Validation of Predictive Liquid Model Systems for the Growth of Listeria monocytogenes and Yersinia enterocolitica on Pork at Various Temperatures

  • Rho, Min-Jeong (Korea Health Industry Development Institute) ;
  • Chung, Myung-Sub (Korea Health Industry Development Institute) ;
  • Kim, Jeong-Weon (Department of Science & Technology Education for Life, Seoul National University of Education) ;
  • Park, Ji-Yong (Department of Biotechnology, Yonsei University)
  • Published : 2005.02.28

Abstract

The present study was carried out to envisage the aerobic growth of Listeria monocytogenes and Yersinia enterocolitica on pork, which is one of the major meat sources in Korea. The results were compared with the previously developed predictive model systems for the verification of microbial growth in a real situation during pork processing. Pork loin samples (8.0 g, 5 mm thick) were aseptically prepared and inoculated with each pathogen by immersing into the respective inoculums for one min. Each of the samples were then wrapped with PE film and stored at 5, 10, and $15^{\circ}C$ up to 36 days to measure the growth profile of the respective pathogens. The growth parameters were calculated by using Gompertz equation and were compared with the previously reported data. The predicted generation time (GT) of L. monocytogenes at 5, 10 and $15^{\circ}C$ was 28.74, 7.85 and 4.02 hr, respectively, and for Y. enterocolitica was 10.29, 4.74 and 2.50 hr, at the same temperatures respectively. In this study, the GT values predicted on pork were slightly higher than the values predicted in other studies using liquid model systems. Unlike previous reports, both the pathogens were found to grow at $5^{\circ}C$ on pork. This finding recommends the necessity of controlling the growth of both the pathogens during the slaughtering process and distribution.

