Browsing by Author "Danyluk, Michelle D."
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- Factors Associated With E. coli Levels in and Salmonella Contamination of Agricultural Water Differed Between North and South Florida WaterwaysMurphy, Claire M.; Strawn, Laura K.; Chapin, Travis K.; McEgan, Rachel; Gopidi, Sweeya; Friedrich, Loretta; Goodridge, Lawrence D.; Weller, Daniel L.; Schneider, Keith R.; Danyluk, Michelle D. (Frontiers, 2022-02-02)The microbial quality of agricultural water is often assessed using fecal indicator bacteria (FIB) and physicochemical parameters. The presence, direction, and strength of associations between microbial and physicochemical parameters, and the presence of human pathogens in surface water vary across space (e.g., region) and time. This study was undertaken to understand these associations in two produce-growing regions in Florida, USA, and to examine the pathogen ecology in waterways used for produce production. The relationship between Salmonella presence, and microbial and physicochemical water quality; as well as weather and land use factors were evaluated. Water samples were collected from six sites in North Florida (N = 72 samples) and eight sites in South Florida (N = 96 samples) over 12 sampling months. Land use around each sampling site was characterized, and weather and water quality data were collected at each sampling. Salmonella, generic Escherichia coli, total coliform, and aerobic plate count bacteria populations were enumerated in each sample. Univariable and multivariable regression models were then developed to characterize associations between microbial water quality (i.e., E. coli levels and Salmonella presence), and water quality, weather, and land use factors separately for North and South Florida. The E. coli and total coliforms mean concentrations (log(10) MPN/100 mL) were 1.8 +/- 0.6 and >3.0 +/- 0.4 in North and 1.3 +/- 0.6 and >3.3 +/- 0.2 in South Florida waterways, respectively. While Salmonella was detected in 23.6% (17/72) of North Florida and 28.1% (27/96) of South Florida samples, the concentration ranged between <0.48 and 1.4 log(10) MPN/100 mL in North Florida, and E. coli levels, and if a sample was Salmonella-positive. The factors associated with Salmonella presence and log(10) E. coli levels in North Florida differed from those in South Florida; no factors retrained in multivariable regression models were the same for the North and South Florida models. The differences in associations between regions highlight the complexity of understanding pathogen ecology in freshwater environments and suggest substantial differences between intra-state regions in risk factors for Salmonella contamination of agricultural water.
- Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safetyWeller, Daniel L.; Murphy, Claire M.; Love, Tanzy M. T.; Danyluk, Michelle D.; Strawn, Laura K. (American Society for Microbiology, 2024-01-12)Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.