Predictive Models to Describe Kinetic Behavior of Staphylococcus aureus on Various Cheeses

Background: Staphylococcus aureus is an important human pathogen. Sometimes S. aureus is the major causative agent of food-borne disease due to dairy products. Purpose: This study developed mathematical models to describe kinetic behaviors of Staphylococcus aureus on natural and processed cheeses. Methods: Two natural cheeses (Brie and Camembert) and three processed cheeses (Mozzarella, Cheddar, and Gouda) were inoculated with a five-strain mixture of S. aureus at 3-4log CFU/g. The samples were then stored at 4-30℃. Total bacterial and S. aureus cell counts were enumerated on tryptic soy agar and mannitol salt agar, respectively. The growth data of S. aureus from each cheese were fitted to the Baranyi model to calculate maximum specific growth rate (max; log CFU/g/h) and lag phase duration (LPD; h). The kinetic parameters were further analyzed by the square root model as a function of storage temperature. The model performance was validated with observed data, and root mean square error (RMSE) was calculated. Results: S. aureus growth was observed at 10-30℃ for natural cheeses, but the growth of S. aureus on Mozzarella and Cheddar slice cheeses was observed at 15-30℃. S. aureus growth on Gouda slice cheese was observed only at 25 and 30℃. max values were increased, but LPDs were decreased as storage temperature increased. No differences of the maxand LPD values were observed between Brie and Camembert cheeses. S. aureus had lower (P<0.05) growth on processed cheeses than on natural cheeses, especially Gouda slice cheese had the lowest growth of S. aureus. In addition, the prediction of the developed model also showed acceptable performance (RMSE=0.351-0.750). The results indicate that the developed mathematical models should be helpful in exposure assessment S. aureus growth on various cheeses.