Quantitative Microbial Risk Assessment Model for Staphylococcus aureus in Kimbab

김밥에서의 Staphylococcus aureus에 대한 정량적 미생물위해평가 모델 개발

  • Bahk, Gyung-Jin (National Food Safety & Toxicology Center, Michigan State University) ;
  • Oh, Deog-Hwan (School of Biotechnology and Bioengineering, Kangwon National University) ;
  • Ha, Sang-Do (Department of Food Science and Technology, Chung-Ang University) ;
  • Park, Ki-Hwan (Department of Food Science and Technology, Chung-Ang University) ;
  • Joung, Myung-Sub (Korea Health Industry Development Institute) ;
  • Chun, Suk-Jo (Korea Health Industry Development Institute) ;
  • Park, Jong-Seok (Korea Food and Drug Administration) ;
  • Woo, Gun-Jo (Korea Food and Drug Administration) ;
  • Hong, Chong-Hae (Department of Veterinary Medicine, Kangwon National University)
  • Published : 2005.06.30

Abstract

Quantitative microbial risk assessment (QMRA) analyzes potential hazard of microorganisms on public health and offers structured approach to assess risks associated with microorganisms in foods. This paper addresses specific risk management questions associated with Staphylococcus aureus in kimbab and improvement and dissemination of QMRA methodology, QMRA model was developed by constructing four nodes from retail to table pathway. Predictive microbial growth model and survey data were combined with probabilistic modeling to simulate levels of S. aureus in kimbab at time of consumption, Due to lack of dose-response models, final level of S. aureus in kimbeb was used as proxy for potential hazard level, based on which possibility of contamination over this level and consumption level of S. aureus through kimbab were estimated as 30.7% and 3.67 log cfu/g, respectively. Regression sensitivity results showed time-temperature during storage at selling was the most significant factor. These results suggested temperature control under $10^{\circ}C$ was critical control point for kimbab production to prevent growth of S. aureus and showed QMRA was useful for evaluation of factors influencing potential risk and could be applied directly to risk management.

정량적 미생물 위해평가(Quantitative microbial risk assessment: QMRA)는 국민건강에 영향을 주는 잠재된 위해를 연구하여 식품내 존재하는 병원성미생물과 관련한 위해를 체계적으로 평가하는 것이다. 본 연구는 깁밥에서의 Staphylococcus aureus에 대한 QMRA 모델을 개발하고 이를 식품위생관리에서 이용할 수 있는 기준을 제시하여, 식품안전 분야에서의 QMRA의 필요성과 활용성을 알리기 위해서 실시하였다. QMRA 모델은 매장에서부터 최종소비에 이르기까지 4 단계로 구성되었으며, 미생물 성장모델과 조사자료 그리고 확률분포가 김밥의 최종소비에서의 S. aureus 수준을 평가하기 위하여 이용되었다. S. aureus에 대한 양-반응모델이 없는 관계로 최종 소비단계에서의 S. aureus의 오염수준을 잠재적인 위해를 결정하는데 이용하였다. 이를 위하여 5 log CFU/g이상을 잠재적 유해수준으로 가정하였으며, 시뮬레이션 결과 최종 소비되는 김밥에서 이 유해수준을 초과할 가능성은 30.7%로 나타났다. 김밥에서의 S. aureus의 오염수준은 평균 2.67 log CFU/g으로 나타났으며, 민감도 분석에서는 매장에서의 김밥 보관온도 및 시간이 가장 중요한 요인으로 결정되었다. 이러한 결과를 종합하여 볼 때 김밥 매장에서는 현실적으로 보존시간 관리가 어렵다고 한다면 보관온도를 $10^{\circ}C$ 이하로 유지하는 것이 가장 중요한 것으로 나타났다. 본 연구에서와 같이 QMRA는 식품 내 존재할 수 있는 잠재적인 위해에 영향을 미치는 인자들에 대한 평가에 이용될 수 있으며 이를 식품위생관리에 직접적으로 활용 가능한 것으로 나타났다.삼의 분석방법별 기준인 ginsenoside -Rg1과 -Re의 함량비($Rg1/Re{\Leq}3.87$)에 부합되었다.도에서 MA 저해 효과는 쑥갓>미나리>참깨의 순으로, 각각 54, 48, 29%를 나타냈다. 참깨는 20, $100{\mu}g/mL$의 농도에서처럼 가장 작은 효과를 보여줬고, 쑥갓은 50% 이상의 항산화 효과를 나타냈다. Aldehyde/Carboxylic acid assay에서는 참깨가 가장 높은 효과를 보여줬지만 Lipid MA asaay에서는 그에 비해 가장 낮은 효과를 나타냈다.안전한 수준인 것으로 판단된다. 보여진다.ificantly more inclusive. As a result of the evolution of new fibers, materials, processes and markets, we assert that a new "ENGINEERING WITH FIBERS" (EwF)(중략)web.cnu.ac.kr/~fabric이다. 제작된 멀티미디어를 실제 수업에 활용한 결과 수강생(32명)의 96.9%가 보조자료로 사용된 멀티미디어 콘텐츠자료가 실험관련 교과목 수업에 효과적이라고 응답하였고, 87.5%가 활용된 멀티미디어 콘텐츠 자료에 만족하며, 75%가 기존의 교과서와 비교하여 더 많이 활용하였다고 응답하였다. 따라서 멀티미디어 콘텐츠를 활용한 교육은 개인차에 따른 개별화 학습을 가능하게 할 뿐만 아니라 능동적인 참여를 유도하여 학습효율을 높일 수 있을 것으로 기대된다.향은 패션마케팅의 정의와 적용범위를 축소시킬 수 있는 위험을 내재한 것으로 보여진다. 그런가 하면, 많이 다루어진 주제라 할지라도 개념이나 용어가 통일되지

