**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 CONVENTIONAL MANAGEMENT APPROACH IN AGRICULTURAL PRODUCTION IS APPLYING WATER AND CHEMICALS AT A FIXED RATE THROUGHOUT THE WHOLE FIELD. THIS PRACTICE DID NOT CONSIDER THE EXISTENCE OF IN-FIELD VARIABILITY IN SPATIAL AND TEMPORAL DOMAINS AND RESULTS IN OVER- AND UNDER-APPLICATIONS ON CROP AND SERIOUS ENVIRONMENT ISSUES SUCH AS NITROGEN LEAKING TO AND CONTAMINATION OF GROUNDWATER. VARIABLE-RATE TECHNOLOGY IS THE KEY TECHNOLOGY IN AGRICULTURAL PRODUCTION TO ADDRESS THE IN-FIELD VARIABILITY, MAXIMIZE YIELD AND PROFIT, AND MINIMIZE THE AGRICULTURAL INPUTS OR FOOTPRINTS ON THE ENVIRONMENT. HENCE, THIS PROJECT PULLS A MULTIDISCIPLINARY EFFORT TO ADDRESS CHALLENGES IN TODAY'S VARIABLE-RATE TECHNOLOGY (VRT) IN AGRICULTURAL PRODUCTION BY TIGHTLY INTEGRATING SENSING, NETWORKING, AI-BASED AND PROCESS-BASED DATA ANALYTICS, AND CONTROL SYSTEMS WITH CLASSIC PLANT AND SOIL BIOPHYSICAL PRINCIPLES AND WELL-RECOGNIZED MANAGEMENT PRACTICES, TO PROVIDE A GENERALIZABLE AND SCALABLE FRAMEWORK FOR THE REAL-TIME IN-SEASON VARIABLE-RATE APPLICATION. MEANWHILE, IT ALSO IMPROVES THE DATA ANALYTICS AND DECISION-MAKING MODELS BY TURNING THE MASSIVE AMOUNT OF DATA GENERATED IN DAILY AGRICULTURAL PRODUCTION INTO A DYNAMIC AND DISTRIBUTED TRAINING PROCESS FOR MODEL SELF-IMPROVING WHILE KEEPING THE FARMERS' PRIVACY AND COMPUTATIONAL EFFICIENCY.