A dynamic predictive model for Bacillus cereus growth from spores under temperature abuse conditions

Bacillus cereus, a common foodborne pathogen, can cause emetic and diarrheal food poisoning. The associated outbreaks are commonly caused by temperature abuse during food cooling, storage, and transportation. This study developed a model to predict B. cereus growth from spores based on isothermal growth data collected at 10-54.4 °C in tryptic soy broth. A four-strain spore cocktail was heated at 80 °C for 10 min and inoculated at an initial level of ∼2 log CFU/mL. Growth curves at temperatures showing growth (15-50 °C) were fitted using the Baranyi model. The average h₀ value was 3.04. The temperature dependence of the maximum specific growth rate was characterized using the modified Ratkowsky model. The estimated theoretical minimum and maximum growth temperatures were 8.94 °C and 54.11 °C, respectively. The lag phase duration was related to temperature using a hyperbolic function. All models showed good agreement with the observed data, with satisfactory fit statistics (R² = 0.953-0.998 and RMSE = 0.073-0.904). The Baranyi differential equations were solved numerically using a fourth-order Runge-Kutta method to build the dynamic model. Model validation was conducted under two sinusoidal non-isothermal temperature profiles (10-30 °C for 30 h and 25-45 °C for 23 h). The accuracy factor (A_f) and bias factor (B_f) values were 1.2117 and 1.2117 for the 10-30 °C profile, and 1.1359 and 1.1288 for the 25-45 °C profile, respectively. These results demonstrated that the dynamic model could precisely predict B. cereus growth and be used as a baseline reference for food system research and risk assessment.