Matematiksel Modelleme ve Su Ürünlerinde Kullanılan Raf Ömrü Tahmin Modelleri

Öz

Matematiksel modelleme su ürünleri gibi çabuk bozulan gıdalarda sıcaklık-zaman ilişkisini belirleyebilen önemli bir konudur. Raf ömrü tahmininde mikroorganizmaların gelişim kinetiklerinin belirlenmesi esastır. Su ürünlerinde raf ömrü tahmin modelleri geliştirilirken birincil, ikincil ve üçüncül modellerin ürün veya mikroorganizma temel alınarak uygulanması gerekmektedir. Bu kapsamda yapılan çalışmada matematiksel model terminolojileri, kullanılan matematiksel eşitlikler ve su ürünlerinde geliştirilen ve uygulanan modeller derlenmeye çalışılmıştır. Yapılan çalışmalar incelendiğinde matematiksel modelleme için kullanılan ve bu çalışmada belirtilen tekniklerin sistematik bir şekilde uygulanması gerektiği sonucuna varılmıştır. 

Anahtar Kelimeler

• Prediktif Mikrobiyoloji
• Matematiksel Modelleme
• Su Ürünleri

Mathematical Modelling and Shelf Life Prediction Models Used in Seafood

Öz

Mathematical modelling is a significant discipline that can determine the temperaturetime relationship in perishable foods such as seafood. It is essential to determine the growth kinetics of microorganisms in shelf life estimations. While developing the shelf-life prediction models in seafood, primary, secondary and tertiary models need to be applied based on the product or microorganism. In this context, the terminology of the mathematical models, the mathematical equations used and the models developed and applied in seafood products have been tried to be compiled. In accordance with the results of the previous studies, it is concluded that the techniques used for mathematical modelling and the techniques mentioned in this study should be applied in a systematic way.

Anahtar Kelimeler

• Predictive Microbiology
• Mathematical Modelling
• Seafood
• Shelf Life

Kaynakça

1. Baranyi, J., Roberts, T. A., McClure, P. (1993). A Non-Autonomus Differential Equation To Model Bacterial Growth. Food Microbiology, 10, 43-59.
2. Bono, G., Badalucco, C. (2012). Combining Ozone and Modified Atmosphere Packaging (MAP) to Maximize Shelf Life and Quality of Striped Red Mullet (Mullus surmelatus). LWT-Food Science and Technology, 47(2), 500-504.
3. Buchanan, R. L., Phillips, J. G. (1990). Response Surface Model For Predicting The Effects Of Temperature, pH, Sodium Chloride Content, Sodium Nitrite Concentration And Atmosphere On The Growth Of Listeria Monocytogenes. Journal of Food Protection, 53, 370-376.
4. Buchanan, R.L. (1994). Predictive food microbiology. Trends in Food Science and Technology, 4: 6-11.
5. Dalgaard, P. (1995). Modelling of microbial activity and prediction of shelf-life for packed fresh fish. International Journal of Food Microbiology, 26, 305-317.
6. Dalgaard, P., Koutsoumanis, K. (2001). Comparison Of Maximum Specific Growth Rates And Lag Times Estimated From Absorbance And Viable Count Data By Different Mathematical Models. Journal of Microbiological Methods, 43(3), 183-196.
7. Dalgaard, P., Mejlholm, O., Huss H.H. (1997). Application Of An Iterative Approach For Development Of A Microbial Model Predicting The Shelf-Life Of Packed Fish. International Journal of Food Microbiology, 38(2-3), 169-179.
8. Davey, K.R. (1992). A Terminology For Models In Predictive Micribiology. Food Microbiology, 9, 353-356.

9. Fraser, O. P., Sumar, S. (1998). Compositional Changes and Spoilage in Fish (Part II) Microbiological Induced Deterioration. Nutrition and Food Science, 6, 325–329.
10. Fu, B., Taoukis P. S., Labuza, T. P. (1991). Predictive Microbiology for Monitoring Spoilage of Dairy Products with Time-Temperature Integrators. Journal of Food Science, 56(5), 1209-1215.
11. Genç, İ.Y., Esteves, E., Diler, A. (2016). Handbook of Seafood: Quality and Safety Mainetenance and Appliations. Nova Science Publishers, 350 p, New York.
12. Huang, L. (2014). A Comprehensive Data Analysis Tool For Predictive Microbiology. International Journal of Food Microbiology, 171, 100-107.
13. Huss, H. H. (1997). Control Of İndigenous Pathogenic Bacterial in Seafood. Food Control, 8(2), 91-98.
14. Huss, H.H. (1995). Quality and Quality Changes in Fresh Fish. FAO. Fisheries Technical Paper 348. 202 p. Rome Italy.
15. Koutsoumanis, K., Nychas G.J.E. (2000). Application Of A Systematic Experimental Procedure To Develop A Microbial Model For Rapid Fish Shelf Life Predictions. International Journal of Food Microbiology, 60(2-3), 171-184.
16. Lougovois, V, Kyranas E., Kyrana V. (2003). Comparison Of Selected Methods Of Assessing Freshness Quality And Remaining Storage Life Of Iced Gilthead Sea Bream. Food Research International, 36(6), 551-560.
17. Mejlholm, O., Gunvig, A., Borggaard, C., Bolm-Hansen, J., Mellefont, L., Ross, T., Leroi, F., Else, T., Visser, T., Dalgaard, P. (2010). Predicting Growth Rates and Growth Boundary of Listeria monocytogenes – An International validation Study With Focus on Processed and Ready to Eat Meat and Seafood. International Journal of Food Microbiology, 141(3), 137-150.
18. Ratkowsky, D.A., Ross, T., McMeekin, T.A. Olley, J. (1991). Comparison of Arrhenius type and Belehradek models for Prediction Of Bacterial Growth In Foods. Journal of Applied Bacteriology, 71, 452–459.
19. Roberts, T.A. (1998). Mathematical Modeling Of Microbial Growth. 3th Karlsruhe Nutrition Symposium Eurpean Research Towards Safer and Better Food, October 18-20, Karlsruhe, Germany, 33-42.
20. Ross, T., Dalgaard, P., Tienungoon, S. (2000). Predictive Modeling Of The Growth Of Listeria In Fishery Products. 62(3), 231-245.
21. Ross, T., McMeekin T.A. (1994). Predictive Microbiology. International Journal of Food Microbiology, 23, 241-264.
22. Stelling, J. (2004). Mathematical Models in Microbial Systems Biology. Current Opinion in Microbiology, 7(5), 513-518.
23. Taokis, P. S., Koutsoumanis, K., Nychas, G.J.E. (1999). Use of Time-Temperature Integrators and Predictive Modeling For Shelf Life Control Of Chilled Fish Under Dynamic Storage Conditions. International Journal of Food Microbiology, 53, 21-31.
24. Whiting, R.C., Buchanan, R.L. (1993). A classification of models for predictive microbiology. Food Microbiology. 10, 175-177.
25. Zwietering, M.H., Jongenburger, I., Rombouts, F.M., Van’T Riet, K. (1990). Modelling Of The Bacterial Growth Curve. Applied Environmental Microbiology, 56, 1875–1881.