Korean Journal of Food Science and Technology (한국식품과학회지)

Korean Society of Food Science and Technology (한국식품과학회)
권호 표지

Predicting the Contamination of Listeria Monocytogenes and Yersinia enterocolitica in Pork Production Using Monte Carlo Simulation

몬테카를로 시뮬레이션을 이용한 돈육 생산공정에서의 Listeria monocytogenes 및 Yersinia enterocolitica의 오염수준 예측

  • Published : 2003.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

Monte Carlo simulation was used to predict the contamination levels of Listeria monocytogenes and Yersinia enterocolitica in final pork products. Mean values of the estimated log contaminated levels of L. monocytogenes on carcasses, cut meats, and cut meats after storage were -4.59, -4.46 and -4.45 $log_{10}CFU/cm^2$ respectively. The mean values of estimated log contaminated levels of Y. enterocolitica on carcasses, cut meats, and cut meats after storage were -3.44, -4.00 and -3.97 $log_{10}CFU/cm^2$, respectively. Sensitivity analysis showed that L. monocytogenes and Y. enterocolitica in pork was most sensitive to the prevalence of L. monocytogenes and Y. enterocolitica in the equipment used.

본 연구는 돈육의 생산공정에서 발생 가능성이 높은 병원성 미생물인 L. monocytogenes와 Y. enterocolitica의 돈육 생산공정에서의 위해를 평가하기 위하여 확률적 접근방법을 통하여 오염수준을 예측하여 보았다. 몬테카를로 simulation을 이용하여 simulation을 한 결과 이분도체, 가공한 부분육, 저장 후 출고 전의 부분육에서의 L. monocytogenes의 오염 평균값은 각각 -4.59, -4.46, -4.45 $log_{10}CFU/cm^2$이었으며 Y. enterocolitica의 경우는 오염 평균값이 각각 -3.44, -4.00, -3.97 $log_{10}CFU/cm^2$의 값을 나타내었다. Sensitivity analysis 결과 생산된 돈육의 L. monocytogenes 및 Y. enterocolitica 오염 정도에 영향이 가장 큰 요인은 장비에서의 이들 병원성 미생물의 prevalence였다. 최종 세척의 경우는 세척의 효과가 클수록 돈육의 오염수준이 감소하는 것으로 나타났으며, 육가공장에서의 부분육 저장 온도는 $5^{\circ}C$ 이하로만 유지한다면 L. monocytogenes 및 Y. enterocolitica의 오염을 억제하기에 충분한 것으로 분석되었다.

