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Journals / Gıda ve Yem Bilimi Teknolojisi Dergisi / 2026 / Sayı: 36

Modelling of the growth of Listeria monocytogenes in cooked ground beef stored under different storage conditions for 21 days

Farklı depolama koşullarında 21 gün depolanan pişmiş sığır kıymasında Listeria monocytogenes gelişiminin modellenmesi

Alper Küçükyılmaz(BURDUR MEHMET AKİF ERSOY ÜNİVERSİTESİ, BURDUR MESLEK YÜKSEKOKULU, GIDA İŞLEME BÖLÜMÜ)0009-0004-6938-0440
Zübeyde Polat(BURDUR MEHMET AKİF ERSOY ÜNİVERSİTESİ, VETERİNER FAKÜLTESİ, GIDA HİJYENİ VE TEKNOLOJİSİ BÖLÜMÜ)0000-0001-6662-1721
Ali Soyuçok(BURDUR MEHMET AKİF ERSOY ÜNİVERSİTESİ, BURDUR MESLEK YÜKSEKOKULU, GIDA İŞLEME BÖLÜMÜ)0000-0003-2626-5827
Pages
93–101
Publication Date
2026-07-02
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Richards and Logistic models were found to be more suitable for predicting L. monocytogenes growth under the evaluated storage conditions.

📌 3 Key Takeaways

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Objective & Hypothesis:Objective: The aim of this study was to evaluate the growth behavior of L. monocytogenes in cooked ground beef stored under aerobic and vacuum packaging conditions for 21 days and to compare the performance of different mathematical models in describing its growth kinetics under these storage conditions.
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Key Findings & Data:Materials and methods: Cooked ground beef samples were inoculated with L. monocytogenes and stored at 4 °C under aerobic and vacuum packaging conditions for 21 days.
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Conclusion & Impact:Richards and Logistic models were found to be more suitable for predicting L. monocytogenes growth under the evaluated storage conditions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:L. monocytogenes · tahminsel modelleme · meat

Abstract

Objective: The aim of this study was to evaluate the growth behavior of L. monocytogenes in cooked ground beef stored under aerobic and vacuum packaging conditions for 21 days and to compare the performance of different mathematical models in describing its growth kinetics under these storage conditions. Materials and methods: Cooked ground beef samples were inoculated with L. monocytogenes and stored at 4 °C under aerobic and vacuum packaging conditions for 21 days. Microbial counts were monitored during storage and the obtained data were fitted to Henderson, Baranyi, Gompertz, Logistic, Richards, and Stannard models. Results and discussion: L. monocytogenes growth was observed under both packaging conditions, although the growth curves differed between aerobic and vacuum storage. Among the tested models, the Richards model provided the best fit under both conditions, achieving R² values of 0.9984 (aerobic) and 0.9942 (vacuum), followed by the Logistic model with R² values of 0.9970 and 0.9922, respectively. The Gompertz model also showed acceptable performance under aerobic storage (R²=0.9727), whereas the Baranyi and Stannard models did not adequately describe the growth behavior of L. monocytogenes. Conclusion: Packaging conditions significantly affected the growth dynamics of L. monocytogenes in cooked ground beef. Richards and Logistic models were found to be more suitable for predicting L. monocytogenes growth under the evaluated storage conditions.

Özet

Amaç: Bu çalışmanın amacı, aerobik ve vakumlu paketleme koşullarında 21 gün boyunca depolanan pişmiş kıymada L. monocytogenes’in gelişim davranışını değerlendirmek ve farklı matematiksel modellerin bu gelişim kinetiğini açıklamadaki performansını karşılaştırmaktır. Materyal ve metot: Pişmiş kıyma örnekleri L. monocytogenes ile inoküle edilmiş ve 4 °C’de aerobik ve vakumlu paketleme koşullarında 21 gün boyunca depolanmıştır. Depolama süresince mikrobiyal sayımlar yapılmış ve elde edilen veriler Henderson, Baranyi, Gompertz, Lojistik, Richards ve Stannard modellerine uygulanmıştır. Bulgular ve tartışma: L. monocytogenes gelişimi her iki paketleme koşulunda da gözlenmiştir, ancak gelişim eğrileri aerobik ve vakumlu depolama arasında farklılık göstermiştir. Test edilen modeller arasında Richards modeli her iki koşulda da en yüksek uyumu sağlamış; aerobik depolamada R²=0.9984, vakumlu depolamada ise R²=0.9942 değerine ulaşmıştır. Lojistik model sırasıyla R²=0.9970 ve R²=0.9922 değerleriyle ikinci sırada yer almıştır. Gompertz modeli özellikle aerobik depolamada kabul edilebilir sonuçlar verirken (R²=0.9727), Baranyi ve Stannard modelleri L. monocytogenes gelişimini yeterli düzeyde açıklayamamıştır. Sonuç: Paketleme koşulları, pişmiş kıymada L. monocytogenes’in gelişim dinamikleri üzerinde önemli etkiye sahiptir. Richards ve Lojistik modellerinin, değerlendirilen depolama koşullarında L. monocytogenes gelişimini tahmin etmek için daha uygun modeller olduğu sonucuna varılmıştır.

