Persistence of Microcystin in Three Agricultural Ponds in Georgia, USA.

Cyanobacteria and their toxins can have multiple effects on agricultural productivity and water bodies. Cyanotoxins can be transported to nearby crops and fields during irrigation and may pose a risk to animal health through water sources. Spatial and temporal variations in cyanotoxin concentrations have been reported for large freshwater sources such as lakes and reservoirs, but there are fewer studies on smaller agricultural surface water bodies.

Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.

The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations.

Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water.

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e.