Modelling the growth of Staphylococcus aureus with different levels of resistance to low temperatures in glutinous rice dough

Abstract

When using predictive models to assess the risk posed by foodborne pathogens, certain strains exhibit resistance at low temperatures, which may affect the assessment result. To understand the influence of strain heterogeneity on growth dynamics, two Staphylococcus aureus strains, including comparatively low temperature tolerant BB-11 and sensitive BA-26, were inoculated into glutinous rice dough at temperatures ranging from 10 to 37 °C. The primary Gompertz model fit showed an obvious difference in the maximum specific growth (μmax) and duration of the lag phase (λ) values at 10 °C (0.071/h and 28 h for BB-11 and 0.049/h and 34 h for BA-26, respectively). When Huang and Ratkowsky models were compared as secondary models, a log-linear relationship was demonstrated between μmax and λ for both models. Ratkowsky's model fit was more accurate with a high R2 of 0.95. The predicted minimum growth temperatures were 4.8 °C and 6.3 °C for BB-11 and BA-26, respectively. The time for achieving a 4-log increase (t4.0) was 96 h for BB-11 at 10 °C, but only 2.4 log CFU/g increase was determined in BA-26 at 144 h. This study suggests that cold-tolerant strains should be considered when a predictive model is used for risk assessment of foodborne pathogens.