Keywords

References

  1. Notermans S, Teunis P. Quantitative risk analysis and the production of microbiologically safe food: an introduction. Int. J. Food Microbiol. 30: 3-7 (1996) https://doi.org/10.1016/0168-1605(96)00987-7
  2. CAC (Codex Alimentarius Commission). Draft principles and guidelines for the conduct of microbiological risk assessment. Codex Committee on Food Hygiene. Report of the thirty-first session, Orlando, United States (1998)
  3. FAO/WHO. Risk assessment of microbiological risk assessment. Report of the Joint FAO/WHO Expert Consultation, March 15-19, Geneva, Switzerland (1999)
  4. CAC (Codex Alimentarius Commission). Principles and guidelines for the conduct of microbiological risk assessment. CAC/GL-30. FAO Rome, Italy (1999)
  5. FAO/WHO. Joint FAO/WHO expert consultation on risk assessment of microbiological hazards in foods. FAO Food and Nutrition Paper No. 71. FAO Rome, Italy (2000)
  6. Vose DJ. The application of quantitative risk assessment to microbial food safety. J. Food Prot. 61: 640-648 (1998) https://doi.org/10.4315/0362-028X-61.5.640
  7. Bahk GJ. Trends of Microbial Risk Assessment, pp. 46-69. In: 2001 Symposium of Korean Society for HACCP Research. The Korean Society for HACCP Research, Seoul, Korea (2001)
  8. Buchanan RL, Demis S, Miliotis M. Initiating managing risk assessments within risk analysis framework: FDA/CFSAN's practical approach. J. Food Prot. 67: 2058-2062 (2004) https://doi.org/10.4315/0362-028X-67.9.2058
  9. Korea Food and Drug Administration. Annual report of food-borne disease in Korea. Available from: http://www.kfda.co.kr. Accessed Dec. 3, 2004
  10. Bahk GJ, Chun SJ, Park KH, Hong CH, and Kim JW. Survey on the foodborne illness experience and awareness of food safety practice among korean consumers. J. Fd. Hyg. Safety 18: 139-145(2003)
  11. Palisade Inc. Guide to using $\circledR$RISK: risk analysis and simulation add-in for microsoft excel, ver 4.5, Newfield, NY, USA (2002)
  12. Park SY, Choi JW, Yeon JH, Lee MJ, Oh DH, Hong CH, Bahk GJ, Woo GJ, Park JS, Ha SD. Assessment of contamination level of foodborne pathogens isolated in kimbab and its main ingredients in the process of preparation. Korean J. Food Sci. Tech. 37: 122-128(2005)
  13. Oh DH, Ha SD, Hong CH. Study on the reduction of foodborne pathogenic bacteria in ready-to-eat (RTE) foods. 2004 K.FDA research project report (project No. FBD-563). KFDA, Seoul, Korea (2004)
