**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** DETECTION OF BACTERIA IN FOOD AND AGRICULTURE ENVIRONMENTS IS VITAL FOR ENSURING THE SAFETY, SHELF LIFE, AND SECURITY OF FOOD. CURRENT DETECTION TECHNOLOGIES, HOWEVER, REQUIRE SIGNIFICANT HUMAN AND LABORATORY RESOURCES TO PROCESS AND PREPARE SAMPLES, RUN ANALYSIS, AND INTERPRET THE RESULTS, ULTIMATELY LIMITING THE EFFICIENCY AND SCALABILITY OF EXISTING ON-SITE PATHOGEN DETECTION SYSTEMS. TO ADDRESS THESE CHALLENGES, THE PROPOSED RESEARCH AIMS TO DEVELOP AN ARTIFICIAL INTELLIGENCE (AI) PLATFORM FOR THE DETECTION OF VIABLE BACTERIAL PATHOGENS THAT CAN DELIVER RESULTS WITHIN A SINGLE WORK SHIFT (LESS THAN 6 HOURS) AT A FOOD PRODUCTION FACILITY. THE SPECIFIC GOALS OF THIS RESEARCH ARE: (A) DEVELOP AN AI-BASED FRAMEWORK FOR SPECIFIC DETECTION OF VIABLE BACTERIAL PATHOGENS IN MIXED MICROBIAL CULTURES CONTAINING COMMENSAL MICROBES AND (B) EVALUATE POINT-OF-USE DETECTION OF TARGET PATHOGENS IN A SIMULATED LIMITED TESTING RESOURCE ENVIRONMENT USING AN AUTOMATED, LOW-COST EDGE AI DATA ACQUISITION AND ANALYSIS PLATFORM FOR FOOD AND ENVIRONMENTAL SAMPLES. THE RESEARCH PLAN IS BASED ON A COMBINATION OF AI AND BACTERIOPHAGES TO PROVIDE HIGHLY SPECIFIC AND RAPID DETECTION OF VIABLE PATHOGENS USING SIMPLE MICROSCOPY METHODS. BACTERIOPHAGES PROVIDES SPECIFIC MICROSCOPIC TRANSFORMATION OF TARGET VIABLE PATHOGENS THAT IS DETECTED USING AI BASED IMAGE ANALYSIS IN THE PRESENCE OF COMMENSAL BACTERIA. THE EDGE AI COMPUTE CAPABILITIES ENABLE DEPLOYMENT OF AI TECHNOLOGIES IN FIELD APPLICATIONS INCLUDING LOCAL MICRO LABS WITH LIMITED RESOURCES IN FOOD PROCESSING AND PACKING HOUSE FACILITIES. OVERALL THE PROPOSAL ADDRESSES THE UNMET NEEDS FOR RAPID AND SPECIFIC DETECTION OF LOW NUMBERS OF VIABLE PATHOGENS IN FOOD AND ENVIRONMENTAL SAMPLES.