A NOVEL MODELING APPROACH FOR PREDICTING MICROBIAL-GROWTH IN A RAW CURED MEAT PRODUCT STORED AT 3-DEGREES-C AND AT 12-DEGREES-C IN AIR

To predict microbial growth during chill storage of a traditional Gree k raw sausage, a numerical model was developed and validated. In our n ovel approach, the specific growth rate of each microbial population w as calculated on the basis of the main microbial populations grown in the sausage. In addition, the specific destructive effect of the sausa ge ecosystem was introduced to evaluate microbial growth. The model wa s integrated by the Runge-Kutta method and the parameter values were o ptimised by the least squares method. Fitting of the model to the expe rimental data derived from four sausage batches stored aerobically at 3 and 12 degrees C successfully described the microbial growth kinetic s 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 pre dict microbial growth in the other batches at both storage temperature s. (C) 1998 Elsevier Science B.V. All rights reserved.