United States Department of Agriculture

Agricultural Marketing Service

Science & Technology

Pesticide Data Program

Annual Summary Calendar Year 1995
Pesticide Data Program - Annual Summary Calendar Year 1995 

iii

Contents

Page No.

Preface .......................................................... vii

Executive Summary .................................................. xi

Section I

Introduction ............................................................ 1

Section II

Sampling Protocol ....................................................... 6

Section III

Laboratory Operations ................................................... 10

Section IV

Sample Results and Discussion ............................................. 11

Appendixes A-F Fruit and Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..17

Appendix A Origin by Grower, Packer, or Distributor

Appendix B Quality Assurance Program Elements

Appendix C Distribution of Residues Detected by Pesticide

Appendix D National Estimates for Concentration Percentiles vs. Tolerance

Appendix E Number of Non-Detected Residues by Pesticide/Commodity Pairs

Appendix F Percentage of Samples vs. Number of Residues Detected per Sample

Appendix G Distribution of Pesticide Residues in Wheat 

Appendix H Commodity History (A Chronological Listing)
Pesticide Data Program - Annual Summary Calendar Year 1995 

v

List of Figures and Tables

Figures

Page No.

 1 Overview of PDP Operations .................................... 2

 2 Participating States and Their Geographical Distribution Areas ............ 3

 3 Commodity Origin (Percentage Domestic vs. Imported) ................. 8

 4 Distribution of Wheat Samples .................................... 9

Tables

 1 Pesticides in Pesticide Data Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

 2 Samples Collected Per Commodity by Each Participating State ............ 7

 3A Number of Samples and Residues Detected, by Commodity

 (Includes Post-Harvest Applications) ............................ 13

 3B Number of Samples and Residues Detected, by Commodity

 (Excludes Post-Harvest Applications) ........................... 14
Pesticide Data Program - Annual Summary Calendar Year 1995 

vii

Preface

In 1991, the United States Department of Agriculture this report, the Academy recommends that pesticide

(USDA) was charged with implementing a program to residue monitoring programs target foods highly

collect data on pesticide residues in food. USDA’s consumed by children, and that analytical testing

Agricultural Marketing Service (AMS) was appointed to methods used be standardized, validated, and subject to

undertake the creation and implementation of such a strict quality control and quality assurance programs.

program, currently known as the Pesticide Data Program PDP is now a critical component of the Food Quality

(PDP). PDP has been in operation since May 1991 and Protection Act of 1996. Title III Sec. 301(c) of the Act

has published its findings for calendar years 1991 states: The Secretary of Agriculture shall ensure that

through 1994. This is the summary for calendar year the residue data collection activities conducted by the

1995. Department of Agriculture in cooperation with the

PDP’s data on pesticides in selected commodities of Health and Human Services, provide for the

strengthen the Government's ability to respond to food improved data collection of pesticide residues,

safety and marketing concerns, to protect public health, including guidelines for the use of comparable

and to provide the Environmental Protection Agency analytical and standardized reporting methods, and

(EPA) with data needed to assess the actual dietary risk increased sampling of foods most likely consumed by

posed by pesticides. infants and children. PDP, as a result of the provisions

EPA registers pesticides under a statutory standard that the data needed to evaluate cumulative exposure to

requires balancing the benefits of a pesticide use against pesticide residues with a common toxicological effect,

its potential risks to human health and the environment. and create a statistically reliable database on endocrine

In making risk estimates, EPA uses a stepwise approach disruptors at minute detection levels needed to assess

to minimize resource expenditures. As an initial worst dietary risk to compromised population groups. 

case assessment, EPA assumes that all acres of all crops

are treated with all pesticides for which they have a The States participating in PDP deserve special

registered use. EPA also assumes that residues in recognition for their contributions to the program.

treated crops are present at the maximum allowable Sample collectors’ vigilance and dedication allow AMS

level. A theoretical assessment risk based on these to adjust sampling protocols to respond to changing

worst case assumptions may significantly exceed the trendsin commodity distribution. Laboratory staff have

actual risk of pesticide residues in the food supply and formulated recommendations to increase productivity

jeopardize the registration of pesticides important to and improve methodologies. PDP also thanks Phillip

American agriculture. Further refinements to the risk Kott of USDA's National Agricultural Statistics Service

assessment are done if needed. These stepwise (NASS); Edward Zager of EPA; John Jones of the Food

refinements include the use of percent of crop treated; and Drug Administration (FDA); and the staffs at

statistical analyses of field data; considerations of the USDA’s Animal and Plant Health Inspection Service

effects of washing, cooking, processing, storage, and use (APHIS); Grain Inspection, Packers and Stockyards

of monitoring data, if available and reliable. This is Administration (GIPSA); and Agricultural Marketing

where PDP data are pivotal. PDP’s sampling procedures Service laboratories for providing their support to the

were designed to capture actual residues in the food program. In addition, we acknowledge GIPSA’s

supply as close as possible to the time of consumption, servicesfor the collection and analysis of wheat samples

thereby significantly upgrading the statistical reliability for PDP.

and extent of information needed for risk assessment.

PDP continues to focus on the National Academy of presentation. Please send your comments and

Sciences’ conclusions as shown in the 1993 report suggestions to the Science and Technology Division

Pesticides in the Diets of Infants and Children. In address listed below.

Environmental Protection Agency and the Department

of this Act, will have a more significant role in providing

We welcome any comments on the Summary’s
Pesticide Data Program - Annual Summary Calendar Year 1995 

viii

Data presented in this summary were collected and Florida Department of Agriculture and

processed through the efforts of the following: Consumer Services

U.S. Department of Agriculture 3125 Conner Boulevard

Science and Technology Division

Agricultural Marketing Service, USDA Florida Department of Agriculture and

14th and Independence Avenue, S.W. Consumer Services

Room 3507, South Building, Mail Stop 0222 Chemical Residue Laboratory

Post Office Box 96456 500 3rd Street, Northwest

Washington, DC 20090-6456 Winter Haven, FL 33880

Director: William J. Franks, Jr. Michigan Department of Agriculture

Phone: (202) 720-5231 Fax: (202) 720-6496 Laboratory Division

Deputy Director: Robert L. Epstein 1615 South Harrison Road

Phone: (202) 720-2158 East Lansing, MI 48823-5224

Pesticide Data Program Staff

Phone: (703) 330-2300 Fax: (703) 330-6110 New York Department of Agriculture and Markets

INTERNET HOME PAGE

http://www.usda.gov/ams/index.htm North Carolina Department of Agriculture

Participating State Agencies 4000 Reedy Creek Road

California Department of Food and Agriculture

California Department of Pesticide Regulation Ohio Department of Agriculture

Colorado Department of Agriculture Consumer Analytical Laboratory

Florida Department of Agriculture and 8995 East Main Street

 Consumer Services Reynoldsburg, OH 43068

Michigan Department of Agriculture

New York Department of Agriculture and Markets Texas Department of Agriculture

North Carolina Department of Agriculture Brenham Pesticide Laboratory

Ohio Department of Agriculture 200 East Horton Street

Texas Department of Agriculture Brenham, TX 77834

Washington State Department of Agriculture

Participating State Laboratories 2017 South First Street

California Department of Food and Agriculture

Division of Inspection Services

Center for Analytical Chemistry

3292 Meadowview Road

Sacramento, CA 95832

Chemical Residue Laboratory, Building #3

Tallahassee, FL 32399-1650

Food Laboratory

State Campus, Building #7

Albany, NY 12235

Food and Drug Protection Division

Constable Laboratory

Raleigh, NC 27607

Washington State Department of Agriculture

Chemical and Hop Laboratory

Yakima, WA 98903
Pesticide Data Program - Annual Summary Calendar Year 1995 

ix

Participating Federal Laboratories

United States Department of Agriculture

Animal and Plant Health Inspection Service

National Monitoring and Residue Analysis Laboratory

3505 25th Avenue, Building 9

Gulfport, MS 39501

United States Department of Agriculture

Grain Inspection, Packers and Stockyards

Administration

Grain Inspection Service

Technical Services Division

10383 North Executive Hills Blvd.

Kansas City, MO 64153

United States Department of Agriculture

Agricultural Marketing Service

Science and Technology Division, Eastern Laboratory

645 Cox Road

Gastonia, NC 28054
Pesticide Data Program - Annual Summary Calendar Year 1995 

xi

Executive Summary

The Pesticide Data Program (PDP) was implemented by quality of data that EPA uses to determine the residue

the United States Department of Agriculture (USDA) in levels in foods and estimate exposure to consumers.

May 1991 to collect data on pesticide residues in foods. Without actual residue data, initial risk assessments are

The data are used by the Environmental Protection based on the theoretical maximum amounts of pesticide

Agency (EPA) for its dietary risk assessment process use and may overstate dietary exposure. A theoretical

and pesticide registration process, the Food and Drug risk based on worst case assumptions may exceed the

Administration (FDA) to refine sampling for actual risk of pesticide residues in the food supply and

enforcement of tolerances, Foreign Agricultural Service, jeopardize the registration of pesticides important to

USDA, to support export of U.S. commodities in a American agriculture. Where needed, EPA conducts

competitive global market, the Economic Research further refinements to the risk assessment by using

Service, USDA, to evaluate pesticide alternatives, and additional information that includes residue monitoring

the public sector in addressing food safety issues. PDP data, if available and reliable. This is where PDP data

has issued data summaries for calendar years 1991 are pivotal. PDP data, which are collected as close to

through 1994. This summary contains PDP findings for the point of consumption as possible, follows

calendar year 1995. statistically reliable sampling protocols, thereby

During 1995, pesticides monitored by PDP included

insecticides, herbicides, fungicides, and growth PDP samples are collected without regard for commodity

regulators in fresh and processed fruits and vegetables, origin or variety, as close to the point of consumption as

and wheat. Pesticides and commodities were chosen for possible. Samples reflect what is available to the

inclusion in the program based on EPA's data needs and consumer throughout the year. PDP's sampling protocol

USDA's food consumption surveys. takes into account the different volumes of produce

distributed annually by each sampling site, thus

PDP planning and policy are coordinated through an removing a potential source of bias for estimates of

Executive Steering Committee consisting of residues in PDP commodities. Wheat samples were

representatives of USDA, EPA, and FDA. USDA collected nationally from GIPSA’s “file” samples

representatives to the committee include: Agricultural submitted for quality assurance evaluation, based on

Marketing Service (AMS), National Agricultural state and monthly production.

Statistics Service (NASS), Economic Research Service

(ERS), and Agricultural Research Service (ARS). PDP's Samples collected during 1995 consisted of 12

administrative, sampling, technical, and database commodities: apples, bananas, carrots, grapes, green

activities are the responsibility of the Science and beans, oranges, peaches, potatoes, spinach, sweet corn,

Technology Division of AMS. sweet peas, and wheat. Sweet corn and peas were

PDP operations in 1995 were managed through other PDP samples were fresh. Samples collected

cooperative agreements with nine States, which are originated from 39 States and 17 foreign countries. Of

responsible for sample collection and analysis. Eight the 6,924 fruit and vegetable samples collected and

participating States (California, Florida, Michigan, New analyzed: 1,143 (16.5 percent) were imported, with

York, North Carolina, Ohio, Texas, and Washington) bananas, grapes, and peaches accounting for most

collected and analyzed samples during 1995. imports. In addition, 600 wheat samples were collected

Colorado’s samples were shipped to other participating and analyzed. Thirty-seven samples were received

laboratories for analysis. Together, these nine States unsuitable for analyses and were discarded. 

represent approximately 50 percent of the Nation's

population. Of the 6,924 fruit and vegetable samples analyzed by the

PDP was designed to provide information on the contained at least one pesticide residue. Also, 79

concentrations of pesticides in order to improve the percent of the 600 wheat samples had at least one

upgrading their usefulness for risk assessment. 

collected as frozen and canned processed products. All

participating laboratories, approximately 65 percent
Pesticide Data Program - Annual Summary Calendar Year 1995 

xii

pesticide residue. About 29 percent of the residue

detections were due to post-harvest uses. 

In 1995, there were 316 presumptive violations in 263

samples. Nine presumptive violations were for pesticide

residues where the EPA tolerance was exceeded and 307

were presumptive violations where there was no

established tolerance for the pesticide/commodity pair.

Most pesticide residue detections were below tolerance

levels established by EPA. In PDP, the limits of

detection for each pesticide/ commodity pair in the

testing system are analytically defined at levels low

enough to conduct realistic dietary risk assessments.

This enables scientists using PDP data to consider not

only residue detection findings but also the inverse, nondetected residues, in calculating dietary risk. Hence, risk

assessment evaluations by EPA in the reregistration

process can be based on the range of levels detected,

including non-detected residues for each of the

pesticide/commodity pairs tested. 

PDP continuously strives to improve methodologies for

the collection, testing, and reporting of data. PDP data

are available to EPA and other Federal and State

agencies charged with regulating and setting policies on

the use of pesticides.
Pesticide Data Program - Annual Summary Calendar Year 1995

1

Pesticide Data Program (PDP)

Annual Summary, Calendar Year 1995

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

Laboratory Operations, and (IV.) Sample Results and Discussion.

I. Introduction

To implement the Pesticide Data Program (PDP), the

United States Department of Agriculture (USDA)

utilized the expertise available in four of its agencies:

the Agricultural Marketing Service (AMS), the National

Agricultural Statistics Service (NASS), the Economic

Research Service (ERS), and the Agricultural Research

Service (ARS). AMS was selected as the lead agency to

coordinate and implement the various facets of the

residue program and manage program operations.

NASS provides statistically reliable data on chemical

usage at the State level and collects economic input data

that link chemical usage with economic characteristics.

ERS analyzes AMS and NASS data to understand

producer behavior and to determine the impact various

production practices and policies might have on the

Nation's agricultural production, food supply, and

consumers. ARS conducts nationwide surveys of

individual food intake and household use and is

developing a Food Grouping System to translate data on

foods as consumed into forms that can be linked with

pesticide residue data. AMS selected its Science and

Technology Division to oversee PDP’s policy planning

and program direction with the participating State and

Federal facilities.

Figure 1, Overview of PDP Management and

Operations, describes the program’s three major

components - sample collection, laboratory analysis, and

database management. In 1995, PDP sampling and/or

analytical operations were performed by nine States

(California, Colorado, Florida, Michigan, New York,

North Carolina, Ohio, Texas, and Washington) through

agreements with their respective State agencies.

Accordingly, a significant part of PDP's financial

resources (75 percent) went directly to the States for

operating expenses. Ten percent of PDP funding was

given to USDA laboratory facilities to support State

testing activities for analyses requiring selective residue

methods. An additional 2 percent was provided to

GIPSA to conduct the wheat sampling and residue

testing program.

Figure 2 shows the States participating in the program

for collection of fresh and processed fruit and vegetable

samples , which together represent about 50 percent of

the Nation's population. Also shown are nine other

States (Alaska, Connecticut, Hawaii, Massachusetts,

Nevada, New Jersey, New Mexico, Vermont, and

Wyoming) where a significant amount of produce is

directly marketed from the participating States. Figure

3 shows the distribution of commodities by origin,

domestic versus imported. Figure 4 is a map showing the

distribution by State of wheat samples collected in 1995.