Keywords

References

  1. Chung, M.S., Lee, S.W., Park, G.Y., Lee, J.H., Lee, C.S. and Lee, J.H. Analysis of microbiological hazards at pork processing plants in Korea. Korean J. Food Sci. Anim. Resour. 19: 36-40 (1999)
  2. Korea Food and Drug Administration. Food Code. Moonyoung Sa, Seoul, Korea (2000)
  3. Huis-in't-Veld, J.H.J., Mulder, R.W.A.W. and Snijders, J.M.A. Impact of animal husbandry and slaughter technologies on microbial contamination of meat: monitoring and control. Meat Sci. 36: 123-154 (1994) https://doi.org/10.1016/0309-1740(94)90038-8
  4. Rho, M.J., Chung, M.S., Lee, J.H. and Park, J. Monitoring of microbial hazards at farms, slaughterhouses, and processing lines of swine in Korea. J. Food Prot. 64: 1388-1391 (2001) https://doi.org/10.4315/0362-028X-64.9.1388
  5. Carr, M.A., Thompson, L.D., Miller, M.F., Ramsey, C.B. and Kaster, C.S. Chilling and trimming effects on the microbial populations of pork carcasses. J. Food Prot. 61: 487-489 (1998) https://doi.org/10.4315/0362-028X-61.4.487
  6. Dickson, J.S. and Anderson, M.E. Microbiological decontamination of food animal carcasses by washing and sanitizing systems: a review. J. Food Prot. 55: 133-140 (1992) https://doi.org/10.4315/0362-028X-55.2.133
  7. Gill, C.O. and McGinnis, J.C. Improvement of the hygienic performance of the hindquarters skinning operations at a beef packing plant, Int. J. Food Microbiol. 51: 123-132 (1999) https://doi.org/10.1016/S0168-1605(99)00111-7
  8. Korea Ministry of Agriculture and Forestry. Manual for Hazard Analysis and Critical Control Point System of Livestock and Livestock Products, Official Notification 2000-15, Seoul, Korea (2000)
  9. Potter, M.E. Risk assessment terms and definitions. J. Food Prot. Supplement: 6-9 (1996)
  10. Codex Alimentarius. Guidelines on the Applications of the PrincipIes of Risk Assessment and Risk Management to Food Hygiene Including Strategies for Their Application. CX/FH 95/8 (1995)
  11. Codex Alimentarius. Risk Analysis in Codex Work. CX/EXEC 96/43/6 (1996)
  12. Notermans, S. and 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
  13. Jaykus, L. The application of quantitative risk assessment to microbial food safety risks. Crit. Rev. Microbiol. 22: 279-293 (1996) https://doi.org/10.3109/10408419609105483
  14. ICMSF. Potential application of risk assessment techniques to microbiological issues related to international trade in food and food products. J. Food Prot. 61: 1075-1086 (1998) https://doi.org/10.4315/0362-028X-61.8.1075
  15. Lammerding, A.M. and Fazil, A. Hazard identification and exposure assessment for microbial food safety risk assessment, Int. J. Food Microbiol. 58: 147-157 (2000) https://doi.org/10.1016/S0168-1605(00)00269-5
  16. Buchanan, R.L., Smith, J.L. and Long, W. 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
  17. Mayes, T. Risk analysis in HACCP: burden or benefit? Food Control 9: 171-176 (1998) https://doi.org/10.1016/S0956-7135(97)00055-8
  18. Cassin, M.H., Lammerding, A.M., Todd, E.C.D., Ross, W. and McColl, R.S. Quantitative risk assessment for Escherichia coli O157:H7 in ground beef hamburgers, Int. J. Food Microbiol. 41: 21-44 (1998) https://doi.org/10.1016/S0168-1605(98)00028-2
  19. Whiting, R.C. and Buchanan, R.L. Development of a quantitative risk assessment model for Salmonella enteritidis in pasteurized liquid eggs. Int. J. Food Microbiol. 36: 111-125 (1997) https://doi.org/10.1016/S0168-1605(97)01262-2
  20. Food and Drug Administration. Bacteriological Analytical Manual, 8th ed., rev. A. Association of Official Analytical Chemists, Gaithersburg, USA (1998)
  21. Greer, G.G. and Jones, S.D.M. Effects of lactic acid and vacuum packaging on beef processed in a research abattoir, Can. Inst. Food Sci. Technol. J. 24: 161-168 (1991) https://doi.org/10.1016/S0315-5463(91)70040-0
  22. Joint FAO/WHO. Risk Assessment: Listeria monocytogenes in Ready-to-Eat Foods. Preliminary Report, Rome, Italy (2000)
  23. Vose, D. Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modelling. John Wiley & Sons, Chichester, England (1996)
  24. Palisade. Guide to Using @RISK: Risk Analysis and Simulation Add-in for Microsoft Excel, vers. 4. Palisade Corp., Newfield, USA (2000)
  25. Skelly, G.C., Fandino, G.E., Haigler, J.H. and Sherard, R.C. Bacteriology and weight loss of pork carcasses treated with a sodium hypochlorite solution. J. Food Prot. 48: 578-581 (1985) https://doi.org/10.4315/0362-028X-48.7.578
  26. Reynolds, A.E. and Carpenter, J.A. Bactericidal properties of acetic and propionic acids on pork carcassess. J. Anim. Sci. 38: 515-519 (1974) https://doi.org/10.2527/jas1974.383515x
  27. Netten, P.van., Mossel, D.A.A. and Huis-in't-Veld, J.H.J. Microbial changes on freshly slaughtered pork carcasses due to 'hot' lactic acid decontamination. J. Food Saf. 17: 89-111 (1997) https://doi.org/10.1111/j.1745-4565.1997.tb00179.x
  28. Marples, R.R. and Towers, A.G. A laboratory model for the investigation of contact transfer of micro-organism. J. Hyg. 82: 237-248 (1979) https://doi.org/10.1017/S0022172400025651
  29. Mackintosh, C.A. and Hoffman, P.N. An extended model for transfer of microorganisms via the hands: differences between organisms and the effect of alcohol disinfection. J. Hyg. 92: 345-355 (1984) https://doi.org/10.1017/S0022172400064561
  30. McClure, P.J., Beaumont, A.L., Sutherland, J.P. and Roberts, T.A. Predictive modelling of growth of Listeria monocytoeenes: the effects on growth of NaCl, pH, storage temperature and $NaNO_2$. Int. J. Food Microbiol. 34: 221-232 (1997) https://doi.org/10.1016/S0168-1605(96)01193-2
  31. Bhaduri, S., Turner-Jones, C.O., Buchanan, R.L. and Phillips, J.G. Response surface model of the effect of pH, sodium chloride and sodium nitrite on growth of Yersinia enterocolitica at low temperatures. Int. J. Food Microbiol. 23: 333-343 (1994) https://doi.org/10.1016/0168-1605(94)90161-9
  32. Gibson, A.M., Bratchell, N. and Roberts, T.A. The effect of pH, sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry. J. Appl. Bacteriol. 62: 479-490 (1987) https://doi.org/10.1111/j.1365-2672.1987.tb02680.x
  33. Zweitering, M.H. and van Gerwen, S.J.C. Sensitivity analysis in quantitative microbial risk assessment. Int. J. Food Microbiol. 58: 213-221 (2000) https://doi.org/10.1016/S0168-1605(00)00275-0
  34. Buchanan, R.L. and Phillips, J.G. Response surface model for predicting the effects of temperature pH, sodium chloride content, sodium nitrite concentration and atmosphere on the growth of L. monocytogenes. J. Food Prot. 53: 370-376 (1990) https://doi.org/10.4315/0362-028X-53.5.370