Introduction: The purpose of the study was to determine and model the growth rates of L. monocytogenes in cooked cured ham stored at various temperatures.
Material and Methods: Samples of cured ham were artificially contaminated with a mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12, or 15°C for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14, and 16 days. A series of decimal dilutions were prepared from each sample and plated onto ALOA agar, after which the plates were incubated at 37°C for 48 h under aerobic conditions. The bacterial counts were logarithmised and analysed statistically. Five repetitions of the experiment were performed.
Results: Both storage temperature and time were found to significantly influence the growth rate of listeriae (P < 0.01). The test bacteria growth curves were fitted to three primary models: the Gompertz, Baranyi, and logistic. The mean square error (MSE) and Akaike’s information criterion (AIC) were calculated to evaluate the goodness of fit. It transpired that the logistic model fit the experimental data best. The natural logarithms of L. monocytogenes’ mean growth rates from this model were fitted to two secondary models: the square root and polynomial.
Conclusion: Modelling in both secondary types can predict the growth rates of L. monocytogenes in cooked cured ham stored at each studied temperature, but mathematical validation showed the polynomial model to be more accurate.
1. Ahmed O., Pangloli P., Hwang C., Zivanovic S., Wu T., D'Souza D., Draughon F.A.: The occurrence of Listeria monocytogens in retail ready-to-eat meat and poultry products related to the levels of acetate and lactate in the products. Food Control 2014. http://dx.doi.org/10.1016/j.foodcont.2014.12.015.
2. Baranyi J., Roberts T.A.: A dynamic approach to predicting bacterial growth in food. Int J Food Microbiol 1994, 23, 277–294.
3. Berger S.: Listeriosis: Global Status. GIDEON Informatics, Inc, Los Angeles, 2016.
4. Black D.G., Davidson P.M.: Use of modeling to enhance the microbiological safety of the food system. Compr Rev Food Sci Food Saf 2008, 7, 159–167.
5. Buchanan R.L., 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 Listeria monocytogenes. J. Food Protection 1990, 53, 370–376. http://wyndmoor.errc.ars.usda.gov/pubs/viewpub.aspx?iden=5478
6. ComBase 2016. http://browser.combase.cc/ComBase_Predictor.aspx?model=1#
7. Corlett D.A., Brown M.H. pH and acidity. In: Microbial ecology of foods. Factors affecting life and death of microorganisms. International Commission on Microbiological Specification for Foods. Academic Press, New York, 1980, p 101.
8. Czarkowski M.P., Cielebąk E., Kondej B., Staszewska E.: Infectious diseases and poisonings in Poland in 2012. National Institute of Public Health – National Institute of Hygiene, Department of Epidemiology, Warsaw, 2013 pp. 24, 126.
9. Gómez D., Iguácel L.P., Rota M.C., Carramiñana J.J., Ariño A., Yangüela J.: Occurrence of Listeria monocytogenes in ready-to-eat meat products and meat processing plants in Spain. Foods 2015, 4, 271–282.
10. Dalgaard P., Jorgensen L.V.: Predicted and observed growth of Listeria monocytogenes in seafood challenge tests and in naturally contaminated cold-smoked salmon. Int J Food Microbiol 1998, 40, 105–115.
11. Devlieghere F., Francois K., De Meulenaer B., Baert K.: Modelling Food Safety. In: Luning P.A, Devlieghere F., Verhe F. (ed) Safety in the agri-food chain. Wageningen Academic Publishers, the Netherlands 2006, pp. 397–417.
12. EFSA. European Food Safety Authority: Analysis of the baseline survey on the prevalence of Listeria monocytogenes in certain ready-to-eat (RTE) foods in the EU, 2010–2011 Part A: Listeria monocytogenes prevalence estimates. EFSA J 2013, 11, 3241.
13. EFSA. European Food Safety Authority: The European Union Summary Report on Trends and Sources of Zoonoses, Zoonotic Agents and Food-borne Outbreaks in 2013. EFSA J 2015, 13, 3991.
14. European Commission. 2005. Commission Regulation (EC) no. 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Official J Eur Union L 22.12.2005, 338, 1–26.
