A non-linear random coefficient model for the destruction ofEnterococcus faeciumin a high-temperature short-time pasteurizer

The thermal inactivation ofEnterocuccus faeciumin bovine whole milk was studied in a high-temperature short-time pilot scale pasteurizer. Integrated lethal effect, or pasteurization effect (PE), was obtained by converting times at different temperatures in the various sections of the pasteurizer to the equivalent time at the reference temperature (72°C). Survival curves showed distinct tailing, suggesting the presence of a secondary, more heat-resistant population. PE was initially related by a simple linear function to the log10of the percentage viable counts, with a power transformation of the PE values to improve linear fit. Residuals obtained from fitting the power transformation model to the various trials showed considerable systematic deviations, and an improved fit was obtained with a biphasic logistic function. A single model based on average parameter values from pooled data was inadequate, and a random coefficient model was used to incorporate inter-trial variability. The random coefficient model replaces the average predicted value with a distribution of possible outcomes, and yielded superior fits to the data, thus is preferred for prediction.