|dc.description.abstract||Produce (fruits and vegetables) has been frequently linked to foodborne disease outbreaks in the United States and worldwide. Produce-related outbreaks have been traced back to contamination occurring at pre-harvest production level. The overall goal of this dissertation was to identify risk factors for produce pre-harvest contamination and develop models to predict the introduction, survival, and persistence of enteric foodborne bacteria in produce at the pre-harvest level.
Produce from mixed farms, where vegetable crops and animals are grown at the same premise, is potentially at higher risk of microbial contamination due to its proximity to environmental reservoirs such animal enclosures and composting facilities. Such contamination can be affected by meteorological factors such as temperature, precipitation, and wind speed. By integrating microbial sampling and meteorological data, the effects of meteorological factors on prevalence and concentration of Listeria species and generic Escherichia coli in samples collected from a mixed produce and dairy farm were analyzed using logistic regression and tree-based methods. The developed models have robust predictive ability and can be used to estimate the risk of microbial contamination in mixed farms under different weather conditions.
Survival and persistence of pathogens in field soil is a food safety concern as soil can serve as a source and route for microbial contamination in produce. Regression models were developed to evaluate the effects of meteorological factors, cover cropping, and farming system on the survival and persistence of generic E. coli and L. innocua in produce field soil. The models revealed that survival of E. coli and persistence of L. innocua were predominately influenced by temperature, precipitation, and relative humidity.
Further, data from a large microbial sampling study were used to determine the effects of a variety of meteorological, environmental, and farm management factors on the presence and concentration of food safety and quality bacteria indicator in tomatoes and tomato environmental samples. The results suggest that microbial contamination in tomatoes and in tomato production environments can be significantly affected by certain meteorological conditions, environmental factors, and farm management practices.
In conclusion, this study identified potential risk factors associated with the presence, concentration, survival, and persistence of enteric foodborne bacteria in produce and in produce production environments. The developed models can be used to predict the risk of microbial contamination in produce farms under different meteorological conditions, geographical regions, and farm management practices. Such information and tools will help growers to improve farm management practices to reduce potential contamination of produce.||en_US