United States 

Department of 

Agriculture 

Agricultural 

Marketing Service 

Science & 

Technology 

Programs 

Microbiological Data Program 

Progress Update and 2003 Data Summary 
January 2005 

To the Reader: 

I am pleased to present the USDA Microbiological Data Program 2003 Data 

Summary. In 2003, MDP continued testing the five commodities begun in 

2002. Cantaloupe, tomatoes, celery, leaf lettuce, and romaine lettuce were 

selected because they are high consumption fruit and vegetables in the United 

States. Sample collection was performed using a statistical framework. The 

laboratory methods used in the program were primarily traditional cultural 

techniques. However, in 2004 MDP initiated the use of new and innovative 

technologies for the identification of microorganisms. A description of these 

technologies is provided at the end of this publication. 

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

sample collection and analyses. Ten States participated in 2003: California, 

Colorado, Florida, Maryland, Michigan, New York, Ohio, Texas, Washington, 

and Wisconsin. Because these States together represent all regions of the 

country and more than half the Nation’s population, MDP data can be used to 

develop inferences about the national food supply. 

This summary is intended to provide the reader with an update on the 

methods, modifications, and refinements made during program development, 

as well as an overview of the data obtained during 2003. MDP data are 

important in developing baseline levels of targeted pathogens in the domestic 

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

to identify microbial trends and to develop risk models. 

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

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

http://www.ams.usda.gov/science/MPO/MDP.htm. 

Sincerely, 

A. J. Yates 

Administrator 

United States 

Department of 

Agriculture 

Marketing and 

Regulatory 

Programs 

Agricultural 

Marketing 

Service 

1400 Independence Ave. 

Washington, DC 

20250 

AMS-Agricultural Marketing Service 

An Equal Opportunity Provider and Employer 
Contents

Page No.

Participating Organizations........................................................................................................... iv 

Executive Summary ........................................................................................................................ vi

 

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

 

Section II. Sampling........................................................................................................................ 3 

 

Section III. Laboratory Operations.................................................................................................. 5 

 

Section IV. Database Management ................................................................................................. 6 

 

Section V. Summary of 2003 Data.................................................................................................. 8 

References ..................................................................................................................................... 12 

Disclaimer ..................................................................................................................................... 12 

Definitions..................................................................................................................................... 13 

 

Microbiological Data Program — Annual Summary, Calendar Year 2003 

ii 
Figures and Tables

Figures Page No. 

 1 Overview of MDP Management and Operations.......................................................... 2 

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

 3 Data Life Cycle ............................................................................................................. 7 

 

4 Commodity Origin ..................................................................................................... 10 

 

Tables

 1 Number of Samples Collected and Analyzed by State................................................ 9 

 

 2 Distribution of Imported Samples ............................................................................... 9 

 3 Summary of Analysis of Pathogenic E. coli by Virulence Attributes....................... 11 

 4 Summary of Sample Analysis for E. coli .................................................................. 12 

 5 Summary of Sample Analysis for Salmonella........................................................... 12 

Microbiological Data Program — Annual Summary, Calendar Year 2003 

iii 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

iv 

Data presented in this report were collected and 

processed through the efforts of the following 

organizations: 

State Agencies

California Department of Food and Agriculture 

California Department of Pesticide Regulation 

Colorado Department of Agriculture 

Florida Department of Agriculture and 

 Consumer Services 

Maryland Department of Agriculture 

Michigan Department of Agriculture 

New York Department of Agriculture and 

 Markets 

Ohio Department of Agriculture 

Texas Department of Agriculture 

Washington State Department of Agriculture 

Wisconsin Department of Agriculture, Trade, 

 and Consumer Protection 

Laboratories

California Department of Food and Agriculture 

Division of Inspection Services 

CDFA Agricultural Microbiology Laboratory 

McClellan Park (McClellan AFB), Bldg. 929 

5431 Arnold Ave. 

Sacramento, CA 95652 

 

Colorado Department of Agriculture 

Inspection & Consumer Services Division 

Laboratory Section 

2331 West 31st Ave. 

Denver, CO 80211-3859 

Florida Department of Agriculture and 

 Consumer Services 

Bureau of Food Laboratories, Bldg. 9 

3125 Conner Blvd. 

Tallahassee, FL 32399-1650 

Michigan Department of Agriculture 

Laboratory Division 

1615 South Harrison Rd. 

East Lansing, MI 48823-5224 

 

Minnesota Department of Agriculture 

Laboratory Services Division 

90 West Plato Blvd. 

St. Paul, MN 55107-2004 

New York Department of Agriculture and 

Markets 

Food Laboratory 

1220 Washington Ave. 

State Office Campus, Bldg. 7 

Albany, NY 12235 

Ohio Department of Agriculture 

Consumer Analytical Laboratory Bldg. 3 

8995 East Main St. 

Reynoldsburg, OH 43068 

U.S. Department of Agriculture 

Agricultural Marketing Service 

National Science Laboratory 

801 Summit Crossing Pl. 

Gastonia, NC 28054 

 