AMS works closely with EPA to select the commodities

and pesticides to be placed in PDP. Commodities

chosen for inclusion are those most often consumed by

the American public, with emphasis on those consumed

by infants and children. Twelve commodities (apples,

bananas, carrots, grapes, green beans, oranges, peaches,

potatoes, spinach, canned and frozen sweet corn and

sweet peas, and wheat) were sampled and analyzed in

1995. The pesticides EPA suggests for monitoring

consist mainly of those whose toxicities and estimated

dietary exposures indicate the need for more refined

exposure estimates. The list is revised periodically
Pesticide Data Program - Annual Summary Calendar Year 1995

2

Main Objectives

C Provide the Environmental Protection Agency (EPA) with highquality data on residues in food. The data are used for dietary risk

assessments and to address pesticide reregistration and special

reviews.

C Address the recommendations of the National Academy of Science

report Pesticides in the Diets of Infants and Children.

C Support Foreign Agricultural Service’s international marketing of

U.S. commodities.

C Address USDA’s Food Quality Protection Act responsibility.

Laboratory Analysis

C Samples prepared as if for consumption

C State-of-the-art instrumentation used

C Detection at very low levels

C QA based on EPA Good Laboratory

Practices

C Confirmation of detected pesticides

C Multiple residue detection methodology

C Standard Operating Procedures

Database Management

C Customized query capability

C Electronic transmission or data

C Standardized data summaries

Participating States - 1995

C California

C Colorado

C Florida

C Michigan

C New York

C North Carolina

C Ohio

C Texas

C Washington

USDA Laboratories - 1995

C AMS Eastern Laboratory, Gastonia, NC

C APHIS, NMRAL, Gulfport, MS

C GIPSA, Kansas City, MO

ñ

C EPA

C FDA

Executive Steering Committee

C USDA

-AMS

-NASS

-ERS

-ARS

ñ

Management and Operations

C Science and Technology Division

ñ ñ

ñ ñ

ñ

ñ

Sample Collection

C Statistically reliable sampling plan

C Data used to make national estimates

C Collected near consumer level

C Represent about 50% of U.S. population

C Commodities consumed mostly by infants

and children

C Origin of product retained

C Post-harvest fungicides & minor use

registration

C Standard Operating Procedures

 Figure 1. Overview of PDP Management and Operations
Hawaii

Figure 2. Participating States and Their Geographical Distribution Areas

Wyoming

New 

Mexico

Alaska

Michigan

Massachusetts

Vermont

Connecticut

New Jersey

Florida

Nevada

States Where Produce is Directly

Participating States

Marketed from Participating States

Pesticide Data Program - Annual Summary Calendar Year 1995

3

to address EPA’s data needs. Table I is a list of Currently, PDP collects data for over 400 pesticide and

pesticides included in the 1995 PDP testing profile for commodity combinations whose uses are legal under the

fruit and vegetables, and wheat. Federal Insecticide, Fungicide, and Rodenticide Act

Although EPA continues to be a primary recipient of commodity combinations with pending use registrations,

PDP data, over the past year PDP has received requests or where uses have been granted under other provisions

for data from the Foreign Agricultural Service (FAS) and of FIFRA. In many of these cases, these uses are granted

other government and industry sources to promote to alleviate the lack of effective pesticides registered for

exporting American agricultural products in international

markets. PDP data have also been solicited by chemical

companies surveying use and residues of their products.

PDP is now a critical component of the Food Quality

Protection Act of 1996, which directs the Secretary of

Agriculture to collect pesticide residue data on

commodities highly consumed by infants and children in

a uniform manner. 

(FIFRA). Data are also collected for other pesticide and

minor use crops (fruits and vegetables). Consequently,

PDP data are also used for reregistration of pesticides for

minor use crops.

PDP has also provided information to the Codex

Alimentarius Commission and the World Health

Organization, both of which operate under the auspices
Pesticide Data Program - Annual Summary Calendar Year 1995

4

Table 1. Pesticides in Pesticide Data Program 1995

PART IA. Fresh and Processed Fruits and Vegetables (F&V)

(Quality Assurance Program)

Analyzed by Multiresidue Methods (MRMs)

48 Pesticides & 17 Metabolites / Degradates / Isomers

Acephate Lindane

Aldicarb + sulfone & sulfoxide Malathion

Atrazine Methamidophos

Azinphos methyl Methidathion

Captan Methomyl

Carbaryl Methoxychlor

Carbofuran + 3-OH Carbofuran Mevinphos

Chlorothalonil Myclobutanyl

Chlorpropham Omethoate

Chlorpyrifos Oxamyl

Dacthal (DCPA) Parathion 

DDT + DDD + DDE Parathion methyl

Diazinon Permethrin cis & trans

Dichlorvos (DDVP) Phorate + sulfone & sulfoxide

Dicloran Phosphamidon

Dicofol Propargite

Dimethoate Quintozene (PCNB)

Diphenylamine Hexachlorobenzene (HCB)

Disulfoton + sulfone + sulfoxide Pentachloroaniline (PCA)

Endosulfan I, II & sulfate Pentachlorobenzene (PCB)

Esfenvalerate/Fenvalerate Terbufos + sulfone & O-analog

Ethion Thiabendazole

Fenamiphos + sulfone + sulfoxide Thiodicarb (as methomyl metabolite)

Imazalil Trifluralin

Iprodione Vinclozolin

Analyzed by Selective Residue Methods (SRMs)

5 Pesticides + 3 Isomers

2,4-D

Abamectin (Avermectin b1a and delta 8,9 isomer)

Benomyl (as Carbendazim)

Fenbutatin Oxide (Hexakis) + metabolites

Formetanate
Pesticide Data Program - Annual Summary Calendar Year 1995

5

PART IB. Other Pesticides/Metabolites Analyzed in F&V

20 Pesticides + 5 Metabolites / Isomers

Allethrin Linuron

Anilazine MCPA (m-chlorophenoxyacetic acid)

Azinphos ethyl Metalaxyl

Benfluralin Methiocarb + sulfoxide

Cyhalothrin lambda & isomer 1-Napthol (Carbaryl Metabolite)

Cypermethrin Ovex

Demeton-S Phosalone

 Demeton + sulfone Phosmet

Dieldrin Piperonyl Butoxide

Diuron Tecnazine

Ethoprop Toxaphene

 4-OH Diphenylamine Metabolite

PART II. Wheat

Analyzed by Multiresidue Methods (MRMs) - Quality Assurance Program

23 Pesticides + 5 Metabolites/Isomers

Atrazine Endosulfan I, II & sulfate

Azinphos Methyl Imazalil

Carbaryl Linuron

Carbofuran + 3 -OH Carbofuran Malathion

Chlorpyrifios Methomyl

Chlorpyrifos methyl Methoxychlor

Demeton S Parathion

Diazinon Parathion methyl

Dichlorvos (DDVP) Phorate & sulfone

Diclofop methyl Triallate

Dimethoate Trifluralin

Disulfoton & sulfone

of the United Nations. The information provided was on potentialsites granting access and providing information

extraneous residues in foods (environmental to sample collectors. Their cooperation makes it possible

contaminants), such as DDT and metabolites, pesticide to adjust sampling protocols in response to fluctuations

residue stability data, and PDP’s Proficiency Check in food distribution. 

Sample Program.

To obtain pesticide residue data on fruit and vegetable programs (tolerance enforcement) which require quick

commodities as close to the point of consumption as turnaround time for analysis of enforcement samples.

possible, samples are collected at distribution points just Under tolerance enforcement, the sampled commodity

before release to supermarkets and grocery stores. may be detained at the distribution facility while awaiting

Sampling at these locations allows for residue sample results. PDP places emphasis on searching for

measurements that include fungicides and growth residues at the lowest detectable levels, rather than on

regulators, and takes into account degradation of quick sample turnaround; therefore, analysis of PDP

pesticides while in storage. Participation of PDP samples may take over a month, and does not affect

sampling sites is voluntary, which sets it apart from State commodity distribution.

and Federal enforcement programs. There are over 650

PDP differs markedly from regulatory monitoring
Pesticide Data Program - Annual Summary Calendar Year 1995

6

As of the publication date of this Summary, PDP has determine the probability for selection. For example, a

considered 26 commodities in the testing program. site that distributes 100,000 pounds of produce annually

Appendix H is a chronological history of the commodities might be given a weight of “10,” and a site that

in PDP from program inception to January 1997. distributes 10,000 pounds might be weighted “1.” The

II. Sampling Protocol

Fruit and Vegetables Sampling Plan

PDP’s statistically reliable sampling protocol for fresh

and processed fruit and vegetables allows for making

nearly unbiased estimates of pesticide residues for

commodities collected in the participating States and

makes it possible to quantify the accuracy of the

estimates for the Nation as a whole. The protocol also

reflects the relative proportion of imported versus

domestic produce available to the consumer. This has

been corroborated by comparing the composition of PDP

samples with import data compiled by the Economic

Analysis Branch, AMS Fruit and Vegetable Division.

 Sampling Procedures 

Participating States are responsible for compiling and

maintaining lists of sites used for sample collection.

Since PDP strives to collect samples as close to the

consumer as possible, while maintaining sample origin,

most of the sites for fresh fruits and vegetables are either

terminal markets or large chain store distribution centers.

Both of these locations serve as the last stopover before

produce reaches retailers and, ultimately, consumers.

This provides a better picture of actual dietary exposure

to pesticide residues by taking into account pesticide

degradation that occurs during transit and storage.

Sampling at these locations also provides information on

post-harvest application of fungicides and growth

regulators.

Processed commodity samples are collected at

distribution centers or large warehouses. To provide PDP

with data on both canned and frozen sweet corn and peas,

collection of the two types of processed commodity were

alternated monthly. 

After establishing their site lists, States are required to

provide AMS and NASS with annual volume information

for each site (quantity of commodity distributed in one

year). This information is used to “weight” the site to

probability proportionate to size method of site selection

would then result in the larger site (distributing 100,000

pounds) being 10 times more likely to be selected for

sampling than the smaller site (distributing 10,000

pounds). Participating States are required to work with

NASS to develop their statistical procedures for site

weighting and selection. States are also given the option

of having NASS perform their quarterly site selection for

them. The number of sampling sites and the volume of

produce distributed by the sites varies greatly from State

to State. 

State population figures are used to assign the number of

fruit and vegetable samples scheduled for collection per

commodity each month. For 1995, these numbers were:

California-14, Colorado-2, Florida-7, Michigan-6, New

York-9, North Carolina-4, Ohio-6, Texas-8, and

Washington-4; for an annual total of 720 per commodity.

Sample size was approximately 5 pounds for each

applicable testing facility. 

Sampling plans, which were prepared by the States on a

quarterly basis, included sampling dates, sites, and fruit

and vegetable commodities for collection during each

month of the quarter. Although sites could only be

sampled once per month for the same commodity, States

were allowed to collect two different commodities at the

same site on the same date. This “pairing” of

commodities reduced the number of sampling dates; and,

therefore, the cost of sample collection. States were also

instructed to collect all samples of the same commodity

on one sampling date, or, if needed, within two

consecutive dates. Collection of commodities was

randomly assigned to various weeks of the month, prior

to selecting specific sampling dates within the week.

Since sampling sites were selected for the entire quarter,

States were allowed to assign the sites to particular

months based on geographic location.

In 1995, seven of the participating States formed

transshipment pools, whereby commodities collected by

the paired States were combined into one set for

analytical testing in one State laboratory. This

arrangement created larger sample sets, increased

proficiency and productivity, and substantially reduced

the mandatory quality assurance costs. These paired
Pesticide Data Program - Annual Summary Calendar Year 1995

7

States are: Colorado, Michigan, and Washington; Florida States have been given Statement of Procedures (SOPs)

and Texas; and North Carolina and Ohio. for PDP sampling, which cover sample administration;

Chain-of-custody for PDP samples is documented documentation. These SOPs, which are updated as

through the use of “Sample Information Forms.” These needed, are provided to sample collectors, and used as a

forms are used by the sample collectors to record all guide for determining compliance during sampling

pertinent sample information, such as: (1) the State reviews. 

where the sample was collected; (2) the date of collection;

(3) the 3-digit code for the sampling site; and (4) the Synopsis of Sample Collection (Fruit and

commodity code. These four pieces of information are Vegetables) 

combined to form a unique “sample identification

number” for recording in the PDP database. Other

information included on the form is: (1) whether the

sample is domestic or imported and, if imported, the

country of origin; (2) the name of the sampling site,

grower, packer, or distributor; and (3) a list of potential

or known post-harvest applications. The Sample

Information Forms are also used to keep track of any

missing samples that are not collected, lost in transit, or

damaged and unable to be analyzed when received at the

laboratory. Sampling managers in the participating

collection, packing, and shipping procedures; and

A total of 6,924 samples of fresh and processed fruits

and vegetables were collected and analyzed during 1995.

As shown in Table 2, the number of samples collected

per State was: California - 1,607, Colorado - 228,

Florida - 772, Michigan - 721, New York - 1,034, North

Carolina - 477, Ohio - 696, Texas - 933, and Washington

- 456. These figures are less than the total number of

assigned samples for 1995 due to the unavailability of

product at either the original or alternate sampling site,

which is often due to the commodity growing season.

Table 2. Samples Collected & Analyzed per Commodity by Each Participating State

 Commodity

State AP BN CR CS GB GR OG PC PO PS SP Total

California 156 121 163 139 146 160 163 91 169 140 159 1607

Colorado 23 17 24 23 17 24 22 12 22 23 21 228

Florida 78 49 80 77 64 76 76 41 81 80 70 772

Michigan 72 49 71 71 62 72 72 45 70 70 67 721

New York 106 74 104 104 82 105 106 60 105 104 84 1034

North Carolina 48 35 48 47 46 46 48 25 47 46 41 477

Ohio 71 46 71 71 56 68 72 36 72 70 63 696

Texas 94 63 96 93 80 95 93 48 95 92 84 933

Washington 47 32 46 46 34 48 48 19 46 45 45 456

Total 695 486 703 671 587 694 700 377 707 670 634 6924

Commodities

AP - Apples GB - Green Beans PO - Potatoes

BN - Bananas (Jan-Sep) GR - Grapes PS - Sweet Peas

CR - Carrots OG - Oranges SP - Spinach

CS - Sweet Corn PC - Peaches

Figure 3 shows the total number of samples per

commodity and the percentage of each that were either

domestic, imported, or of unknown origin. Appendix A

provides a more detailed breakdown of sample origin
Pesticide Data Program - Annual Summary Calendar Year 1995

8

by State or country. As indicated, samples collected

during 1995 originated from 39 States and 17 foreign

countries.

Figure 3. COMMODITY ORIGIN (Percentage Domestic vs. Imported)

A. Fresh Commodities
95.1 % Domestic

4.9 % Import

Carrots

(703 Samples)

Bananas

(486 Samples)

Apples

(695 Samples)

Oranges

(700 Samples)

Green Beans

(587 Samples)

Grapes

(694 Samples)

Spinach

(634 Samples)

Peaches

(377 Samples)

Potatoes

(707 Samples)

Figure 3. COMMODITY ORIGIN (Percentage Domestic vs. Imported)

A. Fresh Commodities

B. Processed Commodities*
Sweet Peas

(670 Samples)

Sweet Corn

(671 Samples)

* For

processed commodities, percentages were mainly derived from packer and/or distributor information.
Pesticide Data Program - Annual Summary Calendar Year 1995

9

Wheat Sampling Program

 The Grain Inspection, Packers and Stockyards sixteen samples in GIPSA’s 13 regional offices.

