Evaluating the U.S. Food Safety Modernization Act Produce Safety Rule Standard for Microbial Quality of Agricultural Water for Growing Produce

Arie H Havelaar; Kathleen M Vazquez; Zeynal Topalcengiz; Rafael Muñoz-Carpena; Michelle D Danyluk

doi:10.4315/0362-028X.JFP-17-122

Evaluating the U.S. Food Safety Modernization Act Produce Safety Rule Standard for Microbial Quality of Agricultural Water for Growing Produce

J Food Prot. 2017 Nov 1;80(11):1832-1841. doi: 10.4315/0362-028X.JFP-17-122.

Authors

Arie H Havelaar¹, Kathleen M Vazquez², Zeynal Topalcengiz^{3

4}, Rafael Muñoz-Carpena², Michelle D Danyluk³

Affiliations

¹ Emerging Pathogens Institute, Institute for Sustainable Food Systems, Department of Animal Sciences (ORCID: http://orcid.org/0000-0002-6456-5460).
² Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida 32610, USA.
³ Department of Food Science and Human Nutrition, Citrus Research and Education Center, Lake Alfred, Florida 33850, USA.
⁴ Department of Food Engineering, Faculty of Engineering and Architecture, Muş Alparslan University, 49250 Muş, Turkey.

PMID: 28990819
DOI: 10.4315/0362-028X.JFP-17-122

Abstract

The U.S. Food and Drug Administration (FDA) has defined standards for the microbial quality of agricultural surface water used for irrigation. According to the FDA produce safety rule (PSR), a microbial water quality profile requires analysis of a minimum of 20 samples for Escherichia coli over 2 to 4 years. The geometric mean (GM) level of E. coli should not exceed 126 CFU/100 mL, and the statistical threshold value (STV) should not exceed 410 CFU/100 mL. The water quality profile should be updated by analysis of a minimum of five samples per year. We used an extensive set of data on levels of E. coli and other fecal indicator organisms, the presence or absence of Salmonella, and physicochemical parameters in six agricultural irrigation ponds in West Central Florida to evaluate the empirical and theoretical basis of this PSR. We found highly variable log-transformed E. coli levels, with standard deviations exceeding those assumed in the PSR by up to threefold. Lognormal distributions provided an acceptable fit to the data in most cases but may underestimate extreme levels. Replacing censored data with the detection limit of the microbial tests underestimated the true variability, leading to biased estimates of GM and STV. Maximum likelihood estimation using truncated lognormal distributions is recommended. Twenty samples are not sufficient to characterize the bacteriological quality of irrigation ponds, and a rolling data set of five samples per year used to update GM and STV values results in highly uncertain results and delays in detecting a shift in water quality. In these ponds, E. coli was an adequate predictor of the presence of Salmonella in 150-mL samples, and turbidity was a second significant variable. The variability in levels of E. coli in agricultural water was higher than that anticipated when the PSR was finalized, and more detailed information based on mechanistic modeling is necessary to develop targeted risk management strategies.

Keywords: Escherichia coli; Salmonella; Agricultural water; Food Safety Modernization Act; Statistical analysis.