FSMA agricultural-water die-off compliance provisions benefit from condition-specific modifiers

Recent provisions by the US FDA Food Safety Modernization Act (FSMA) Produce Safety Rule established criteria for microbial quality of agricultural water based on the quantitative presence of generic Escherichia coli. If water for irrigation is contaminated above a specified threshold, a grower can apply a waiting time between irrigation and harvest to achieve an acceptable calculated reduction of E. coli that is based on an assumed die-off rate of 0.5 log per day for up to four days. There is an urgent need for validation of the assumed FSMA agricultural-water die-off rate under tightly controlled field conditions that represent and reflect the diversity of industry practices, climates and environmental conditions. This project is specifically designed to generate standardized, multi-commodity and multi-regional data that will provide foundational evidence for predictive modeling of pathogen die-off and evaluate the validity of assumptions underlying the FSMA agricultural water die-off matrix. Our objectives are to: (1) Estimate die-off rates of indicators and attenuated pathogens on baby-spinach and baby-lettuce in a replicated trial under field conditions in three different climatic regions; and (2) Develop a predictive model of pathogen die-off under relevant environmental conditions and industry practices and use the model to evaluate the FSMA agricultural water matrix. Our proposed trial will simulate non-compliant or contaminated irrigation water using rifampicin resistant generic E. coli strains and an attenuated Salmonella Typhimurium strain. Experiments will be conducted in three locations: California, New York, and Spain. Baby spinach and lettuce will be used as representatives of leafy greens. Produce planting will be staggered so that at least 5 cohorts of experimental irrigations, per each of the 2 produce commodities and 3 locations, are conducted under different weather conditions over two years. The findings from the field experiments about the magnitude of correlation between die-off rates in E. coli and S. Typhimurium and the identified field conditions that modulate the die-off rates will provide mechanistic evidence for the development of a mathematical model of pathogen die-off following direct water application. The developed and validated mathematical model will be used for prediction of pathogen die-off under diverse conditions. As a result of the proposed studies we expect to identify factors that significantly affect the rate of microbial die-off. This will confirm that the pathogen die-off rates are affected by weather, and provide a foundation for policy development in terms of region- and produce- specific die-off rates. Estimated correlation between the die-off rates of E. coli and S. Typhimurium will either strengthen or question the current use of generic E. coli as an indicator of microbial hazards related to agricultural water. The developed mathematical model will indicate the conditions under which the FSMA's regulatory matrix for pathogen die-off in agricultural water may be relied upon. These anticipated outcomes will have a direct impact on the FSMA agricultural water die-off matrix by either strengthening it or demonstrating the need to modify it. This will fundamentally advance the risk management of agricultural water and protection of public health.