Modeling and Evaluating the Growth/No Growth Boundaries of Bacillus cereus: Effect of Temperature, pH, and Water Activity
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Abstract:
Bacillus cereus is an opportunistic pathogen, implicated in two main food-borne diseases: emetic syndrome and diarrheal syndrome. The aim of this study was to establish a probabilistic model to predict the growth/no growth conditions or growth probability of B. cereus as a function of temperature, pH, and water activity (Aw). Using a cocktail of five strains of B .cereus, a logistic regression model was chosen to study the effects of different values of temperature, pH, Aw on the growth probability of B. cereus. A fractional factorial design was applied and the experimental data were divided into two parts: 80% data was chosen as model data and 20% data was chosen as validation data. A comparison was made between the predicted and observed values by selecting 30 experimental data from the literature, to test the model. The results showed that the concordance index of the model data was 0.991, while that of the validation data was 0.988. This indicated that the model showed high predictive accuracy for homogeneous data. Additionally, the performance statistics obtained indicated a reasonable goodness-of-?t of the model obtained, mainly owing to the high values of R2-Nagelkerke (0.949) and χ2 = 0.012, p = 1 of the Hosmer–Lemeshow statistic. A high predictive accuracy was obtained (83.3%) with test data, showing a wide range of possible applications.
