR can be used to 

identify, with a very high probability, disease-causing viruses and/or bacteria. 

Multiplex PCR (mPCR) involves simultaneous amplification of more than one specific region of DNA 

or specific genes for various analytes.

Proficiency test sample: Any matrix sample prepared for the purpose of determining biases, accuracy, 

and/or precision among analysts and/or laboratories or of a single analyst or laboratory.

PulseNet: A national network of local, State, and Federal public health and food laboratories 

coordinated by the Centers for Disease Control and Prevention (CDC) to detect foodborne disease case 

clusters and outbreaks and facilitate identification of the source by standardized genomic fingerprinting 

(molecular subtyping) of various pathogenic bacteria using pulsed-field gel electrophoresis (PFGE) 

technology.

Pulsed field gel electrophoresis: (PFGE) is designed to separate DNA too large to be separated by 

conventional gel electrophoresis and is a highly discriminatory method for the differentiation of 

bacterial isolates based on differences in DNA content. 

Serotyping: An antigen and antibody reaction technique that is used to differentiate strains of 

microorganisms based on differences in the antigenic composition of a certain structure such as the cell 

wall components or flagella.

Shiga toxin: A family of toxins produced by Shigella dysenteriae type I and shiga toxin-producing E. 

coli. These toxins have a cytotoxic effect on intestinal epithelial cells that causes characteristic bloody 

diarrhea.

Virulence attributes/factors: A bacterial product, usually a protein or carbohydrate (polysaccharide) 

that contributes to virulence or pathogenicity.

Virulence: The degree or intensity of pathogenicity of an organism as indicated by case fatality rates 

and/or ability to invade host tissues and cause disease.

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, 

color, national origin, age, disability, and where applicable, sex, marital status, familial status, parental status, religion, 

sexual orientation, genetic information, political beliefs, reprisal, or because all or part of an individual’s income is derived 

from any public assistance program (Not all prohibited bases apply to all programs.) Persons with disabilities who require 

alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact USDA’s 

TARGET Center at (202) 720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, Director, Office of 

Civil Rights, 1400 Independence Avenue, S.W., Washington, D.C. 20250-9410, or call (800) 795-3272 (voice) or (202) 720-

6382 (TDD). USDA is an equal opportunity provider and employer.

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