Administration (GIPSA) collected 600 wheat samples in Numbers of samples collected were based on product

calendar year 1995. Samples were collected from availability on a national basis by State and month,

available “file” samples received from grain elevators and encompassing all seven varieties of wheat. Figure 4 is a

other storage facilities, but excluded wheat already map of the U.S. showing the distribution of the 600

segregated for export. Sample selection was done wheat samples by State.

randomly based on predetermined algorithm of one in

Figure 4. Distribution of Wheat Samples

A minimum of 500 to 1,000 grams of individuals levels of detection. Major changes in methodology are

representative samples of wheat were forwarded for evaluated, and their soundness demonstrated and

pesticide analysis to GIPSA’s Technical Services documented in accordance with PDP Standard Operating

Division laboratory in Kansas City, MO. Chain-of- Procedures (SOPs).

custody procedures were the same as for fruit and

vegetable samples. The Sample Information Form PDP participating laboratories monitored 48 pesticides

included the location of the field office, inspection point, plus 17 metabolites, degradates, and isomers using

wheat variety, and date of inspection. multiresidue methods (MRMs) and 5 pesticides plus 3

III. Laboratory Operations

Twelve laboratories (nine State and three Federal)

performed analyses for PDP during 1995. These

laboratories are equipped with advanced technical

instrumentation capable of detecting residues at very low

levels. The laboratory staff receives intensive training

and must demonstrate analytical proficiency on an

ongoing basis. Scientists continuously test new

technologies and develop new techniques to improve the

metabolites by single or selective residue methods

(SRMs). Since SRMs are resource intensive, this type of

analysis was performed only at selected laboratories for

specific commodities as indicated below: 

Laboratories Performing SRMs

1. APHIS, NMRAL, Gulfport, MS

Pesticide: Benomyl

Commodities: Carrots, Grapes, Green Beans, 

Oranges (Jan.-Sep.), Peaches, 

Sweet Corn, and Spinach.
Figure 4. Distribution of Wheat Samples

Montana

Colorado

So. Dakota

Nebraska

Washington

Texas

Missouri

Michigan

States with less than 30 Samples

States with more than 30 Samples

Oregon

Idaho

Utah

No. Dakota

Minnesota

Michigan

Louisiana

Mississippi

Alabama

Tennessee

Alaska

Oklahoma Arkansas

Kentucky

Iowa

Illinois

Wisconsin

Indiana 6

Ohio

6

6

10

4

1

8

22 5

2

22

23

10

3

1

4

4

7

1

18

10

19

10

3
Pesticide Data Program - Annual Summary Calendar Year 1995

10

2. AMS Eastern Laboratory, Gastonia, NC set is ready to be homogenized.

Pesticide: Abamectin Upon arrival at the testing facility, samples are visually

Commodities: Oranges examined for acceptability and discarded if determined to

Pesticide: Formetanate samples are then prepared emulating the practices of the

Commodities: Apples (Jan.-July), Oranges, and average consumer, to more closely represent actual

Peaches (Jan.-July) exposure to residues. Fresh samples are prepared as

 3. APHIS, NMRAL, Gulfport, MS, and Selected State follows: (1) apples and peaches are washed and cored;

Laboratories (2) bananas and oranges are peeled; (3) carrots and

Pesticide: 2,4-D (Jan.-June) removed; (5) green beans and grapes are washed and

Commodities: Peaches, Sweet Peas, and Sweet stems removed; and (6) wheat is ground and then

Corn analyzed. For processed commodities, the entire contents

4. APHIS, NMRAL, Gulfport MS, and the Washington present.

State Laboratory, Yakima, WA

Pesticide: Fenbutatin Oxide (Hexakis) and and separated into analytical portions (aliquots) for

metabolites (July-Dec.) analysis. If testing cannot be performed immediately, the

Commodities: Apples, Grapes, Oranges, and entire analytical set (sample set plus all quality control

Peaches samples) is frozen at -40E C, or lower, according to

PDP's QA/QC requirements. Surplus aliquots, not used

 Quality Assurance Program for the initial testing, are retained frozen in the event that

The main objectives of the quality assurance/quality

control (QA/QC) program are to ensure the reliability of

PDP data and the performance equivalency of the

participating laboratories. Direction for PDP's QA

Program is provided through SOPs based on EPA's Good

Laboratory Practices (GLPs). For day-to-day quality

assurance oversight, PDP relies on the Quality Assurance

Unit (QAU) at each participating facility. As required

under EPA’s GLPs, the QAU operates independently

from their laboratory staff. Preliminary QA/QC review

procedures are performed on-site by each laboratory's

QAU. Final review procedures are performed by PDP

staff, who are responsible for collating and reviewing

data for conformance with SOPs. Additionally, PDP

staff also monitors the participants' performance through

proficiency samples, QAU quarterly internal reviews, and

on-site visits. Additional information on PDP's QA

Program is provided in Appendix B.

 Sample Preparation

Laboratories are permitted to refrigerate fresh incoming

samples of the same commodity for up to 72 hours, to

allow for different sample arrival times from the

collection sites. Frozen and canned commodities can be

held in storage (freezer or shelf) until the entire sample

be inedible (decayed, extensively bruised). Accepted

potatoes are washed; (4) spinach is washed with inedibles

of the sample is homogenized--including any liquid

Samples are homogenized using choppers and/or blenders

replication of analysis or verification testing is needed.

 Sample Analysis

For analysis of fruit and vegetables, variations of the

Luke I and II extraction procedures developed by FDA

were used by Florida, Michigan, New York, North

Carolina, Ohio, and Texas. California and Washington

used the multiresidue method developed by the California

Department of Food and Agriculture. These two methods

were determined to produce equivalent data for PDP

analytical purposes. Residues are extracted from samples

using organic solvents followed by various cleanup

procedures. Selective residue methods, used for 2,4-D,

abamectin, benomyl, fenbutatin oxide (hexakis), and

formetanate, were independently validated by the

laboratory(ies) performing analysis. 

Various types of chromatography are used for the initial

identification and quantitation of pesticides.

Confirmation is accomplished by mass spectrometry or

by alternate detection systems, depending on the

concentration reported. Limits of detection for various

selective detectors are lower than those achieved by mass

spectrometry detectors. Confirmation is deemed

necessary due to the complexity of commodity matrices
Pesticide Data Program - Annual Summary Calendar Year 1995

11

and the low concentration levels of detected residues. PDP sampling procedures require that the same number

The confirmatory analysis provides an extra measure of of samples be collected each month. As a result, the

confidence in the identification of both the pesticide relative sample composition for these seasonal

residue and its concentration. commodities may not exactly match product availability

Analysis of wheat samples were performed by the GIPSA pronounced example of this (limited availability in April

laboratory for 23 pesticides and 5 metabolites/isomers in and November, including both domestically grown and

PDP. Extraction was accomplished using supercritical imported peaches). According to independent USDA

fluid extraction (a solventless system) coupled with mass data (Fresh Fruit and Vegetable Arrival Totals for 22

spectrometry detection or post-column high performance Cities-FVAS-3 Calendar Year 1995, published in 1996

liquid chromatography detection. by Fruit and Vegetable Division, AMS, Washington, DC)

IV. Sample Results and Discussion

 Sample Results

During 1995, most pesticide residue detections were

below tolerance levels established by EPA. A tolerance

is the maximum allowable quantity of a pesticide residue

for a particular commodity. In PDP, the limits of

detection for each pesticide/commodity pair in the testing

system is analytically defined at levels low enough to

conduct realistic dietary risk assessments. This enables

scientists using PDP data to consider not only residue

detection findings, but also the inverse, non-detected

residues, in calculating dietary risk. Hence, risk

assessment evaluations by EPA in the reregistration

process can be based on the range of levels detected,

including non-detected residues for each of the

pesticide/commodity pairs tested. This is illustrated in

Appendixes C, D, E, and G. 

Appendix C shows the distribution of detected residues

per pesticide per commodity. Also shown are the

minimum and maximum concentrations detected,

tolerances, and samples for which there is no tolerance

established or for which the concentration detected

exceeds the tolerance. Non-detected residues for each of

the pesticide/commodity pairs tested are shown in

Appendix E.

 National Estimates

One objective of PDP is to use the data collected by the

nine participating States, which represent approximately

50 percent of the Nation’s population (Figure 2), to

project national estimates of pesticide residues for

Program commodities. Some of these national estimates

are shown in Appendix D. Although the availability of

certain commodities may vary, depending on the season,

throughout the year. Availability of peaches is the most

approximately 88 percent of all peaches available for

consumption in 1995 arrived at wholesalers during the

May-September time period. However, during this 5-

month time period, PDP collected only 65 percent of the

yearly total, or 23 percent less than what USDA’s figures

indicate was nationally available. This percentage is still

substantially higher than the 42 percent scheduled for

collection if peaches were readily available throughout

the year. Consequently, the fact that peaches are not

available consistently from month-to-month actually

provides an automatic adjustment to the monthly sample

numbers, causing them to more closely represent national

availability. To further adjust for the remaining

difference in actual sample numbers versus availability,

the sampling data have been weighted to reflect U.S.

wholesale arrivals. For more information on the

weighting process used to determine national estimates,

and on the statistical attributes of those estimates, refer to

Kott, P.S., 1996, Estimating Pesticide Residues in

Selected Fruits and Vegetables for the 1994 Pesticide

Data Program; National Agricultural Statistics Service;

Washington, DC. (The methods used in the 1994 and

1995 programs were identical.)

Appendix D focuses on the 52 pesticide/commodity pairs

with detectable residues in at least 10 percent of the

samples tested. A range of values for the estimated

national mean (or average) level of residue concentration

for each pair is provided. The lower value for the range

was determined by treating a sample without detectable

residues as if it had a residue concentration equal to zero.

The upper value for the range was determined by treating

such a sample as if it had a residue concentration equal to

the limit of detection. In addition, Appendix D also

provides national estimates for the 50th, 75th, and 90th

percentiles for each of the pairs. The ratio of the 90th

percentile to the tolerance, as a normalization factor, is

also shown. This demonstrates that, in most cases, the

levels of detected residues are a small fraction of the

tolerances for the listed pesticide/commodity pairs.
Pesticide Data Program - Annual Summary Calendar Year 1995

12

been prohibited in the United States since 1972.

 Post-Harvest Applications However, due to the persistence of this chemical in the

Before PDP began collecting data, most available

information on pesticide use in the United States was

limited to pesticides applied to sustain agricultural

production (pre-harvest applications). Little was known

about pesticides applied to preserve the fruit and

vegetable products after harvest (post-harvest

applications). PDP’s database has since become one of

the most comprehensive sources of post-harvest pesticide

use patterns because samples are collected at points

where such uses have already taken place. Most postharvest applications are confined to fungicides (to control

mold and fungus) and growth regulators (to prevent

sprouting). PDP compounds with mostly post-harvest

applications are the fungicides diphenylamine, ophenylphenol, thiabendazole, and the growth regulator

chlorpropham. Other compounds with post-harvest uses

on selected commodities are the fungicides dicloran

(carrots and peaches) and imazalil (citrus).

Consequently, residues from these pesticides can be

assumed to result from post-harvest applications. To

illustrate the impact of post-harvest uses, detections

including and excluding residues of these compounds are

listed in Tables 3A and 3B, respectively. Significant

differences in the number of residue detections as a result

of post-harvest uses are in apples, bananas, oranges,

potatoes, and, to a lesser extent, peaches. As these tables

indicate, the 5 fungicides listed above, along with

chlorpropham, accounted for 2,870 detections (29

percent of the number of residue detections in fruit and

vegetables). The pesticide most frequently found in fruit

and potatoes (1,146 detections) was the fungicide

thiabendazole, representing about 11 percent of all

detections. Wheat data presented in Appendix G

indicates that the most frequently pesticides found were

chlorpyrifos, chlorpyrifos methyl, and malathion. These

three pesticides have pre- and post-harvest uses in wheat.

These three pesticides account for 868 (96 percent) of the

904 residue detections in the 600 wheat samples tested.

Malathion, the most prevalently detected residue, was

found in 71 percent of the wheat samples tested. 

 Environmental Contaminants

DDT, DDD, and DDE

A total of 6,873 fruit and vegetable samples were

screened for DDE metabolite of DDT. Use of DDT has

environment, residues of the DDE metabolite were

detected in 10 percent of all samples tested. In some

samples, the parent DDT and the DDD metabolite were

also reported. Residues were found primarily in soil

crops, carrots (37.6 percent), potatoes (15.0 percent), 
Pesticide Data Program - Annual Summary Calendar Year 1995

13

Table 3A. Number of Samples and Residues Detected 

(Includes Post-Harvest Applications)

Total Samples % of Samples Different Total

Samples with Residues with Pesticides Residues Residue

Analyzed Detected Detected Detected Detections

Fresh Fruits and Vegetables:

 Apples 695 657 95 30 2,097

 Bananas 486 300 62 3 325

 Carrots 703 498 71 29 1,005

 Grapes 694 552 80 31 1,331

 Green Beans 587 332 57 28 696

 Oranges 700 589 84 17 1,086

 Peaches 377 347 92 31 1,076

 Potatoes 707 588 83 18 987

 Spinach 634 526 83 34 1,254

Processed Vegetables:

 Sweet Corn 671 3 0 2 3

 Sweet Peas 670 106 16 9 155

Number of Samples Analyzed = 6,924

Number of Samples with Pesticides Detected = 4,498

Percent with Pesticide Detections = 65.0%

Total Number of Residue Detections = 10,015

Total Number of Different Residues = 69

Grain:*

 Wheat 600 475 79 10 904

* Includes pre- and post-harvest uses for chlorpyrifos, chlorpyrifos methyl and malathion
Pesticide Data Program - Annual Summary Calendar Year 1995

14

Table 3B. Number of Samples and Residues Detected 

(Excludes Post-harvest Applications)*

Total Samples % of Samples Different Total

Samples with Residues with Pesticides Residues Residue

Analyzed Detected Detected Detected Detections

Fresh Fruits and Vegetables:

 Apples 695 556 80 27 1,215

 Bananas 486 73 15 1 73

 Carrots 703 498 71 26 997

 Grapes 694 552 80 28 1,328

 Green Beans 587 325 55 27 677

 Oranges 700 167 24 14 197

 Peaches 377 344 91 26 914

 Potatoes 707 225 32 14 343

 Spinach 634 526 83 34 1,253

Processed Vegetables:

 Sweet Corn 671 1 0 1 1

 Sweet Peas 670 98 15 8 147

Number of Samples Analyzed = 6,924

Number of Samples with Pesticides Detected = 3,365

Percent with Pesticide Detections = 48.6%

Total Number of Residue Detections = 7,145

Total Number of Different Residues = 65

* Chlorpropham, Dicloran (carrots and peaches), Diphenylamine, Imazalil (citrus), o-Phenylphenol, 

and Thiabendazole
Pesticide Data Program - Annual Summary Calendar Year 1995

15

and spinach 49.2 percent). No findings were above the Appendices E and G (Part II) show the number of nonallowable levels established by FDA. DDE was not in detected residues by pesticide/commodity pair. There

the testing profile for wheat. were other pesticide/commodity pairs with non-detected

 Single/Selective Residue Analyses they did not meet the criteria given above (i.e.,

2,4-D

A total of 722 samples were tested for 2,4-D.

Commodities tested were peaches, peas, potatoes, and

sweet corn. No 2,4-D residues were detected. 

ABAMECTIN

A total of 688 samples of oranges were tested for

abamectin. No residues were detected in any of the

samples tested.

