** 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 CENTRAL COAST REGION OF CALIFORNIA FACES SIGNIFICANT CHALLENGES IN WEED MANAGEMENT WITHIN SPECIALTY CROP SYSTEMS LIKE STRAWBERRIES, BROCCOLI, AND LEAFY GREEN VEGETABLES. TRADITIONAL METHODS, INCLUDING MANUAL WEEDING AND ROBOTIC WEEDERS BASED ON SHAPE DIFFERENCES BETWEEN CROPS AND WEEDS, ARE INCREASINGLY UNECONOMICAL DUE TO LABOR SHORTAGES AND HIGH COSTS. THIS PROJECT PROPOSES A NOVEL APPROACH: LEVERAGING HYPERSPECTRAL IMAGING (HSI) IN COMBINATION WITH MACHINE LEARNING TO REVOLUTIONIZE WEED CONTROL IN AGRICULTURAL SETTINGS. THIS TECHNIQUE USES SPECIALIZED CAMERAS TO MEASURE LIGHT REFLECTION AMONGPLANT SPECIES AS A WAY TO DIFFERENTIATE WEEDS FROM CROPS.HSI OFFERS A SIGNIFICANT ADVANTAGE OVER CONVENTIONAL METHODS OF WEED MANAGEMENT. IT IS EFFECTIVE EVEN IN COMPLEX SCENARIOS LIKE PARTIAL VISIBILITY OF WEEDSOR SIZE VARIATIONS, AND IS ADAPTABLE TO DIFFERENT PLANTING METHODS. OUR OBJECTIVE IS TO HARNESS HSI'S POTENTIAL, CREATING AN EXTENSIVE DATASET OF HYPERSPECTRAL AND DIGITAL IMAGES. THIS DATASET WILL FOCUS ON WEEDS COEXISTING WITH LEAFY GREEN SPECIALTY CROPS, PARTICULARLY THOSE THAT HOST ECONOMICALLY DAMAGING DISEASES.