PLANT BREEDING AND AGRONOMIC TECHNOLOGY IMPROVEMENTS HAVE IMPROVED YIELDS OF SOME CROPS NINE FOLD IN THE LAST 120 YEARS, MEANING NINE FOLD LESS LAND IS NEED TO PRODUCE THE SAME AMOUNT OF FOOD. THIS HAS ALLOWED MORE LAND TO BE USED FOR RECREATION, URBANIZATION OR PRODUCING MORE FOOD FIBER AND FUEL SUSTAINABLY FOR A GROWING HUMAN POPULATION. STILL FURTHER IMPROVEMENT OF CROP SELECTION ABILITIES IS NEEDED TO MAKE PLANT BREEDING MORE RESOURCE-EFFICIENT AND RESPONSIVE TO ENVIRONMENTAL CHANGES FOR A GROWING POPULATION. UNOCCUPIED AERIAL SYSTEMS (UASS, AKA DRONES) HAVE PROVEN USEFUL AS TOOLS TO AUTOMATE ROUTINE MEASUREMENTS IN PLANT BREEDING AND INCREASINGLY TO MEASURE TRAITS PREVIOUSLY IMPOSSIBLE OR INFEASIBLE WITH MANUAL APPROACHES. NEW STATISTICAL PREDICTION APPROACHES USING UAS INFORMATION COLLECTED THROUGHOUT THE GROWING SEASON COULD ALLOW ACCURATE SELECTIONS TO BE MADE BEFORE HARVEST, SPEEDING THE BREEDING CYCLE AND EXTENDING RESOURCES. THE OVERALL GOAL OF THIS PROJECT IS TO EVALUATE IF PLANT SELECTION USING MANY PHENOTYPES MEASURED BY UAS CAN IMPROVE THE SPEED AND ACCURACY OF DECISION-MAKING COMPARED WITH CONVENTIONAL PHENOTYPIC SELECTIONS; LEVERAGING A PUBLIC MAIZE (CORN, ZEA MAYS L.) BREEDING PROGRAM AS A CASE STUDY. SPECIFICALLY IN THIS PROJECT WE WILL COLLECT UAS IMAGERY OF LARGE BREEDING POPULATIONS WEEKLY THROUGHOUT THE GROWING SEASON AND EXTRACT DOZENS OF MEASUREMENTS PER FLIGHT; DEVELOP IMPROVED STATISTICAL MODELS THAT IDENTIFY AND MINIMIZE ERROR USING UAS FIELD MEASUREMENTS OVER TIME AND SPACE; THEN APPLY UAS AND GRAIN-BASED PHENOMIC SELECTION MODELS TO SELECT THE VARIETIES WITH THE MOST IMPROVED YIELD. MAIZE IS AMONG THE MOST PRODUCTIVE CROPS IN THE U.S., BUT COMPARATIVELY LITTLE IMPROVEMENT HAS OCCURRED ACROSS THE SOUTHERN U.S. IMPROVED LINES FROM TROPICAL GERMPLASM WILL HELP SOUTHERN GROWERS, AND ALSO ENHANCE ADAPTATION TO STRESSES EXPECTED THROUGHOUT THE ENTIRE U.S. UNDER A CHANGING CLIMATE. THIS PROJECT WILL LEVERAGE, ADVANCE AND DEPLOY UAS ANALYSIS APPROACHES INTO PUBLIC TOOLS. THE MAJOR OUTPUTS WILL INCLUDE TRANSFORMATIVE SELECTION AND STATISTICAL METHODOLOGIES THAT WILL IMPROVE PLANT BREEDING IN ALL CROPS, NEW MAIZE GERMPLASM FOR CURRENT AND FUTURE FARMERS, AND POSSIBLY DISCOVERY OF FUNDAMENTAL BIOLOGICAL INDICATORS THAT CAN HELP BETTER UNDERSTAND THE BIOLOGICAL ADAPTATION OF MAIZE.