Scientists Develop Technology That Can Predict Location Of Foodborne Pathogens

Researchers at Cornell University have developed a way to predict “hot spots” where disease-causing pathogens – Listeria monocytogenes, Salmonella, Shiga toxin-producing E. coli and L. monocytogenes – may be present and spread on farms before harvest time. The technology uses geospatial algorithms, foodborne pathogen ecology and Geographic Information System (GIS) tools. Classification tree tools apply remotely sensed data such as topography, soil type, weather trends, etc., to predict where pathogens are likely to show up. Scientists share the information with farmers who can then implement preventive practices such as draining standing water, adjusting where livestock graze, or planting crops that should be consumed cooked rather than raw, for example.