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Determining the Likelihood that Salmonella Develops Heat Resistance during Thermal Processing of Commercial, Whole-Muscle, Ready-to-Eat Meat Products


The objectives of this research were to modifying a new thermal inactivation model that accounts for the effect of sub-lethal injury on subsequent heat resistance of Salmonella; validate the model via laboratory- and pilot-scale challenge studies, and; evaluate whether the resulting increase in Salmonella thermal resistance has practical impact on the compliance of typical commercial cooking operations with USDA-FSIS lethality performance standards for ready-to-eat (RTE) products.

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Salmonella can develop significantly increased thermal resistance due to sub-lethal injury that can occur during slow cooking of whole-muscle meat and poultry products. Traditional inactivation models (D and z) based on isothermal inactivation studies can significantly over-predict the actual lethality of Salmonella in slow-cooked meat and poultry products, with the degree of over-prediction increasing with the extent of sub-lethal heating. The uncertainty underlying thermal process validations increases significantly when scaling predictions from laboratory- to pilot-scale (and presumably commercial-scale) applications. Whole-muscle turkey and beef products cooked in a moist-air convection oven to a core temperature of 71.1°C (160°C) all exceeded the lethality performance standards. There was a significant risk of not achieving the lethality performance standards for whole-muscle turkey and beef products cooked just to the target lethality (i.e., 7.0 or 6.5 log10 reductions, respectively), computed via traditional methods (D and z from laboratory studies). Therefore, particular caution (and/or improved modeling methods) should be exercised for marginally-processed products.
Deliverable <br/>

These results can be translated with a concurrent funded USDA project into a web-based process lethality tool that will account for the effects of product species, structure, composition, and heating profile (including sub-lethal injury) in computing process lethality and reliable estimates of uncertainty.

Ryser, Elliot; Orta-Ramirez, Alicia ; Marks, Bradley; Booren, Alden
Michigan State University
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