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Reducing Risk of Clostridium Spp. Food Poisoning Using Predictive Modeling

Schaffner, Donald
Rutgers University
Start date
End date
This project will assist processors and retail operators in the safe cooling of food products by: Validating existing mathematical models for the growth of C. perfringens under exponentially changing temperature and temperature abuse situations; ensure that cooling scenarios that are safe for C. perfringens can also meet the C. botulinum regulations; developing a user-friendly computer program that will predict the risk of foodborne illness during changing temperature conditions; teaching processors and retail operators around the country to use this computer program during face-to-face workshops and by providing accessibility to the program and related documentation through web sites; and educating students in the practical application of predictive models to solve food science problems through guest lectures in existing courses.
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The project starts in year 1 with collection of data for validation of standard exponential cooling rates at times ranging from 6.5 to 24 hr. This phase of the research will be completed by the end of the first year, and data collection for the first set of cooling variations will begin in the last quarter of year 1. C. botulinum will be studied during selected cooling scenarios simultaneous to data analysis. The first research publication based on validation of the model with standard exponential cooling will also be initiated in the final quarter of year 1. Once this preliminary validation is complete, revision of our prototype spreadsheet, and plans for the first educational module (for Principles of Food Engineering) can also begin. The second set of validation experiments will be complete by the middle of year 2, and the third and final set of validation experiments (cooling interrupted by a variable static hold time) will begin. The first research manuscript will also be completed and submitted by the middle of year 2. Our first outreach workshop will be conducted during year 2, along with education modules at both the graduate and undergraduate courses. The computer model will be revised in response to feedback from the workshop, the two courses and from the second set of validation data. The final set of validation data will be collected early in year 3, and work on the second peer-reviewed publication will begin. This publication will summarize the research findings from the latter two validation datasets. Workshop 2 will be held early in year three, with workshops 3 and 4 to be held later in the same year.Revised education modules for both the graduate and undergraduate courses will be taught in the first half of year 3. A final revision of the computer model will be made based on the last set of validation data, feedback from workshop 2 and the graduate level class.
Funding Source
Nat'l. Inst. of Food and Agriculture
Project source
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Food Preparation and Handling
Education and Training
Bacterial Pathogens
Predictive Microbiology