{"id":35313,"date":"2024-08-20T11:09:12","date_gmt":"2024-08-20T15:09:12","guid":{"rendered":"https:\/\/www.eng.ufl.edu\/newengineer\/?p=35313"},"modified":"2025-06-11T12:26:56","modified_gmt":"2025-06-11T17:26:56","slug":"uf-scientists-use-ai-algorithm-to-improve-strawberry-disease-detection","status":"publish","type":"post","link":"https:\/\/www.eng.ufl.edu\/news\/department-of-agricultural-and-biological-engineering\/uf-scientists-use-ai-algorithm-to-improve-strawberry-disease-detection\/","title":{"rendered":"UF scientists use AI algorithm to improve strawberry disease detection"},"content":{"rendered":"\n

Florida\u2019s strawberry season doesn\u2019t 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<\/a>.<\/p>\n\n\n\n

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

Most of Florida\u2019s 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<\/a> (SAS) to tell them when to spray fungicides to prevent plant diseases.<\/p>\n\n\n\n

SAS works with data generated by Florida Automated Weather Network<\/a> stations near farms \u2013 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.<\/p>\n\n\n\n

In newly published research<\/a>, Won Suk \u201cDaniel\u201d Lee, a professor of agricultural and biological engineering<\/a> and Natalia Peres, a professor of plant pathology<\/a>, show how artificial intelligence (AI) can improve leaf wetness detection.<\/p>\n\n\n\n

Read full story on UF IFAS Blogs<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

In newly published research, Won Suk \u201cDaniel\u201d 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 to help growers estimate the risk of their fruit getting infected with a fungal disease.<\/p>\n","protected":false},"author":2592,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-templates\/single-sidebar-none.php","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[9,61,57],"tags":[399],"class_list":["post-35313","post","type-post","status-publish","format-standard","hentry","category-department-of-agricultural-and-biological-engineering","category-research-innovation","category-stories","tag-wonsuk-daniel-lee"],"acf":[],"yoast_head":"\nUF scientists use AI algorithm to improve strawberry disease detection - 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