Modeling and predicting the effect of temperature on the growth of Proteus mirabilis in chicken

• We model the growth of Proteus mirabilis under different isothermal conditions.
• Baranyi model performs best among three primary models.
• The modified Gompertz and Baranyi models fit data better among three secondary models.
• Overall, the Baranyi model predicts the growth of Proteus mirabilis from raw meat best.
• Baranyi model can be used to evaluate meat safety during processing and storage.

A predictive model to study the effect of temperature on the growth of Proteus mirabilis was developed. The growth data were collected under several isothermal conditions (8, 12, 16, 20, 25, 30, 35, 40, and 45 °C) and were fitted into three primary models, namely the logistic model, the modified Gompertz model, and the Baranyi model. The statistical characteristics to evaluate the models such as R2, mean square error, and Sawa's Bayesian information criteria (BIC) were used. Results showed that the Baranyi model performed best, followed by the logistic model and the modified Gompertz model. R2 values for the secondary model derived from logistic, modified Gompertz, and Baranyi models were 0.965, 0.974, and 0.971, respectively. Bias factor and accuracy factor indicated that both the modified Gompertz and Baranyi models fitted the growth data better. Therefore, the Baranyi model was proposed to be the best predictive model for the growth of P. mirabilis.