Washington State Department of Agriculture 

3939 Cleveland Ave., SE. 

Olympia, WA 98501 

Wisconsin Department of Agriculture, Trade, 

 and Consumer Protection 

Bureau of Laboratory Services 

4702 University Ave. 

Madison, WI 53705 

Participating Organizations 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

v 

Program Administration

U.S. Department of Agriculture 

Agricultural Marketing Service 

Science and Technology Programs 

1400 Independence Ave., SW. 

Mail Stop 0222 

Washington, DC 20250 

Deputy Administrator, Science and 

 Technology Programs: 

Robert L. Epstein 

(202) 720-5231 

Monitoring Programs Office 

8609 Sudley Rd., Ste. 206 

Manassas, VA 20110 

Director: Martha Lamont 

(703) 330-2300 x17, Facsimile (703) 369-0678 

E-mail: amsmpo.data@usda.gov 

Web site: http://www.ams.usda.gov/science/

MPO/MDP.htm
Microbiological Data Program — Annual Summary, Calendar Year 2003 

vi 

In 2001, the U.S. Department of Agriculture 

(USDA) Agricultural Marketing Service (AMS) 

was charged with implementing microbiological 

testing of fresh fruit and vegetables in the 

United States. The program’s mission is to provide statistically reliable information regarding 

targeted foodborne pathogens and indicator 

organisms on fresh fruit and vegetables. The 

Microbiological Data Program (MDP) is a voluntary data-gathering program, not a regulatory 

enforcement effort. 

AMS coordinates MDP planning and program 

requirements on a continual basis with the Centers for Disease Control and Prevention (CDC), 

the Food and Drug Administration (FDA), and 

the USDA National Agricultural Statistics 

Service. 

MDP collects produce samples from terminal 

markets and wholesale distribution centers on a 

year-round basis. The MDP sampling frame is 

designed to take into account population and 

consumption on a national scale. 

In 2003, 10 States collected fruit and vegetable 

samples (California, Colorado, Florida, Maryland, Michigan, New York, Ohio, Texas, Washington, and Wisconsin, with Minnesota joining 

the program in 2004). 

The program tested five commodities 

(cantaloupe, celery, leaf lettuce, romaine lettuce, and tomatoes) for Escherichia coli (E. 

coli) with pathogenic potential and Salmonella. 

MDP analyzed a total of 10,972 samples. 

Eighty-one percent of the samples were from 

domestic sources, 15 percent were imported, 

and 4 percent were of unspecified origin. MDP 

identified 44 E. coli isolates with virulence 

attributes. The presence of virulence attributes 

does not necessarily mean that these strains are 

pathogenic to humans, only that they may have 

pathogenic potential. MDP screening also 

resulted in three Salmonella isolates: one each 

from leaf lettuce, romaine lettuce, and tomato. 

A number of important benefits are expected 

from MDP. Microbiological data obtained from 

this fresh produce screening effort will 

contribute significantly to a national produce 

microbiological baseline. The data will enhance the understanding of the microbial 

ecology of fresh fruit and vegetables in the 

food supply and permit the identification of 

long-term trends. Such baseline data, combined 

with virulence attributes, serotypes, antimicrobial resistance, and genomic fingerprints will 

help collaborators such as CDC and FDA in 

planning public health initiatives. 

Executive Summary 
1 

I. Introduction 

In 2001, Congress authorized funding for a 

microbiological monitoring program to establish 

a microbial baseline for the domestic food 

supply. The Microbiological Data Program 

(MDP) was established as part of the broader 

1997 Presidential Food Safety Initiative. 

MDP’s mission is to collect data regarding the 

incidence and identification of targeted foodborne pathogens and indicator organisms on 

fresh fruit and vegetables. This publication 

summarizes progress made toward 

implementation of the program and provides an 

overview of data collected in 2003. The 

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

and is responsible for administrative, sampling, 

technical, and database activities. This publication is available on the Internet at http://

www.ams.usda.gov/science/MPO/MDP.htm. 

AMS coordinates its planning and program 

requirements with the Centers for Disease 

Control and Prevention (CDC) and the Food and 

Drug Administration (FDA). The USDA 

Agricultural Research Service (ARS) provides 

consultation as an independent research authority on laboratory methods. AMS and USDA’s 

National Agricultural Statistics Service (NASS) 

statisticians designed sampling plans based on 

per capita consumption, marketplace availability, product origin, and time in transit and 

storage. AMS used USDA consumption surveys 

to select commodities that are highly consumed 

in the United States and can be eaten raw: 

cantaloupe, celery, leaf lettuce, romaine lettuce, 

and tomatoes. Commodities were tested for 

Escherichia coli (E. coli) strains with pathogenic 

potential and Salmonella. Isolates of these 

organisms were sent to specialized laboratories 

for further characterization including serotyping, antibiotic resistance, and virulence 

attributes. 

