ArticleApplied and environmental microbiology2013
Predicting Salmonella populations from biological, chemical, and physical indicators in Florida surface waters.
Article in Applied and environmental microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
49 citing papers in PubMed.
- Salmonella enterica serovars co-exist sporadically and at low abundance in US mid-Atlantic irrigation ponds.Journal of the science of food and agriculture · 2026Article
- Microbial bioindicators for multidimensional assessment of environmental alterations and ecosystem functioning.World journal of microbiology & biotechnology · 2026Review
- Efficacy of peracetic acid and chlorine in managingApplied and environmental microbiology · 2026Article
- A two-year study ofApplied and environmental microbiology · 2025Article
- Recent developments in waterborne pathogen detection technologies.Environmental monitoring and assessment · 2025Review
- Article
- Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety.Applied and environmental microbiology · 2024Article
- Prevalence of STEC virulence markers andFrontiers in microbiology · 2024Article
- Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data.Journal of applied microbiology · 2023Article
- Conditional Forest Models Built Using Metagenomic Data Accurately PredictedMicrobiology spectrum · 2023Article
- Salmonella Prevalence Is Strongly Associated with Spatial Factors while Listeria monocytogenes Prevalence Is Strongly Associated with Temporal Factors on Virginia Produce Farms.Applied and environmental microbiology · 2023Article
- Prevalence and Genomic Diversity ofMicroorganisms · 2022Article
- Correlation value determined to increase Salmonella prediction success of deep neural network for agricultural waters.Environmental monitoring and assessment · 2022Article
- Genomic Epidemiology of Salmonella enterica Circulating in Surface Waters Used in Agriculture and Aquaculture in Central Mexico.Applied and environmental microbiology · 2022Article
- Humans and Hoofed Livestock Are the Main Sources of Fecal Contamination of Rivers Used for Crop Irrigation: A Microbial Source Tracking Approach.Frontiers in microbiology · 2022Article
- Levels of Salmonella enterica and Listeria monocytogenes in Alternative Irrigation Water Vary Based on Water Source on the Eastern Shore of Maryland.Microbiology spectrum · 2021Article
- The Persistence of Bacterial Pathogens in Surface Water and Its Impact on Global Food Safety.Pathogens (Basel, Switzerland) · 2021Review
- Pathogen and Surrogate Survival in Relation to Fecal Indicator Bacteria in Freshwater Mesocosms.Applied and environmental microbiology · 2021Article
- Article
- Prediction ofFrontiers in artificial intelligence · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coliforms, Escherichia coli, and various physicochemical water characteristics have been suggested as indicators of microbial water quality or index organisms for pathogen populations. The relationship between the presence and/or concentration of Salmonella and biological, physical, or chemical indicators in Central Florida surface water samples over 12 consecutive months was explored. Samples were taken monthly for 12 months from 18 locations throughout Central Florida (n = 202). Air and water temperature, pH, oxidation-reduction potential (ORP), turbidity, and conductivity were measured. Weather data were obtained from nearby weather stations. Aerobic plate counts and most probable numbers (MPN) for Salmonella, E. coli, and coliforms were performed. Weak linear relationships existed between biological indicators (E. coli/coliforms) and Salmonella levels (R(2) < 0.1) and between physicochemical indicators and Salmonella levels (R(2) < 0.1). The average rainfall (previous day, week, and month) before sampling did not correlate well with bacterial levels. Logistic regression analysis showed that E. coli concentration can predict the probability of enumerating selected Salmonella levels. The lack of good correlations between biological indicators and Salmonella levels and between physicochemical indicators and Salmonella levels shows that the relationship between pathogens and indicators is complex. However, Escherichia coli provides a reasonable way to predict Salmonella levels in Central Florida surface water through logistic regression.
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