Assessment of Mathematical Models for Predicting Staphylococcus aureus Growth in Cooked Meat Products

Abstract

The growth of Staphylococcus aureus in commercially available vacuum-packaged cooked ham, turkey breast meat, and chicken breast meat stored at 2.3, 6.5, 10, 13.5, and 17.7°C was studied. Growth rates observed in these food products were compared with those predicted on the basis of various growth models found in the literature and with those generated by the Pathogen Modeling Program and the Food MicroModel software using graphical and mathematical analysis for performance evaluation. In general, the models studied overestimated the growth of S. aureus. The Dengremont and Membré model most closely matched the observed behavior of S. aureus in ham and chicken breast meat, with bias factors of 1.56 and 1.09, respectively. The Eifert et al. model accurately described the growth of S. aureus in turkey breast meat, with a bias factor of 1.51. The remaining models provided safe predictions of the growth rate of S. aureus, but with poor accuracy. Predictive microbiology models have an immediate practical application in improving microbial food safety and quality and are very useful decision support tools, but they should not be used as the sole determinant of product safety.