A mathematical model for predicting growth/no-growth of psychrotrophic C. botulinum in meat products with five variables

The inputs for the final model are the five variables: temperature, pH, added sodium nitrite, NaCl and sodium lactate within the ranges 4-12 °C, 5.4-6.4, 0-150 ppm, 1.2-2.4% and 0-3% respectively. As reference a logistic regression method was also applied and subsequently compared to the full neural network model. Based on RMSEC value of 0.104 and 0.144 for ANN and the logistic regression model respectively, the ANN was preferred. On a separate set of test data (n = 60) the ANN model was validated by comparing the predicted “probability of growth” with the observed growth. A bias of 0.0166 was obtained, indicative of a model that is slightly fail-safe.