Figure 1 provides an overview of MDP 

management and operations. Figure 2 highlights 

participating States and their geographical 

distribution areas. Samples were collected in the 

10 participating States through cooperative 

agreements with their respective agencies. Also 

shown are the 12 neighboring States that are in 

the direct distribution networks for the MDP 

collection States: Alaska, Connecticut, Delaware, Hawaii, Idaho, Massachusetts, Nevada, 

New Jersey, New Mexico, Vermont, Virginia, 

and Wyoming. Together these States represent 

over 50 percent of the Nation’s population and 

all regions of the country, with significant ruralto-urban variability. Therefore, MDP samples 

are a statistically defensible representation of 

the country as a whole. 

Microbiology laboratory services were provided 

by eight States (California, Colorado, Florida, 

Michigan, New York, Ohio, Washington, and 

Wisconsin) and the AMS National Science 

Laboratory. Laboratory operations are designed 

to minimize variability of results across 

laboratories through the use of uniform methodologies and a comprehensive quality assurance/

quality control (QA/QC) program. The data are 

submitted electronically via a Web-based 

Remote Data Entry (RDE) system and entered 

into a central database managed by MPO in 

Manassas, VA. 

MDP data can be used to establish baselines for 

the incidence of target organisms at the 

wholesale level, to understand trends, and to 

improve risk communication. 

Microbiological Data Program (MDP) 

Annual Summary, Calendar Year 2003 

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

Operations, (IV.) Database Management, (V.) Summary of 2003 Data 

Microbiological Data Program — Annual Summary, Calendar Year 2003 
2 

Microbiological Data Program — Annual Summary, Calendar Year 2003 

Figure 1. Overview of MDP Management and Operations

Main Objectives

• Collect information at wholesale level regarding the incidence, number, and species 

of important foodborne pathogens and indicator organisms on frequently consumed 

domestic and imported fresh fruit and vegetables 

• Establish a microbial baseline on the U.S. food supply 

• Provide data to CDC and FDA 

• Designed as a voluntary data gathering program, not a regulatory or enforcement 

effort 

• Data can be modeled to make national inferences 

Sample Collection

• Statistical sampling plan 

• Collected near consumer level 

• Represents about 50% of U.S. 

population 

• Country of origin retained 

• Reflects postharvest treatments 

Participating Laboratories

• AMS National Science Laboratory, Gastonia, NC 

• California Department of Food & Agriculture 

• Colorado Department of Agriculture 

• Florida Department of Agriculture & Consumer Services 

• Michigan Department of Agriculture 

• New York Department of Agriculture & Markets 

• Ohio Department of Agriculture 

• Washington State Department of Agriculture 

• Wisconsin Department of Agriculture, Trade and 

Consumer Protection 

• Minnesota Department of Agriculture 

• Pennsylvania State University, Gastroenteric Disease 

Center 

• University of Pennsylvania, The Salmonella Reference 

Center 

Laboratory Analysis

• QA based on EPA Good Laboratory 

Practices 

• Standard Operating Procedures 

• Implementing DNA-based 

technologies 

• Technical direction is derived from 

consultation with MDP Technical 

Advisory Group and Federal, State, 

and academic experts 

• Customized proficiency testing 

program 

Database Management

• Electronic transmission of data 

• Customized query capability 

• Standardized data summaries 

• MDP summary available on 

Internet 

• Implementing e-SIFs 

Participating States

• California 

• Colorado 

• Florida 

• Maryland 

• Michigan 

• New York 

• Ohio 

• Texas 

• Washington 

• Wisconsin 
3 

The information gathered from MDP can help 

identify technology development priorities and 

risk modeling needs for fresh produce in the 

food chain. The MDP data can also supplement 

the FDA/USDA “Guidance for Industry—

Guide to Minimize Microbial Food Safety 

Hazards for Fresh Fruits and Vegetables.” The 

“Guide,” developed in concert with industry, 

has fostered proactive leadership and broad 

adherence to good agricultural practices as well 

as a commitment to continually seeking practices based on the best available science that 

will minimize microbial contamination. 

USDA is a member of the interagency Task 

Force on Antimicrobial Resistance established 

in 1999 to seek better surveillance and education regarding optimal use of antimicrobials. 

Isolates from MDP samples testing positive for 

Salmonella or E. coli were sent to Pennsylvania 

State University (Penn State) for antimicrobial 

resistance testing. These data will be added to 

the National Antimicrobial Resistance 

Monitoring System database. 

As the program evolves, procedures and 

methods will be modified and refined to 

provide information necessary for making 

science-based food safety decisions. AMS 

continues to improve data collection systems 

and to use improved microbial detection 

methods that are quicker, more reliable, and 

more sensitive. AMS implemented DNA-based 

testing of samples in October 2003 following 

program-wide validation studies. 

II. Sampling 

The goal of the MDP sampling program is to 

obtain a statistical representation of selected 

commodities in the U.S. food supply by 

randomly selecting samples from the national 

food distribution system. The MDP sampling 

frame is designed to take into account regional 

diversity, population, and consumption on a 

national scale. The sampling rationale was 

developed in consultation with the FDA, CDC, 

and NASS (1). 