BENOMYL

A total of 3,575 samples of carrots, grapes, oranges, Multiple Residues Detections

peaches, spinach, and sweet corn were tested for

benomyl, as the carbendazim metabolite. Carbendazim The PDP database provides information that can be used

residues were detected in 0.5 percent of the samples by EPA in evaluating the incidence of multiple residues.

tested. These residues found in carrots, grapes, and These mutiple residues may derive from various sources,

peaches were at levels below the established tolerances. such as applications of more than one pesticide on a crop

FENBUTATIN OXIDE (HEXAKIS) persistent environmental residues. The multiple residue

A total of 1,187 samples of apples, grapes, oranges, and 1993 National Research Council report, Pesticides in

peaches were tested for Fenbutatin Oxide, and 2 of its the Diets of Infants and Children, which recommended

metabolites. Fenbutatin Oxide residues were found in that coordinated recording of multiple residue scans

6.5 percent of the samples tested. None were above would make possible more accurate evaluation of

EPA established tolerances. exposure distributions for multiple chemicals.

FORMETANATE The distribution of multiple residues in PDP’s database

A total of 1,019 samples of apples, oranges, and peaches individual or multiple residues depends on the actual

were tested for formetanate. Approximately 5 percent of levels of the residues detected. PDP’s 1995 data

the samples were found to contain residues of this indicate that the total pesticide level in a sample is

compound, all at levels below the established tolerance. independent of the number of residues detected.

 Non-Detected Residues number of residues and presumptive tolerance

Approximately 35 percent of the samples analyzed had

no detectable levels of pesticide residues. If post-harvest Presumptive Tolerance Violations 

applications of pesticides are excluded, the percentage

becomes approximately 51. Non-detected residues could

happen because a pesticide was not applied, because it

dissipates rapidly, or for various other reasons. 

residues which were not included in Appendix E because

established tolerances or EPA requested) or because they

were analyzed by fewer than five of PDP laboratories. 

Three pesticides, abamectin, fenamiphos, and terbufos,

in the PDP fruit and vegetable testing system, Table 1-

Part IA, were not detected in any of the samples tested.

Abamectin undergoes rapid photolysis and degradation

by soil microorganisms. Fenamiphos dissipates fairly

quickly and likely was not present at detectable levels at

the time samples were collected. Terbufos is not widely

used in either of the two commodities for which it is

registered. In Appendix G-Part II , 13 of the 23

pesticides referenced in Table 1-Part II for the wheat

testing profile were not detected. 

during a growing season, possible spray drift, or

information is particularly useful in responding to the

is included as Appendix F. Any exposure assessment of

Furthermore, there is no relationship between the

violations. 

Tolerances are defined under Section 408 of the Federal

Food, Drug, and Cosmetic Act as the maximum quantity

of a pesticide residue allowable on a raw agricultural
Pesticide Data Program - Annual Summary Calendar Year 1995

16

commodity. Tolerances are established by EPA for Synopsis

pesticides used on food crops. A violation occurs when

a residue is found which exceeds the tolerance level or

when a residue is found for which there is no tolerance

for that particular crop. With the exception of meat,

poultry, and egg products, for which USDA is

responsible, tolerances for all other foods are enforced

by FDA. When agencies with regulatory enforcement

authority collect samples for tolerance enforcement

purposes, they must adhere to a quick turnaround time

and chain of custody protocols which allow them to

detain the sampled lot until results are available. 

PDP is not an enforcement program. Consequently,

sample analysis does not have to be completed quickly

(emphasis is placed on searching for residues at the

lowest detectable levels--not on quick turnaround time)

and sample collection does not interfere with commodity

distribution. Therefore, when samples are reported to

have residues, for which there is no tolerance established

or which exceed the tolerance, they are designated as

“presumptive tolerance violations” and reported as such

to FDA regional and headquarters offices. This is done

in accordance with a Memorandum of Understanding

between USDA and FDA for the purpose of pinpointing

areas where closer surveillance may be needed. FDA

enforcement action on PDP samples generally is not a

viable option due to the time lag from sample collection

to data reporting. Presumptive tolerance violations for

1995 data are indicated in Appendix C and are discussed

on the cover page.

In 1995, a total of 6,873 fruit and vegetable (plus 51

samples for SRM analysis) and 600 wheat samples were

analyzed using MRMs. Analysis using SRMs was

performed in certain commodities only. Accordingly,

688 samples were tested for abamectin; 722 were tested

for 2,4-D; 3,575 were tested for benomyl; 1,187 for

fenbutatin oxide; and 1,019 for formetanate. Pesticides

detected included insecticides, herbicides, fungicides,

and growth regulators. Also detected were DDT and its

metabolites, although their presence is almost certainly

due to environmental contamination, not the result of

prohibited crop application. 

Approximately 83 percent of samples tested were

domestic, and 16.5 percent were imported (0.5 percent

were of unknown origin). Of all fruit and vegetable

samples tested, 263 (3.8 percent) were reported as

presumptive tolerance violations, although most of these

were for residues where no tolerance was established.

There were no reported wheat sample violations. For

fruit and vegetables, 65 percent of the samples contained

at least one residue, whereas 79 percent of the 600 wheat

samples contained at least one residue. It was also

observed that, for certain commodities, post-harvest

applications contribute significantly to the number of

residues detected. Overall, levels of residues detected

were below tolerances.

For more information on the Pesticide Data Program,

contact William J. Franks, Jr., Director, AMS Science

and Technology Division, at (202) 720-5231; or Robert

L. Epstein, Deputy Director, at (202) 720-2158. You

may also reach them by facsimile at (202) 720-6496.

gggggg

May 1997

The United States Department of Agriculture (USDA) prohibits discrimination in its programs on the basis of race, color, national

origin, sex, religion, age, disability, political beliefs, and marital or familial status. (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 the USDA Office of Communications at (202) 720-2791.

To file a complaint, write the Secretary of Agriculture, U.S. Department of Agriculture, Washington, DC 20250, or call 

800-245-6340 (voice) or (202) 720-1127 (TDD). USDA is an equal employment opportunity employer.
Appendix A

Sample Origin by Grower, Packer, or Distributor

Appendix A gives the number of samples per State or country of origin and the

number of samples of unknown origin. Where available, origin of fresh commodities is

determined by grower or packer information. For processed commodities, origin is

determined primarily by packer or distributor.

As shown in Appendix A, samples collected and analyzed during 1995 originated

from 39 States and 17 foreign countries.
APPENDIX A. SAMPLE ORIGIN BY GROWER, PACKER, OR DISTRIBUTOR

(Number of Samples per State/Country)

No. of % of 

Part1. AP BN CR CS GB GR OG PC PO PS SP Domestic Total

States = 39 Domestic Samples

Alabama 1 1 <0.1

Arizona 18 2 5 3 4 3 5 40 0.7

California 63 445 176 137 369 563 165 124 196 402 2640 45.9

Colorado 4 28 2 4 1 1 2 36 3 22 103 1.2

Delaware 10 10 0.2

Florida 21 25 159 101 1 33 23 16 379 6.6

Georgia 1 10 38 1 11 7 1 69 1.2

Idaho 13 1 26 1 148 30 219 3.8

Illinois 49 2 3 45 1 100 1.7

Indiana 2 1 3 0.1

Kentucky 1 1 <0.1

Louisiana 1 2 3 0.1

Maine 2 3 8 2 1 16 0.3

Maryland 2 1 1 3 7 0.1

Massachusetts 2 3 2 4 11 0.2

Michigan 52 80 23 11 4 1 3 36 23 38 271 4.7

Minnesota 77 17 65 159 2.8

Missouri 1 1 <0.1

Montana 6 6 0.1

Nebraska 3 3 0.1

Nevada 1 5 6 0.1

New Hampshire 2 2 <0.1

New Jersey 1 1 2 8 14 2 4 13 45 0.8

New York 61 5 40 12 2 2 55 33 15 225 3.9

North Carolina 7 1 9 37 1 1 3 11 5 75 1.3

North Dakota 6 6 0.1

Ohio 11 7 22 15 9 13 77 1.3

Oklahoma 22 24 46 0.8

Oregon 11 4 31 2 41 32 3 124 2.2

Pennsylvania 8 16 1 5 1 12 10 53 0.9

South Carolina 3 7 29 7 2 48 0.8

Tennessee 19 25 18 1 63 1.1

Texas 4 13 42 12 15 3 31 50 43 213 3.7

Utah 1 3 4 8 0.1

Vermont 2 1 1 4 0.1

Virginia 4 6 3 7 10 30 0.5

Washington 407 23 11 6 1 13 90 12 8 571 9.9

West Virginia 1 2 1 4 0.1

Wisconsin 45 18 44 107 1.9

No. of Domestics 661 0 648 651 483 382 689 256 702 660 617 5749 --

% of Total (nearest %) 95 0 92 97 82 55 98 68 99 99 97 83.0

Page 1 of 2
No. of % of 

Part 2. AP BN CR CS GB GR OG PC PO PS SP Import Total

Countries = 17 Imported Samples

Argentina 3 3 0.3

Australia 2 7 9 0.8

Brazil 2 2 0.2

Canada 8 35 16 4 5 7 75 6.6

Chile 4 257 118 379 33.2

Colombia 54 54 4.7

Costa Rica 125 125 10.9

Equador 153 153 13.4

Guatemala 46 46 4.0

Honduras 47 47 4.1

Israel 1 1 <0.1

Mexico 16 19 80 46 2 14 177 15.5

New Zealand 13 1 14 1.2

Nicaragua 6 6 0.5

Panama 21 21 1.8

Peru 1 1 <0.1

South Africa 5 5 10 0.9

Unknown Country 1 18 1 20 1.7

No. of Import 34 486 54 18 84 312 10 119 5 7 14 1143

% of Total (nearest %) 5 100 8 3 14 45 1 32 1 1 2 16.5

No. of % of 

Part 3. AP BN CR CS GB GR OG PC PO PS SP Unknown Total

No. of Unknown Origin 1 2 20 1 2 3 3 32 --

% of Total (nearest %) 0 0 <1 <1 3 0 <1 <1 0 <1 <1 0.5

GRAND TOTALS = 695 486 703 671 587 694 700 377 707 670 634 6924

Commodities

AP = Apples

BN = Bananas

CR = Carrots

CS = Sweet Corn

GB = Green Beans

GR = Grapes

OG = Oranges

PC = Peaches

PO = Potatoes

PS = Sweet Peas

SP = Spinach

Page 2 of 2
Appendix B

Quality Assurance Program Elements

PDP’s Quality Assurance (QA) program covers all aspects of data gathering, from

sample collection to data reporting. QA protocols for sampling are designed to protect

sample integrity from the time of collection to the time of delivery to the testing facilities. 

QA protocols for testing comprise all laboratory operations from the time of sample

receipt to the time data are reported to PDP’s central database. As described in this

appendix, the QA program has five elements: 1) Standard Operating Procedures; 2)

On-site reviews; 3) Proficiency Check Samples; 4) Quality Control Procedures; and

5) Method Performance and Confirmation Procedures.
APPENDIX B. QUALITY ASSURANCE PROGRAM ELEMENTS

1. Standard Operating Procedures - Written SOPs are in place to provide uniform administrative, sampling, and

laboratory procedures. SOPs are revised annually to accommodate changes in the program. Before

submission, data are reviewed by each Quality Assurance Unit for completeness and adherence to PDP

requirements.

2. On-site Reviews - On-site reviews are performed to determine compliance with SOPs. Improvements in

sampling, chain of custody, recordkeeping, and laboratory procedures are made as a result of on-site reviews.

3. Proficiency Check Samples - All facilities are required to participate in PDP's Check Sample Program. 

Check samples are issued to laboratories performing analysis with multiresidue methods and/or single/selective

residue methods. Periodically, one to four prepared commodities, containing pesticide(s) of known quantities, are

sent to the participating laboratories and tested under the same conditions as routine samples. The resulting

data are used to determine performance equivalency among the testing laboratories, and to evaluate individual

laboratory performance. During 1995, PDP laboratories received 2 proficiency sample sets consisting of 6

samples for multiresidue screening, 6 sets for single/selective residue screening, and a wheat multiresidue set.

4. Quality Control Procedures - PDP operating procedures for quality control (QC) are intended to assess

method and analyst performance during sample preparation, clean-up, extraction, and, where applicable,

derivatization. To maximize sample output and decrease the QC/sample ratio, samples are analyzed in analytical

sets, which include the sample set and the following components.

a. Reagent Blank: An amount of distilled water, equivalent to the natural moisture content of the

commodity, is run through the entire analytical process to determine glassware cleanliness and system

integrity.

b. Matrix Blank: A previously analyzed sample of the same commodity, which contains either very low

concentrations of known residues or no detectable residues, is divided into two portions. The first portion

is used to give background information on naturally occurring chemicals, and the second one is used to

prepare a matrix spike.

c. Matrix Spike(s): Prior to extraction, a portion(s) of matrix blank is spiked with marker pesticides to

determine the accuracy of the analyst and instrument performance. Marker pesticides are compounds

selected from different pesticide classes (organochlorines, organophosphates, carbamates), which have

physical and chemical characteristics similar to those in the class they represent. The use of marker

pesticides to monitor recoveries is a modification of PDP’s previous requirements that called for spiking

with all pesticides. Because of the large number of pesticides in the program, spiking with all compounds

required several spike mixtures (to avert coelution problems), which, in turn, resulted in lengthy run times. 

d. Process Control Spike: A compound of physical and chemical characteristics, similar to those of

the pesticides being tested, is used to evaluate the analytical process on a sample-by-sample basis. 

Each of the analytical set components, except the reagent and matrix blanks, is spiked with process

controls.

e. Storage Spikes: If a sample set is going to be frozen as a homogenate for more than 72 hours prior

to analysis, analysts are required to prepare storage spikes. Storage spikes provide information on

whether degradation has occurred while the sample was frozen, and are prepared in the same manner

as matrix spikes. However, they do not replace the requirement to run a fresh matrix spike at the time of

analysis.

5. Method Performance and Confirmation Procedures - Laboratories are required to determine the limits of

detection (LOD) and limits of quantitation (LOQ) for each commodity/pesticide pair. LODs depend on matrix,

analyte, and detector used, and range from 0.001 to 0.150 ppm. (Information on specific LODs and LOQs is

available upon request.) Confirmation by mass spectrometry, or a suitable alternate detection system, is required

for all initial determinations. If a detected residue does not have a tolerance, or it exceeds the established

tolerance, the sample is reanalyzed in duplicate from the frozen homogenate, along with the appropriate blanks

and a spike of the residue at the suspected level. 

Page 1 of 1
Appendix C

Distribution of Residues Detected by Pesticide

Appendix C shows residue detections for all pesticide/commodity pairs tested,

including minimum and maximum concentrations reported and whether a tolerance is

established for each pair. 

 In 1995, 6,924 samples were analyzed. A total of 263 samples (3.8 percent)

were reported as presumptive violations. Nine samples (0.13 percent) exceeded the

established EPA tolerance for the pesticide/commodity pair and 254 samples (3.7

percent) were reported for which no EPA tolerance was established. Domestic

commodities accounted for 231 samples (87.8 percent). Imported commodities

accounted for 26 samples (9.9 percent). Unknown origin commodities accounted for 6

samples (2.3 percent) of the presumptive violation samples.

Presumptive violations were reported for 316 residues, 9 residues (2.8 percent)

exceeded an established EPA tolerance and 307 residues (97.2 percent) were reported

for which there is no EPA tolerance. Approximately half of the reported presumptive

violations (163) were in spinach.

