Performing Department
Food Science & Human Nutrition
Non Technical Summary
Simulation approaches provide the opportunity to study real food safety hazards, albeit in digital representations of the system rather than in the physical world. Various simulation-based approaches have been applied to food safety problems, including: (i) Quantitative Microbial Risk Assessment (QMRA);(ii) Agent-based modelling; and (iii) Statistical analysis of food system tasks such as sampling. The outcome is both a representation of a physical food system in a digital space, and then use of that digital system to conduct food safety experiments that would otherwise be impractical or impossible. This project will apply these tools to two problems:(i) Simulating Milk Powder Testing to Improve Capabilities to Detect Rare Pathogens and (ii) Simulating K-12 Share Tables to Assess Food Safety. For the milk powder work we will represent production as if it were stretched out across a long belt conveying the powder away from the production site. Food safety hazards will then cover an area of the production belt. Samples will be taken across specific areas of the belt where the width of the sample (represented by production time) will converge to zero to represent essentially an instant sample process.Our model could then be used to analyze a variety of sampling plans explicitly designed to manage ranges of hazards. For the share table work, will use QMRA to build a simulation of the relevant components of a share table system includingmeal preparation, child selection of food from the cafeteria, the choice of the student to consume the food, share it, or dispose of it, and the food safety hazard transmission during these steps. Each of these two sub-projects would resultin focused simulations appropriate for asking and answering specific questions relevant to food safety. In addition, these projects will also result in graphic user interfaces that are appropriate for stakeholders to use to assess their specific food safety concerns.
Animal Health Component
0%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Hatch funds will be used to support the following project objectives:Objective One:Simulating milk powder testing to improve capabilities to detect rare pathogens.Objective Two:Simulating K-12 share tables to assess food safety.
Project Methods
Objective One: Simulating Milk Powder Testing to Improve Capabilities to Detect Rare PathogensWe believe our 2D sampling simulation model could be adapted to sampling powders for safety parameters. Essentially, this project will represent production as if it were stretched out across a long belt conveying the powder away from the production site. Food safety hazards will then cover an area of the production belt. Samples will be taken across specific areas of the belt where the width of the sample (represented by production time) will converge to zero to represent essentially an instant sample process.Our model could then be used to analyze a variety of sampling plans explicitly designed to manage ranges of hazards. We could then provide comprehensive guidance as well as a tool for industry users. Progress on this task will have the following sub-objectives: Model adaptation, Benchmarking existing industry sampling plans, Web-based graphical user interface development.Objective Two: Simulating K-12 Share Tables to Assess Food SafetyShare tables are locations in school cafeterias where students can place unwanted school menu items so that other hungry students can eat these foods. At the end of the day, unselected share table items can be donated to food pantries and/or used for future meal service. We hypothesize that food safety risks are not meaningfully increased by share tables, as cross-contamination risk is already present during meal selection. To evaluate our hypothesis, we will use Quantitative Microbial Risk Assessment (QMRA) to build a simulation of the relevant components of a share table system. Progress on this task will have the following sub-objectives: Hazard identification, Literature Review, QMRA, Model comparison and what-if scenarios, and outcomes.