UF scientists use AI algorithm to improve strawberry disease detection

In Department of Agricultural and Biological Engineering, News, Research & InnovationBy Brad BuckStory originally published on UF IFAS News

Florida’s strawberry season doesn’t return until December. But University of Florida scientists work year-round to support an industry with a $500 million-a-year farm-gate value in Florida.

Among their research endeavors, UF/IFAS scientists search for ways to help growers control diseases that can damage strawberries.

Most of Florida’s 13,500 acres of strawberries grow in Hillsborough, Polk and Manatee counties. For over a decade, Florida farmers have used the UF/IFAS-designed Strawberry Advisory System (SAS) to tell them when to spray fungicides to prevent plant diseases.

SAS works with data generated by Florida Automated Weather Network stations near farms – in this case, near strawberry fields. SAS uses leaf wetness duration to help growers estimate the risk of their fruit getting infected with a fungal disease.

In newly published research, Won Suk “Daniel” Lee, a professor of agricultural and biological engineering and Natalia Peres, a professor of plant pathology, show how artificial intelligence (AI) can improve leaf wetness detection.

Read full story on UF IFAS Blogs

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