A predictive growth model of Staphylococcus aureus during temperature abuse conditions

Abstract

The primary contributing factor leading to Staphylococcus aureus food poisoning is that some foods are not cooked after handling or are not appropriately refrigerated during storage. A predictive model for S. aureus was developed and validated using growth kinetic data. The growth data were collected in the Tryptic Soy Broth at isothermal temperatures from 7 to 48.9 °C. Baranyi model was fitted to the growth data, and Ratkowsky's secondary model was fitted to the growth rates with respect to temperature. Both primary and secondary models fitted the growth data well, as depicted by the goodness of fit measures (high R², low RMSE/SSE). The average h₀ value was 5.06 across all growth temperatures (10 to 45 °C). The maximum growth temperature was 47.3 °C, while the minimum was 5.7 °C. Bacteria growth was estimated under dynamic temperature profiles by solving the differential form of the Baranyi model in combination with the Ratkowsky model equation for rate constants using the fourth-order Runge-Kutta method. The dynamic model was developed and validated using growth data obtained with two sinusoidal temperature profiles, 10–30 °C and 25–45 °C for 30 h and 24 h. Data for these two profiles were assessed using acceptable prediction zone analysis; >70 % of the observed growth observations were within the acceptable prediction zone (−1.0 to 0.5 log₁₀ CFU/mL), although the model may overestimate or underestimate at some points, generally <1 log. The model will assist in estimating the growth of S. aureus in temperature abuse conditions.