Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-22T23:53:32.907Z Has data issue: false hasContentIssue false
  • English
  • Français

Growth kinetics of Staphylococcus aureus on Brie and Camembert cheeses

Published online by Cambridge University Press:  14 April 2014

Heeyoung Lee ,
Kyungmi Kim ,
Soomin Lee ,
Minkyung Han  and
Yohan Yoon
Heeyoung Lee
Affiliation:
Department of Food and Nutrition, Sookmyung Women's University, Seoul 140-742, Korea
Kyungmi Kim
Affiliation:
Department of Food and Nutrition, Sookmyung Women's University, Seoul 140-742, Korea
Soomin Lee
Affiliation:
Department of Food and Nutrition, Sookmyung Women's University, Seoul 140-742, Korea
Minkyung Han
Affiliation:
Food Microbiology Division, Ministry of Food and Drug Safety, Osong 363-700, Korea
Yohan Yoon*
Affiliation:
Department of Food and Nutrition, Sookmyung Women's University, Seoul 140-742, Korea
*
*For correspondence; e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

In this study, we developed mathematical models to describe the growth kinetics of Staphylococcus aureus on natural cheeses. A five-strain mixture of Staph. aureus was inoculated onto 15 g of Brie and Camembert cheeses at 4 log CFU/g. The samples were then stored at 4, 10, 15, 25, and 30 °C for 2–60 d, with a different storage time being used for each temperature. Total bacterial and Staph. aureus cells were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of Staph. aureus to calculate kinetic parameters such as the maximum growth rate in log CFU units (rmax; log CFU/g/h) and the lag phase duration (λ; h). The effects of temperature on the square root of rmax and on the natural logarithm of λ were modelled in the second stage (secondary model). Independent experimental data (observed data) were compared with prediction and the respective root mean square error compared with the RMSE of the fit on the original data, as a measure of model performance. The total growth of bacteria was observed at 10, 15, 25, and 30 °C on both cheeses. The rmax values increased with storage temperature (P<0·05), but a significant effect of storage temperature on λ values was only observed between 4 and 15 °C (P<0·05). The square root model and linear equation were found to be appropriate for description of the effect of storage temperature on growth kinetics (R2=0·894–0·983). Our results indicate that the models developed in this study should be useful for describing the growth kinetics of Staph. aureus on Brie and Camembert cheeses.

