A systems approach to microbial food safety in produce: Leveraging data science approaches to inform food safety decisions

The Produce Safety Center of Excellence is a collaborative initiative in between Cornell University, Virginia Tech and University of Florida with the goal to provide the produce industry with advanced computational tools to reduce the public health, economic, environmental and societal impacts of produce related microbial food safety issues. The initiative is funded by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award no. 2019-51181-30016.

We use a systems approach that encompasses produce production, packing, processing, retail distribution and consumer systems, and their overlaps with the following goals:

Develop a farm-to-consumer hazard transmission model to facilitate a systems approach to identifying environment appropriate, socially acceptable and cost-effective interventions.

We will characterize contamination of romaine lettuce with Escherichia coli O157:H7 and contamination of cantaloupes with Listeria monocytogenes along the farm-to-table continuum and evaluate different interventions implemented to reduce the consumer exposure to these foodborne pathogens. The goal is to identify interventions that not only improve safety of these foods but are also environment appropriate, socially acceptable and cost-effective. Learn more about the farm-to-consumer hazard transmission model …

Improve GIS tools and approaches to reduce produce microbial food safety hazard introduction from agricultural water, environmental and animal sources at the pre-harvest level.

The goal is to develop models that allow for the prediction of times and locations with an increased risk of microbial hazards on-farm in different US growing regions. Models will be built using a combination of pathogen and indicator data, remotely sensed weather and adjacent land-use buffer data, and on-site physiochemical data. Outputs from model predictions will assist with region-specific guidance for industry on reducing microbial hazards on-farm from water and soil; as well as, educational programming for extension educators (targeted efforts). Learn more about GIS tools and approaches to food safety at the pre-harvest level …

Develop and validate simulation models for (i) packing houses, (ii) processing plants and (iii) retailers to facilitate use of in silico tools to optimize pathogen sampling plans and control strategies.

The goal is to develop agent-based model (ABM) of Listeria transmission in packing houses and produce processing plant and use the model outputs to design, implement, and evaluate improved control strategies in selected facilities. These will be valuable tools for the industry to justify sampling plans and corrective action responses to Listeria detection. Learn more about simulation models …

Assemble a library of existing models and modelling tools applicable to the produce industry, and review these tools with respect to the intended purpose, utility (pros and cons) and current usage, to facilitate computer enabled food safety decision making.

We will assemble a library of existing models and decision support tools applicable to food safety of fresh produce to aid access of the food industry to these tools. Also, we will survey the food industry about their use of decision-support tools to identify industry needs regarding such tools. Learn more about the model library …

Develop a comprehensive on-line and in-person (mixed model) outreach program to provide technical and systems-based produce food safety training and to enable industry to use modeling tools.

The goal is to develop training programs for the various sectors of the produce industry, that include growers, packing houses and processors, retail, and consumer educators. The training programs will allow for a produce safety certificate program that is comprised of training modules that are specific for the different sectors of the produce chain. Learn more about produce safety training for industry…

Develop graduate and undergraduate teaching modules to train students to use and develop computational and modelling tools for produce safety.

The goal is to develop teaching modules for graduate and undergraduate student to improve their understanding of (i) the produce supply chain from “farm-to-table” and (ii) application of modern computational tools, analytics, and modelling approaches to produce safety. Learn more about the teaching modules…

Contact us

Email: producesafetycoe [at] cornell.edu (producesafetycoe[at]cornell[dot]edu)