Pesticide residue established tolerances for pesticide/commodity pairs in PDP

span several orders of magnitude--from 0.05 ppm for chlorpyrifos/peaches, to 60.0 ppm

for iprodione/grapes. Of the 263 reported samples containing violations (316 individual

violations), 186 samples contained a single residue, 26 samples contained two

residues, 7 samples contained three residues, and 1 sample contained 4 residue

violations. 

In some cases, a tolerance may or may not apply, depending on whether certain

conditions are met. For example, residues of methamidophos in green beans are

covered by a tolerance only if residues of acephate are also present. Of the 112 green

bean samples found to contain residues of methamidophos, 108 were found in

combination with acephate. Only four samples had methamidophos residues where

acephate was not present and were reported as presumptive violations. 
APPENDIX C. DISTRIBUTION OF RESIDUES DETECTED

BY PESTICIDE

Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

1. Acephate

Carrots (V-3) 701 3 0.4 0.006 0.021 NT

Grapes (V-1) 690 1 0.1 0.006 0.006 NT

Green Beans 587 120 20.4 0.005 2.2 3

Spinach (V-29) 609 29 4.8 0.005 0.19 NT

Total 153

2. Aldicarb sulfoxide (metabolite)

Oranges 691 1 0.1 0.015 0.015 0.3

Total 1

3. Atrazine

Spinach (V-2) 610 2 0.3 0.030 0.030 NT

Total 2

4. Azinphos methyl

Apples 691 320 46.3 0.010 0.46 2.0

Grapes 690 3 0.4 0.010 0.17 5.0

Green Beans 587 4 0.7 0.010 0.051 2.0

Oranges 691 1 0.1 0.073 0.073 2.0

Peaches 367 102 27.8 0.010 0.24 2.0

Total 430

5. Benomyl (analyzed as carbendazim)

Carrots 700 3 0.4 0.084 0.084 0.2

Grapes 688 9 1.3 0.084 0.48 10.0

Peaches 371 6 1.6 0.084 1.1 15.0

Total 18

6. Captan

Apples 691 98 14.2 0.010 2.0 25

Carrots 555 3 0.5 0.010 0.020 2

Grapes 689 255 37.0 0.010 2.8 50

Green Beans 438 13 3.0 0.013 0.20 25

Peaches 367 60 16.3 0.010 1.5 50

Total 429

Page 1 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

7. Carbaryl

Apples 693 76 11.0 0.010 0.74 10

Grapes 690 19 2.8 0.011 0.38 10

Green Beans 586 18 3.1 0.011 1.6 10

Oranges 691 71 10.3 0.010 0.19 10

Peaches 367 54 14.7 0.10 4.8 10

Spinach 610 8 1.3 0.010 0.11 12

Sweet Peas 670 8 1.2 0.010 0.37 10

Total 254

8. Carbofuran (parent only)

Grapes 690 3 0.4 0.015 0.052 0.4

Total 3

Carbofuran (parent and metabolite)

Spinach (V-1) 610 1 0.2 0.17 0.17 NT

Total 1

3-Hydroxycarbofuran (without parent)

Grapes (X-3) 690 5 0.7 0.021 0.42 0.2

Total 5

9. Chlorothalonil

Green Beans 587 84 14.3 0.010 1.1 5

Peaches 353 1 0.3 0.065 0.065 0.5

Spinach (V-7) 597 7 1.2 0.009 0.052 NT

Total 92

10. Chlorpropham

Grapes (V-1) 689 1 0.1 0.027 0.027 NT

Green Beans 587 19 3.2 0.029 0.21 5

Peaches (V-1) 367 1 0.3 0.013 0.013 NT

Potatoes 707 482 68.2 0.013 11 50

Total 503

11. Chlorpyrifos

Apples 692 153 22.1 0.005 0.42 1.5

Carrots (V-6) 701 6 0.9 0.005 0.019 NT

Grapes (V-9) 690 56 8.1 0.005 0.16 0.5 R

Oranges 691 50 7.2 0.005 0.019 1.0

Peaches 367 60 16.3 0.005 0.034 0.05

Spinach (V-46) 610 46 7.5 0.005 0.11 NT

Total 371

12. Cypermethrin

Spinach (V-2) 288 2 0.7 0.11 0.49 NT

 Total 2

Page 2 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

13. Dacthal (DCPA)

Green Beans 584 29 5.0 0.003 0.12 2

Spinach (V-30) 610 30 4.9 0.003 0.10 NT

Total 59

14. DDT (parent)

Carrots 265 21 7.9 0.010 0.026 3 #

Grapes 348 1 0.3 0.010 0.010 0.5 #

Green Beans 228 1 0.4 0.010 0.010 0.2 #

Potatoes 393 41 10.4 0.010 0.013 1 #

Spinach 517 86 16.6 0.005 0.11 0.5 #

Total 150

DDD (metabolite)

Carrots 266 3 1.1 0.002 0.006 3 #

Spinach 516 8 1.6 0.002 0.020 0.5 #

Total 11

DDE (metabolite)

Carrots 701 263 37.6 0.004 0.21 3 #

Grapes 690 11 1.6 0.004 0.012 0.5 #

Green Beans 587 8 1.4 0.004 0.023 0.2 #

Peaches 367 1 0.3 0.005 0.005 0.2 #

Potatoes 707 106 15.0 0.004 0.037 1 #

Spinach 610 300 49.2 0.004 0.54 0.5 #

Total 689

15. Demeton S Sulfone

Green Beans (V-4) 77 4 5.2 0.010 0.038 NT

Potatoes (V-3) 148 3 2.0 0.010 0.030 NT

Spinach (V-1) 70 1 1.4 0.010 0.010 NT

Total 8

16. Diazinon

Apples 693 7 1.0 0.005 0.020 0.5

Carrots 700 26 3.7 0.005 0.086 0.75

Grapes 690 7 1.0 0.005 0.037 0.75

Green Beans (X-1) 587 3 0.5 0.011 1.1 0.5

Peaches 367 23 6.3 0.005 0.16 0.7

Spinach 609 18 3.0 0.005 0.39 0.7

Sweet Peas 670 7 1.0 0.005 0.049 0.5

Total 91

Page 3 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

17. Dicloran

Apples (V-2) 693 2 0.3 0.005 0.005 NT

Carrots 701 3 0.4 0.010 0.45 10

Grapes 690 18 2.6 0.010 1.2 10

Green Beans 587 3 0.5 0.13 0.71 20

Peaches 367 156 42.5 0.005 12 20

Spinach (V-13) 610 13 2.1 0.005 0.02 NT

Total 195

18. Dicofol

Apples 692 7 1.0 0.008 0.48 5

Grapes 688 43 6.3 0.008 1.9 5

Green Beans 587 1 0.2 0.008 0.008 5

Oranges 691 1 0.1 0.008 0.008 10

Peaches 367 4 1.1 0.25 0.40 10

Total 56

19. Dieldrin

Spinach 133 2 1.5 0.005 0.020 0.05 #

 Total 2

20. Dimethoate (see omethoate)

Apples 693 26 3.8 0.004 0.43 2

Grapes 689 93 13.5 0.004 1.1 1

Green Beans 587 24 4.1 0.004 0.78 2

Oranges 691 3 0.4 0.004 0.005 2

Peaches (V-4) 367 4 1.1 0.004 0.35 NT

Spinach (X-1) 609 31 5.1 0.004 11 2

Sweet Peas 670 77 11.5 0.004 0.074 2

Total 258

21. Diphenylamine

Apples 691 489 70.8 0.013 5.1 10

Bananas (V-1) 479 1 0.2 0.15 0.15 NT

Grapes (V-1) 677 1 0.1 0.014 0.014 NT

Peaches (V-1) 285 1 0.4 0.017 0.017 NT

Potatoes (V-1) 692 1 0.1 0.057 0.057 NT

Total 493

 4-Hydroxydiphenylamine (metabolite)

Apples 5 5 100.0 0.28 0.52 10

Total 5

22. Disulfoton (parent)

Apples (V-1) 693 1 0.1 0.11 0.11 NT

Potatoes 707 1 0.1 0.005 0.005 0.75

Total 2

Page 4 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

23. Endosulfans

Apples 693 46 6.6 0.005 0.15 2.0

Carrots 701 25 3.6 0.005 0.024 0.2

Grapes 690 28 4.1 0.003 0.22 2.0

Green Beans 587 139 23.7 0.003 0.77 2.0

Oranges (V-14) 691 14 2.0 0.003 0.005 NT

Peaches 367 29 7.9 0.003 0.18 2.0

Potatoes 707 137 19.4 0.003 0.096 0.2

Spinach 610 87 14.3 0.003 1.8 2.0

Sweet Corn 671 1 0.1 0.003 0.003 0.2

Sweet Peas 670 2 0.3 0.008 0.009 2.0

Total 508

24. Esfenvalerate

Apples 551 2 0.4 0.036 0.036 2.0

Carrots 561 2 0.4 0.020 0.020 0.5

Green Beans 474 23 4.9 0.020 0.16 2.0

Peaches 202 4 2.0 0.020 0.090 10

 Total 31

Fenvalerate

Apples 693 1 0.1 0.17 0.17 2.0

Carrots 701 1 0.1 0.020 0.020 0.5

Grapes (V-1) 690 1 0.1 0.070 0.070 NT

Green Beans 587 1 0.2 0.020 0.020 2.0

Peaches 362 2 0.6 0.020 0.038 10.0

Spinach (V-1) 570 1 0.2 0.038 0.038 NT

 Total 7

25. Ethion

Oranges 691 5 0.7 0.002 0.002 2.0

Total 5

26. Fenbutatin Oxide

Apples 351 13 3.7 0.005 0.51 15.0

Grapes 324 42 13.0 0.005 1.5 5

Oranges 345 3 0.9 0.005 0.005 20.0

Peaches 167 20 12.0 0.005 0.41 10.0

Total 78

27. Formetanate Hydrochloride

Apples 330 5 1.5 0.085 0.085 3

Oranges 522 18 3.4 0.083 0.19 4

Peaches 167 26 15.6 0.085 0.43 5

Total 49

Page 5 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

28. Imazalil

Bananas (X-1) 486 73 15.0 0.015 0.25 0.20

Oranges 691 395 57.2 0.011 0.61 10

Total 468

29. Iprodione

Apples (V-6) 693 6 0.9 0.014 0.025 NT

Carrots 701 173 24.7 0.014 0.13 5.0

Grapes 689 267 38.8 0.014 1.8 60.0

Green Beans 587 9 1.5 0.025 1.4 2.0

Peaches 367 256 69.8 0.025 13 20.0

Total 711

30. Lambda Cyhalothrin and Isomer

Spinach (V-1) 1 1 100.0 0.17 0.17 NT

Total 1

31. Lindane

Carrots 701 1 0.1 0.005 0.005 0.5

Green Beans 587 1 0.2 0.005 0.005 0.5

Spinach 610 2 0.3 0.006 0.023 1

Total 4

32. Linuron

Carrots 257 159 61.9 0.005 0.36 1

Spinach (V-1) 79 1 1.3 0.051 0.051 NT

Total 160

33. Malathion

Carrots 678 1 0.1 0.017 0.017 8

Oranges 691 2 0.3 0.005 0.013 8

Peaches 367 2 0.5 0.005 0.005 8

Spinach 610 4 0.7 0.005 0.028 8

Total 9

34. Metalaxyl

Carrots 18 7 38.9 0.005 0.024 0.5

Green Beans 19 6 31.6 0.005 0.005 0.2

Potatoes 44 6 13.6 0.005 0.020 0.5

Spinach 22 4 18.2 0.005 0.016 10.0

Total 23

Page 6 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

35. Methamidophos

Carrots (V-1) 701 1 0.1 0.004 0.004 NT

Grapes (V-1) 690 1 0.1 0.004 0.004 NT

Green Beans @ (V-4) 587 112 19.1 0.004 0.40 NT

Potatoes 707 14 2.0 0.004 0.038 0.1

Spinach (V-14) 609 14 2.3 0.004 0.034 NT

Total 142

36. Methidathion

Green Beans (V-1) 587 1 0.2 0.04 0.04 NT

Oranges 691 21 3.0 0.004 0.031 2.0

Total 22

37. Methomyl

Apples 693 24 3.5 0.012 0.13 1

Grapes 689 48 7.0 0.012 1.3 5

Green Beans 587 23 3.9 0.012 0.30 2

Peaches 367 3 0.8 0.026 0.10 5

Spinach 610 65 10.7 0.012 1.3 6

Total 163

38. Methoxychlor

Apples 693 110 15.9 0.010 0.70 14

Peaches 367 2 0.5 0.29 0.55 14

Sweet Peas 670 2 0.3 0.032 0.13 14

Total 114

39. Mevinphos

Grapes 690 5 0.7 0.003 0.044 0.5

Spinach 609 16 2.6 0.003 0.14 1.0

Total 21

40. Myclobutanil

Apples 678 8 1.2 0.014 0.033 0.5

Carrots (V-1) 701 1 0.1 0.014 0.014 NT

Grapes 689 172 25.0 0.014 0.44 1.0

Peaches 367 3 0.8 0.025 0.10 2.0

Total 184

41. Omethoate (see Dimethoate)

Apples 461 19 4.1 0.005 0.050 2

Grapes 530 92 17.4 0.005 0.37 1

Green Beans 379 13 3.4 0.005 0.077 2

Oranges 625 5 0.8 0.005 0.025 2

Peaches (V-2) 321 2 0.6 0.025 0.032 NT

Spinach 515 89 17.3 0.005 0.28 2

Sweet Peas 584 41 7.0 0.005 0.019 2

Total 261

Page 7 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

42. Oxamyl

Apples 693 29 4.2 0.015 0.088 2

Green Beans (V-1) 587 1 0.2 0.025 0.025 NT

Total 30

43. Parathion

Carrots 582 11 1.9 0.003 0.019 1

Grapes 662 5 0.8 0.003 0.010 1

Sweet Peas 670 1 0.1 0.003 0.003 1

Total 17

44. Parathion methyl

Apples 693 33 4.8 0.004 0.22 1

Carrots 701 2 0.3 0.005 0.010 1

Grapes 690 2 0.3 0.052 0.091 1

Peaches 367 104 28.3 0.004 0.45 1

Sweet Peas 670 9 1.3 0.004 0.005 1

Total 150

45. Permethrins

Apples (X-2) 693 3 0.4 0.016 0.14 0.05

Green Beans (V-5) 587 5 0.9 0.016 0.23 NT

Peaches 367 9 2.5 0.016 0.28 5.0

Spinach 610 372 61.0 0.016 18 20.0

Total 389

46. o-Phenylphenol

Apples 507 44 8.7 0.013 0.84 25

Carrots 563 4 0.7 0.017 0.017 20

Oranges 520 81 15.6 0.016 0.45 10

Peaches 245 3 1.2 0.015 0.062 20

Potatoes (V-31) 661 31 4.7 0.025 0.57 NT **

Spinach (V-1) 385 1 0.3 0.052 0.052 NT

Sweet Corn (V-2) 612 2 0.3 0.015 0.025 NT

Sweet Peas (V-8) 601 8 1.3 0.017 0.025 NT

Total 174

47. Phorate (parent)

Phorate Oxygen Analog sulfone (metabolite)

Potatoes 63 4 6.3 0.005 0.005 0.5

Total 4

Phorate sulfone (metabolite)