Microbiological Data Program — Annual Summary, Calendar Year 2003 

Figure 2. Participating States and their Geographical Distribution Areas 

Nevada 

Idaho 

Wyoming 

Mexico 

New 

Hawaii Alaska 

Virginia 

Delaware 

Maryland 

Connecticut 

Massachusetts 

Michigan Vermont 

Ohio New Jersey 

Florida 

Wisconsin 

New 

York 

Texas 

Colorado 

Washington 

California 

Participating States 

States where produce is directly 

marketed from participating States 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

4 

sampling reviews to ensure that program goals 

and objectives are met. All program SOPs are 

available on the Internet at http://www.ams.usda. 

gov/science/MPO/SOPs.htm. 

MDP uses Sample Information Forms (SIFs) to 

document information required for chain-ofcustody, which is captured in the MDP database 

files. Sample collectors use the forms to record 

information such as (1) the State of sample 

collection, (2) the collection date, (3) the commodity code, and (4) the testing laboratory code. 

Other information collected includes the country 

of origin of the sample, any production claims 

(such as organic), and any postharvest treatments. A customized software application allows 

States to capture SIFs electronically using laptop 

or hand-held computers. MDP samples are 

collected aseptically by trained collectors who 

safeguard sample integrity. Food samples are 

collected at terminal markets and large chain 

store distribution centers from which food 

commodities are released to supermarkets and 

grocery stores. If samples are not available at the 

designated site, an alternate site can be used. 

Sample collection at retail grocery stores, 

however, is not permitted because commodity 

handling practices at this level in the distribution 

chain may vary. 

State population figures are used to assign the 

number of samples scheduled for collection each 

month. These population-based numbers are as 

follows: California, 14; Colorado, 2; Florida, 7; 

Maryland, 4; Michigan, 6; New York, 9; Ohio, 

6; Texas, 8; Washington, 4; and Wisconsin, 2. 

This schedule results in a monthly target of 62 

samples per commodity. Each site sample 

collected consists of three individual units, 

which are treated as three distinct laboratory 

samples. Samples are collected and transported 

using aseptic techniques (i.e., sterile latex gloves 

and sample bags). Samples are measured for 

surface temperature at the time of collection and 

on receipt at the laboratory to characterize 

conditions during shipping. 

The sampling of commodities in commerce is 

conducted at wholesale markets and/or distribution centers on a year-round basis and over at 

least two growing seasons to accommodate 

differences in growing conditions. Sampling is 

apportioned according to population of the 

participating State. That is, the higher the 

population in the State, the greater the number 

of samples taken. Distribution centers and 

terminal markets in each State are selected at 

random based on probability proportional to the 

site’s distribution volume (i.e., the amount of 

produce that moves through the site). Therefore, 

the larger the site, the greater the chance it will 

be sampled. 

Collecting data over time from a range of 

sources permits statistical statements to be made 

about the distribution of targeted pathogens 

within the target population. The target population is all units of a commodity available at the 

wholesale level in a participating State during a 

defined time frame (e.g., one year). The 

extension of statistical statements to the distribution of microorganisms within the inferential 

population—the entire amount of the commodity actually consumed by the U.S. public 

during the same timeframe—requires strong 

assumptions be made about the relationship 

between the participating States and the United 

States as a whole, and between the wholesale 

and point-of-consumption levels. Nevertheless, 

because the States that participate in MDP fully 

represent the U.S. inferential population, and 

many microorganisms may enter the food 

supply at or before the wholesale level, the MDP 

is a useful and defensible baseline survey. 

MDP sampling is conducted with the use of 

Standard Operating Procedures (SOPs) designed 

to provide consistency across the program and 

ensure the integrity of the analytical data. SOPs 

also contain specific instructions for sample 

selection, shipping and handling, and chain-ofcustody. SOPs are updated as needed and serve 

as a technical reference for conducting program 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

5 

During 2003, MDP collected data on cantaloupe, 

tomatoes, celery, leaf lettuce, and romaine 

lettuce. These commodities are harvested 

primarily by hand although some mechanical 

harvesting does occur. The produce may be 

packaged in the field (except tomatoes, which 

require classification for color and size) or taken 

to a packinghouse. At the packinghouse, the 

produce is cleaned, trimmed, sized, sorted, wrapped, and chilled for preservation until arrival at 

distribution centers and terminal markets. Cleaning is typically accomplished with chlorinated 

water, although other disinfecting agents, such as 

ozone, may be used. Tomatoes and cantaloupe 

often have a food-grade wax applied to replace 

natural waxes removed during washing to help 

prevent water loss. Fungicides may be added to 

the wax or applied separately to retard spoilage. 

Chilling may be accomplished by various means 

such as vacuum cooling, hydrovac cooling, room 

chilling, or forced air cooling. After initial chilling, the produce is stored under chilled conditions 

(avoiding freezing) and depending on the commodity, under low oxygen atmospheric conditions (primarily carbon dioxide). To minimize 

spoilage and bruising, the produce is often 

harvested before reaching full ripeness. Prior to 

shipment to distribution centers and terminal 

markets, tomatoes are often artificially ripened 

using techniques such as ethylene oxide gas. 

