PATHOGENS ARE A COMMON PROBLEM IN DRY FOODS, SUCH AS PEANUTS, WHICH CAUSEFOODBORNE ILLNESS OUTBREAKS. FOODBORNE ILLNESS OUTBREAKS HAVE AN ADVERSE IMPACT ON THE ECONOMY DUE TO LOST WORK TIME FROM SICK WORKERS, MEDICAL EXPENSES TO TREAT ILLNESSES, AND PRODUCT LOSS AND BRAND DAMAGE TO PROCESSORS. THIS CAN BE PARTICULARLY DETRIMENTAL TO SMALL PROCESSORS.ONE WAY TO HELP REDUCE POTENTIAL FOR FOODBORNE ILLNESS OUTBREAKS IS TO VALIDATE THERMAL PROCESSES FOR PATHOGEN REDUCTION, WHICH CAN BE ACHIEVED WITH MATHEMATICAL MODELING. ACCURATE MODELS THAT ARE BASED ON MEASURED VARIABLES AND PHYSICAL PHENOMENA ARE FLEXIBLE BECAUSE AS THE CONDITION CHANGES, THE MODEL CAN BE UPDATED TO MATCH THAT CONDITION. THIS PROJECT AIMS TO DEVELOP AND VALIDATE A MODEL FOR A PATHOGENIC SURROGATE, ENTEROCOCCUSFAECIUM, IN PEANUTS, BASED ON FUNDAMENTAL SCIENTIFIC PRINCIPLES OF HEAT AND MASS TRANSFER. FIRST, A HEAT AND MASS TRANSFER MODEL WILL BE DEVELOPED FOR PEANUTS UNDER TYPICAL ROASTING CONDITIONS. THIS MODEL WILL USE THERMAL AND PHYSICAL PROPERTIES OF PEANUTS AS INPUTSAND WILL PROVIDE SURFACE TEMPERATURE AND MOISTURE PROFILES AS OUTPUTS. THE MODEL WILL BE DEVELOPED FOR A SINGLE PEANUT, AND THEN SCALED UP TO A THICKER LAYER WITH MULTIPLE PEANUTS.THEN, PEANUTS INOCULATED WITH E. FAECIUM WILL BE TREATED AT MULTIPLE TEMPERATURES (121, 149, AND 177&DEG;C)AND AIR VELOCITIES (0.75 AND 1.25 M/S). SURFACE TEMPERATURE OF THE SAMPLES WILL BE MONITORED DURING THE HEATING PROCESS, AND MOISTURE CONTENT, WATER ACTIVITY, AND E. FAECIUM SURVIVORS WILL BE MEASURED AFTER HEATING. THESE TEMPERATURE AND MOISTURE CURVES WILL BE COMPARED TO THOSE DEVELOPED WITH THE HEAT AND MASS TRANSFER MODEL. FINALLY, THE MODELS WILL BE SCALED UP AND VALIDATED AT THE COMMERCIAL SCALE. BOTH INOCULATED SAMPLES AND TEMPERATURE PROFILES OF PEANUTS WILL BE USED FROM A COMMERCIAL-SCALE ROASTER. A STATISTICAL DISTRIBUTION OF E. FAECIUM REDUCTION WILL BE USED IN A RISK MODEL FOR SALMONELLOSIS RISK FROM PEANUTS TO DETERMINE THE RISK FOR THE ROASTER TESTED. THIS PROJECT WILL HELP ADVANCE RISK-BASED VALIDATION METHODS BY PROVIDING FLEXIBLEMODELING TOOLS FOR PROCESSORS TO USE IN VALIDATING THEIR PROCESSES. ADDITIONALLY, THIS STUDY WILL PROVIDE VALUABLE INSIGHT ON THE PERFORMANCE OF DRY ROASTERS OVER TIME WITH LONGITUDINAL TEMPERATURE DATA THAT CAN BE TRANSLATED INTO MICROBIAL INACTIVATION, POTENTIALLY HELPING TO REDUCE THE BURDEN OF PAYING FORVALIDATION EACH YEAR. THIS PROJECT WILL HELP PROCESSORS UNDERSTAND HOW TO REDUCE THE RISK OF FOODBORNE ILLNESSES IN DRY FOODS.