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

Frontiers in Microbiology

Erika Mudrak¹  Daniel Weller²  Martin Wiedmann²  Sherry Roof²  Erika Ganda²  Renata Ivanek³  Channah Rock⁴  Natalie Brassill⁴ 

[1] Cornell Statistical Consulting Unit, Cornell University, Ithaca, NY, United States;Department of Food Science and Technology, Cornell University, Ithaca, NY, United States;Department of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY, United States;Department of Soil, Water and Environmental Science, University of Arizona, Maricopa, AZ, United States;

关键词: agricultural water;    produce safety;    Listeria;    Salmonella;    irrigation;    E. coli;   

DOI  :  10.3389/fmicb.2020.00134

来源: DOAJ

【 摘 要 】

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 Escherichia coli 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 Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella 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 E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli 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 E. coli 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.

【 授权许可】

Unknown