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Cite This Article

Küçükyılmaz, A., Polat, Z., Soyuçok, A. (2026). Modelling of the growth of Listeria monocytogenes in cooked ground beef stored under different storage conditions for 21 days. Gıda ve Yem Bilimi Teknolojisi Dergisi, Sayı: 36, 93–101. https://doi.org/10.56833/gidaveyem.1984347

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References (32)

  1. Annadurai, G., Rajesh Babu, S., and Srinivasamoorthy, V. R. (2000). Development of mathematical models (Logistic, Gompertz and Richards models) describing the growth pattern of Pseudomonas putida (NICM 2174). Bioprocess Engineering, 23(6), 607-612.
  2. Arroyo, F. N., Quintana, M. D., and Fernández, A. G. (2005). Evaluation of primary models to describe the growth of Pichia anomala and study of temperature, NaCl, and pH effects on its biological parameters by response surface methodology. Journal of food protection, 68(3), 562-570.
  3. Baranyi, J., and Roberts, T. A. (1994). A dynamic approach to predicting bacterial growth in food. International journal of food microbiology, 23(3-4), 277-294.
  4. Bolívar, A., Costa, J. C. C. P., Posada-Izquierdo, G. D., Valero, A., Zurera, G., and Pérez-Rodríguez, F. (2018). Modelling the growth of Listeria monocytogenes in Mediterranean fish species from aquaculture production. International journal of food microbiology, 270, 14-21.
  5. Cavalcanti, A. A. C., Limeira, C. H., de Siqueira, I. N., de Lima, A. C., de Medeiros, F. J. P., de Souza, J. G.,. and de Melo, M. A. (2022). The prevalence of Listeria monocytogenes in meat products in Brazil: A systematic literature review and meta-analysis. Research in Veterinary Science, 145, 169-176.
  6. Ding, T., Shim, Y. H., Kim, H. N., Ha, S. D., Chung, M. S., Hwang, I. G., and Oh, D. H. (2011). Development of predictive model for the growth of Staphylococcus au- reus in Kimbab. Food Science and Biotechnology, 20, 471-476.
  7. Domínguez, R., Pateiro, M., Gagaoua, M., Barba, F. J., Zhang, W., and Lorenzo, J. M. (2019). A comprehensive review on lipid oxidation in meat and meat products. Antioxidants, 8(10), 429.
  8. Dorota, Z., Danuta, K. K., Antoni, G., and Motyl, I. (2014). Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage. Journal of Microbiology, 52, 169-178.
  9. Doroudian, M., Soezi, M., Rasouli, M., Arshadi Far, M., Yousefi Dehbidi, M., Maafi, P., and Omidi, B. (2024). Identification of meat adulteration in minced meat samples labeled as beef and mutton in Tehran stores using duplex PCR. Food science & nutrition, 12(10), 7504-7511.
  10. European Food Safety Authority. (2011). Use of the EFSA comprehensive European food consumption database in exposure assessment. EFSA journal, 9(3), 2097.
  11. Giannuzzi, L., Contreras, E., and Zaritzky, N. (1999). Modeling the aerobic growth and decline of Staphylococcus aureus as affected by pH and potassium sorbate con- centration. Journal of food protection, 62(4), 356-362.
  12. Hitchins, A. D., Jinneman, K., and Chen, Y. (2016). Food and Drug Administration bacteriological analytical manual chapter 10, detection and enumeration of Listeria monocytogenes in foods. US Food and Drug Administration, Silver Spring, MD: http://www. fda. gov/Food/FoodScienceResearch/LaboratoryMethods/ucm071400. htm.[Google Scholar].
  13. İşeri, Ö., and Erol, İ. (2009). Hindi etinden kaynaklanan başlıca bakteriyel infeksiyon ve intoksikasyonlar. Ankara Üniversitesi Veteriner Fakültesi Dergisi, 56(1), 47-54.
  14. Kalaba, V., Ilić, T., & Golić, B. (2021). Microbiological quality of minced meat and meat preparations. Veterinary Journal of Republic of Srpska, 1, 178-186.
  15. McMinn, W. A. M., McLoughlin, C. M., and Magee, T. R. A. (2005). Thin-layer modeling of microwave, microwave-convective, and microwave-vacuum drying of pharmaceutical powders. Drying Technology, 23(3), 513-532.
