Predictive Model for Growth of Staphylococcus aureus on Raw Pork, Ham, and Sausage

Abstract

ABSTRACT Recent Staphylococcus aureus outbreaks linked to meat and poultry products underscore the importance of understanding the growth kinetics of S. aureus in these products at different temperatures. Raw pork, ham, and sausage (each 10 ± 0.3 g) were inoculated with a three-strain cocktail of S. aureus, resulting in an initial level of ca. 3 log CFU/g. Samples were stored isothermally at 10, 15, 20, 25, 30, 35, and 40°C, and S. aureus was enumerated at appropriate time intervals. The square root model was developed using experimental data collected from S. aureus grown on all samples (where data from raw pork, ham, and sausage were combined) so as to describe the growth rate of S. aureus as a function of temperature. The model was then compared with models for S. aureus growth on each individual sample in the experiments (raw pork, ham, or sausage) and the S. aureus ComBase models, as well as models for the growth of different types of pathogens (S. aureus, Escherichia coli O157:H7, Clostridium perfringens, Salmonella serovars, and Salmonella Typhimurium) on various types of meat and poultry products. The results show that the S. aureus model developed here based on the pooled data from all three pork products seems suitable for the prediction of S. aureus growth on different pork products under isothermal conditions from 10 to 25°C, as well as for S. aureus growth on different meat and poultry products at higher temperatures between 20 and 35°C. Regardless of some high deviations observed at temperatures between 25 and 40°C, the developed model still seems suitable to predict the growth of other pathogens on different types of meat and poultry products over the temperature ranges used here, especially for E. coli O157:H7 and Salmonella Typhimurium. The developed model, therefore, may be useful for estimating the effects of storage temperature on the behavior of pathogens in different meat and poultry products and for microbial risk assessments evaluating meat safety.