Potatoes 315 14 4.4 0.004 0.055 0.5

Total 14

Page 8 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

Phorate sulfoxide (metabolite)

Potatoes 315 5 1.6 0.006 0.19 0.5

Total 5

48. Phosalone

Apples 421 3 0.7 0.10 0.22 10.0

Total 3

49. Phosmet

Apples 591 24 4.1 0.017 0.20 10

Carrots (V-3) 582 3 0.5 0.010 0.029 NT

Grapes 662 5 0.8 0.010 0.026 10

Peaches 321 59 18.4 0.010 1.1 10

Total 91

50. Phosphamidon

Apples 693 15 2.2 0.003 0.13 1

Potatoes 707 1 0.1 0.003 0.003 0.1

Total 16

51. Piperonyl Butoxide

Spinach (V-1) 1 1 100 3.6 3.6 NT

Total 1

52. Propargite

Apples 660 179 27.1 0.013 2.2 3

Grapes 689 33 4.8 0.014 1.5 10

Oranges 666 2 0.3 0.22 0.94 5

Peaches 367 73 19.9 0.033 1.2 7

Total 287

53. Quintozene (PCNB parent, or parent and metabolites)

Carrots (V-5) 701 5 0.7 0.005 0.022 NT

Green Beans 587 16 2.7 0.005 0.012 0.1

Potatoes 707 4 0.6 0.005 0.037 0.1

 Total 25

Hexachlorobenzene (HCB, impurity without parent)

Carrots (V-1) 701 1 0.14 0.011 0.015 NT

Total 1

Pentachloroaniline (PCA, metabolite without parent)

Spinach (V-10) 133 10 7.5 0.005 0.013 NT

Total 10

Page 9 of 10
Number No. of % of Minimum Maximum

of Samples Samples with Samples with Value Value Tolerance

Pesticide Screened Detections Detections Detected, ppm Detected, ppm Level, ppm

Pentachlorobenzene (PCB, metabolite without parent)

Carrots (V-1) 701 1 0.14 0.003 0.003 NT

Potatoes (V-1) 707 5 0.7 0.003 0.015 NT

Total 6

54. Tecnazine

Potatoes 105 2 1.9 0.015 0.045 * 25

Total 2

55. Terbufos Sulfone

Carrots (V-1) 327 1 0.3 0.004 0.004 NT

Total 1

56. Thiabendazole

Apples 664 349 52.6 0.013 5.7 10

Bananas (X-1) 486 251 51.6 0.013 0.46 0.4 *** 

Carrots 693 1 0.1 0.050 0.050 10

Grapes 690 1 0.1 0.050 0.050 10.0

Oranges 683 413 60.5 0.010 1.4 10

Peaches (V-1) 367 1 0.3 0.050 0.050 NT

Potatoes 707 130 18.4 0.019 2.0 10.0

Total 1146

57. Trifluralin

Carrots 701 274 39.1 0.013 0.79 1.0

Total 274

58. Vinclozolin

Grapes 690 103 14.9 0.010 1.1 6.0

Green Beans (V-15) 472 15 3.2 0.036 0.26 NT

Peaches 367 5 1.4 0.007 0.062 25.0

Spinach (V-2) 610 2 0.3 0.039 0.044 NT

Total 125

 Total No. of Different Residues Detected: 69

 Total No. of Samples Analyzed: 6924

 Total No. of Residues Detected: 10015

KEY

(V) Residue was found where no tolerance was established by EPA. Following V are the number of occurrences.

(X) Residue was found which exceeds EPA tolerance. Following X are the number of occurrences.

NT No tolerance level was set for that pesticide / commodity pair.

@ All other residues were detected in combination with acephate, for which a tolerance exists.

R Regional tolerance.

# Number shown are Action Levels established by FDA.

* Tolerance changed 09/27/95 to NT.

** May be subject to Food Additive Tolerance due to packaging materials.

*** Tolerance applies to banana pulp only.

Page 10 of 10
Appendix D

National Estimates for Concentration Percentiles vs. Tolerance

Appendix D shows 52 pesticide/commodity pairs with detections in at least 10

percent of the samples tested. Concentrations detected are arranged in percentiles. 

The 90th percentile is compared to the tolerance established for each

pesticide/commodity pair.

The meaning of a percentile can be most easily explained through an example. 

For the bananas-thiabendazole pair, the 50th percentile is estimated to be 0.014 ppm. 

This means that PDP estimates that at least 50 percent of bananas available to U.S.

consumers had thiabendazole residues of 0.014 ppm or less, while at least 50 percent

had residues of 0.014 ppm or more. Similarly, the 75th percentile (or the upper

quartile) for this pair is estimated to be 0.088 ppm, which means that at least 75

percent of bananas had residues of 0.088 ppm or less, while at least 25 percent had

residues of 0.088 ppm or more. Finally, the 90th percentile (or the last decile) is

estimated to be 0.124 ppm, meaning that at least 90 percent of all bananas had

thiabendazole residues of 0.124 ppm or less, while at least 10 percent had residues of

0.124 ppm or more.

When calculating the national estimates, PDP sampling data were weighted to

more accurately reflect U.S. wholesale arrivals. This weighting had a surprising effect

on the pair carbaryl / oranges (see page 1 of this appendix), for which detectable

residues were found in 10.3 percent of the samples. When the sampling data were

weighted to reflect U.S. arrivals (oranges are slightly more plentiful in winter months

then at other times of the year), less than 9 percent of the total product available for

consumption in 1995 was estimated to have detectable residues. Thus, the 90th

percentile of carbaryl in oranges resulted in no value, even though more than 10

percent of the orange samples had detectable levels of carbaryl.
APPENDIX D. NATIONAL ESTIMATES FOR

CONCENTRATION PERCENTILES vs. TOLERANCE

(Pairs with Residue Detections in at Least 10 Percent of Samples)

% of Ratio of

Samples with Mean** Percentiles 90th Percentile

Commodity / Pesticide Detections Lower Upper 50th 75th 90th to Tolerance

1. Apples

Azinphos-Methyl 46.3 0.035 0.058 * 0.058 0.11 0.055

Captan 14.2 0.016 0.027 * * 0.022 0.001

Carbaryl 11.0 0.018 0.048 * * 0.015 0.002

Chlorpyrifos 22.1 0.006 0.011 * * 0.017 0.011

Diphenylamine 70.8 0.554 0.562 0.20 0.94 1.5 0.150

Methoxychlor 15.9 0.022 0.036 * * 0.064 0.005

Propargite 27.1 0.124 0.161 * 0.12 0.45 0.150

Thiabendazole 52.6 0.464 0.503 0.075 0.61 1.5 0.150

2. Bananas

Imazalil 15.0 0.011 0.039 * * 0.035 0.175

Thiabendazole 51.6 0.049 0.063 0.014 0.088 0.124 0.309

3. Carrots

DDE 37.6 0.012 0.016 * 0.017 0.038 0.013

Iprodione 24.7 0.012 0.037 * * 0.050 0.010

Linuron (a) 61.9 0.032 0.035 0.012 0.042 0.080 0.080

Trifluralin 39.1 0.024 0.042 * 0.042 0.075 0.075

4. Grapes

Captan 37.0 0.039 0.047 * 0.015 0.094 0.002

Dimethoate 13.5 0.008 0.012 * * 0.006 0.006

Fenbutatin Oxide (b) 13.0 0.022 0.025 * * 0.010 0.002

Iprodione 38.8 0.077 0.094 * 0.050 0.25 0.004

Myclobutanil 25.0 0.020 0.037 * 0.021 0.063 0.063

Omethoate 17.4 0.007 0.013 * * 0.015 0.015

Vinclozolin 14.9 0.017 0.026 * * 0.015 0.003

5. Green Beans

Acephate 20.4 0.052 0.056 * * 0.18 0.060

Chlorothalonil 14.3 0.014 0.026 * * 0.023 0.005

Endosulfans 23.7 0.026 0.031 * * 0.064 0.032

Methamidophos 19.1 0.020 0.025 * * 0.083 0.083

6. Oranges

Carbaryl 10.3 0.004 0.020 * * *** ***

Imazalil 57.2 0.068 0.093 0.034 0.099 0.18 0.018

o-Phenylphenol 15.6 0.008 0.026 * * 0.026 0.003

Thiabendazole 60.5 0.124 0.146 0.060 0.18 0.36 0.036

Page 1 of 2
% of Ratio of

Samples with Mean** Percentiles 90th Percentile

Commodity / Pesticide Detections Lower Upper 50th 75th 90th to Tolerance

7. Peaches

Azinphos-methyl 27.8 0.011 0.030 * * 0.045 0.023

Captan 16.3 0.042 0.050 * * 0.061 0.001

Carbaryl 14.7 0.089 0.105 * * 0.25 0.025

Chlorpyrifos 16.3 0.001 0.007 * * 0.004 0.070

Dicloran 42.5 0.517 0.520 0.01 0.34 1.3 0.065

Fenbutatin Oxide (b) 12.0 0.006 0.009 * * 0.006 0.001

Formetanate HCI (b) 15.6 0.028 0.072 * * 0.13 0.026

Iprodione 69.8 0.816 0.824 0.21 0.65 1.7 0.085

Parathion-methyl 28.3 0.025 0.030 * 0.033 0.069 0.069

Phosmet 18.4 0.037 0.051 * * 0.075 0.008

Propargite 19.9 0.104 0.159 * * 0.41 0.059

8. Potatoes

Chlorpropham 68.2 1.129 1.133 0.12 1.7 3.5 0.070

DDE 15.0 0.001 0.007 * * 0.006 0.006

DDT (c) 10.4 0.001 0.008 * * 0.007 0.007

Endosulfans 19.4 0.003 0.008 * * 0.010 0.048

Thiabendazole 18.4 0.078 0.123 * * 0.25 0.025

9. Spinach

DDE 49.2 0.011 0.014 * 0.014 0.030 0.060

DDT (c) 16.6 0.003 0.008 * * 0.015 0.030

Endosulfans 14.3 0.015 0.019 * * 0.010 0.005

Methomyl 10.7 0.019 0.040 * * 0.014 0.002

Omethoate 17.3 0.010 0.029 * * 0.027 0.014

Permethrins 61.0 1.501 1.506 0.23 1.84 5.2 0.260

10. Sweet Peas

Dimethoate 11.5 0.003 0.008 * * 0.010 0.005

(a) Tested in only three States.

(b) In PDP for 6 months.

(c) Not reported in Ohio and inconsistent reporting in some other States.

* The percentile value is estimated to be below the Limit of Detection (LOD).

** The mean is estimated with a range of values. The lower bound is calculated with non-detections valued

at zero. The upper bound is calculated using the LOD.

*** No estimated value.

Page 2 of 2
Appendix E

Number of Non-Detected Residues by Pesticide/Commodity Pairs

(Pairs with established tolerances and pairs requested by EPA)

Appendix E gives the number of samples per commodity for which no pesticide

residues were detected (non-detected) by the participating laboratories. Only

pesticides with registered uses (i.e., established tolerances) and pesticides specifically

requested by EPA are included. The appendix also shows the range of limits of

detection for each pesticide.

The laboratories reported other non-detected residues which are not shown in

this appendix but are available upon request. These include pesticides not expected to

be present (i.e., not registered for use in PDP commodities). These data resulted from

the laboratories’ need to simplify spiking requirements for pesticides analyzed by

multiresidue screens. For example, chlorpropham was tested in all samples although it

is registered for use in only four PDP commodities--carrots, green beans, potatoes, and

sweet peas. The number of non-detected residues for carrots and sweet peas is given

in this appendix. Residues of chlorpropham were detected in green beans and

potatoes; therefore, this information is shown in Appendix C. 
APPENDIX E. NUMBER OF NON-DETECTED RESIDUES

BY PESTICIDE/COMMODITY PAIRS

(Pairs with established tolerances and pairs requested by EPA)

No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

1. 1-Naphthol

Bananas 98 0.055 - 0.055 10

Carrots 140 0.055 - 0.055 10

Grapes 143 0.055 - 0.055 10

Green Beans 113 0.055 - 0.055 10

Potatoes 138 0.055 - 0.055 0.2

Sweet Corn 140 0.055 - 0.055 5

Sweet Peas 69 0.055 - 0.055 10

2. 2,4-D (5)

Peaches 133 0.006 - 0.010 0.2

Sweet Corn 304 0.006 - 0.016 0.5

Sweet Peas 285 0.006 - 0.010 1.0 (1)

3. Abamectin

Oranges 688 0.002 NT

4. Acephate (5)

Apples 693 0.003 - 0.030 NT

Bananas 486 0.003 - 0.010 NT

Oranges 691 0.003 - 0.030 NT

Peaches 367 0.003 - 0.025 NT

Potatoes 707 0.003 - 0.005 NT

Sweet Corn 671 0.003 - 0.005 NT

Sweet Peas 670 0.003 - 0.025 NT

5. Aldicarb & Metabolites

Apples 499 0.007 - 0.040 NT

Bananas 486 0.007 - 0.040 NT

Carrots 509 0.007 - 0.040 NT

Grapes 519 0.007 - 0.040 NT

Green Beans 420 0.007 - 0.040 NT

Oranges 675 0.007 - 0.036 0.3

Peaches 367 0.007 - 0.040 NT

Potatoes 531 0.007 - 0.015 1

Spinach 599 0.007 - 0.040 NT

Sweet Corn 629 0.007 - 0.020 NT

Sweet Peas 540 0.007 - 0.036 NT

Page 1 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

6. Anilazine

Apples 142 0.035 - 0.037 NT

Oranges 142 0.035 - 0.037 NT

Peaches 76 0.035 - 0.037 NT

Spinach 133 0.035 - 0.037 NT

Sweet Peas 69 0.035 - 0.037 NT

7. Atrazine

Apples 693 0.018 - 0.030 NT

Bananas 486 0.003 - 0.028 NT

Carrots 701 0.018 - 0.030 NT

Grapes 690 0.018 - 0.028 NT

Green Beans 587 0.018 - 0.030 NT

Oranges 691 0.003 - 0.030 NT

Peaches 367 0.003 - 0.020 NT

Potatoes 707 0.018 - 0.028 NT

Sweet Corn 671 0.003 - 0.028 0.25

Sweet Peas 670 0.003 - 0.028 NT

8. Azinphos Ethyl

Apples 188 0.020 - 0.025 2

Bananas 121 0.020 - 0.020 NT

Carrots 194 0.020 - 0.025 NT

Grapes 195 0.020 - 0.020 5

Green Beans 172 0.020 - 0.025 2

Oranges 199 0.020 - 0.025 2

Peaches 99 0.020 - 0.020 2

Potatoes 216 0.020 - 0.020 0.3

Spinach 176 0.020 - 0.025 2

Sweet Corn 186 0.020 - 0.020 NT

Sweet Peas 186 0.020 - 0.020 NT

9. Azinphos Methyl

Bananas 486 0.006 - 0.030 NT

Carrots 701 0.006 - 0.130 NT

Potatoes 707 0.006 - 0.029 0.3

Spinach 610 0.006 - 0.130 2

Sweet Corn 671 0.006 - 0.030 NT

Sweet Peas 670 0.006 - 0.033 NT

10. Benfluralin

Carrots 161 0.010 - 0.010 NT

Page 2 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

11. Benomyl

Oranges 525 0.050 10

Spinach 623 0.050 0.2

Sweet Corn 668 0.050 0.2

12. Captan

Bananas 377 0.006 - 0.017 NT

Oranges 691 0.006 - 0.040 NT

Potatoes 569 0.006 - 0.012 25 (2)

