급식외식위생학회지 (Journal of the FoodService Safety)

한국급식외식위생학회 (The Korean Society of Food Service Sanitation)
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즉석섭취 샌드위치에서의 Staphylococcus aureus 성장예측모델 개발

Development of a Predictive Model Describing the Growth of Staphylococcus aureus in Ready-to-Eat Sandwiches

  • 투고 : 2021.12.08
  • 심사 : 2021.12.16
  • 발행 : 2021.12.31
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초록

This study was performed to provide fundamental data on hygiene and quality control of ready-to-eat sandwiches. Predictive models were developed to the kinetics of Staphylococcus aureus growth in these sandwiches as a function of temperature (10, 15, 25, and 35℃). The result of the primary model that used the Gompertz equation showed that the lag phase duration (LPD) and generation time (GT) decreased and the exponential growth rate (EGR) increased with increasing storage temperature. The secondary model showed an R2 for M and B of 0.9967 and 09916, respectively. A predictive growth model of the growth degree as a function of temperature was developed. L(t)=A+Cexp(-exp(-B(t-M))) (A=Initial contamination level, C=MPD-A, B=0.473166-0.045040*Temp-0.001718*Temp*Temp, M=19.924824-0.627442*Temp-0.004493*Temp*Temp, t=time, Temp=temperature). This model showed an R2 value of 0.9288. All the models developed in this study showed a good fit.

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참고문헌

  1. Augustin JC, Vincent C. 2000. Modelling the growth rate of Listeria monocytogenes with a multiplicative type model including interactions between environmental factors. Int. J. Food Microbiol., 56(1):53-70. https://doi.org/10.1016/S0168-1605(00)00224-5
  2. Bearanyi J, Roberts TA. 1995. A dynamic approach to predicting bacterial growth in food. Int. Food Microbiol., 26(1995):199-218. https://doi.org/10.1016/0168-1605(94)00121-L
  3. Buchanan RL. 1993. Predictive food microbiology trends. Food Sci. Technol., 4(1):6-11. https://doi.org/10.1016/S0924-2244(05)80004-4
  4. Buchanan RL, Phillips JG. 1990. Response surface model for predicting the effects of temperature, pH, sodium chloride content, sodium nitrite concentration, and atmosphere on the growth of Listeria monocytogenes. J. Food Prot., 53(5):370-376. https://doi.org/10.4315/0362-028x-53.5.370
  5. Cho JL, Lee SH, Lim JS, Kwak HS, Hwang IG. 2011. Development of a predictive model describing the growth of Listera monocytogenes in fresh cut vegetable. J. Food Hyg. Saf., 26(1):25-30.
  6. Duffy G, Sheridan JJ, Buchanan RL, McDowell DA, Blair IS. 1994. The effect of aeration, initial inoculum and meat microflora on the growth kinetics of Listeria monocytogenes in selective enrichments broths. Food Microbiol., 11(5):429-438. https://doi.org/10.1006/fmic.1994.1048
  7. Hass NC, Rose JB, Gerba CP. 1999. Quantitative microbial risk assessment. John Wily & Sons, Inc. NY, USA, p324-327.
  8. Hong CH, Sim WC, Chun SJ, Kim YS, Oh DH, Ha SD, Choi WS, Bahk GJ. 2005. Predictive growth model of native isolated Listeria monocytogenes on raw pork as a function of temperature and time. Korean J. Food Sci. Technol., 37(5):850-855.
  9. Karl M, Da-Wen S. 1999. Predictive food microbiology for the meat industry. Int. J. Food Microbiol., 52(1-2):1-27. https://doi.org/10.1016/S0168-1605(99)00126-9
  10. Kim DH, Song HP, Kim JK, Kim JO, Lee HJ, Byun MW. 2003. Determination of microbial contamination in the process of rice rolled in dried laver and improvement of shelf-life by gamma irradiation. J. Korean Soc. Food Sci. Nutr., 32(7):991-996. https://doi.org/10.3746/JKFN.2003.32.7.991
  11. Kim EJ. 2004. Analysis of microbiological hazards and quantitative microbial risk assessment of Staphylococcus aureus inoculated onto potentially hazardous foods in school foodservice operations. Master's degree thesis, Yonsei University, Korea, p103-141.
  12. Lee HM, Lee GY, Yoon YK, Kim HJ, Kang YS, Lee DH, Park JS, Lee SH, Woo GJ, Kang SH, Yang GH, Yang JS. 2004. Computation of maximum edible time using monitoring data of Staphylococcus aureus in Kimbap and food micro-model. J. Food Hyg. Saf., 19(1):49-54.
  13. Moon SY, Chang TE, Woo GJ, Shin IS. 2004. Development of predictive growth model of Vibrio parahaemolyticus using mathematical quantitative model. Korean J. Food Sci. Technol., 36(2): 349-354.
  14. Moon SY, Paek JM, Shin IS. 2005. Development of predictive growth model of imitation crab sticks putrefactive bacteria using mathematical quantitative assessment model. Korean J. Food Sci. Technol., 37(6):1012-1017.
  15. No MJ. 2001. Analysis of microbiological hazards and application of quantitative risk assessment in pork production. Doctoral's degree thesis, Yonsei University, Korea, p 61-68.
  16. Panisello PJ, Quantick PC. 1998. Application of food micro-model predictive software in the development of Hazard Analysis Critical Control Point (HACCP) systems. J. Food Microbiol., 15(4): 425-439. https://doi.org/10.1006/fmic.1998.0195
  17. Park KJ. 2001. Application of quantitative risk assessment in sanitation management model for icecream processing. Doctoral's degree thesis, Seoul National University, Korea, p 64-113.
  18. Solberg M, Buckalwe JJ, Chen CM, Schaffner DW, O'Neil K, McDowell J, Post LS, Boderck M. 1990. Microbiological safety assurance system for food service facilities. Food Technol., 44(12):68-73.
  19. Tatini SR. 1973. Influence of food enviroments on growth of Staphylococcus aureus and production of various enterotoxins. J. Milk Food Technol., 36(11):559-563. https://doi.org/10.4315/0022-2747-36.11.559
  20. Yoon YH. 2010. Principal theory and application of predictive microbiology. Food Sci. Ind., 43(1):70-74. https://doi.org/10.23093/FSI.2010.43.1.70
  21. Zwietering MH, Cuppers HGAH, de wit JC, Van T Riet K. 1994. Evaluation of data transformations and validation of a model for the effect of temperature on bacterial growth. Appl. Environ. Microbiol., 60(1):195-203. https://doi.org/10.1128/aem.60.1.195-203.1994
  22. Choi SK. 2021. Home meal replacement, it should be differentiated from processed foods by using domestic raw materials. Available from: http://www.sisajournal-e.com/news/articleView.html?idxno=236058, [cited 2021 Nov 30]
  23. Korea Statistical Information Service. 2021. Average of monthly purchase expenditure on HMR, Available from: https://kosis.kr/statHtml/statHtml.do?orgId=114&tblId=DT_114053_059&conn_path=I2, [cited 2021 Nov 30]
  24. Kwon HJ. 2021. Normalizing school and going to work....E-Mart 24 "Sandwich sales increased 56% in March", Available from: https://www.yna.co.kr/view/AKR20210405020800030?section=search, [cited 2021 Nov 30]