Keywords

Staphylococcus aureusBrie cheeseCamembert cheeseMathematical model
Type
Research Article
Information
Journal of Dairy Research , Volume 81 , Issue 2 , May 2014 , pp. 252 - 256
Copyright
Copyright © Proprietors of Journal of Dairy Research 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baranyi, J & Roberts, TA 1994 A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23 277–294CrossRefGoogle ScholarPubMed
Bergdoll, MS 1989 Staphylococcus aureus. In Foodborne Bacterial Pathogens, pp. 463–523 (Ed. Doyle, MP). New York, NY, USA: Marcel Dekker, Inc.Google Scholar
Colombari, V, Mayer, MD, Laicini, ZM, Mamizuka, E, Franco, BD, Destro, MT & Landgraf, M 2007 Foodborne outbreak caused by Staphylococcus aureus: phenotypic and genotypic characterization of strains of food and human sources. Journal of Food Protection 70 489–493CrossRefGoogle ScholarPubMed
Jablonski, LM & Bohach, GA 2001 Staphylococcus aureus. In Fundamentals of Food Microbiology, pp. 410–434 (Eds Beuchat, L, Doyle, M & Montville, T). Washington, DC: American Society for MicrobiologyGoogle Scholar
JLW 2013 Canada's Food and Drugs Act & Regulations. http://laws-lois.justice.gc.ca/Search/Search.aspx?txtS3archA11=cheese&txtT1tl3=%22Food+and+Drug+Regulations%22&h1ts0n1y=0&ddC0nt3ntTyp3=Regulations (Accessed 03 September 2013: Justice Laws Website)Google Scholar
Jorgensen, HJ, Mathisen, T, Lovseth, A, Omoe, K, Qvale, KS & Loncarevic, S 2005 An outbreak of staphylococcal food poisoning caused by enterotoxin H in mashed potato made with raw milk. FEMS Microbiololy Letters 252 267–272CrossRefGoogle Scholar
Kousta, M, Mataragas, M, Skandamis, P & Drosinos, EH 2010 Prevalence and sources of cheese contamination with pathogens at farm and processing levels. Food Control 21 805–815CrossRefGoogle Scholar
Lee, J, Skandamis, P, Park, A, Yoon, H, Hwang, IG, Lee, SH, Cho, JI & Yoon, Y 2013 Development of mathematical models to predict Staphylococcus aureus growth in sauces under constant and dynamic temperatures. Food Science and Technology Research 19 331–335CrossRefGoogle Scholar
Lee, JY, Suk, HJ, Lee, H, Lee, S & Yoon, Y 2012 Application of probabilistic model to calculate probabilities of Escherichia coli O157:H7 growth on polyethylene cutting board. Korean Jourmal For Food Science of Animal Resources 32 62–67CrossRefGoogle Scholar
Le Loir, Y, Baron, F & Gautier, M 2003 Staphylococcus aureus and food poisoning. Genetics and Molecular Research 2 63–76Google ScholarPubMed
Little, CL, Rhoades, JR, Sagoo, SK, Harris, J, Greenwood, M & Mithani, V 2008 Microbial quality of retail cheese made from raw, thermised or pasteurized milk in UK. Food Microbiology 25 304–312CrossRefGoogle ScholarPubMed
Mataragas, M, Drosinos, EH, Siana, P, Skandamis, P & Metaxopoulos, I 2006 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. Journal of Food Protection 69 1312–1321CrossRefGoogle Scholar
McMeekin, TA, Brown, J, Krist, K, Miles, D, Neumeyer, K, Nichols, DS, Olley, J, Presser, K, Ratkowsky, DA, Ross, T, Slater, M & Soontranon, S 1997 Quantitative microbiology: a basis for food safety. Emerging Inrectious Diseases 3 541–550CrossRefGoogle ScholarPubMed
MFDS 2013 Status of food poisoning outbreaks in Korea. http://www.mfds.go.kr/e-stat/index.do (Accessed 03 September 2013: Ministry of Food and Drug Safety)Google Scholar
Oscar, TP 2005a Development and validation of primary, secondary, and tertiary models for growth of Salmonella Typhimurium on sterile chicken. Journal of Food Protection 68 2606–2613CrossRefGoogle ScholarPubMed
Oscar, TP 2005b Validation of lag time and growth rate models for Salmonella Typhimurium: acceptable prediction zone method. Journal of Food Science 70 M129–M137CrossRefGoogle Scholar
Perez-Rodriguez, F, Posada-Izquierdo, GD, Valero, A, Garcia-Gimeno, RM & Zurera, G 2013 Modelling survival kinetics of Staphylococcus aureus and Escherichia coli O157:H7 on stainless steel surfaces soiled with different substrates under static conditions of temperature and relative humidity. Food Microbiology 33 197–204CrossRefGoogle ScholarPubMed
QIA 2011 Standard for Livestock Product Processing Ingredients. Anyang: Animal, Plant and Fisheries Quarantine and Inspection AgencyGoogle Scholar
Ratkowsky, DA, Olley, J, McMeekin, TA & Ball, A 1982 Relationship between temperature and growth rate of bacterial cultures. Journal of Bacteriology 149 1–5CrossRefGoogle ScholarPubMed
Tamarapu, S, McKillip, JL & Drake, M 2001 Development of a multiplex Polymerase chain reaction assay for detection and differentation of Staphylococcus aureus in dairy products. Journal of Food Protection 64 664–668CrossRefGoogle Scholar
Yoon, Y 2010 Principal theory and application of predictive microbiology. Food Science and industry 43 70–74Google Scholar
Yoon, Y, Belk, KE, Scanga, JA, Smith, GC & Sofos, JN 2009 Modeling the growth/no-growth boundaries of postprocessing Listeria monocytogenes contamination on frankfurters and bologna treated with lactic acid. Applied Environmental Microbiology 75 353–358CrossRefGoogle ScholarPubMed
Yoon, Y, Geornaras, I, Scanga, JA, Belk, KE, Smith, GC, Kendall, PA & Sofos, JN 2011 Probabilistic models for the prediction of target growth interfaces of Listeria monocytgenes on ham and turkey breast products. Journal of Food Science 76 450–455CrossRefGoogle Scholar