15. Gibson A.M., Bratchell N., Roberts T.A.: Predicting microbial growth: growth responses of salmonellae in a laboratory medium as affected by pH, sodium chloride and storage temperature. Int J Food Microbiol 1988, 6, 155–178.
16. Giffel M.C., Zwietering M.H.: Validation of predictive models describing the growth of Listeria monocytogenes. Int. J. Food Microbiol., 1999, 46, 135–149.
17. Hoang H.M., Flick D., Derens E., Alvarez G., Laguerre O.: Combined deterministic and stochastic approaches for modeling the evolution of food products along the cold chain. Part II: A case study. Int J Refrig 2012, 35, 915–926.
18. Hwang C.A., Tamplin M.L.: Modeling the lag phase and growth rate of Listeria monocytogenes in ground ham containing sodium lactate and sodium diacetate at various storage temperatures. J Food Sci 2007, 72, M246–M253.
19. Laguerre O., Derens E., Palagos B.: Study of domestic refrigerator temperature and analysis of factors affecting temperature: a French survey. Int J Refrig 2002, 25, 653–659.
20. Likar K., Jevsnik M.: Cold chain maintaining in food trade. Food Control 2006, 17, 108–113.
21. López S., Prieto M., Dijkstra J., Ghanoa M.S., France J.: Statistical evaluation of mathematical models for microbial growth. Int J Food Microbiol 2004, 96, 289–300.
22. Luo K., Hong S.S., Oh D.H.: Modeling the effect of storage temperatures on the growth of Listeria monocytogenes on ready-to-eat ham and sausage. J Food Prot 2015, 78, 1675–1681.
23. Mataragas M., Drosinos E.H., Siana P., Skandamis P., Metaxopoulos I.: Determination of the growth limits and kinetic behavior of Listeria monocytogenes in a sliced cooked cured meat product: validation of the predictive growth model under constant and dynamic temperature storage conditions. J Food Prot 2006, 69, 1312–1321.
24. McKellar R.C., Lu X.: Primary models. In: Modeling microbial responses in food, edited by R.C. McKellar, X. Lu, CRC Press LLC, Boca Raton, 2004, pp. 21–62.
25. Pathogen Modeling Program (PMP) Online. http://pmp.errc.ars.usda.gov/PMPOnline.aspx. Modified: 11/3/2015
26. Polish Standard: PN-A-82007 Meat products.
27. Posfay-Barbe K.M., Wald E.R.: Listeriosis. Semin Fetal Neonatal Med 2009, 14, 228–233.
28. Ray B., Bhunia A.: Control by low pH and organic acids. In: Fundamental food microbiology. CRC Press by Taylor & Francis Group, Boca Raton, London, New York, 2008, p. 394.
29. Ross T.: Indices for performance evaluation of predictive models in food microbiology. J Appl Bacteriol 1996, 81, 501–508.
30. Sadkowska-Todys M., Zieliński A., Czarkowski M.P.: Infectious diseases in Poland in 2013. Epidemiological Review 2015, 69, 195–204.
31. Seman D.L., Borger A.C., Meyer J.D., Hall P.A., Milkowski A.L.: Modeling the growth of Listeria monocytogenes in cured ready-to-eat processed meat products by manipulation of sodium chloride, sodium diacetate, potassium lactate, and product moisture content. J Food Prot 2002, 65, 651–658.
32. Szczawińska M.E., Szczawiński J., Łobacz A.: Effect of temperature on the growth kinetics of Salmonella Enteritidis in cooked ham. Bull Vet Inst Pulawy 2014, 58, 47–56.
33. Szczawiński J. Predictive microbiology - practical applications. Med Weter 2012, 68, 540–543.
34. Szczawiński J., Stańczak B., Pęconek J.: Behaviour of Listeria monocytogenes in fermented milk products - prediction on the basis of experiments with real food products and Pathogen Modeling Program V. 4.0. In: Shelf life prediction for improved safety and quality of foods. Copernicus Project CIPA-CT94-0120. Copi-Print Library Building University College Dublin 1998, pp. 187–192.
35. Szczawiński J., Szczawińska M.E., Łobacz A., Jackowska-Tracz A.: Modeling the effect of temperature on survival rate of Listeria monocytogenes in yogurt. Pol J Vet Sci 2016, 19, 317–324.