The overall goal of this project was to improve the tools used by the industry to ensure that thermal processes are meeting the USDA-FSIS lethality performance standards for ready-to-eat products. The specific objective was to improve the AMI Process Lethality Spreadsheet (AMI-PLS) by adding a user-friendly “front-end” that accounts for the effects of key product factors (e.g., species, fat content) on the thermal inactivation parameters for Salmonella.
According to the data analysis and modeling, the D-value for thermal inactivation of Salmonella in meat and poultry products could be successfully modeled in a general way, as a function of temperature, fat content, and moisture content. However, further research is needed to validate the model with independent results. Additionally, the confidence intervals (CI) for the D-value (and resulting lethality calculations) are still quite wide, because of the relatively large RMSE. Therefore, more data sets and/or advanced statistical simulations are needed to narrow the CI, to improve model accuracy, and to validate the model with independent data before the enhanced version of the AMI-PLS will be ready for distribution.
Models developed were integrated directly into the AMI-PLS, and a user-friendly “input box” was added, so that the user inputs the product characteristics, and the AMI-PLS calculates and utilizes product-specific D-values in the lethality calculations. The modified AMI-PLS also generates confidence intervals (±>95%) for direct prediction of lethality calculations (i.e., log reductions).