Machine learning calibration of biosensors for microcystin toxin monitoring in freshwater

Machine learning calibration of biosensors for microcystin toxin monitoring in freshwater

Portable screen-printed carbon electrode (SPCE) biosensors offer a rapid, low-cost way to detect microcystin-lysine-arginine (MC-LR), an extremely potent toxin produced by cyanobacteria during harmful algal blooms in freshwater. Even at low concentrations, MC-LR can damage the liver and has been linked to an increased risk of liver and colon cancer, and the World Health Organization has set a guideline value of 1 microgram per liter for MC-LR in drinking water.