Predictive modeling of thermal inactivation for Listeria monocytogenes in a formulated milk system

Listeria monocytogenes is a foodborne pathogen with a low infective dose, survives under stress conditions, has zero tolerance in ready-to-eat foods, and grows at refrigeration temperatures. Two predictive models were developed in a 3 x 3 x 3 factorial experimental design to determine the effects of processing temperature (55°C, 60°C, 65°C), pH (5.0, 6.0, 7.0) and milkfat (0%, 2.5%, 5.0%) on inactivation of L. monocytogenes with regard to survival curve shape, relative heat resistance, and effects of growth conditions before thermal treatment. The two models differed because one used cells grown in the various pH and milkfat levels before inactivation in the same conditions and the other used cells grown in ideal conditions (pH 7.0 and 0% milkfat) before inactivation at other pH and milkfat levels. Data was fit to a modified Gompertz equation where parameter estimates (A, B, C) characterized three regions of a survival curve; shouldering (A), maximum death rate (B) and tailing (C). Regression models using the modified Gompertz equation were based on single and interactive effects of temperature, pH and milkfat. Validation of the models in conditions not tested during model development, but within the testing conditions, indicated that predictions are appropriate for specific processing temperatures in each model. For the model using cells grown in ideal conditions, the shouldering region was significantly (P \u3c 0.05) affected by pH; whereas, in the model with cells grown at various pH and milkfat levels, the shouldering region was significantly (P \u3c 0.05) affected by temperature, milkfat, and the interaction of temperature and milkfat. The maximum slope was significantly (P \u3c 0.05) affected by temperature, milkfat, and the interaction of temperature and milkfat in both models. 4D-values were 50–100% greater at 60 and 65°C for cells grown at pH 6.0 and all milkfat levels compared to cells grown in ideal conditions. The differences between the two models suggested that growth conditions could affect survival curve shape and thermotolerance of L. monocytogenes. Therefore, food microbiologists should consider growth conditions before developing their experimental design because adaptive responses of cells can change depending on food components present during growth and affect the model predictions for L. monocytogenes inactivation