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Engineering for Food Safety and Quality

Datta, Ashim
Cornell University
Start date
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Objective: Advancing the fundamental science and application of technologies to ensure safety and improve quality of food products Predictive food safety is a potent and virtually unused weapon in the food safety arsenal, and is drawing increasing attention from the USDA, the FDA and state regulators. Predictive ability has not been exploited due to the highly interdisciplinary and resource-intensive development needed, involving engineering, microbiology, and practical information.

We have developed a general purpose software tool for predicting food safety that we would like to further enhance and customize for New York. The following are the specific goals:

  1. Include in the predictive software, working with NY-based processors, specific products, processes, and microbiological models, likely deviations, and appropriate analysis of interest to industries ranging in size and commodity base.
  2. Customize the developed software interface to the practical and everyday needs of the stakeholder. Continue improving its intelligence and usability. Fill the gaps between predictions and what a food processor/Extension person can use in everyday situations.
  3. Validate the software's prediction capabilities against real-world data and situations.
  4. Develop training videos, illustrations, and other supporting materials to enable routine use of the predictive tool to enhance food safety.
More information
Non-Technical Summary: Predictive ability (of microbial growth and inactivation and therefore shelf life, etc.) is at the heart of control measures for enhancing food safety. Safety issues due to unintentional contamination and even sabotage of prepared foods are being addressed in several ways but the time is right to include predictive tools as predictive microbiology is beginning to be accepted by the USDA, the FDA and state regulators for specific products as they push science-based regulations. After years of developing the related engineering and microbiology, funded by the National Integrated Food Safety Program of the USDA, we have the first prototype of a predictive software tool that allows testing of truly realistic "what-if" scenarios--this can elevate food safety significantly. Without any specialized training and with simple input such as the food item, its shape and size, and processing/transportation/storage conditions from the user, this tool can predict the microbiological safety by choosing the target microorganism from its built-in intelligence and provide safety predictions, relating them to regulatory and risk concerns. We wish to customize this tool by providing product-, process-, and user-specific information and guidance for the food safety managers, Extension personnel, microbiologists, food engineers, and food scientists working in New York companies ranging in size and commodity base (stakeholders). We would also validate the predictive tool against real-world situations, strengthen available training materials with video developed from the tool and add risk-assessment capabilities to the tool.

Approach: 1, 2) [Years 1 & 2] Make plant visits to identify the specific needs of several food processors in NY ranging in size and commodity base (primary stakeholders) where predictive ability can improve their HAACP systems by performing, for example, "what if" scenarios on deviations. Such needs can be: a) specific products and their compositions, sizes, and packaging materials; b) specific processes; c) specific target microorganisms (whose growth models may not already be in our database); d) specific deviations such as temperature abuse; e) user-friendly ways of presenting predictions (such as bacterial count or risk estimates for older persons) that makes it easier for the user to relate to decision making. Build these specific needs into the software. 3) [Years 1 & 2] Collect data from stakeholder experiences such as recalls or product failures and use such data to validate predictions, increasing the reliability of the software. 4) [Years 3 & 4] Generate tutorials addressing the specific needs discussed above for various product/process/microbiology combinations to encourage stakeholders to integrate this prediction tool as a complement of existing solutions in permanently enhancing food safety. Work with companies to provide access to software and train so that they can use it on their own. 5) [Year 5] Enhance HAACP and other training materials through "what-if" scenarios (case studies) of some of the most critical situations, such as temperature abuse and unintentional contamination or even sabotage, using visualization capabilities of the tool. This will greatly enhance the communication of food safety. This tool is being developed for practical use by industry/Extension personnel (stakeholders) and it is therefore critical to include such personnel throughout the process. We would be working directly with several food companies New York State, together with Extension microbiologist Dr. Worobo of our Food Science Department at Geneva. We would keep stakeholders involved throughout the process to 1) assess their needs as described under the approach; 2) respond to their needs through building the relevant predictive capability in the software and validate predictions using information they make available to us (thus certainly keeping them in the loop); 3) work with them in developing tutorials for safety prediction and enhancing their safety training literature; and finally 4) have them use the predictive tool under our guidance to perform relevant "what-if" scenarios that demonstrate the enhancement of safety and improvement of productivity. We will develop a survey for evaluation of the safety prediction tool that will be completed by all users. The information collected will provide us with the effectiveness and impact of the tool in food safety enhancement.

Funding Source
Nat'l. Inst. of Food and Agriculture
Project source
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Education and Training
Risk Assessment, Management, and Communication
Natural Toxins
Viruses and Prions
Bacterial Pathogens
Chemical Contaminants