Natalia Peres, associate professor of plant pathology at the University of Florida, led development of a Web-based disease forecasting tool for strawberry growers.
Natalia Peres, associate professor of plant pathology at the University of Florida, led development of a Web-based disease forecasting tool for strawberry growers.

A strawberry disease prediction system that lets growers know when disease chances are high and they should spray is expanding to South Carolina from Florida.

The Web-based system, which factors in weather data to alert growers when to apply fungicides, was developed by group led by Natalia Peres, an associate professor of plant pathology at the University of Florida's Gulf Coast Research and Education Center in Balm.

She recently received the Lee M. Hutchins Award from the American Phytopathological Society in recognition of her work, according to a news release.

Peres says she expects the system to be used in South Carolina this spring. She also has tested it in Iowa, North Carolina and Ohio.

Although the system proved successful in the latter three states, scientists say they must work out how growers can automatically access the weather data.

Peres also has won a $114,000 U.S. Department of Agriculture grant to develop a similar disease-prediction system for blueberries. It is expected to take about two years to develop.

The Strawberry Advisory System, which was released in 2012, was developed with the help of Clyde Fraisse, a UF associate professor of agricultural and biological engineering.

Growers log onto the Website and can check the risk of anthracnose fruit rot and Botrytis gray mold developing. If the risk is low, they may choose not to spray.

Before the system, many growers sprayed based on the calendar, applying fungicides weekly during the November-to-March growing season.

Now they can withhold applications when the risk of disease development is low and better time their applications to when the disease risks are high.

Growers also have the option of receiving emails or text alerts about the disease risk.