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This collaborative project will integrate applied research in three areas: short-term temperature abuse of uncooked meat and poultry products, slow-cooking and/or fermentation of meat and poultry products, and low-heat processing of ready-to-eat meat and poultry products, with extension to meet four project objectives: <ol><LI> To meet Critical Limit validation needs of meat and poultry processors by performing lab and pilot plant-based challenge studies;
<LI> To provide challenge study validation of computer-gernerated predictive models of pathogen growth in meat and poultry products;
<LI> To develop computer-generated predictive models of pathogen growth in meat and poultry products; and
<LI>To develop outreach materials that widely disseminate the results of challenge studies and predictive models to various groups: to meat and poultry processors for use in validation and verification of HACCP plans, to industry groups and extension specialists for use in training and to state and federal regulators. </OL>
The range of formulations (e.g., salt, moisture, additive contents etc) and time/temperature conditions commonly used in manufacturing of RTE meat and poultry products will first be identified to obtain test parameters for this research. Challenge studies will be conducted to establish response of L. monocytogenes, Salmonella spp., or E. coli O157:H7 in RTE meat and poultry products during low-heat processing and/or fermentation. This information will be used to develop growth/inactivation models of L. monocytogenes, Salmonella spp., or E. coli O157:H7 in these products with various formulations during low-heat processing of various time/temperature conditions. Products with various formulations will be inoculated with a multi-strain cocktail of L. monocytogenes, Salmonella spp., or E. coli O157:H7 to an inoculum of 103 CFU/g. Each cocktail will consist of a minimum 4 strains, all associated with meat/poultry-related outbreaks. The inoculated products will then be processed under various time/temperature conditions. At various points samples will be analyzed for numbers of inoculum species. Growth/inactivation indicators (e.g., lag phase duration and growth rate) of each inoculated microorganism will be obtained and used to generate models that describe the behaviors of L. monocytogenes, Salmonella spp., or E. coli O157:H7 under various formulation and time/temperature conditions. The models will be validated with selected formulations and time/temperature conditions that are not included in the model generation test.