No current modeling tool accounts for all the necessary factors to validate a thermal process for ready-to-eat (RTE) meat and poultry; some do not address Salmonella and/or important product/process attributes, and most have not been validated against industry-relevant data. Therefore, the objective of this project was to develop a multi-product, multi-factor thermal inactivation model for Salmonella in meat and poultry products. First, the effect of sublethal thermal injury on subsequent bacterial heat resistance was quantified by expanding the capabilities of a previously published path-dependent Salmonella inactivation model. Salmonella inoculated ground turkey, beef, and pork samples were subjected to multiple non-isothermal treatments. The resulting path-dependent model was validated against equivalent data, showing error reductions of 63 to 82%, relative to the state-dependent model, thus confirming the importance of accounting for sublethal injury in inactivation models. In the second part, thermal inactivation data for Salmonella in turkey, beef, and pork were selected from published sources (nobs=411, 764, and 446 for each, respectively) and used to parameterize various versions of a multi-product, multi-factor model, using ordinary least squares and mixed-effects statistical methods. Validated against industry-relevant data, most models performed favorably when considering fat content, sublethal injury, and muscle structure. Overall, this project illustrated the current difficulties and positive outcomes of pooling thermal inactivation data from different sources, parameterizing models with them, and validating them against industry-relevant data.
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