Browse > Article
http://dx.doi.org/10.13103/JFHS.2013.28.3.217

Mathematical Models to Predict Staphylococcus aureus Growth on Processed Cheeses  

Kim, Kyungmi (Department of Food and Nutrition, Sookmyung Women's University)
Lee, Heeyoung (Department of Food and Nutrition, Sookmyung Women's University)
Moon, Jinsan (Veterinary Pharmaceutical Management Division, Animal, Plant and Fisheries Quarantine and Inspection Agency)
Kim, Youngjo (Livestock Products Sanitation Division, Ministry of Food and Drug Safety)
Heo, Eunjeong (Food Microbiology Division, Ministry of Food and Drug Safety)
Park, Hyunjung (Agro-Livestock and Fishery Products Policy Division, Ministry of Food and Drug Safety)
Yoon, Yohan (Department of Food and Nutrition, Sookmyung Women's University)
Publication Information
Journal of Food Hygiene and Safety / v.28, no.3, 2013 , pp. 217-221 More about this Journal
Abstract
This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at $4^{\circ}C$ (1440 h), $15^{\circ}C$ (288 h), $25^{\circ}C$ (72 h), and $30^{\circ}C$ (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (${\mu}_{max}$; ${\log}CFU{\cdot}g^{-1}{\cdot}h^{-1}$), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at $15^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. The ${\mu}_{max}$ values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.
Keywords
Staphylococcus aureus; processed cheese; predictive model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Baranyi, J. and Roberts T. A. A dynamic approach to predicting bacterial growth in food. Int. J. Food Microbiol. 23, 277- 294 (1994).   DOI   ScienceOn
2 McClure, P. J., Beaumont, A. L., Sutherland, J. P., and Roberts, T. A. Predictive modeling of growth of Listeria monocytogenes: the effects on growth of NaCl, pH, storage temperature and sodium nitrate. Int. J. Food Microbiol. 34, 221-232 (1997).   DOI   ScienceOn
3 Lee, J., Skandamis, P., Park, A., Yoon, H., Hwang, I. G., Lee, S. H., Cho, J. I., Yoon, Y. Development of mathematical models to predict Staphylococcus aureus growth in sauces under constant and dynamic temperatures. Food Sci. Technol. Res. 19, 331-335 (2013).   DOI
4 Dengremont, E. and Membre, J. M. Statistical approach for comparison of the growth rates of five strains of Staphylococcus aureus. Appl. Environ. Microbiol. 61, 4389-4395 (1995).
5 Oscar, T. Validation of lag time and growth rate models for Salmonella Typhimurium: acceptable prediction zone method. J. Food Sci. 70, M129-M137 (2005).   DOI   ScienceOn
6 FDAP (Food and Drug Administration Philippines). Revised Guidelines for the Assessment of Microbiological Quality of Processed Foods. Available from: http://www.fda.gov.ph/ attachments/article/17218/FC2013-010.pdf. Accessed on November 13, 2012 (2013).
7 JETRO (Japan External Trade Organization). Specifications and standards for foods, food additives, etc. under the food sanitation act (Abstract) 2010. Available at: http://www.jetro. go.jp/en/reports/regulations/pdf/foodext2010e.pdf. Accessed on November 10, 2012 (2011).
8 MPI (Ministry for Primary Industries). Microbiological Reference Criteria for Food. Available at: http://www.foodsafety. govt.nz/elibrary/industry/microbiological_referenceguide_ assess.pdf. Accessed on November 10, 2012 (1995).
9 QIA (Animal, Plant and Fisheries Quarantine and Inspection Agency) Standard for livestock product processing ingredients. pp. 14, 35-36 (2011).
10 Varga L. Microbiological quality of commercial dairy products In: Communicating Current Research and Educational Topics and Trends in Applied Microbiology. Mendez-Vilas A. (ed) Formatex Research Center, Badajoz. pp. 487-494 (2007).
11 Coroller, L., Guerrot, V., Huchet, V., Le Marc, Y., Mafart, P., Sohier, D., and Thuault, D. Modelling the influence of single acid and mixture on bacterial growth. Int. J. Food Microbiol. 100, 167-178 (2005).   DOI   ScienceOn
12 Van Impe, J. F., Posche,t F., Geeraerd, A. H., and Vereecken, K. M. Towards a novel class of predictive microbial growth models. Int. J. Food Microbiol. 100, 97-105 (2005).   DOI   ScienceOn
13 Jo, C., Kim, H. J., Kim, D. H., Lee, W. K., Ham, J. S., and Byun, M. W. Radiation sensitivity of selected pathogens in ice cream. Food Control. 18, 859-865 (2007).   DOI   ScienceOn
14 Lihono, M. A., Mendonca, A. F., Dickson, J. S., and Dixon, P. M. A predictive model to determine the effects of temperature, sodium pyrophosphate, and sodiuchloride on thermal inactivation of starved Listeria monocytogenes in pork slurry. J. Food Prot. 66, 1216-1221 (2003).
15 Xanthiakos, K., Simos, D., Angelidis, A. S., Nychas, G. J., and Koutsoumanis, K. Dynamic modeling of Listeria monocytogenes growth in pasteurized milk. J. Appl. Microbil. 100, 1289-1298 (2006).   DOI   ScienceOn
16 Kim, H. J., Song, B. S., Kim, J. H., Choi, J., Lee, J. W., Jo, C., and Byun, M. W. Application of gamma irradiation for the microbiological safety of sliced cheddar cheese. J. Radiat. Ind. 1, 15-19 (2007).
17 Tekinsen, K. K. and Ozdemir, Z. Prevalence of foodborne pathogens in Turkish Van otlu (Herb) cheese. Food Control. 17, 707-711 (2006).   DOI   ScienceOn
18 KFDA (Korea Food and Drug Administration) Status of food poisoning outbreaks in Korea. Available at: http://fm.kfda.go. kr. Accessed on March 23, 2013 (2013).
19 Dinges, M. M., Orwin, M., and Schlievert, P. M. Exotoxins of Staphylococcus aureus. Clin. Microbiol. Rev. 13, 16-34 (2000).   DOI   ScienceOn
20 Glass, K. and Doyle, E. M. Safety of processed cheese: A review of the scientific literature. Available at: http://fri.wisc. edu/docs/pdf/ProcCheese.pdf. Accessed on December 5, 2012 (2005).
21 Tirado, C. and Schimdt, K. WHO surveillance program for control of foodborne infections and intoxication: preliminary results and trends across greater Europe. World Health Organization. J. Infect. 43, 80-84 (2001).
22 Wieneke, A. A., Roberts, D., and Gilbert, R. J. Staphylococcal food poisoning in the United Kingdom 1969-90. Epidemiol. Infect. 110, 519-531 (1993).   DOI   ScienceOn
23 Zinke, C., Winter, M., Mohr, E., and Kromker, V. Occurrence of methicillin-resistant Staphylococcus aureus in cheese produced in German farm-dairies. Adv. Microbiol. 2, 629-633 (2011).
24 Haran, K., Gooden, S. M., Boxrud, D., Jawahir, S., Bender, J. B., and Sreevatsan, S. Prevalence and characterization of Staphylococcus aureus, including methicillin-resistant Staphylococcus aureus, isolated from bulk tank milk from Minnesota dairy farms. J. Clin. Microbiol. 50, 688-695 (2011).