T5-09 Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions

Monday, August 1, 2016: 4:00 PM
241 (America's Center - St. Louis)
Lihan Huang, U.S. Department of Agriculture-ARS-ERRC, Wyndmoor, PA
Introduction: Clostridium perfringens Type A is a significant public health threat. It may germinate, outgrow, and multiply during cooling of cooked meats.  Computer simulation may be used to evaluate the growth of C. perfringens in cooked meats during cooling.

Purpose: The objective of this study is to evaluate the performance of a new C. perfringens growth model in IPMP Dynamic Prediction for predicting its growth under dynamic cooling, isothermal, and dynamic heating temperature profiles. 

Methods: Computer simulation is used to predict the growth of C. perfringens under different temperature profiles.  The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square errors (RMSE) calculated.

Results: For isothermal and heating profiles, each data point in growth curves is compared.  The mean residual errors of predictions (MRE) range from -0.40 to 0.02 log CFU/g, with a RMSE of ~0.6 log CFU/g.  For cooling, the end-point predictions are conservative in nature, with an MRE of -1.16 log CFU/g for single rate cooling and -0.66 log CFU/g for dual rate cooling.  The RMSE is between 0.6 and 0.7 log CFU/g.  Compared with other models reported in Mohr and others (2015), this model makes comparable or mostly better accurate and fail-safe predictions.  For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%.  Under criterion 1, the percentage of accurate predictions is 47.5% for single rate and 66.7% for dual rate cooling, while the fail-dangerous predictions are between 0 and 2.4%. 

Significance: This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules.  This study also demonstrates the need for more accurate data collection during cooling.