Establishment of Growth/No Growth Model for Bacillus cereus on Different Temperature, pH and Water Activity

Abstract

The aim of this research was to establish a probabilistic model to predict the growth probability of B. cereus. The five strains of B.cereus were studied and a logistic regression model was chosen to study the interaction of different temperature (10°C, 15°C,20°C,25°C,30°C,35°C), pH(4.5, 5, 5.5, 6, 6.5, 7, 7.5), Aw( 14 levels from 0.992 to 0.932) on the probability of growth. This paper made a fractional factorial design and the experimental data was divided to two parts: 80% of data was chosen as model data and 20% of data was chosen as validation data . At last comparison was made between the predicted values and observed value by choosing 19 experimental data from the published studies. The results showed the concordance index of model data was 0.991 while the validation data was 0.976, indicating that the data was correctly classified and model had a high predictive ability. Also The performance statistics obtained indicate a reasonable goodness of fit of the model obtained, mainly due to the high values of R2-Nagelkerke (0.954) and χ2=0.0119,P=1 of the HosmerLemeshow statistic. A high predictive accuracy is obtained (89.47%) with test data, showing a good predictive ability. In this paper, the growth/no growth model can quantized the combination of environmental factors for B. cereus. This study can help food manufacturers in making decision on the more reasonable and safer formulations for food products in order to prevent the growth of B.cereus along their shelf-life.