** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** INCREASES IN GLOBAL MEAN TEMPERATURES, CO2 CONCENTRATIONS, VARIABLE PRECIPITATION AND HUMIDITY ARE AFFECTING CROP WATER USE EFFICIENCY (WUE). RECENT STUDIES HAVE SHOWN THAT SOYBEAN WUE DECREASES WITH INCREASING SEASONAL TEMPERATURES, DESPITE GAINS FROM ELEVATED CO2. IT WAS ALSO SHOWN THAT SOYBEAN LEAF SHAPE AND CANOPY ARCHITECTURE COULD INFLUENCE LIGHT AND WATER USE EFFICIENCY. HOWEVER, THE COMPLEX INTERACTIONS AMONG [CO2], TEMPERATURE, AND SOIL MOISTURE WITH VARIABLE CANOPY ARCHITECTURES HAVE NOT BEEN STUDIED. WE PROPOSE TO ADDRESS A1152 PROGRAM AREA PRIORITIES A AND B BY INVESTIGATING THE RELATIONSHIP AMONG PLANT ARCHITECTURE, CARBON ASSIMILATION, AND WUE AS THEY INHERENTLY RELATE TO SOYBEAN PRODUCTIVITY. THE OVERALL GOAL OF THIS PROJECT IS TO PREDICT OPTIMAL SOYBEAN CANOPY ARCHITECTURE FOR MAXIMUM LIGHT CAPTURE AND WUE UNDER FUTURE CLIMATE SCENARIOS. SPECIFIC OBJECTIVES INCLUDE: 1. CREATE A DIGITAL SOYBEAN CANOPY WITH DETAILED 3D-GEOMETRY, ILLUMINATION, AND MICROCLIMATE DATA. 2. APPLY ALGORITHMS FOR THE FAST CALCULATION OF LIGHT DISTRIBUTION THROUGHOUT THE CANOPY UNDER VARYING ARCHITECTURES AND SEEDING STRATEGIES. 3. PERFORM INTEGRATIVE MODELING TO ESTIMATE THE PHOTOSYNTHETIC AND WUE OF SOY CANOPIES OPTIMIZED FOR LIGHT CAPTURE UNDER VARIABLE CLIMATE CONDITIONS. THESE OBJECTIVES WILL BE ACCOMPLISHED BY DEVELOPING, TESTING, AND OPTIMIZING A DIGITAL TWIN THAT EXTENDS THE IDEA OF PLANT IDEOTYPES INTO INTERACTIVE, AI-BASED, 3D COMPUTER SIMULATIONS USING PROCEDURAL MODELING WITH AN ADVANCED LIGHT TRANSPORTATION MODEL. MODEL OUTPUTS WILL INFORM SHORT-TERM RECOMMENDATIONS INVOLVING SELECTION AND MANAGEMENT STRATEGIES, AS WELL AS LONG-TERM RECOMMENDATIONS FOR TARGETING STRUCTURAL TRAITS WITH GENETIC MODIFICATION.