Therefore, the data reflect handling practices and 

postharvest treatments. 

III. Laboratory Operations 

Nine microbiology laboratories performed 

analyses for MDP. Specialized laboratories, 

including the Salmonella Reference Center 

(SRC), University of Pennsylvania (UPenn), and 

the Gastroenteric Disease Center, Penn State, 

performed serotyping, antimicrobial resistance, 

and virulence attribute testing. In addition, the 

Minnesota Department of Agriculture laboratory 

performed method development studies for MDP. 

Upon arrival at the testing facility, samples were 

logged, visually examined for acceptability, and 

discarded if determined to be damaged (decayed, 

extensively bruised, or spoiled). Samples were 

refrigerated until analysis commenced. Laboratories were permitted to refrigerate commodities 

for up to 24 hours to allow for different sample 

arrival times from the various collection sites. 

Only excess soil was removed prior to testing. 

Samples were washed in a buffered solution and 

all analyses were conducted from this surface 

wash eluent. MDP also tested the use of newly 

developed wash buffers and growth media. An 

Enzyme-linked immunofluorescent assay 

(ELFA) and cultural microbiological techniques, 

described in Section V, were used to obtain data 

through September 2003. As data were obtained 

and reviewed, modifications were introduced to 

refine and improve the techniques used to 

produce these data. 

MDP evaluated the use of DNA-based polymerase chain reaction (PCR) and instruments 

associated with this technology to compare 

performance with the ELFA method. PCR technology has been shown to adequately address 

concerns such as sample matrix interferences, 

low cell counts, and reaction inhibition due to 

enrichment media. MDP successfully completed 

validation studies and began using DNA-based 

automated instruments for the detection of 

Salmonella isolates in October 2003. AOAC®, 

an internationally recognized organization that 

validates analytical methods for testing food and 

agricultural products, approved the use of these 

instruments and methodologies for microbial 

screening programs; the USDA Food Safety and 

Inspection Service (FSIS) also uses this 

technology for microbiological screening 

programs. 

MDP methods were routinely reviewed and 

modified as necessary to enhance productivity 

and to provide data that will be useful for risk 

model development. As new microbial technologies became commercially available, they 

were evaluated for use in the program. As with 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

6 

all methods modifications, all programmatic 

QA/QC criteria must be met prior to implementation by MDP laboratories. 

The main objectives of the QA/QC program 

were to ensure the reliability of MDP data and to 

ensure performance equivalency of participating 

laboratories. Direction for the MDP QA program 

was provided through written SOPs based on 

FDA’s 2001 Bacteriological Analytical Manual 

(BAM) (2) methods, AOAC®-certified methods, 

FSIS Microbiological Laboratory Guide, and the 

Environmental Protection Agency’s Good Laboratory Practices. MDP analytical methods are 

published at http://www.ams.usda.gov/science/

MPO/SOPs.htm. SOPs provide uniform administrative, sampling, and laboratory procedures. 

Positive and negative controls and a sterile 

media blank were required for each sample set. 

MDP laboratories used positive control strains of 

E. coli and Salmonella that carry a gene coding 

for Green Fluorescent Protein (GFP). Expression 

of the GFP, detected by exposing the cultures to 

ultraviolet light, indicates the presence of the 

control cultures without having to perform 

lengthy biochemical tests. All controls and 

blanks were taken through the entire analytical 

procedure. MDP laboratories used automated 

instrumentation for confirmation of isolates. 

A Technical Advisory Group, comprised of 

microbiologists from each participating 

laboratory, provided technical feedback on 

revised program SOPs and addressed technical 

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

each participating facility was required to have a 

Quality Assurance Unit (QAU) that operates 

independently from the laboratory staff. 

Preliminary QA/QC review procedures were 

performed on-site by each laboratory’s QAU. 

Final review procedures were performed by 

MDP staff that is responsible for collating and 

reviewing data for conformance with SOPs. 

Laboratory performance was monitored through 

on-site reviews by MDP staff to determine 

compliance with MDP SOPs. Corrective 

actions, if necessary, were performed as a result 

of on-site reviews. Performance equivalency of 

the participating laboratories was monitored by 

a program-wide proficiency testing program. 

MDP laboratories participated in a check 

sample program administered through AOAC®. 

IV. Database Management 

 

MDP maintains an electronic database that 

serves as a central data repository. The central 

database resides at the Monitoring Programs 

Office in Manassas, VA. The data captured and 

stored in the MDP database include product 

information and analytical findings for each 

sample collected along with QA/QC results for 

each set of samples. The MDP data life-cycle is 

depicted in Figure 3. 

MDP utilizes a Web-based RDE system to 

capture and report MDP data. The RDE system 

is centralized with all user interface software 

and database files residing in Washington, DC. 

