** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** PLANT DISEASES CAUSE 20 TO 40% OF GLOBAL CROP LOSS ANNUALLY, RESULTING IN ESTIMATED ECONOMIC LOSSES OF $30 BILLION TO $50 BILLION ANNUALLY. PRECISE PLANT DISEASE PHENOTYPING IS CRUCIAL TO SELECTING PLANTS IN RESISTANCE BREEDING PROGRAMS FOR DEVELOPING BETTER DISEASE-MANAGEMENT STRATEGIES. HOWEVER, TRADITIONAL SELECTION PRACTICES FOR DESIRABLE PHENOTYPE RELATED TO PLANT DISEASES AND YIELD IS IN-FIELD MANUAL SCOUTING, A LABOR-INTENSIVE, SUBJECTIVE, AND INEFFICIENT PROCESS WHICH CONSIDERABLY LIMITS EXPERIMENT SCALE AND DATA ACQUISITION FREQUENCY. WE PROPOSE A DYNAMIC IN-FIELD PHENOTYPING SYSTEM FOR MONITORING DISEASE-RELATED TRAITS ACROSS MULTIPLE SCALES AND ENVIRONMENTS TO EXPEDITE GENOMIC RESEARCH. IN THIS PROJECT, WE WILL USE TOMATO PRODUCTION AS OUR MODEL SYSTEM FOR OPTIMIZATION, TOMATO IS A MAJOR INDUSTRY IN THE SOUTHEASTERN UNITED STATES.