Predictive Modeling of the Growth of Staphylococcus aureus in Glutinous Rice Dough

The aim of this study was to develop primary and secondary models to describe the growth kinetics of Staphylococcus aureus in glutinous rice dough in order to provide a basis for monitoring the growth of S. aureus in raw materials for glutinous rice products. Glutinous rice dough was inoculated with a mixture of two S. aureus strains (ATCC 8095 and NCTC 8325) and cultured at 4, 11, 18, 25, 32 or 37 ℃. The results showed that the growth data of S. aureus in glutinous rice dough at all temperatures except 4 ℃, at which S. aureus grew slowly, could be fitted to three primary growth models (the Baranyi, modified Gompertz and Huang models). However, the modified Gompertz model most accurately fitted the growth data of S. aureus at lower and higher temperatures (11 and 37 ℃). The Akaike information criterion (AIC) and the coefficient of determination (R2) showed that the modified Gompertz model could be used as the optimal primary model for the prediction of S. aureus growth. Thereafter, the effect of temperature on the growth rate of S. aureus was analyzed using the Ratkowsky (RSR) and Huang square-root (HSR) models. The results showed that the RSR model provided more accurate predictions of the lowest (0.049 ℃) and highest (47.135 ℃) growth temperatures than did the HSR model, suggesting the RSR model was a more suitable secondary growth model for S. aureus in glutinous rice dough. The results of this study can provide a scientific basis for food companies and regulatory agencies to predict the growth of S. aureus in glutinous rice products for food safety risk assessment.