The laboratory users need only a Web browser 

to interface with the RDE system. Access to the 

RDE system is controlled through separate user 

login/password accounts and user access rights 

for the various system functions based on 

position requirements. The RDE system utilizes 

Secure Socket Layer technology to encrypt all 

data passed between users’ computers and the 

central Web server. At MDP headquarters, the 

RDE system allows scientists to review and 

approve the data for inclusion in the central 

database. A separate Windows-based system 

allows sample collectors to electronically 

capture the standardized Sample Information 

Form (e-SIF) on handheld or laptop computers. 

The e-SIF system generates formatted text files 

containing sample information that are e-mailed 

to MDP headquarters and then imported into the 

Web-based RDE system. 

The RDE data entry screens have extensive 

edits and cross-checks built in to ensure that 

acceptable values are entered for all critical data 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

7 

Figure 3. Data Life Cycle 

Sample Collection 

- Collection in 10 States 

- Samples taken close to consumer 

- Standardized Sample Information Form 

- Data entry on handheld/laptop computers 

- 8 State laboratories + 1 Federal laboratory 

 for sample testing 

- Standardized sample preparation 

- Test for specific foodborne pathogens

Laboratory Analysis 

Lab Remote Data Entry (RDE) 

Data Review at HQ 

- Scientists review data on-screen 

- Upload data to central database

- Web-based data entry software 

- Import data from other systems 

- Access controlled by user login 

- Extensive data cross-checks 

Internet 

Year-end 

Review 

Data Reporting 

- Centralized data storage 

- Encrypted data transmissions 

Internet 

- Data reconciliation 

- Standard & ad-hoc reporting
Microbiological Data Program — Annual Summary, Calendar Year 2003 

8 

elements. This task is made easier by the 

practice of capturing and storing standardized 

codes for all critical alphanumeric data elements rather than their complete names, meanings, or descriptions. This coding scheme 

allows for faster and more accurate data entry, 

saves disk storage space, and makes it easy to 

perform queries on the database. The data entry 

screens also perform edits on numeric fields, 

dates, and other character fields to ensure that 

entries are within prescribed boundaries. The 

central MDP database is maintained using 

Microsoft® Access in a Windows® 2000 operating environment. 

Access to the central MDP database is limited 

to MDP headquarters personnel and is controlled through password protection and user 

access rights. The system is backed-up each 

night and back-up tapes are sent to off-site 

storage once a week. 

V. Summary of 2003 Data 

In 2003, the second full year of testing, MDP 

screened 10,972 samples for the presence of E. 

coli and Salmonella. E. coli has been used as an 

indicator of fecal contamination in food and 

water; pathogenic E. coli and Salmonella are 

frequently implicated in foodborne outbreaks 

involving produce (3). Consequently, these 

organisms are of public health significance. 

Baseline data-gathering efforts designed to 

identify relevant trends ideally require data 

generated over multiple growing seasons that 

span several years. Although 2003 provided a 

second year of data for MDP, continued data 

collection is needed before multi-year inferences can be made. Additionally, MDP began 

implementing major changes in detection 

technology that will further affect data 

interpretation. 

Commodities tested in 2003 remained the same 

as those in 2002: cantaloupe, tomatoes, celery, 

leaf lettuce, and romaine lettuce. These crops 

were selected because they are high consumption fruit and vegetables in the U.S. diet 

and are often consumed raw. All samples in a 

State are collected on the same day or within a 

two-day interval. Samples from a site consist of 

three individual units of produce generally 

collected from the same container. Inferences 

cannot reasonably be made from the sample 

units to the lots from which they originate 

because the units do not provide enough 

information to produce statistically reliable lot 

estimates. Nevertheless, statistical methods can 

be applied to make whole target-population 

inferences from the data and to compare these 

inferences over time. 

 

Table 1 shows the distribution of samples among 

each commodity and collection State. Figure 4 

illustrates the proportion of samples that were 

domestic, imported, and of unknown origin for 

each commodity. Table 2 specifies the 

distribution of imported samples by commodity 

and country of origin. 

The samples were screened for E. coli using an 

AOAC®-certified method. When E. coli was detected through the initial screening process, the 

organism was isolated and identified. To screen 

for potentially pathogenic strains, the isolates 

were sent to Penn State for further identification 

and characterization, including serotyping, antimicrobial resistance testing, and testing for 

virulence attributes. 

To determine pathogenic potential, Penn State 

tested the isolates for the presence of 13 different 

virulence-specific genes associated with 7 

different categories of pathogenic E. coli. A 

summary of the analysis of pathogenic E. coli by 

virulence attributes is presented in Table 3. The 

isolates listed in Table 3, containing Enterohemorrhagic E. coli, Enterotoxigenic E. coli, and 

Enteropathogenic E. coli, are of importance to 

human health. Most of the remaining isolates 

listed can be grouped as Necrotoxigenic E. coli, 

Enteroaggregative E. coli, and Enteroinvasive E. 

coli based on presence of virulence attributes. 

