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KMID : 0881720130280030217
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Journal of Food Hygiene and Safety
2013 Volume.28 No. 3 p.217 ~ p.221
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Mathematical Models to Predict Staphylococcus aureus Growth on Processed Cheeses
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Kim Kyung-Mi
Lee Hee-Young
Yoon Yo-Han
Moon Jin-san
Kim Young-jo
Heo Eun-jeong
Park Hyun-jung
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Abstract
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This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at 4oC (1440 h), 15o C (288 h), 25oC (72 h), and 30o C (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (μmax; log CFU·g?1 ·h?1 ), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At 4o
C, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at 15o C, 25oC, and 30o C. The μmax values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.
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KEYWORD
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Staphylococcus aureus, processed cheese, predictive model
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