Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water.

Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of detection (Odds Ratio [OR] = 2.18), and codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting was not. Regression also showed that codetection in AZ (OR = 50.2) and NY (OR = 18.4), and detection in AZ (OR = 4.4) were significantly associated with levels, while detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.