4.4 Article

Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds

Journal

JOURNAL OF FOOD PROTECTION
Volume 86, Issue 3, Pages -

Publisher

INT ASSOC FOOD PROTECTION
DOI: 10.1016/j.jfp.2023.100045

Keywords

Escherichia coli; FSMA; Microbial water quality; Produce Safety Rule; Representative sample; Water testing

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This study aimed to understand the variation in microbial water quality within and between Virginia ponds. The results showed that spatial factors had a greater influence on water quality within ponds, while nonspatial factors were more significant between ponds. Rainfall was positively associated with microbial levels, while pH was negatively associated.
Surface water environments are inherently heterogenous, and little is known about variation in microbial water quality between locations. This study sought to understand how microbial water quality differs within and between Virginia ponds. Grab samples were collected twice per week from 30 sampling sites across nine Virginia ponds (n = 600). Samples (100 mL) were enumerated for total coliform (TC) and Escherichia coli (EC) levels, and physicochemical, weather, and environmental data were collected. Bayesian models of coregional-ization were used to quantify the variance in TC and EC levels attributable to spatial (e.g., site, pond) versus nonspatial (e.g., date, pH) sources. Mixed-effects Bayesian regressions and conditional inference trees were used to characterize relationships between data and TC or EC levels. Analyses were performed separately for each pond with >= 3 sampling sites (5 intrapond) while one interpond model was developed using data from all sampling sites and all ponds. More variance in TC levels were attributable to spatial opposed to nonspatial sources for the interpond model (variance ratio [VR] = 1.55) while intrapond models were pond dependent (VR: 0.65-18.89). For EC levels, more variance was attributable to spatial sources in the interpond model (VR = 1.62), compared to all intrapond models (VR < 1.0) suggesting that more variance is attributable to nonspatial factors within individual ponds and spatial factors when multiple ponds are considered. Within each pond, TC and EC levels were spatially independent for sites 56-87 m apart, indicating that different sites within the same pond represent different water quality for risk management. Rainfall was positively and pH negatively associated with TC and EC levels in both inter-and intrapond models. For all other factors, the direction and strength of associations varied. Factors driving microbial dynamics in ponds appear to be pond-specific and dif-fer depending on the spatial scale considered.

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