Predictive model for the growth kinetics of Listeria monocytogenes in raw pork meat as a function of temperature

Abstract

This study was performed to develop a predictive growth model of Listeria monocytogenes to ensure the safety of raw pork. The pork samples were inoculated with a cocktail of two L. monocytogenes strains ATCC 15313 and L13-2 isolated from pork and were stored at 5, 15, and 25 °C. Results were evaluated using the MicroFit program. To develop primary models, the Baranyi, modified Gompertz, and Logistic model equations were applied to the observed data. The mathematically predicted growth rate parameters were evaluated using the coefficient of determination ( R 2 ), bias factor ( B f ), accuracy factor ( A f ), and mean square error (MSE). The Baranyi model, which showed an R 2 of 0.998 and MSE of 0.006, was more suitable than the modified Gompertz and Logistic models. In validation study of secondary model, it appeared that MSE's of specific growth rate (SGR) and lag time (LT) were relatively accurate and suitable for modeling the growth of L. monocytogenes . These values indicated that the developed models were acceptable for expressing the growth of microorganisms on raw pork, which can be applied to ensure the safety of meats and to establish standards for avoiding microbial contamination. • Baranyi model is proper than others for predicting a growth of Listeria strain . • Values of μ max were inversely proportional to LT in secondary modeling. • This predictive model can be applied for food safety in meat industry.