A novel modelling approach for predicting microbial growth in a raw cured meat product stored at 3°C and at 12°C in air

To predict microbial growth during chill storage of a traditional Greek raw sausage, a numerical model was developed and validated. In our novel approach, the specific growth rate of each microbial population was calculated on the basis of the main microbial populations grown in the sausage. In addition, the specific destructive effect of the sausage ecosystem was introduced to evaluate microbial growth. The model was integrated by the Runge-Kutta method and the parameter values were optimised by the least squares method. Fitting of the model to the experimental data derived from four sausage batches stored aerobically at 3 and 12 degrees C successfully described the microbial growth kinetics in the sausage niche. Finally, the parameter values estimated by the fitting of the model on the data set from each batch were used to predict microbial growth in the other batches at both storage temperatures. (C) 1998 Elsevier Science B.V. All rights reserved.