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Models of Pseudomonas Growth Kinetics and Shelf Life in Chilled Longissimus dorsi Muscles of Beef

  • Zhang, Yimin (College of Food Science and Engineering, Shandong Agricultural University) ;
  • Mao, Yanwei (College of Food Science and Engineering, Shandong Agricultural University) ;
  • Li, Ke (College of Food Science and Engineering, Shandong Agricultural University) ;
  • Dong, Pengcheng (College of Food Science and Engineering, Shandong Agricultural University) ;
  • Liang, Rongrong (College of Food Science and Engineering, Shandong Agricultural University) ;
  • Luo, Xin (College of Food Science and Engineering, Shandong Agricultural University)
  • Received : 2010.11.05
  • Accepted : 2011.03.01
  • Published : 2011.05.01

Abstract

The aim of this study was to confirm Pseudomonas spp. as the specific spoilage organism (SSO) of chilled beef during aerobic storage and to establish a model to predict the shelf life of beef. Naturally contaminated beef was stored at $4^{\circ}C$, and the spoilage limit of Pseudomonas organisms was determined by measuring several quality indicators during storage, including the number of Pseudomonas organisms, total number of bacteria, total volatile basic nitrogen (TVBN) values, L value color scale scores and sensory evaluation scores. The beef was then stored at 0, 4, 7, 10, 15 or $20^{\circ}C$ for varying amounts of time, and the number of Pseudomonas organisms were counted, allowing a corresponding growth model to be established. The results showed that the presence of Pseudomonas spp. was significantly correlated to each quality characteristic (p<0.01), demonstrating that Pseudomonas spp. are the SSO of chilled beef and that the spoilage limit was $10^{8.20}$ cfu/g. The Baranyi and Roberts equation can predict the growth of Pseudomonas spp. in beef, and the $R^2$ value of each model was greater than 0.95. The square root model was used as follows, and the absolute values of the residuals were less than ${0.05:\;{\mu_{max}}^{1/2}$ = 0.15604 [T+(-0.08472)] (p<0.01), $R^2$ = 0.98, $\lambda^{-1/2}$ = 0.0649+0.0242T (p<0.01, $R^2$ = 0.94). The model presented here describes the impact of different temperatures on the growth of Pseudomonas spp., thereby establishing a model for the prediction of the shelf life of beef stored between 0 to $20^{\circ}C$.

