Microbial quality of agricultural water in Central Florida

Abstract

The microbial quality of water that comes into the edible portion of produce is believed to directly relate to the safety of produce, and metrics describing indicator organisms are commonly used to ensure safety. The US FDA Produce Safety Rule (PSR) sets very specific microbiological water quality metrics for agricultural water that contacts the harvestable portion of produce. Validation of these metrics for agricultural water is essential for produce safety. Water samples (500 mL) from six agricultural ponds were collected during the 2012/2013 and 2013/2014 growing seasons (46 and 44 samples respectively, 540 from all ponds). Microbial indicator populations (total coliforms, generic Escherichia coli, and enterococci) were enumerated, environmental variables (temperature, pH, conductivity, redox potential, and turbidity) measured, and pathogen presence evaluated by PCR. Salmonella isolates were serotyped and analyzed by pulsed-field gel electrophoresis. Following rain events, coliforms increased up to 4.2 log MPN/100 mL. Populations of coliforms and enterococci ranged from 2 to 8 and 1 to 5 log MPN/100 mL, respectively. Microbial indicators did not correlate with environmental variables, except pH (P<0.0001). The invA gene (Salmonella) was detected in 26/540 (4.8%) samples, in all ponds and growing seasons, and 14 serotypes detected. Six STEC genes were detected in samples: hly (83.3%), fliC (51.8%), eaeA (17.4%), rfbE (17.4%), stx-I (32.6%), stx-II (9.4%). While all ponds met the PSR requirements, at least one virulence gene from Salmonella (invA-4.8%) or STEC (stx-I-32.6%, stx-II-9.4%) was detected in each pond. Water quality for tested agricultural ponds, below recommended standards, did not guarantee the absence of pathogens. Investigating the relationships among physicochemical attributes, environmental factors, indicator microorganisms, and pathogen presence allows researchers to have a greater understanding of contamination risks from agricultural surface waters in the field.

Complex interactions between weather, and microbial and physiochemical water quality impact the likelihood of detecting foodborne pathogens in agricultural water

“…Overall these findings suggest that E. coli alone may not be a reliable indicator of the food safety risks associated with preharvest surface water use. The fact that other studies (Benjamin et al, 2013; Harwood et al, 2005; Havelaar et al, 2017; Ishii and Sadowsky, 2008; McEgan et al, 2013a; Pachepsky et al, 2015; Topalcengiz et al, 2017; Truitt et al, 2018) conducted out in other regions, in other years, and using different protocols reached the same conclusion as the study reported here, suggests that our conclusion is robust despite limitations associated with our study’s observational nature and time frame.…”

“…For example, turbidity was ranked as an important factor in 7 of the 15 random forest analyses performed here, and was associated detecting pathogens in samples collected from both AZ and NY waterways. Multiple studies (Christensen et al, 2000; Francy et al, 2013; Havelaar et al, 2017; Horman et al, 2004; Nagels et al, 2002; Rao et al, 2015; Topalcengiz et al, 2017), including the study reported here and the Ecuadorian study discussed above (Rao et al, 2015), found a positive association between E. coli levels and temperature, or between E. coli levels and turbidity. Francy et al (Francy et al, 2013) surveyed recreational water quality at 22 Ohio beaches along inland lakes and found that turbidity was one of the best predictors of E. coli levels.…”

Factors Impacting the Prevalence of Foodborne Pathogens in Agricultural Water Sources in the Southeastern United States

“…Therefore, using bacterial source tracking of fecal coliform isolates, the source of fecal coliform contamination found in water was suggested to come from human waste, especially during periods of increased rainfall in summer months, and from wild animals during the fall [74]. In contrast, two studies conducted across central Florida were unable to provide consistent evidence to correlate rainfall to microbial water quality in surface water [52,75]. In the first scenario, Salmonella were isolated from all water samples collected from 18 surface water sites including ponds, canals, rivers, and creeks far from animal agriculture over one year, indicating that the prevalence of Salmonella was possibly not due to runoff from livestock [52].…”

“…In the first scenario, Salmonella were isolated from all water samples collected from 18 surface water sites including ponds, canals, rivers, and creeks far from animal agriculture over one year, indicating that the prevalence of Salmonella was possibly not due to runoff from livestock [52]. In the second, rainfall occasionally influenced the prevalence of E. coli in water sampled from eight farm ponds during a period of 3 years [75]. These data may suggest that rainfall influences the prevalence of fecal contamination in surface water in several ways, and perhaps other factors such as resuspension of sediments and water dilution also directly affect the microbial concentration [76].…”

Evaluation of ultraviolet (UV‐C) light treatment for microbial inactivation in agricultural waters with different levels of turbidity

“…Although chlorine treatment is the most common practice for disinfecting municipal water, UV-C light treatment has also been applied by some municipalities (Hijnen et al, 2006). As the turbidity of groundwater and surface water is generally higher than municipal water (Topalcengiz, Strawn, & Danyluk, 2017), the efficacy of UV-C in these waters could be different. This study used a large volume of surface water and well water to simulate a water treatment system in agricultural settings (Jones, Worobo, & Smart, 2014).…”