Validation of Geospatial Algorithms to Predict the Prevalence and Persistence of Pathogens in Produce Fields to Improve GAPs

<p>Foodborne pathogen contamination of produce in the production environment continues to present a considerable concern and can lead to recalls or even outbreaks. There is a need for further development of science-based approaches to assist growers in minimizing the risk of produce preharvest contamination. The purpose of this project is to validate a GIS-based modeling tool that identifies specific locations and times on a produce farm where the prevalence of foodborne pathogens is elevated, and as a result, the risk of produce contamination is higher. This GIS tool can be applied to any location because it utilizes a farms unique combination of landscape characteristics (e.g., proximity to domestic animal operations), soil properties (e.g., soil moisture), and climate (e.g., precipitation) in its prediction process. The implementation of GIS by the produce industry will increase the understanding of factors that promote foodborne pathogen prevalence and persistence on fields, and will assist growers in focusing their food safety efforts using risk-based strategies. Growers will be able to target areas within their farms that are at high risk for contamination and implement more informed field management decisions and science-based strategies (e.g., alteration of cropping schemes) to limit potential produce contamination.</p>