This research applied a new 1-step methodology to directly construct a tertiary model that describes the growth of Clostridium perfringens in cooked turkey meat under dynamically cooling conditions. The kinetic parameters of the growth models were determined by numerical analysis and optimization using multiple dynamic growth curves. The models and kinetic parameters were validated using independent growth curves obtained under various cooling conditions. The results showed that the residual errors (å) of the predictions followed a Laplace distribution that is symmetric with respect to å = 0. For residual errors, 90.6% are within ±0.5 Log CFU/g and 73.4% are ±0.25 Log CFU/g for all growth curves used for validation. For relative growth <1.0 Log CFU/g, 88.9% of the residual errors are within ±0.5 Log CFU/g, and 63.0% are within ±0.25 Log CFU/g. For relative growth of <2.0 Log CFU/g, 92.7% of the residual errors are within ±0.5 Log CFU/g, and 70.3% are within ±0.25 Log CFU/g. The scale and distribution of residual errors clearly suggests that the models and estimated kinetic parameters are reasonably accurate in predicting the growth of C. perfringens. Monte Carlo simulation was used to estimate the probabilities of >1.0 and 2.0 Log CFU/g relative growth of C. perfringens in the final products at the end of cooling. This probabilistic process analysis approach provides a new alternative for estimating and managing the risk of a product and can help the food industry and regulatory agencies assess the safety of cooked meat in the event of cooling deviation.
Animals Clostridium perfringens