Keywords

References

  1. The current status of foodborne outbreaks and the prevention plans in Korea Korea Food and Drug Administration
  2. CRC Crit. Rev. Food Sci. Nutr. v.35 Microbial modeling Whiting, R.C. https://doi.org/10.1080/10408399509527711
  3. J. Food Safety v.13 Response surface models for the effects of temperature, pH, sodium chloride, and sodium nitrite on the aerobic and anaerobic growth of Staphylococcus aureus 196E Buchanan, R.L.;Smith, J.L.;McColgan, C.;Marmer, B.S.;Golden, M.;Dell, B. https://doi.org/10.1111/j.1745-4565.1993.tb00103.x
  4. Int. J. Food Microbiol. v.21 Predictive modelling of growth of Staphylococcus aureus: the effects of temperature, pH and sodium chloride Sutherland, J.P.;Bayliss, A.J.;Roberts, T.A. https://doi.org/10.1016/0168-1605(94)90029-9
  5. J. Food Prot. v.58 Growth of Escherichia coli 0157:H7 at fluctuating incubation temperatures Rajkowski, K.T.;Marmer, B.S.
  6. Int. J. Food Microbiol. v.25 Predictive modelling of growth of Escherichia coli 0157:H7: the effects of temperature, pH and sodium chloride Sutherland, J.P.;Bayliss, A.J.;Braxton, D.S. https://doi.org/10.1016/0168-1605(94)00082-H
  7. Int. J. Food Microbiol. v.6 Predicting microbial growth: growth responses of Salmonellae in a laboratory medium as affected by pH, sidium chloride, and storage temperature Gibson, A.M.;Bratchell, N.;Roberts, T.A. https://doi.org/10.1016/0168-1605(88)90051-7
  8. Int. J. Food Microbiol. v.23 Response surface model of the effect of pH, sodium chloride and sodium nitrite on growth of Yersinia enterocolitica at low temperatures Bhaduri, S.;Turner-Jones, C.O.;Buchanan, R.L.;Phillips, J.G. https://doi.org/10.1016/0168-1605(94)90161-9
  9. J. Appl. Bacteriol. v.79 Expanded response surface model for predicting the effects of temperatures, pH, sodium chloride contents and sodium nitrite concentrations on the growth rate of Yersinia enterocolitica Bhaduri, S.;Buchanan, R.L.;Phillips, J.G. https://doi.org/10.1111/j.1365-2672.1995.tb00930.x
  10. Int. J. Food Microbiol. v.34 Predictive modelling of growth of Listeria monocytogenes: the effects on growth of NaCl, pH, storage temperature and ${NaNO}_2$ McClure, P.J.;Beaumont, A.L.;Sutherland, J.P.;Roberts, T.A. https://doi.org/10.1016/S0168-1605(96)01193-2
  11. Int. J. Food Microbiol. v.32 Predictive models of the effect of temperature, pH and acetic and lactic acids on the growth of Listeria monocytogenes George, S.M.;Richardson, L.C.C.;Peck, M.W. https://doi.org/10.1016/0168-1605(96)01108-7
  12. J. Food Prot. v.53 Response surface model for predicting the effects of temperature, pH, sodium chloride content, sodium nitrite concentration and atmosphere on the growth of L. monocytogenes Buchanan, R.L.;Phillips, J.G.
  13. J. Food Prot. v.59 Interactive effects of temperature, initial pH, sodium chloride, and sodium pyrophosphate on the growth kinetics of Clostridium perfringens Juneja, V.K.;Marmer, B.S.;Phillips, J.G.;Palumbo, S.A.
  14. J. Fd Hyg. Safety v.19 Computation of maximum edible time using monitoring data of Staphylococcus aureus in Kimbap and Food MicroModel Lee, H.;Lee, G.;Yoon, E.;Kim, H.;Kang, Y.;Lee, D.;Park, J.;Lee, S.;Woo, G.;Kang, S.;Yang, J.;Yang, K.
  15. Korean J. Food Sci. Technol. v.35 Predicting the contamination of Listeria monocytogenes and Yersinia enterocolitica in pork production using Monte Carlo simulation Rho, M.J.;Chung, M.S.;Park, J.
  16. Int. J. Food Microbiol. v.52 Predictive food microbiology for the meat industry: a review McDonald, K.;Sun, D.W. https://doi.org/10.1016/S0168-1605(99)00126-9
  17. Int. J. Food Microbiol. v.46 Validation of predictive models describing the growth of Listeria monocytogenes te Giffel, M.C.;Zwietering, M.R. https://doi.org/10.1016/S0168-1605(98)00189-5
  18. 2001 National health and nutrition survey report Korea Ministry of Health and Welfare
  19. Meat Sci. v.36 Impact of animal husbandry and slaughter technologies on microbial contamination of meat: monitoring and control Huis in't Veld, J.R.J.;Mulder, R.W.A.W.;Snijders, J.M.A. https://doi.org/10.1016/0309-1740(94)90038-8
  20. Generic HACCP model for pork slaughter United States Department of Agriculture
  21. J. Food Prot. v.64 Monitoring of microbial hazards at farms, slaughterhouses, and processing lines of swine in Korea Rho, M.J.;Chung, M.S.;Lee, J.R.;Park, J.
  22. Int. J. Food Microbiol. v.35 The aerobic growth of Aeromonas hydrophila and Listeria monocytogenes in broths and on pork Gill, C.O.;Greer, G.G.;Dilts, B.D. https://doi.org/10.1016/S0168-1605(96)01224-X
  23. Food Microbiol. v.12 Predicting the aerobic growth of Yersinis enterocolitica on pork fat and muscle tissues Greer, G.G.;Gill, C.O.;Dilts, B.D. https://doi.org/10.1016/S0740-0020(95)80131-6
  24. Can. Inst. Food Sci. Technol. J. v.24 Effects of lactic acid and vacuum packaging on beef processed in a research abattoir Greer, G.G.;Jones, S.D.M. https://doi.org/10.1016/S0315-5463(91)70040-0
  25. Bacteriological analytical manual US Food and Drug Administration
  26. J. Appl. Bacteriol. v.62 The effect of pH, sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry Gibson, A.M.;Bratchell, N.;Roberts, T.A. https://doi.org/10.1111/j.1365-2672.1987.tb02680.x
  27. Food Code Korea Food and Drug Administration