Mathematical Models To Predict Kinetic Behavior and Growth Probabilities of Listeria monocytogenes on Pork Skin at Constant and Dynamic Temperatures

Abstract

In this study, mathematical models were developed to predict the growth probability and kinetic behavior of Listeria monocytogenes on fresh pork skin during storage at different temperatures. A 10-strain mixture of L. monocytogenes was inoculated on fresh pork skin (3 by 5 cm) at 4 log CFU/cm(2). The inoculated samples were stored aerobically at 4, 7, and 10 degrees C for 240 h, at 15 and 20 degrees C for 96 h, and at 25 and 30 degrees C for 12 h. The Baranyi model was fitted to L. monocytogenes growth data on PALCAM agar to calculate the maximum specific growth rate, lag-phase duration, the lower asymptote, and the upper asymptote. The kinetic parameters were then further analyzed as a function of storage temperature. The model simulated growth of L. monocytogenes under constant and changing temperatures, and the performances of the models were evaluated by the root mean square error and bias factor (B-f). Of the 49 combinations (temperature x sampling time), the combinations with significant growth (P < 0.05) of L. monocytogenes were assigned a value of 1, and the combinations with nonsignificant growth (P >= 0.05) were given a value of 0. These data were analyzed by logistic regression to develop a model predicting the probabilities of L. monocytogenes growth. At 4 to 10 degrees C, obvious L. monocytogenes growth was observable after 24 h of storage; but, at other temperatures, the pathogen had obvious growth after 12 h of storage. Because the root mean square error value (0.184) and B-f (1.01) were close to 0 and 1, respectively, the performance of the developed model was acceptable, and the probabilistic model also showed good performance. These results indicate that the developed model should be useful in predicting kinetic behavior and calculating growth probabilities of L. monocytogenes as a function of temperature and time.