TO DATE MUCH OF THE FOCUS OF AGRICULTURAL RESEARCH HAS BEEN ON INCREASING YIELD RATHER THAN ENSURING THE STABILITY OF YIELDS WITHIN AND ACROSS REGIONS AND YEARS. IT IS OF COURSE IMPORTANT TO DEVELOP HIGHER YIELDING CROP VARIETIES. HOWEVER, INCREASINGLY VARIABLE WEATHER PATTERNS HAVE ALREADY BEGUN TO NEGATIVELY IMPACT AGRICULTURE. WE CURRENTLY LACK THE KNOWLEDGE AND TOOLS NECESSARY TO EFFICIENTLY DEVELOP RESILIENT CROP VARIETIES THAT WILL PROVIDE STABLE AND ECONOMICALLY VIABLE YIELDS ACROSS INCREASINGLY VARIABLE ENVIRONMENTS. THIS PROBLEM IS EXACERBATED BY THE FACT THAT BREEDING NEW CROP VARIETIES TAKES 7-10 YEARS, AND AT MANY LOCATIONS TODAY'S WEATHER MAY NOT BE AN ACCURATE REPRESENTATION OF THE SPECTRUM OF WEATHER NEW VARIETIES WILL EXPERIENCE AT THAT SAME LOCATIONS 10 YEARS FROM NOW. TO ADDRESS THE CHALLENGE OF BREEDING NEXT GENERATION RESILIENT CROP VARIETIES WE REQUIRE ACCURATE AND MECHANISTICALLY BASED MODELS THAT CAN PREDICT PHENOTYPIC OUTCOMES BASED ON GENETIC, ENVIRONMENTAL, AND CROP MANAGEMENT DATA. FORTUNATELY, ADVANCES IN THE PLANT SCIENCES, COMPUTATIONAL AND DATA SCIENCES, AND ENGINEERING OFFER THE POTENTIAL TO HELP US ADDRESS THIS CHALLENGE AND THEREBY CREATE A MORE SUSTAINABLE, RESILIENT AND PROFITABLE US AGRICULTURAL SYSTEM.DEVELOPING ACCURATE PREDICTIVE CROP MODELS REQUIRES AN ENHANCED UNDERSTANDING OF THE COMBINED EFFECT OF CROP VARIETY (G) AND ENVIRONMENT (9), GXE. THIS IN TURN REQUIRES LARGE COLLECTIONS OF PLANT TRAITS AND ENVIRONMENTAL DATA GATHERED FROM COMMON SETS OF CROP VARIETIES GROWN IN DIVERSE ENVIRONMENTS. WITH SUPPORT FROM STATE AND NATIONAL CORN GROWERS, THE GENOMES TO FIELDS (G2F) INITIATIVE HAS BEEN CONDUCTING COMMUNITY-BASED EXPERIMENTS TO DO JUST THAT. SINCE 2014, G2F PARTICIPANTS HAVE BEEN GENERATING AND ANALYZING GENOTYPIC, ENVIRONMENTAL, AND CROP MANAGEMENT DATA FROM COMMERCIALLY RELEVANT MAIZE GERMPLASM TO LEARN HOW GXE INTERACTIONS INFLUENCE PLANT TRAITS.THE PROPOSED PROJECT, G2F-HIPS, WILL SUPPORT AND INTENSIFY G2F BY DEPLOYING, EVALUATING AND VALIDATING A COMBINATION OF ESTABLISHED, IMAGE-BASED SENSING TECHNOLOGIES AND PROMISING NEW FIELD-BASED AGRICULTURAL SENSORS, GENERATING AND SHARING REFERENCE DATA TO FOSTER COMMUNITY INNOVATION, DEVELOPING AND DEMOCRATIZING ANALYSIS PIPELINES FOR PHENOTYPIC DATA, CONDUCTING PROOF-OF-PRINCIPLE RESEARCH PROJECTS TO IDENTIFY GENES RESPONSIBLE FOR CROP RESPONSES TO ENVIRONMENTAL VARIATION, AND CONTRIBUTING IN A SUBSTANTIAL MANNER TO THE TRAINING OF CURRENT AND FUTURE AGRICULTURAL RESEARCHERS TO MAKE USE OF THESE INNOVATIONS. AS SUCH, G2F-HIPS WILL PROMOTE THE WIDESPREAD ADOPTION OF NEW SENSING TECHNOLOGIES, METHODS OF DATA ANALYSIS AND THINKING ACROSS THE MANY G2F SITES. IN COMBINATION, THESE ACTIVITIES HAVE THE POTENTIAL TO FACILITATE A MORE MECHANISTIC UNDERSTANDING OF HOW PHENOTYPES RESPOND TO GENOTYPIC AND ENVIRONMENTAL VARIATION, THEREBY FACILITATING THE DEVELOPMENT OF MORE RESILIENT CROP VARIETIES THAT MAKE MORE EFFICIENT USE OF AGRICULTURAL INPUTS SUCH AS NITROGEN AND WATER, WITH CORRESPONDING ENVIRONMENTAL BENEFITS.