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 (Af) and bias factor (Bf) 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.