Mathematical Modeling for the Growth of Salmonella spp. and Staphylococcus aureus in Cake at Fluctuating Temperatures

This study aimed to develop dynamic mathematical models to predict the growth of Salmonella spp. and Staphylococcus aureus in a cake under fluctuating temperatures. Among the nine different types of cakes frequently served during school meals, one type of cake was selected based on bacterial growth and water activity. Cocktails of Salmonella spp. and S. aureus were inoculated in the samples and stored at 4-35 degrees C for up to 336 h. The growth of Salmonella spp. and S. aureus was observed above 20 and 15 degrees C, respectively. The bacterial cell counts were fitted in the Baranyi model, and the maximum specific growth rate (mu(max); log CFU/g/h) and lag phase duration (LPD; h) were analyzed using a polynomial model as a function of temperature (R-2 = 0.968-0.988), and the performance of the developed models was appropriate. Furthermore, dynamic models were developed, and the predictions were acceptable in changing the temperature, indicating that the developed dynamic models can successfully predict the outcomes of Salmonella spp. and S. aureus in cake. These results provide useful information for assessing and managing microbial risk in foods by predicting the behavior of Salmonella spp. and S. aureus in cake, especially in changing temperature.

Automated summary

This study developed dynamic mathematical models to predict the growth of Salmonella spp. and Staphylococcus aureus in cakes under fluctuating temperatures. The models successfully predicted the outcomes of bacterial growth in cakes, providing useful information for assessing and managing microbial risk in foods.