Keywords

References

  1. Baranyi, J. and T. A. Roberts. 1995. Mathematics of predictive food microbiology. Int. J. Food Microbiol. 26(2):199-218. https://doi.org/10.1016/0168-1605(94)00121-L
  2. Brooks, J. C., M. Alvarado, T. P. Stephens, J. D. Kellermeier, A. W. Tittor, M. F. Miller and M. M. Brashears. 2008. Spoilage and safety characteristics of ground beef packaged in traditional and modified atmosphere packages. J. Food Prot. 71(2):293-301.
  3. Ca′rdenas, F. C., L. Giannuzzi and N. E. Zaritzky. 2008. Mathematical modelling of microbial growth in ground beef from Argentina. Effect of lactic acid addition, temperature and packaging filma. Meat Science 79(3):509-520. https://doi.org/10.1016/j.meatsci.2007.12.003
  4. Dalgaard, P. 1995. Modelling of microbial activity and prediction of shelf life of packed fresh fish. Int. J. Food Microbiol. 26(3):305-317. https://doi.org/10.1016/0168-1605(94)00136-T
  5. Ercolini, D., F. Russo, E. Torrieri, P. Masi and F. Villani. 2006. Changes in the spoilage-related microbiota of beef during refrigerated storage under different packaging conditions. Appl. Environ. Microbiol. 72(7):4663-4671. https://doi.org/10.1128/AEM.00468-06
  6. Ercolini, D., F. Russo, G. Blaiotta, O. Pepe, G. Mauriello and F. Villani. 2007. Simultaneous detection of pseudomonas fragi, P. lundensis, and P. putida from meat by use of a multiplex PCR assay targeting the carA gene. Appl. Environ. Microbiol. 73(7):2354-2359. https://doi.org/10.1128/AEM.02603-06
  7. Fu, P., P. Li, K. Zhou and W. Cheng. 2008. Development of models to predict the growth of Pseudomonas isolated from chilling pork. Transactions of the Chinese Society of Agricultural Engineering 24(4):229-234.
  8. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China and Standardization Administration of the People's Republic of China. 2008. Fresh and frozen beef, cuts: GB17238-2008. Standards Press of China. P. R. China.
  9. Giannuzzi, L., A. Pinotti and N. Zaritzky. 1998. Mathematical modelling of microbial growth in packaged refrigerated beef stored at different temperatures. Int. J. Food Microbiol. 39(1-2):101-110. https://doi.org/10.1016/S0168-1605(97)00127-X
  10. Gill, C. O., F. Dussault, R. A. Holley, A. Houde, T. Jones, N. Rheault, A. Rosales and S. Quessy. 2000. Evaluation of the hygienic performances of the processes for cleaning, dressing and cooling of pig carcasses in eight packing plants. Int. J. Food Microbiol. 58(1-2):65-72. https://doi.org/10.1016/S0168-1605(00)00294-4
  11. Gill, C. O., G. G. Greer and B. D. Dilts. 1997. The aerobic growth of Aeromonas hydrophila and Listeria monocytogenes in broths and on pork. Int. J. Food Microbiol. 35(1):67-74. https://doi.org/10.1016/S0168-1605(96)01224-X
  12. Gospavic, R., J. Kreyenschmidt, S. Bruckner, V. Popov and N. Haque. 2008. Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions. Int. J. Food Microbiol. 127(3):290-297. https://doi.org/10.1016/j.ijfoodmicro.2008.07.022
  13. Huang, X. and M. Xin. 2009. Microbiology, Higher Education Press, Beijing.
  14. Jay J. M., J. P. Vilai and M. E. Hughes. 2003. Profile and activity of the bacterial biota of ground beef held from freshness to spoilage at $5-7^{\circ}C$. Int. J. Food Microbiol. 81(2):105-111. https://doi.org/10.1016/S0168-1605(02)00189-7
  15. Jiang, Y. 2008. Development of models to predict the growth of Pseudomonas and E. coli isolated from chilling pork. Master Thesis, College of Food Science, Nanjing Agricultural University.
  16. Koutsoumanis, K. 2001. Predictive modeling of the shelf life of fish under nonisothermal conditions. Appl. Environ. Microbiol. 67(4):1821-1829. https://doi.org/10.1128/AEM.67.4.1821-1829.2001
  17. Koutsoumanis, K., A. Stamatiou, P. Skandamis and G.-J. E. Nychas. 2006. Development of a microbial model for the combined effect of temperature and pH on spoilage of ground meat and validation of the model under dynamic temperature conditions. Appl. Environ. Microbiol. 72(1):124-134. https://doi.org/10.1128/AEM.72.1.124-134.2006
  18. Lambropoulou, K. A., E. H. Drosinos and G. J. E. Nychas. 1996. The effect of glucose supplementation on the spoilage microflora and chemical composition of minced beef stored aerobically or under a modified atmosphere at $4^{\circ}C$. Int. J. Food Microbiol. 30(3):281-291. https://doi.org/10.1016/0168-1605(96)00954-3
  19. Li, M. 2006. Microbial ecology of chilled pork and prediction model of shelf life. Ph.D. Thesis, College of Food Science, Nanjing Agricultural University.
  20. Li, M., L. Sun, G. Zhou, X. Xu and W. Wu. 2008. Prediction model for the shelf-life of chilled pork stored at different temperatures. Transactions of the Chinese Society of Agricultural Engineering 24(4):235-239.
  21. Mancini, R. A. and M. C. Hunt. 2005. Current research in meat colour. Meat Sci. 71(1):100-121. https://doi.org/10.1016/j.meatsci.2005.03.003
  22. McDonald, K. and D.-W. Sun. 1999. Predictive food microbiology for the meat industry: a review. Int. J. Food Microbiol. 52(1-2):1-27. https://doi.org/10.1016/S0168-1605(99)00126-9
  23. Miller, A. J., J. L. Smith and R. L. Buchanan. 1998. Factors affecting the emergence of new pathogens and research strategies leading to their control. J. Food Saf. 18(4):243-263. https://doi.org/10.1111/j.1745-4565.1998.tb00219.x
  24. Ministry of Health of the People's Republic of China and Standardization Administration of the People's Republic of China. 2003. Method for analysis of hygienic standard of meat and meat products : GB/T5009.44-2003. Standards Press of China. P. R. China.
  25. Ministry of Health of the People's Republic of China and Standardization Administration of the People's Republic of China. 2005. Hygienic standard for fresh (frozen) meat of livestock: GB2707-2005. Standards Press of China. P. R. China.
  26. Nychas, G.-J. E., P. N. Skandamis, C. C. Tassou and K. P. Koutsoumanis. 2008. Meat spoilage during distribution. Meat Sci. 78(1-2):77-89. https://doi.org/10.1016/j.meatsci.2007.06.020
  27. Neumeyer, K., T. Ross and T. A. McMeekin. 1997. Development of a predictive model to describe the effects of temperature and water activity on the growth of spoilage pseudomonads. Int. J. Food Microbiol. 38(1):45-54. https://doi.org/10.1016/S0168-1605(97)00089-5
  28. Ratkowsky, D. A., J. Olley, T. A. McMeekin and A. Ball. 1982. Relationship between temperature and growth rate of bacterial cultures. J. Bacteriol. 149(1):1-5.
  29. Ross, T. 1996. Indices for performance evaluation of predictive models in food microbiology. J. Appl. Microbiol. 81(5):501-508. https://doi.org/10.1111/j.1365-2672.1996.tb01946.x
  30. Skandamis, P. N. and G.-J. E. Nychas. 2002. Preservation of fresh meat with active and modified atmosphere packaging conditions. Int. J. Food Microbiol. 79(1-2):35-45. https://doi.org/10.1016/S0168-1605(02)00177-0
  31. Tsironi, T., E. Dermesonlouoglou, M. Giannakourou and P. Taoukis. 2009. Shelf life modelling of frozen shrimp at variable temperature conditions. Food Sci. Technol. 42(2):664-671. https://doi.org/10.1016/j.lwt.2008.07.010
  32. Van Impe, J. F., F. Poschet, A. H. Geeraerd and K. M. Vereecken. 2005. Towards a novel class of predictive microbial growth models. Int. J. Food Microbiol. 100(1-3):97-105. https://doi.org/10.1016/j.ijfoodmicro.2004.10.007
  33. Xu, Z., L. Xiao and X. Yang. 2005. Microbial growth kinetics model of specific spoilage organisms and shelf life prediction for tilapia. J. Fisheries of China. 29(4):540-546.

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