Summary of Awards to Date

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

Date

Jan. 1, 2018 - Dec. 31, 2018

Funding Agency

Center for Produce Safety

Amount Awarded

$399,617.00

Investigator

Renata Ivanek, Ph.D.
Cornell University

Co-Investigator(s)

Martin Wiedmann, Ph.D., Trevor Suslow, Ph.D., Ana Allende, Ph.D., Daniel Munther, Ph.D.

Summary

Recent Food Safety Modernization Act (FSMA) provisions for the protection of public health allow growers to use agricultural water exceeding the quantitative standards for indicator Escherichia coli if a pre-harvest waiting period after the last irrigation is applied, for a calculated number of days based on an assumed microbial die-off rate. There is an urgent need to validate the microbial die-off rate under standardized, multi-commodity and multi-regional conditions. Our objective is to establish die-off rates of a standardized set of indicators and attenuated pathogens on baby-spinach and -lettuce in a replicated trial under field conditions in three different climatic regions. The estimated die-off rate, and the identified factors that affect it, will provide the foundation for a validated produce- and region-specific agricultural water die-off matrix for stakeholders to more effectively assess water quality and use. Our second objective is to develop a mathematical model of pathogen die-off under relevant environmental conditions and industry practices. The model will predict pathogen die-off under diverse conditions and indicate the conditions under which the regulatory matrix for pathogen die-off in agricultural water may be relied upon. Collectively, the results are expected to strengthen the FSMA regulatory matrix or demonstrate the need to modify it.

Technical Abstract

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 log10/day. 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.