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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 (μ max) 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 μ max and λ for both models. Ratkowsky's model fit was more accurate with a high R 2 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 (t 4.0) 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. • Cold tolerant and sensitive S. aureus exhibited different growth curves in glutinous rice dough. • The two strains showed an obvious difference in μ max and λ values at 10 °C. • Ratkowsky's model fit was more accurate when used as secondary model. • Cold-tolerant strains should be well considered when a predictive model is constructed. [ABSTRACT FROM AUTHOR]