Mathematical Models to Predict Staphylococcus aureus Growth on Processed Cheeses
  • 김경미
  • 이희영
  • 문진산
  • 김영조
  • 허은정
  • ... 윤요한
  • 외 1명
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

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), 15oC (288 h), 25oC (72 h), and 30oC (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 4oC, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at 15oC, 25oC, and 30oC. 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.

키워드

Staphylococcus aureusprocessed cheesepredictive model
제목
Mathematical Models to Predict Staphylococcus aureus Growth on Processed Cheeses
저자
김경미이희영문진산김영조허은정박현정윤요한
DOI
10.13103/JFHS.2013.28.3.217
발행일
2013-09
저널명
한국식품위생안전성학회지
28
3
페이지
217 ~ 221