Source: RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY submitted to
CONTROL OF FOOD-BORNE PATHOGENS IN PRE- AND POST-HARVEST ENVIRONMENTS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0226800
Grant No.
(N/A)
Project No.
NJ10220
Proposal No.
(N/A)
Multistate No.
S-1033
Program Code
(N/A)
Project Start Date
Oct 1, 2007
Project End Date
Sep 30, 2012
Grant Year
(N/A)
Project Director
Schaffner, DO.
Recipient Organization
RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
3 RUTGERS PLZA
NEW BRUNSWICK,NJ 08901-8559
Performing Department
Food Science
Non Technical Summary
Use of predictive modeling and quantitative microbial risk assessment tools are gaining increased acceptance both by the food industry and by regulatory agencies. Despite this increased acceptance, the number of academic researchers actively involved in pioneering the use of these tools is very limited. Examples of the sort of problems currently under investigation in Dr Schaffner's lab include: modeling and assessing the risk posed by the growth of Salmonella in cut tomatoes; simulating the transmission and risk posed by norovirus in foodservice settings; assessing the risk of low levels of Salmonella in peanut butter; and modeling and assessing the risk E. coli O157:H7 in leafy greens from field to fork.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
5015010208010%
5035010208010%
5045010208010%
7125010208070%
Goals / Objectives
Develop or improve methods for control or elimination of pathogens in pre-and post harvest environments including meat, poultry, seafood, fruits and vegetables and nutmeats. Develop and validate mathematical modeling to gain understanding of pathogen behavior in macro and micro-environments. Investigate factors leading to the emergence, persistence and elimination of antimicrobial resistance in food processing and animal production environments.
Project Methods
Our standard procedure in developing predictive models and quantitative risk assessments is to start by surveying the literature, including models available in the USDA ARS Pathogen Modeling Program, and models and data available in ComBase. Available data are then converted into comparable units and combined into statistical distributions. Briefly, the first step is to conduct a literature search and identify studies as sources for growth rates for the relevant commodity-pathogen combinations at different temperatures. Studies presenting growth data on the commodity of interest, as well studies presenting growth data for commodity-associated pathogen strains on laboratory media are selected for further analysis. Growth parameters are extracted directly from tables or growth curves (by superimposing a regression line over the exponential phase of growth). Data are typically modeled using a square-root or Ratkowsky equation relating the square-root of the bacterial growth rate to storage temperature (T). Our quantitative microbial risk assessment technique consists of a literature search where data are collected by searching medical and biological databases for documents related to the topic under study. Software is used to convert graphical data to numerical form. Numerical data are combined wherever appropriate (i.e. where data had approximately the same range and peak). Data are translated into appropriate discrete or probability distribution functions. Numerical data are log transformed and histograms are generated for both literature and experimental data. Quantitative risk assessment models are created and results for simulated input distributions as well as final results are obtained by running iterations of the simulations.