Penn State also classified the E. coli strains 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

9 

 State Cantaloupe Tomatoes Celery 

Leaf 

Lettuce 

Romaine 

Lettuce Total E. coli Salmonella 

 California 504 504 504 501 504 2,517 2,517 2,517 

 Colorado 72 72 72 72 72 360 360 360 

 Florida 248 249 249 252 252 1,250 1,250 1,250 

 Maryland 138 144 141 126 117 666 666 666 

 Michigan 216 213 213 216 213 1,071 1,071 1,071 

 New York 324 324 324 324 324 1,620 1,620 1,620 

 Ohio 214 212 216 213 219 1,074 1,074 1,074 

 Texas 283 280 275 282 285 1,405 1,405 1,402 

 Washington 122 132 144 144 141 683 683 679 

 Wisconsin 69 64 52 72 69 326 326 326 

 TOTAL 2,190 2,194 2,190 2,202 2,196 10,972 10,972 10,965 

Table 1. Number of Samples Collected and Analyzed by State 

Samples Analyzed for 

Commodity Country Name 

Number of 

Samples 

Cantaloupe Costa Rica 273 

 Dominican Republic 58 

 Guatemala 296 

 Honduras 204 

 Guatemala / Honduras 3 

 Mexico 36 

 Unknown Country 59 

 929 

 

Celery Canada 1 

 Mexico 33 

 34 

 

Lettuce, Leaf Canada 6 

 

Lettuce, Romaine Canada 6 

 Unknown Country 3 

9 

 

Tomatoes Canada 114 

 Israel 3 

 Mexico 527 

 Netherlands 3 

 Spain 5 

 Unknown Country 3 

 655 

Table 2. Distribution of Imported Samples 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

10 

Figure 4. Commodity Origin 

Domestic 54.2% 

Unknown 3.4% 

Imported 42.4% 

Cantaloupe 

Domestic 95.2% 

Unknown 3.2% 

Imported 1.6% 

Celery 

Domestic 96.4% 

Unknown 3.3% 

Imported 0.3% 

Leaf Lettuce 

Domestic 97.1% 

Unknown 2.5% 

Imported 0.4% 

Romaine Lettuce 

Domestic 63.3% 

Unknown 6.8% 

Imported 29.9% 

Tomatoes 
based on the somatic “O” type and flagellar “H” 

type antigens using an enzyme-linked 

immunosorbent assay method, commonly known 

as ELISA. 

The number of samples for each commodity 

analyzed for E. coli with subsequent 

characterization of the isolated organism is 

shown in Table 4. Virulence attributes were 

identified in 44 E. coli isolates—4 on imports (2 

tomatoes and 2 cantaloupes), 4 on samples of 

unknown origin, and 36 on domestic samples. 

These isolates may have pathogenic potential but 

cannot be characterized as pathogenic to humans. 

An isolate must carry several genes to be 

positively characterized as a pathogen. MDP 

isolates were tested for those genes referenced in 

Table 3 and were shown to carry only one of 

them. The additional testing required in order to 

determine the actual pathogenicity of the organism to humans is not within the scope of MDP. 

A fully automated ELFA system was used to 

screen for Salmonella through September 2003. 

In October 2003, the BAX® instrument, an 

automated PCR system, was introduced for Salmonella screening. Pooled samples are screened 

initially; if a positive result is obtained, the three 

individual samples are tested. Positive samples 

were cultured for isolation and identification of 

the organism. Identification of isolates was 

confirmed using either a conventional biochemical testing system, an AOAC®

performance-tested kit, or a MDP-accepted 

commercial biochemical kit or system. Isolates 

were then sent to the SRC at UPenn for further 

characterization (serotyping) and to Penn State 

for antimicrobial resistance testing. 

Three samples, all of domestic origin, were 

found to contain Salmonella: one each of leaf 

lettuce, romaine lettuce, and tomato. The 

numbers of each commodity analyzed for 

Salmonella with subsequent characterization 

are shown in Table 5. Based on serotyping, the 

leaf lettuce isolate was identified as 

Salmonella muenchen group C2 and the 

romaine lettuce isolate was identified as 

Salmonella poona group G1. The species 

identity for the tomato isolate was not 

determined; however, the isolate belonged to 

group C2. 

MDP is now implementing an enzyme-based 

assay to detect E. coli followed by multiplex 

PCR techniques to detect E. coli with pathogenic potential. In 2004, E. coli O157:H7 was 

added to the program as a target organism with 

screening performed using PCR techniques. 

MDP plans to add Shigella in 2005 and is 

investigating DNA-based screening methods 

for this organism. 

