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** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THE OVERALL GOAL OF THIS PROJECT IS TO DEVELOP A REAL-TIME YIELD PREDICTION SYSTEM FOR STRAWBERRY PRODUCTION. THERE ARE SEVERAL MAJOR FRUIT WAVES DURING A STRAWBERRY GROWING SEASON WHEN MANY STRAWBERRIES NEED TO BE HARVESTED. THE PROBLEM IS THAT THE GROWERS DON'T ALWAYS KNOW IN ADVANCE WHEN MAJOR FRUIT WAVES COME. ONE WAY TO PREDICT MAJOR FRUIT WAVES IS TO COUNT THE CURRENT NUMBER OF FLOWERS, AND THEN THE GROWERS CAN ESTIMATE SHORT-TERM YIELD SINCE IT TAKES ABOUT 3-4 WEEKS FOR FLOWERS TO BECOME MATURE FRUIT. THUS, WE PROPOSE REAL-TIME AUTOMATED FLOWER AND FRUIT COUNTING AND CANOPY VOLUME MEASUREMENT USING MACHINE VISION AND ARTIFICIAL INTELLIGENCE (AI) INSTALLED ON COMMONLY USED SPRAYERS. STRAWBERRY GROWERS NEED TO PROVIDE FOOD RETAILERS WITH AT LEAST THREE WEEKS' NOTICE OF ANTICIPATED FRUIT VOLUME. THE PREDICTION OF STRAWBERRY YIELD UP TO A FEW WEEKS IN ADVANCE WOULD HELP THE MARKETING AND DISTRIBUTION LOGISTICS, AND INTRA-MARKET COMPETITION MINIMIZED. IN REALITY, FARMERS ESTIMATE ANTICIPATED FRUIT VOLUME BASED ON PAST SEASONS' YIELD, WHICH MAY HAVE A SIGNIFICANT BIAS. THIS PROJECT PROPOSES TO EXTEND THE PREVIOUS EFFORTS TO PREDICT STRAWBERRY YIELD USING PLANT MEASUREMENTS, STATISTICAL ANALYSIS, DISEASE PREDICTION MODELS, AND AI. ALSO, WE PROPOSE TO DEVELOP USER-FRIENDLY WEB-BASED REAL-TIME PROCESSING SOFTWARE TO VISUALIZE FLOWER AND FRUIT DISTRIBUTION AND CREATE PREDICTED YIELD MAPS FOR GROWERS. WE WILL EXPLORE THE POSSIBILITY OF INTEGRATING THIS TECHNOLOGY IN A MECHANICAL STRAWBERRY HARVESTER.

$617,420FY2023National Institute of Food and AgricultureUSDA

University Of Florida, Gainesville FL

Investigators

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** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THE OVERALL GOAL OF THIS PROJECT IS TO DEVELOP A REAL-TIME YIELD PREDICTION SYSTEM FOR STRAWBERRY PRODUCTION. THERE ARE SEVERAL MAJOR FRUIT WAVES DURING A STRAWBERRY GROWING SEASON WHEN MANY STRAWBERRIES NEED TO BE HARVESTED. THE PROBLEM IS THAT THE GROWERS DON'T ALWAYS KNOW IN ADVANCE WHEN MAJOR FRUIT WAVES COME. ONE WAY TO PREDICT MAJOR FRUIT WAVES IS TO COUNT THE CURRENT NUMBER OF FLOWERS, AND THEN THE GROWERS CAN ESTIMATE SHORT-TERM YIELD SINCE IT TAKES ABOUT 3-4 WEEKS FOR FLOWERS TO BECOME MATURE FRUIT. THUS, WE PROPOSE REAL-TIME AUTOMATED FLOWER AND FRUIT COUNTING AND CANOPY VOLUME MEASUREMENT USING MACHINE VISION AND ARTIFICIAL INTELLIGENCE (AI) INSTALLED ON COMMONLY USED SPRAYERS. STRAWBERRY GROWERS NEED TO PROVIDE FOOD RETAILERS WITH AT LEAST THREE WEEKS' NOTICE OF ANTICIPATED FRUIT VOLUME. THE PREDICTION OF STRAWBERRY YIELD UP TO A FEW WEEKS IN ADVANCE WOULD HELP THE MARKETING AND DISTRIBUTION LOGISTICS, AND INTRA-MARKET COMPETITION MINIMIZED. IN REALITY, FARMERS ESTIMATE ANTICIPATED FRUIT VOLUME BASED ON PAST SEASONS' YIELD, WHICH MAY HAVE A SIGNIFICANT BIAS. THIS PROJECT PROPOSES TO EXTEND THE PREVIOUS EFFORTS TO PREDICT STRAWBERRY YIELD USING PLANT MEASUREMENTS, STATISTICAL ANALYSIS, DISEASE PREDICTION MODELS, AND AI. ALSO, WE PROPOSE TO DEVELOP USER-FRIENDLY WEB-BASED REAL-TIME PROCESSING SOFTWARE TO VISUALIZE FLOWER AND FRUIT DISTRIBUTION AND CREATE PREDICTED YIELD MAPS FOR GROWERS. WE WILL EXPLORE THE POSSIBILITY OF INTEGRATING THIS TECHNOLOGY IN A MECHANICAL STRAWBERRY HARVESTER. · GrantIndex