  16. Menezes, N. M. C., Martins, W. F., Longhi, D. A., and de Aragão, G. M. F. (2018). Mode- ling the effect of oregano essential oil on shelf-life extension of vacuum-packed cooked sliced ham. Meat science, 139, 113-119.
  17. Njage, P. M. K., Sawe, C. T., Onyango, C. M., Habib, I., Njagi, E. N., Aerts, M., and Molenberghs, G. (2017). Microbial performance of food safety control and assurance activities in a fresh produce processing sector measured using a microbial assessment scheme and statistical modeling. Journal of food protection, 80(1), 177-188.
  18. Ozturk, F., Kalkan, S., Tirali, T., and Gunduz, H. (2020). The effects of artichoke (Cynara scolymus L.) Leaf extract on the microbial and chemical quality of Sardine (Sar- dina pilchardus Walbaum, 1792) fish patties and shelf life modeling. Journal Of Food Safety And Food Qualıty-Archıv Fur Lebensmıttelhygıene, 71(2), 50-57.
  19. Ross, T., and McMeekin, T. A. (2003). Modeling microbial growth within food safety risk assessments. Risk Analysis: An International Journal, 23(1), 179-197.
  20. Schlundt, J., Tay, M.Y.F., Chengcheng, H., Liwei, C. (2020). Food security: microbio- logical and chemical risks. In: Masys AJ, Izurieta R, Reina Ortiz M (eds) Global health security. Advanced sciences and technologies for security applications. Springer, Cham, pp 231–274.
  21. Soyuçok, A., Kılıç, B., Kılıç, G. B., and Yalçın, H. (2024). In vitro antimicrobial activity of ginseng extract against Staphylococcus aureus, Salmonella Typhimurium and Listeria monocytogenes and its inhibitory effects on these pathogens in cooked ground beef. Meat Science, 216, 109559.
  22. Stavropoulou, E., and Bezirtzoglou, E. (2019). Predictive modeling of microbial behavior in food. Foods, 8(12), 654.
  23. Toldrá, F., and Barat, J. M. (2017). Salt reduction in processed meats. In Advanced Technologies for Meat Processing (pp. 443-460). CRC Press.
  24. Valdramidis, V. (2016) Predictive microbiology. In: Modeling in food microbiology. Elsevier, pp 1–15.
  25. Van Impe, J. F., Poschet, F., Geeraerd, A. H., and Vereecken, K. M. (2005). Towards a novel class of predictive microbial growth models. International Journal of Food Microbiology, 100(1-3), 97-105.
  26. Wachenheim, D. E., Patterson, J. A., and Ladisch, M. R. (2003). Analysis of the logistic function model: derivation and applications specific to batch cultured microorganisms. Bioresource Technology, 86(2), 157-164.
  27. Yang, H., Liu, Y., Nychas, G. J. E., Luo, X., Zhu, L., Mao, Y.,. and Zhang, Y. (2024). Utilizing lactic acid bacteria and their metabolites for controlling Listeria monocytogenes in meat products: Applications, limitations, and future perspectives. Trends in Food Science and Technology, 104699.
  28. Zhang, X., Wang, S., Chen, X., and Qu, C. (2021). Review controlling Listeria monocytogenes in ready-to-eat meat and poultry products: An overview of outbreaks, current legislations, challenges, and future prospects. Trends in Food Science and Technology, 116, 24-35.
  29. Zhou, H., Gao, Z., Luo, G., Han, L., Sun, S., and Wang, H. (2010). Determination of Listeria monocytogenes in milk samples by signal amplification quartz crystal microbalance sensor. Analytical letters, 43(2), 312-322.
  30. Zwietering M. H., Jongenburger, I., Rombouts, F. M., and Van't Riet, K. J. A. E. M. (1990). Modeling of the bacterial growth curve. Applied and environmental microbiology, 56(6), 1875-1881.
  31. Cavalcanti, A. A. C., Limeira, C. H., de Siqueira, I. N., de Lima, A. C., de Medeiros, F. J. P., de Souza, J. G.,. and de Melo, M. A. (2022). The prevalence of Listeria monocytogenes in meat products in Brazil: A systematic literature review and meta-analysis. Research in Veterinary Science, 145, 169-176.
  32. Yang, H., Liu, Y., Nychas, G. J. E., Luo, X., Zhu, L., Mao, Y.,. and Zhang, Y. (2024). Utilizing lactic acid bacteria and their metabolites for controlling Listeria monocytogenes in meat products: Applications, limitations, and future perspectives. Trends in Food Science and Technology, 104699.