Microbiological Data Program — Annual Summary, Calendar Year 2003 

11 

 E. coli Type* 

Number of 

Isolates Virulence Attributes Attribute Description 

 EHEC 3 Stx-1, Stx-2, HlyA Shiga Toxins, EHEC Hemolysin 

 ETEC 2 Heat Stable (STa, STb), 

 Heat Labile (LT) Toxins 

 EAggEC 4 EAggEC Plasmid-encoded Factor 

 EPEC 11 Eae Virulence Factor (Intimin) 

 NTEC 14 CNF-1 and CNF-2 Cytotoxic Necrotizing Factor 

 EIEC 3 IpaH Invasive Plasmid Antigen 

 Other 7 K1 Capsular Antigen 

Table 3. Summary of Analysis of Pathogenic E. coli by Virulence Attributes 

* See Definitions 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

12 

Commodity 

Number of 

Samples 

Tested 

 Number of 

Virulent Strains 

Isolated 

Percent of Isolates 

Testing Positive for 

Virulence 

Attributes Breakdown in Virulent Attributes 

Celery 2,190 3 0.14 1-Eae, 1-Stx-1+CNF2, 1-CNF1+K1 

Cantaloupe 2,190 7 0.32 3-Eae (1-Eae), 2-IpaH, 2-K1 (1-K1) 

Leaf Lettuce 2,202 15 0.68 1-CNF1, 5-CNF2, 1-EAggEC, 3-Eae, 2-K1 

 1-Sta, 1-CNF1+K1, 1-Stx-1+Stx-2+HlyA 

Romaine 

Lettuce 2,196 17 0.77 5-CNF2, 1-IpaH, 2-K1, 3-EAggEC, 5-Eae 

 1-Sta+HlyA 

Tomatoes 2,194 2 0.09 1-Stx-2, 1-EAggEC 

10,972 44 

Table 4. Summary of Sample Analysis for E. coli

Commodity 

Number of 

Samples Tested 

Number of 

Positive Isolates 

Celery 2,190 0 

Cantaloupe 2,184 0 

Leaf Lettuce 2,202 1 

Romaine Lettuce 2,195 1 

Tomato 2,194 1 

10,965 3 

Percent of Samples 

Testing Positive for 

Isolates 

0 

0 

0.045 

0.046 

0.046 

Table 5. Summary of Sample Analysis for Salmonella

References: 

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

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

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

2. Bacteriological Analytical Manual (BAM) (2001). US Food and Drug Administration, 

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

3. Scientific Criteria to Ensure Safe Food (2003). Institute of Medicine, National Research Council of 

the National Academies. The National Academies Press, Washington, DC. 

Disclaimer: 

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

methodology referred to in this 2003 Microbiological Data Program Summary is for the information 

and convenience of the reader. Such use does not constitute an official endorsement or approval by the 

U.S. Department of Agriculture of any product, service, or analytical method to the exclusion of others 

that may be suitable. 
Microbiological Data Program — Annual Summary, Calendar Year 2003 

13 

Definitions: 

Antigen: A substance (such as a toxin or enzyme) capable of stimulating an immune response. 

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

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

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

analytical methods for foods and agriculture. 

Aseptic: Refers to free of microbial contamination. 

Check sample: Any matrix sample prepared for the purpose of determining biases, accuracy, and/or 

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

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

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

sequences of a given organism in detection and identification methods. 

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

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

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

Enteroinvasive E. coli (EIEC): strains that closely resemble Shigella and cause an invasive, dysenteric 

form of diarrhea in humans. 

Enteropathogenic E. coli (EPEC): Strains of E. coli that cause a profuse watery diarrheal disease, a 

leading cause of infantile diarrhea in developing countries. Pathogenesis of EPEC involves intimin 

protein (encoded by eae gene) and EPEC adherence factor. 

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

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

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

Enteroaggregative E. coli (EAggEC): Strains of E. coli that resemble ETEC in causing non-bloody 

diarrhea in children. They attach to tissue culture cells in an aggregative manner. Their significance to 

human diseases is uncertain. 

Enzyme-linked fluorescent assay (ELFA): Similar to ELISA; the secondary antibodies are tagged with 

a fluorescent substrate. 

Enzyme-linked immunosorbent assay (ELISA): A technique for detecting and measuring antigens or 

antibodies in a solution. The presence of specific antigens which bind to the antibodies is detected by 

the application of secondary antibodies that have been tagged with a fluorescent or an enzymatic 

substrate. 

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

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

color, national origin, sex, religion, age, disability, political beliefs, sexual orientation, or marital or family 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 USDA’s TARGET Center at (202) 720-2600 (voice 

and TDD). 

To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326-W, Whitten Building, 1400 

Independence Avenue, SW, Washington, DC 20250-9410 or call (202) 720-5964 (voice and TDD). USDA is an equal 

opportunity provider and employer. 

●●●●●

Microbiological Data Program — Annual Summary, Calendar Year 2003 

14 

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

in-sanitation or fecal contamination. 

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

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

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

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

Necrotoxigenic E. coli (NTEC): pathogenic E. coli strains that carry cytotoxic necrotizing toxins 

CNF-1 and CNF-2 and are known to cause extra-intestinal (urinary tract) infections in humans. 

Pathogen: Specific causative agent (as a bacterium or virus) of disease. 

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

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

identify, with a very high-probability, disease-causing viruses and/or bacteria. Multiplex PCR (mPCR)

involves simultaneous amplification of more than one specific region of DNA or specific genes for 

various analytes. 

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

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

wall components or flagella. 

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

coli. These toxins have a cytotoxic effect on intestinal epithelial cells that probably causes the 

characteristic bloody diarrhea. 

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

that contributes to virulence or pathogenicity. 

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

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