Progress 10/01/07 to 09/30/12

Outputs
Target Audience: Target audiences includes the general public, trade associations, consumer products companies, food processing companies, and retail chains. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Eight graduate students were specifically mentored as part of this project. Seven graduate students were given instruction in quantitative microbial risk assessment as part of special topics class offered through the food science graduate program. Presentations were given at the International Association for Food Protection annual conference in Providence, RI in July 2012, and Charlotte, NC in July 2013, Graduate students from NJ were trained in water and restroom sampling techniques, as well as modeling techniques. Workshop participants were exposed to risk-based decision making tools. How have the results been disseminated to communities of interest? Results have been disseminated through peer reviewed publications, through invited presentations around the world and technical talks and posters a scientific meetings. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Use of predictive modeling and quantitative microbial risk assessment tools are gaining increased acceptance both by the food industry and by regulatory agencies. Despite this increased acceptance, the number of academic researchers actively involved in pioneering the use of these tools is very limited. Examples of the sort of problems currently under investigation in Dr Schaffner's lab include: modeling and assessing the risk posed by the growth of Salmonella in cut tomatoes; simulating the transmission and risk posed by norovirus in foodservice settings; assessing the risk of low levels of Salmonella in peanut butter; and modeling and assessing the risk E. coli O157:H7 in leafy greens from field to fork. Although this multi-state project began in 2007, Dr. Schaffner's lab only joined the project for the final two years (2011 to 2012 and 2012 to 2013). Changes in knowledge occurred in the 7 graduate students studying quantitative microbial risk assessment through the special research topics course. Students gained knowledge regarding the use of quantitative microbial risk assessment in developing food safety policy. Students also improved their skills in conducting quantitative microbial risk assessment. Several students gained new applied knowledge through their research and two peer-reviewed publications were published in 2013 specifically related to this project. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over twelve consecutive months was explored. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R2 < 0.1) and between physicochemical indicators and Salmonella levels (R2 < 0.1). The average rainfall (previous day, week and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration could predict the probability of enumerating selected levels of Salmonella. The lack of good correlations between biological indicators with Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression. Peanuts and peanut-containing products have been linked to at least seven salmonellosis outbreaks worldwide in the past two decades. In response, a workshop was convened to develop a framework for managing risk in low-moisture food commodities where large data sets are unavailable (using peanuts as the example). Workshop attendees were charged with answering questions regarding the appropriate statistical and scientific methods for setting log reduction targets with limited pathogen prevalence and concentration data, suitable quantities of data needed for determining appropriate log reduction targets, whether the requirement of a 5-log reduction in the absence of data to establish a target log reduction is appropriate, and what targeted log reduction would protect public health. Judgment about sufficient data is not solely scientific, but is instead a science-informed policy decision that must weigh additional societal issues. Workshop participants noted that modeling efforts should proceed with sampling efforts, allowing one to compare various assumptions about prevalence and concentration and how they are combined. The discussions made clear that data and risk models developed for other low- moisture foods like almonds and pistachios may be applicable to peanuts. Workshop participants were comfortable with the use of a 5-log reduction for controlling risk in products like peanuts when the level of contamination of the raw ingredients is low (,1 CFU/g) and the process well controlled, even when limited data are available. The relevant stakeholders from the food safety community may eventually conclude that as additional data, assumptions, and models are developed, alternatives to a 5-log reduction might also result in the desired level of protection for peanuts and peanut products. The Central Florida surface water research is of critical importance to farmers in that area, but more importantly it informs the entire discussion of agricultural water quality across the US as FDA prepares to release new regulations governing on-farm food safety. Similarly, the peanut work is of direct value to the peanut industry and other segments of the food industry that use peanuts, but more importantly informs the entire discussion about Salmonella risk in low-moisture food commodities, which is a large segment of the food industry. Again, FDA is preparing to release risk-based preventive control rules which are the most significant change to the food industry in more than 50 year. Our research is central to that discussion.

Publications

  • Type: Journal Articles Status: Published Year Published: 2013 Citation: McEgan, R., G. Mootian, L. D. Goodridge, D. W. Schaffner, and M. D. Danyluk. 2013. Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters. Appl. Environ. Microbiol. 79(13): 40944105.
  • Type: Journal Articles Status: Accepted Year Published: 2013 Citation: Schaffner, D.W., R. L. Buchanan, S. Calhoun, M. D. Danyluk, L. J. Harris, D. Djordjevic, R. C. Whiting, B. Kottapalli, and M. Wiedmann. 2013. Issues to Consider When Setting Intervention Targets With Limited Data for Low-Moisture Food Commodities: A Peanut Case Study. J. Food Protection. 76(2): 360369.


Progress 10/01/11 to 09/30/12

Outputs
OUTPUTS: Experiments were conducted related to modeling the microbial safety of fresh produce; modeling the risk associated with hand washing and cross contamination in kitchen environments; modeling norovirus transmission in foodservice settings; using risk assessment to develop scientifically-based consensus food safety metrics for tomatoes; Enhancing microbial safety of fresh-cut fruit and vegetable salads using modeling and risk assessment; Validation of bacterial surrogates for the survival of norovirus on food contact surfaces; and validation of a mathematical model for holding cold foods without temperature control (ground beef and Salmonella). Eight graduate students were specifically mentored as part of these projects. Seven graduate students were given instruction in quantitative microbial risk assessment as part of special topics class offered through the food science graduate program. Four presentations were given at the International Association for Food Protection annual conference in Providence, Rhode Island in July 2012. PARTICIPANTS: individuals who worked on the project include 9 graduate students, who conducted original research, and more than 20 undergraduate students who assisted with the research. Collaborators and contacts include more than 25 research collaborators on 6 different research projects, representing more than 10 different institutions. Partner Organizations include more than 12 different for-profit companies, several non-profits, the Food and Drug Administration, the Centers for Disease Control and Prevention. Training or professional development was also provided for the 9 graduate students, who conducted original research and more than 20 undergraduate students who assisted with the research.  TARGET AUDIENCES: Target audience includes the general public, two trade associations, a consumer products company, a nonprofit science organization, a food processing company, a retail chain, and numerous meat-processing companies. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Changes in knowledge occurred in the 7 graduate students studying quantitative microbial risk assessment through the special research topics course. Students gained knowledge regarding the use of quantitative microbial risk assessment in developing food safety policy. Students also improved their skills in conducting quantitative microbial risk assessment. Several students gained new applied knowledge through their research, and more than 12 draft publications are in preparation.

Publications

  • No publications reported this period


Progress 12/30/11 to 12/31/11

Outputs
OUTPUTS: Budget letter was issued January 5, 2012. Nothing to report for 2011. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Budget letter was issued January 5, 2012. Nothing to report for 2011.

Publications

  • No publications reported this period