Spinach 596 0.006 - 0.029 100

Sweet Corn 531 0.006 - 0.012 2

Sweet Peas 601 0.006 - 0.060 2

13. Carbaryl

Bananas 486 0.006 - 0.036 10

Carrots 701 0.006 - 0.076 10

Potatoes 707 0.006 - 0.076 0.2

Sweet Corn 671 0.006 - 0.076 5

14. Carbofuran & Carbofuran-3 OH

Apples 693 0.009 - 0.076 NT

Bananas 486 0.009 - 0.031 0.1

Carrots 701 0.009 - 0.076 NT

Green Beans 587 0.009 - 0.076 NT

Oranges 691 0.009 - 0.049 2.5

Peaches 367 0.009 - 0.049 NT

Potatoes 707 0.009 - 0.076 1

Sweet Corn 671 0.009 - 0.076 0.2

Sweet Peas 670 0.009 - 0.076 NT

15. Chlorothalonil

Apples 679 0.005 - 0.045 NT

Bananas 374 0.003 - 0.008 0.05

Carrots 548 0.006 - 0.045 1

Grapes 530 0.006 - 0.008 NT

Oranges 691 0.003 - 0.045 NT

Potatoes 551 0.006 - 0.008 0.1

Sweet Corn 516 0.006 - 0.008 1

Sweet Peas 586 0.006 - 0.008 NT

Page 3 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

16. Chlorpropham

Apples 693 0.008 - 0.047 NT

Bananas 486 0.008 - 0.020 NT

Carrots 701 0.008 - 0.036 0.1

Oranges 691 0.008 - 0.047 NT

Spinach 610 0.008 - 0.300 0.3 (2)

Sweet Corn 671 0.008 - 0.020 NT

Sweet Peas 670 0.008 - 0.047 0.3 (2)

17. Chlorpyrifos (5)

Bananas 486 0.003 - 0.020 0.01

Green Beans 587 0.003 - 0.020 0.1

Potatoes 707 0.003 - 0.011 NT

Sweet Corn 671 0.003 - 0.011 0.1

Sweet Peas 670 0.003 - 0.011 0.1

18. Cypermethrin

Apples 265 0.045 - 0.060 NT

Bananas 153 0.003 - 0.060 NT

Carrots 104 0.060 - 0.060 NT

Grapes 153 0.060 - 0.060 NT

Green Beans 82 0.060 - 0.060 NT

Oranges 390 0.020 - 0.060 NT

Peaches 191 0.020 - 0.060 NT

Potatoes 177 0.060 - 0.060 NT

Sweet Corn 288 0.020 - 0.060 NT

Sweet Peas 243 0.045 - 0.060 NT

19. DCPA (Dacthal)

Apples 693 0.002 - 0.068 NT

Bananas 486 0.002 - 0.010 NT

Carrots 701 0.002 - 0.068 NT

Grapes 690 0.002 - 0.008 NT

Oranges 691 0.002 - 0.068 NT

Peaches 367 0.002 - 0.010 NT

Potatoes 707 0.002 - 0.008 2

Sweet Corn 671 0.002 - 0.008 0.05

Sweet Peas 670 0.002 - 0.008 NT

20. DDE (DDT metabolite)

Apples 693 0.002 - 0.012 0.1 (3)

Bananas 486 0.002 - 0.008 NT

Oranges 691 0.002 - 0.012 0.1 (3)

Sweet Corn 671 0.002 - 0.008 0.1 (3)

Sweet Peas 670 0.002 - 0.008 0.2 (3)

Page 4 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

21. DDVP (Dichlorvos) (4)

Apples 693 0.002 - 0.017 0.5

Bananas 486 0.002 - 0.013 0.5

Carrots 701 0.002 - 0.017 0.5

Grapes 690 0.002 - 0.004 0.5

Green Beans 587 0.002 - 0.017 0.5

Oranges 691 0.002 - 0.020 3

Peaches 367 0.002 - 0.014 0.5

Potatoes 707 0.002 - 0.004 0.5

Spinach 609 0.002 - 0.017 3

Sweet Corn 671 0.002 - 0.013 0.5

Sweet Peas 670 0.002 - 0.014 0.5

22. Demeton

Apples 142 0.028 - 0.029 NT

Oranges 142 0.028 - 0.029 NT

Peaches 76 0.028 - 0.029 NT

Spinach 133 0.028 - 0.029 NT

Sweet Peas 69 0.028 - 0.029 NT

23. Demeton S & Metabolites

Apples 93 0.006 - 0.060 NT

Bananas 58 0.006 - 0.060 NT

Carrots 87 0.006 - 0.060 NT

Grapes 125 0.006 - 0.060 NT

Oranges 129 0.006 - 0.060 NT

Peaches 51 0.006 - 0.060 NT

Sweet Corn 145 0.006 - 0.060 NT

Sweet Peas 144 0.006 - 0.060 NT

24. Diazinon (5)

Bananas 486 0.003 - 0.022 0.1

Oranges 691 0.003 - 0.023 0.7

Potatoes 707 0.003 - 0.007 0.1

Sweet Corn 671 0.003 - 0.007 0.7

25. Dichlorobenzophenone, p p

Apples 123 0.002 - 0.002 5

Bananas 74 0.002 - 0.002 NT

Carrots 104 0.002 - 0.002 NT

Grapes 153 0.002 - 0.002 5

Green Beans 82 0.002 - 0.002 5

Oranges 159 0.002 - 0.002 10

Peaches 57 0.002 - 0.002 10

Potatoes 177 0.002 - 0.002 NT

Spinach 78 0.002 - 0.002 NT

Sweet Corn 175 0.002 - 0.002 NT

Sweet Peas 174 0.002 - 0.002 NT

Page 5 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

26. Dicloran

Bananas 486 0.006 - 0.019 NT

Oranges 691 0.003 - 0.060 NT

Potatoes 707 0.006 - 0.010 0.25

Sweet Corn 671 0.006 - 0.010 NT

Sweet Peas 670 0.003 - 0.010 NT

27. Dicofols

Bananas 486 0.005 - 0.020 NT

Carrots 701 0.005 - 0.050 NT

Potatoes 707 0.005 - 0.020 NT

Spinach 610 0.005 - 0.050 NT

Sweet Corn 671 0.005 - 0.020 NT

Sweet Peas 670 0.005 - 0.025 NT

28. Dieldrin

Apples 142 0.003 - 0.003 NT

Oranges 142 0.003 - 0.003 0.02 (3)

Peaches 76 0.003 - 0.003 0.02 (3)

Sweet Peas 69 0.003 - 0.003 0.02 (3)

29. Dimethoate (6)

Bananas 486 0.002 - 0.012 NT

Carrots 701 0.002 - 0.032 NT

Potatoes 707 0.002 - 0.007 0.2

Sweet Corn 671 0.002 - 0.011 NT

30. Diphenylamine (DPA)

Carrots 701 0.008 - 0.110 NT

Green Beans 587 0.008 - 0.110 NT

Oranges 549 0.010 - 0.110 NT

Spinach 477 0.010 - 0.300 NT

Sweet Corn 671 0.008 - 0.015 NT

Sweet Peas 601 0.008 - 0.015 NT

31. Disulfoton

Bananas 486 0.003 - 0.016 NT

Carrots 701 0.003 - 0.065 0.3

Grapes 690 0.003 - 0.016 NT

Green Beans 587 0.003 - 0.065 0.75

Oranges 691 0.002 - 0.065 NT

Peaches 367 0.003 - 0.036 NT

Spinach 609 0.003 - 0.065 0.75

Sweet Corn 671 0.003 - 0.013 0.3

Sweet Peas 670 0.003 - 0.036 0.75

Page 6 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

32. Diuron

Apples 123 0.010 - 0.030 1

Bananas 74 0.010 - 0.030 0.1

Carrots 104 0.010 - 0.030 NT

Grapes 153 0.010 - 0.030 1

Green Beans 82 0.010 - 0.030 NT

Oranges 159 0.010 - 0.030 1

Peaches 57 0.010 - 0.030 0.1

Potatoes 177 0.010 - 0.030 1

Spinach 78 0.010 - 0.030 NT

Sweet Corn 175 0.010 - 0.030 1

Sweet Peas 174 0.010 - 0.030 1

33. Endosulfans

Bananas 486 0.002 - 0.006 NT

34. Esfenvalerate & Fenvalerate (5)

Bananas 241 0.012 - 0.140 NT

Grapes 547 0.012 - 0.085 NT

Oranges 388 0.012 - 0.310 NT

Potatoes 569 0.012 - 0.050 0.02

Spinach 289 0.012 - 0.310 NT

Sweet Corn 403 0.012 - 0.050 0.1

Sweet Peas 490 0.012 - 0.050 1

35. Ethion

Apples 693 0.001 - 0.032 2

Bananas 486 0.001 - 0.006 NT

Carrots 701 0.001 - 0.032 NT

Grapes 690 0.001 - 0.006 2

Green Beans 587 0.001 - 0.032 2

Peaches 367 0.001 - 0.008 1

Potatoes 707 0.001 - 0.004 NT

Spinach 610 0.001 - 0.032 NT

Sweet Corn 671 0.001 - 0.006 NT

Sweet Peas 670 0.001 - 0.008 NT

36. Ethoprop

Apples 142 0.029 - 0.030 NT

Oranges 142 0.029 - 0.030 NT

Peaches 76 0.029 - 0.030 NT

Spinach 133 0.029 - 0.030 NT

Sweet Peas 69 0.029 - 0.030 NT

Page 7 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

37. Fenamiphos & Metabolites

Apples 693 0.002 - 0.049 0.25

Bananas 483 0.002 - 0.013 0.1

Carrots 701 0.002 - 0.049 NT

Grapes 690 0.002 - 0.009 0.1

Green Beans 587 0.002 - 0.049 NT

Oranges 691 0.002 - 0.049 0.6

Peaches 367 0.002 - 0.013 0.25

Potatoes 707 0.002 - 0.008 NT

Spinach 610 0.002 - 0.049 NT

Sweet Corn 671 0.002 - 0.013 NT

Sweet Peas 670 0.002 - 0.013 NT

38. HCB (Hexachlorobenzene) (7)

Apples 693 0.002 - 0.006 NT

Bananas 486 0.002 - 0.006 0.1

Grapes 690 0.002 - 0.004 NT

Green Beans 587 0.002 - 0.006 0.1

Oranges 691 0.002 - 0.006 NT

Peaches 367 0.002 - 0.006 NT

Potatoes 707 0.002 - 0.004 0.1

Spinach 610 0.002 - 0.006 NT

Sweet Corn 671 0.002 - 0.004 NT

Sweet Peas 670 0.002 - 0.004 NT

39. Imazalil

Apples 678 0.009 - 0.150 NT

Carrots 620 0.009 - 0.150 NT

Grapes 690 0.009 - 0.044 NT

Green Beans 587 0.009 - 0.150 NT

Peaches 367 0.009 - 0.055 NT

Potatoes 707 0.009 - 0.044 NT

Spinach 610 0.009 - 0.150 NT

Sweet Corn 671 0.009 - 0.044 NT (8)

Sweet Peas 670 0.009 - 0.055 NT

40. Iprodione

Bananas 486 0.015 - 0.060 NT

Oranges 691 0.015 - 0.100 NT

Potatoes 707 0.008 - 0.060 0.5

Spinach 610 0.015 - 0.100 NT

Sweet Corn 671 0.008 - 0.060 NT

Sweet Peas 653 0.008 - 0.060 NT

Page 8 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

41. Lindane

Apples 693 0.003 - 0.006 1

Bananas 486 0.003 - 0.005 NT

Grapes 690 0.003 - 0.006 1

Oranges 691 0.003 - 0.006 0.5 (3)

Peaches 367 0.003 - 0.005 1

Potatoes 707 0.003 - 0.006 0.5 (3)

Sweet Corn 671 0.003 - 0.006 0.5 (3)

Sweet Peas 670 0.003 - 0.006 0.5 (3)

42. Linuron

Apples 123 0.003 - 0.003 NT

Bananas 74 0.003 - 0.003 NT

Grapes 153 0.003 - 0.003 NT

Green Beans 82 0.003 - 0.003 NT

Oranges 159 0.003 - 0.003 NT

Peaches 57 0.003 - 0.003 NT

Potatoes 177 0.003 - 0.003 1

Sweet Corn 175 0.003 - 0.003 0.25

Sweet Peas 174 0.003 - 0.003 NT

43. Malathion

Apples 693 0.002 - 0.049 8

Bananas 477 0.002 - 0.038 NT

Grapes 690 0.002 - 0.038 8

Green Beans 587 0.002 - 0.049 8

Potatoes 707 0.002 - 0.010 8

Sweet Corn 671 0.002 - 0.013 2

Sweet Peas 670 0.002 - 0.045 8

44. Metalaxyl

Apples 18 0.003 - 0.003 0.2

Grapes 16 0.003 - 0.003 2

Oranges 18 0.003 - 0.003 1

Peaches 1 0.003 - 0.003 1

Sweet Corn 15 0.003 - 0.003 NT

Sweet Peas 15 0.003 - 0.003 NT

45. Methamidophos (5)

Apples 693 0.002 - 0.030 NT

Bananas 486 0.002 - 0.012 NT

Oranges 691 0.002 - 0.030 NT

Peaches 367 0.002 - 0.019 NT

Sweet Corn 671 0.002 - 0.005 NT

Sweet Peas 670 0.002 - 0.019 NT

Page 9 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

46. Methidathion

Apples 693 0.002 - 0.050 0.05

Bananas 486 0.002 - 0.013 NT

Carrots 701 0.002 - 0.050 NT

Grapes 690 0.002 - 0.010 NT

Peaches 367 0.002 - 0.016 0.05

Potatoes 707 0.002 - 0.010 0.2

Spinach 610 0.002 - 0.050 NT

Sweet Corn 671 0.002 - 0.013 NT

Sweet Peas 670 0.002 - 0.016 NT

47. Methiocarb

Apples 298 0.015 - 0.064 NT

Bananas 268 0.013 - 0.020 NT

Carrots 162 0.015 - 0.016 NT

Grapes 195 0.015 - 0.016 NT

Green Beans 146 0.015 - 0.016 NT

Oranges 466 0.015 - 0.064 0.02

Peaches 264 0.013 - 0.064 15

Potatoes 216 0.015 - 0.016 NT

Spinach 438 0.013 - 0.064 NT

Sweet Corn 314 0.013 - 0.020 0.03

Sweet Peas 297 0.015 - 0.064 NT

48. Methomyl

Bananas 486 0.007 - 0.060 NT

Carrots 701 0.007 - 0.076 0.2

Oranges 691 0.007 - 0.056 2

Potatoes 707 0.007 - 0.076 0.2

Sweet Corn 671 0.007 - 0.076 0.1

Sweet Peas 670 0.007 - 0.076 5

49. Methoxychlor & Metabolites

Bananas 486 0.006 - 0.028 NT

Carrots 701 0.006 - 0.031 14

Grapes 690 0.006 - 0.026 14

Green Beans 587 0.006 - 0.031 14

Oranges 691 0.006 - 0.031 NT

Potatoes 707 0.006 - 0.026 1

Spinach 610 0.006 - 0.031 14

Sweet Corn 671 0.006 - 0.026 14

Page 10 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

50. Mevinphos

Apples 693 0.002 - 0.096 0.5

Bananas 486 0.002 - 0.019 NT

Carrots 701 0.002 - 0.021 0.25

Green Beans 587 0.002 - 0.021 0.25

Oranges 691 0.002 - 0.096 0.2

Peaches 367 0.002 - 0.096 1

Potatoes 707 0.002 - 0.019 0.25

Sweet Corn 671 0.002 - 0.019 0.25

Sweet Peas 670 0.002 - 0.096 0.25

51. Myclobutanil

Bananas 486 0.010 - 0.059 NT

Green Beans 587 0.008 - 0.120 NT

Oranges 691 0.010 - 0.120 NT

Potatoes 707 0.008 - 0.059 NT

Spinach 610 0.010 - 0.300 NT

Sweet Corn 671 0.008 - 0.046 NT

Sweet Peas 670 0.008 - 0.059 NT

52. o-Phenylphenol (5)

