Predictive Models to Describe Behavior of Staphylococcus aureus in Sweet Pumpkin Salad Under Constant and Dynamic Temperature

Abstract

This study developed predictive models to describe the behavior of Staphylococcus aureus in sweet pumpkin salad. A five‐strain mixture of S. aureus was inoculated in 5‐g portions of sweet pumpkin salad. The samples were stored at 10–30C, and cell counts were enumerated. The growth data were fitted to the Baranyi model to calculate lag‐phase duration (h), maximum specific growth rate (Log cfu/g/h), lower asymptote (Log cfu/g) and upper asymptote (Log cfu/g). The growth parameters were then fitted to secondary models as a function of storage temperature. Dynamic models were also developed for changing temperatures. The model was validated using the observed data, and the root mean square error (RMSE) was calculated. S. aureus growth was observed at 15–30C. RMSE values were 0.428–0.847. The results indicate that the developed mathematical models should be useful in describing the behavior of S. aureus as a function of temperature.Practical ApplicationMany Staphylococcus aureus strains can contaminate sweet pumpkin salad. The salad may be stored at constant and nonisothermal temperatures, which may cause different S. aureus behaviors. Therefore, the developed model could be useful in describing and predicting the behavior of S. aureus with respect to temperature and time.