Predictive Population Dynamics of Escherichia coli O157:H7 and Salmonella enterica on plants: a mechanistic mathematical model

In Applied and Environmental Microbiology, scientists from Cornell University published an article on how weather affects key aspects of bacterial behavior on plants as a tool to assess the risk of crop contamination with human foodborne pathogens. A novel mechanistic model informed by weather factors and bacterial state was developed to predict population dynamics on leafy vegetables and tested against published data tracking Escherichia coli O157:H7 (EcO157) and Salmonella enterica populations on lettuce and cilantro plants. The model utilizes temperature, radiation, and dew point depression to characterize pathogen growth and decay rates. The model accurately predicted EcO157 and S. enterica population sizes on lettuce and cilantro leaves in the laboratory under various conditions of temperature, relative humidity, light intensity, and cycles of leaf wetness and dryness. In nearly all field trials, the model successfully predicted EcO157 population dynamics on 4-week-old romaine lettuce plants under variable weather conditions. Prediction of initial EcO157 population decay rates after inoculation of 6-week-old romaine plants in the same field study was better than that of long-term survival. @


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