Bananas 396 0.010 - 0.065 NT

Grapes 614 0.008 - 0.065 NT

Green Beans 474 0.008 - 0.066 NT

53. Oxamyl

Bananas 486 0.009 - 0.043 0.3

Carrots 701 0.009 - 0.076 0.1

Grapes 690 0.009 - 0.076 NT

Oranges 691 0.009 - 0.048 3

Peaches 367 0.009 - 0.048 NT

Potatoes 707 0.009 - 0.076 0.1

Spinach 610 0.009 - 0.048 NT

Sweet Corn 671 0.009 - 0.076 NT

Sweet Peas 670 0.009 - 0.076 NT

54. PCB (Pentachlorobenzene) (7)

Apples 693 0.002 - 0.006 NT

Bananas 486 0.002 - 0.004 NT

Grapes 690 0.002 - 0.004 NT

Green Beans 587 0.002 - 0.006 0.1

Oranges 691 0.002 - 0.006 NT

Peaches 367 0.002 - 0.004 NT

Spinach 610 0.002 - 0.006 NT

Sweet Corn 671 0.002 - 0.004 NT

Sweet Peas 670 0.002 - 0.004 NT

Page 11 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

55. PCNB (Quintozene) (9)

Apples 693 0.003 - 0.006 NT

Bananas 486 0.003 - 0.007 NT

Grapes 690 0.003 - 0.006 NT

Oranges 691 0.003 - 0.006 NT

Peaches 367 0.003 - 0.007 NT

Spinach 610 0.003 - 0.007 NT

Sweet Corn 671 0.003 - 0.006 NT

Sweet Peas 670 0.003 - 0.006 NT

56. Parathion Ethyl

Apples 591 0.002 - 0.013 1

Bananas 440 0.002 - 0.005 NT

Green Beans 485 0.002 - 0.006 1

Oranges 625 0.002 - 0.015 1

Peaches 321 0.002 - 0.013 1

Potatoes 707 0.002 - 0.006 0.1

Spinach 516 0.002 - 0.013 1

Sweet Corn 671 0.002 - 0.006 1

57. Parathion Methyl

Bananas 486 0.002 - 0.013 NT

Green Beans 587 0.002 - 0.034 1

Oranges 691 0.002 - 0.034 1

Potatoes 707 0.002 - 0.006 0.1

Spinach 609 0.002 - 0.034 1

Sweet Corn 671 0.002 - 0.013 1

58. Pentachloroaniline

Apples 142 0.003 - 0.003 NT

Oranges 142 0.003 - 0.003 NT

Peaches 76 0.003 - 0.003 NT

Sweet Peas 69 0.003 - 0.003 NT

59. Permethrins

Bananas 486 0.005 - 0.040 NT

Carrots 701 0.005 - 0.100 NT

Grapes 690 0.005 - 0.040 NT

Oranges 691 0.005 - 0.120 NT

Potatoes 707 0.005 - 0.040 0.05

Sweet Corn 671 0.005 - 0.040 0.1

Sweet Peas 670 0.005 - 0.040 NT

Page 12 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

60. Phorate & Metabolites

Apples 693 0.002 - 0.130 NT

Bananas 486 0.002 - 0.110 NT

Carrots 701 0.002 - 0.110 NT

Grapes 690 0.002 - 0.110 NT

Green Beans 587 0.002 - 0.110 0.1

Oranges 619 0.002 - 0.130 NT

Peaches 362 0.002 - 0.130 NT

Spinach 610 0.002 - 0.130 NT

Sweet Corn 671 0.002 - 0.110 0.1

Sweet Peas 670 0.002 - 0.130 NT

61. Phosalone

Bananas 241 0.006 - 0.020 NT

Carrots 266 0.006 - 0.020 NT

Grapes 348 0.006 - 0.020 10

Green Beans 228 0.006 - 0.020 NT

Oranges 553 0.006 - 0.064 3

Peaches 290 0.006 - 0.064 15

Potatoes 393 0.006 - 0.020 0.1

Spinach 432 0.006 - 0.064 NT

Sweet Corn 461 0.006 - 0.020 NT

Sweet Peas 429 0.006 - 0.064 NT

62. Phosmet

Bananas 440 0.006 - 0.030 NT

Green Beans 485 0.006 - 0.024 NT

Oranges 625 0.006 - 0.030 5

Potatoes 707 0.006 - 0.024 0.1

Spinach 516 0.006 - 0.030 NT

Sweet Corn 671 0.006 - 0.030 0.5

Sweet Peas 670 0.006 - 0.030 0.5

63. Phosphamidon

Bananas 486 0.002 - 0.093 NT

Carrots 701 0.002 - 0.093 NT

Grapes 690 0.002 - 0.093 NT

Green Beans 587 0.002 - 0.093 NT

Oranges 619 0.002 - 0.080 0.75

Peaches 362 0.002 - 0.080 NT

Spinach 610 0.002 - 0.080 NT

Sweet Corn 671 0.002 - 0.093 NT

Sweet Peas 670 0.002 - 0.093 NT

Page 13 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

64. Propargite

Bananas 486 0.020 - 0.180 NT

Carrots 688 0.008 - 0.200 NT

Green Beans 572 0.008 - 0.200 20

Potatoes 707 0.008 - 0.087 0.1

Spinach 599 0.020 - 0.310 NT

Sweet Corn 671 0.020 - 0.150 0.1 (10)

Sweet Peas 670 0.008 - 0.150 NT

65. Tecnazine

Apples 62 0.010 - 0.010 NT

Bananas 33 0.010 - 0.010 NT

Carrots 69 0.010 - 0.010 10

Grapes 84 0.010 - 0.010 10

Green Beans 54 0.010 - 0.010 20

Oranges 86 0.010 - 0.010 NT

Peaches 34 0.010 - 0.010 20

Spinach 49 0.010 - 0.010 NT

Sweet Corn 112 0.010 - 0.010 NT

Sweet Peas 111 0.010 - 0.010 NT

66. Terbufos & Metabolites

Apples 693 0.002 - 0.071 NT

Bananas 486 0.002 - 0.025 0.025

Carrots 701 0.002 - 0.071 NT

Grapes 690 0.002 - 0.029 NT

Green Beans 587 0.002 - 0.035 NT

Oranges 633 0.002 - 0.071 NT

Peaches 367 0.002 - 0.030 NT

Potatoes 707 0.002 - 0.029 NT

Spinach 610 0.002 - 0.035 NT

Sweet Corn 671 0.002 - 0.029 0.05

Sweet Peas 670 0.002 - 0.030 NT

67. Thiabendazole

Green Beans 572 0.011 - 0.180 NT

Spinach 607 0.030 - 0.300 NT

Sweet Corn 671 0.011 - 0.180 NT

Sweet Peas 670 0.011 - 0.180 NT

Page 14 of 15
No. of Samples Range of LODs for Tolerance

Pesticide Analyzed Non-Detects, ppm Level, ppm

68. Trifluralin

Apples 693 0.003 - 0.090 NT

Bananas 388 0.003 - 0.030 NT

Grapes 547 0.008 - 0.030 0.05

Green Beans 474 0.008 - 0.090 0.05

Oranges 691 0.003 - 0.090 0.05

Peaches 367 0.003 - 0.030 0.05

Potatoes 569 0.008 - 0.025 0.05

Spinach 610 0.003 - 0.090 0.05

Sweet Corn 531 0.003 - 0.020 NT

Sweet Peas 601 0.003 - 0.020 0.05

69. Vinclozolin

Apples 693 0.005 - 0.023 NT

Bananas 388 0.004 - 0.012 NT

Carrots 561 0.006 - 0.023 NT

Oranges 691 0.004 - 0.023 NT

Potatoes 566 0.006 - 0.014 NT

Sweet Corn 531 0.006 - 0.014 NT

Sweet Peas 601 0.006 - 0.014 NT

(1) These are special tolerance applications of 2,4-D for western ditches and water hycinth control.

(2) This is an interim tolerance.

(3) Action Level's (AL) are established by FDA and are not considered to be the same as Tolerances. AL's are 

established based on the unavoidability of the pesticide and its persistence in the environment. PDP will treat

AL's as tolerances for FDA reporting purposes.

(4) Diclorvos is the breakdown product of Naled and is included in the Naled tolerance expression in 40CFR180.215.

Therefore, it is appropriate to use the Naled tolerances.

(5) The Food Additive (FA) tolerance has been recently interpreted by EPA (04/10/95) to be in effect if there is a

clear evidence of pesticide use in a warehouse. If such evidence is absent, then one must assume a violation

if there is no established 408 tolerance or the established tolerance is exceeded. Therefore, if the Sample

Information Form indicates that any of the pesticides listed below were applied at the Warehouse/Terminal

Market/Packing establishment, then see the corresponding CFR reference for applicable FA tolerances.

- 2,4-D (40 CFR 185.1450)

- Acephate / Methamidophos (40 CFR 185.100)

- Chlorpyrifos (40 CFR 185.1000)

- Diazinon (40 CFR 185.175)

- Esfenvalerate (40 CFR 185.1310)

- Fenvalerate (40 CFR 185.1300)

- o-Phenylphenol (40 CFR 176.210)

(6) Combined tolerance for dimethoate and/or omethoate, as per FDA revised policy.

(7) The tolerance for PCNB is used, but as a combined tolerance for PCNB. When PCB and or HCB are

detected, they are considered as part of the combined tolerance for PCNB.

(8) May have an active Section 18 Crisis exemption.

(9) This is a combined tolerance for PCNB and its metabolites PCA (pentachloroaniline) and MPCPS

(methyl pentachlorophenyl sulfide).

(10) Regional Tolerance -- California.

Page 15 of 15
Appendix F

Percentage of Samples vs. Number of Residues

 Detected per Sample

(Fresh and Processed Commodities)

Appendix F shows the percentage of samples per commodity containing 0 to 11

residues per sample. Shown at the bottom of the graph are the overall number of

samples and percentages (of the total number of samples analyzed) for each detection

group. For example, of the 6,924 samples tested, 35.0 had no detectable residues and

40.3 percent had more than one residue.
APPENDIX F. PERCENTAGE vs. MULTIPLE RESIDUES DETECTED

FOR FRUIT/VEGETABLE SAMPLES

35

30

25

20

15

10

5

0 1 2 3 4 5 6 7 8 9 10 11

Percent of Samples

35.0

24.6

18.2

11.9

5.6

3.0

1.2

0.2 0.2 .0004 .0001 .0001

Number of Residues Detected per Sample
Number of Residues Detected per Samples

0 1 2 3 4 5 6 7 8 9 10 11

Number of

Samples 2426 1706 1260 826 387 206 82 15 11 3 1 1

Percent of

Total Samples 35.0 24.6 18.2 11.9 5.6 3.0 1.2 0.2 0.2 .0004 .0001 .0001

TOTAL NUMBER OF SAMPLES = 6,924
Appendix G

Distribution of Pesticide Residues in Wheat

 Appendix G Part I shows residue detections for pesticides tested in wheat,

including minimum and maximum concentrations reported and whether a tolerance is

established by EPA for each pesticide/commodity pair. Part II references analyses for

which no pesticide residues were detected by GIPSA. Of the 600 samples run 13

pesticides were routinely analyzed but not detected in any of the tested samples. Part

II also shows the limit of detection for each pesticide.
APPENDIX G. DISTRIBUTION OF PESTICIDE RESIDUES IN WHEAT (600 Samples)

Part I. Detected Residues

Pesticide with Detections with Detections in ppm in ppm Tolerance

# of Samples % of Samples Value Detected Value Detected 

Minimum Maximum

Atrazine 4 0.7 0.004 0.004 0.25

Carbaryl 3 0.5 0.004 0.011 3.0

Chlorpyrifos 117 19.5 0.005 0.021 0.5

Chlorpyrifos methyl 325 54.2 0.002 3.3 6.0

Diazinon 18 3.0 0.007 0.028 0.05

Diclofop methyl 1 0.2 0.009 0.009 0.1

Imazalil 3 0.5 0.010 0.010 0.05

Malathion 426 71.0 0.002 2.9 8.0

Methoxychlor 6 1.0 0.013 0.13 2.0

Trifluralin 1 0.2 0.011 0.011 0.05 (N)

Part II. Non-Detected Residues

Pesticide Non-Detections in ppm in ppm

LODs for Tolerance Level

Azinphos Methyl 0.008 0.2

Carbofuran & 3-OH Carbofuran 0.005 0.1*

Demeton S 0.006 NT

Dichlorvos (DDVP)** 0.003 NT

Dimethoate 0.009 0.04

Disulfoton and sulfone 0.003 0.3

Endosulfans 0.010 0.1

Linuron 0.010 0.25

Methomyl 0.005 1

Parathion Ethyl 0.013 1

Parathion Methyl 0.006 1

Phorate & sulfone 0.003 0.05

Triallate 0.010 0.05

(*) Carbamate only

(**) Dichlorvos - 331 samples

NT No Tolerance established

N Neglible Tolerance
Appendix H

Commodity History

(A Chronological Listing)

 Appendix H shows a chronological listing of all commodities sampled since the

inception of the program to the date of publication for the 1995 Summary.
Page 1 of 1

APPENDIX H. Commodity History (A Chronological Listing)

Start Date End Date Commodity Type

May 91 Dec 96 Grapes Fresh

May 91 Dec 94 Lettuce Fresh

May 91 Dec 95 Potatoes Fresh

Aug 91 Dec 93 Grapefruit Fresh

Aug 91 Dec 96 Oranges Fresh

Sep 91 Dec 96 Apples Fresh

Sep 91 Sep 95 Bananas Fresh

Feb 92 Mar 94 Celery Fresh

Feb 92 Dec 95 Green Beans Fresh

Feb 92 Sep 96 Peaches Fresh

Oct 92 Dec 94 Broccoli Fresh

Oct 92 Sep 96 Carrots Fresh

Apr 94 Mar 96 Sweet Corn Canned/Frozen

Apr 94 Jun 96 Peas Canned/Frozen

Jan 95 Spinach Fresh

Feb 95 Wheat Grain

Jan 96 Milk Dairy

Jan 96 Green Beans Canned/Frozen

Jan 96 Sweet Potatoes Fresh

Jul 96 Tomatoes Fresh

Jul 96 Apple Juice Processed

Sep 96 Soy Beans Grain

Dec 96 Peaches Canned

Jan 97 Orange Juice Processed

Jan 97 Pears Fresh

Jan 97 Winter Squash Fresh
PESTICIDE DATA PROGRAM

 

 Annual Summary - Calendar Year 1995

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