  14. Jin SS, Bimal KK, Choi JH, Ha SD, Hong CH, Woo GJ, Oh DH. The growth of Staphylococcus aureus on kimbab at different temperature, p. 380. In: The current prospects of functional and medicinal food. Korean Society of Food Science and Nutrition, Jeju, Korea (2004)
  15. SAS Institute Inc. SAS User's Guide. Statistical Analysis Systems Institute, Cary, NC, USA (2002)
  16. Hass NC, Rose JB, Gerba, CP. Quantitative microbial risk assessment. John Wily & Sons, Inc. NY, USA. pp. 324-327 (1999)
  17. Buchanan RL, James L, Smith WL. Microbial risk assessment: dose-response relations and risk characterization. Int. J. Food Microbiol. 58: 159-172 (2000) https://doi.org/10.1016/S0168-1605(00)00270-1
  18. Lindqvist R, Sylven S, Vagasolm I. Quantitative microbial risk assessment exemplified by Staphylococcus aureus in unripened cheese made from raw milk. Int. J. Food Microbiol. 78: 155-170 (2002) https://doi.org/10.1016/S0168-1605(02)00237-4
  19. Walls I, Scott VN. Use of predictive microbiology in microbial food safety risk assessment. Int. J. Food Microbiol. 36: 97-102 (1997) https://doi.org/10.1016/S0168-1605(97)01260-9
  20. Dana MM, Lee J, Peggy MF. A quantitative risk assessment for Bacillus cereus emetic disease associated with the consumption of Chinese-style rice. J. Food safty 19:209-229 (1999) https://doi.org/10.1111/j.1745-4565.1999.tb00246.x
  21. Anunciacao LL, Linardi WR, do Camo LS, Bergdoll MS. Production of Staphylococcal enterotoxin A in cream-filled cake. Int. J. Food Microbiol. 26: 259-363 (1995) https://doi.org/10.1016/0168-1605(94)00122-M
  22. Grockler L, Notermans S, Kramer J. Production of enterotoxins and thermonuclease by Staphylococcus aureus in cooked egg-noodles. Int. J. Food Microbiol. 6: 127-139 (1988) https://doi.org/10.1016/0168-1605(88)90049-9
  23. Otero A, Garcia MC, Garcia ML, Prieto M, Moreno B. Behaviour of Staphylococcus aureus strains, products of enterotoxin $C_1$, and $C_2$ during manufacture and storage of Burgos cheese. J. Appl. Bacteriol. 64: 117-112 (1988)
  24. FAO/WHO. Joint FAO/WHO Initiative on Microbial Risk Assessment. IAFP 88th Annual meeting, IAFP, Minneapolis, Minnesota, USA (2001)
  25. Kim DH, Song HP, Kim JK, Kim JO, Lee HJ, Byun MW. 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: 991-996 (2003) https://doi.org/10.3746/jkfn.2003.32.7.991
  26. Buchanan RL, Smith JL, McColgan C, Maimer BS, Golden MH, Dell BJ. Response surface models for the effects of temperature, pH, sodium chloride, and sodium nitrite on the aerobic and anaerobic growth of Staphylococcus aureus 196E. J. Food Safty 13:159-175(1993) https://doi.org/10.1111/j.1745-4565.1993.tb00103.x