A predictive model to determine the effects of pH, milkfat, and temperature on thermal inactivation of Listeria monocytogenes.

Listeria monocytogenes is a foodborne pathogen of significance because of its comparatively high heat resistance, zero tolerance in ready-to-eat foods, and growth at refrigeration temperatures. A 3 x 3 x 3 factorial study was done to determine the effects of milkfat (0%, 2.5%, 5.0%), pH (5.0, 6.0, 7.0), and processing temperature (55 degrees C, 60 degrees C, 65 degrees C) on the thermal resistance of L. monocytogenes in a formulated and homogenized milk system. Data were fit to a modified Gompertz equation where parameter estimates characterized three regions of a survival curve: the shoulder, maximum slope, and tail. Statistical analysis was done for each of the 27 individual treatment sets to visualize individual effects on parameter estimates and to evaluate how well the Gompertz equation represented the data. A regression model for the Gompertz equation was generated to predict the logarithmic surviving fraction of L. monocytogenes based on all 27 treatments and their single and interactive effects. The shoulder region of the survival curve was affected by pH; however, the maximum slope was affected by temperature, milkfat, and the interaction of temperature x milkfat. Validation of the model suggests that the predictions are best suited for processing above 62 degrees C. Trends over time for a 4-log reduction in cells (4D values) were evaluated using results from the 27 individual treatment sets, the regression model for the Gompertz equation, and a linear equation. At lower temperatures, 4D values by the three methods varied by twofold. At higher temperatures, all methods gave similar 4D values, suggesting that death became more linear. Based on this study all three factors affect heat resistance for specific regions of a survival curve, and a predictive model was developed that can be used as a preliminary estimate for L. monocytogenes inactivation.