ArticleFrontiers in microbiology2025
Water metagenomes reflect physicochemical water quality throughout a model agricultural pond.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Conditional superiorities and unaddressed bottlenecks: a critical review of artificial intelligence for waterborne microbial detection.Applied microbiology and biotechnology · 2026Review
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5 authors.
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Abstract
Agricultural ponds are essential irrigation resources, though may also serve as reservoirs for pathogens and antimicrobial resistance (AMR) genes. While monitoring microbiological water quality is critical for food safety, the influence of sampling factors (e.g., when and where to collect samples) in making risk assessments and potential applications for using environmental covariates as indicators remain unclear. Here, we explored the hypothesis that metagenomes of agricultural waters change with spatiotemporal shifts in physicochemical water quality, i.e., across water depths over time. Water samples and underlying sediments were collected at a model pond at the surface and within the water column (0, 1, 2 m depths) throughout one day (i.e., 9:00, 12:00, 15:00). All samples were processed for shotgun metagenomic sequencing analysis and enumeration of various water quality parameters (e.g., temperature, nutrient concentrations, turbidity, pH, culturable
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