Fen Bilimleri ve Mühendislik Uygulamalarında Deneysel Verilerin Matematik Modellerle Tanımlanması

Özet

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Referanslar

Gacula, M.C., Singh, J. (1984). Statistical Methods in Food and Consumer Research. Academic Press, Inc. USA.

van Boekel, M.A.J.S. (1996). Statistical aspects of kinetic modeling for food science problems. Journal of Food Science, 61: 477–486.

van Boekel, M.A.J.S., Zwietering, M.H. (2007). Experimental design, data processing and model fitting in predictive microbiology. In: Modelling Microorganisms in Food, Brul, S., Van Gerwen, S., Zwietering, M.H. (Eds.), pp. 22–43, Cambridge, UK, Woodhead Publishing Ltd.

Baranyi, J., Roberts, T.A. (1995). Mathematics of predictive food microbiology. International Journal of Food Microbiology, 26: 199-218.

Leylak, C., Yurdakul, M., Buzrul, S. (2020). Gıda bilimlerinde Excel kullanımı 1: Doğrusal regresyon. Food and Health, 6: 186-198.

Liengme, B.V. (2016). A Guide to Microsoft® Excel 2013 for Scientists and Engineers. Elsevier.

Harris, D.C. (1998). Nonlinear least-squares curve fitting with Microsoft Excel solver. Journal of Chemical Education, 75: 119-121.

Motulsky, H.J., Christopoulos, A. (2003). Fitting models to biological data using linear and nonlinear regression. In A Practical Guide to Curve Fitting; GraphPad Software Inc.: San Diego, CA, USA.

Ratkowsky, D.A. (2004). Model fitting and uncertainty. In: Modeling Microbial Responses in Food, McKellar, R.C., Lu, X. (Eds.), pp. 151–196, Boca Raton FL, CRC Press.

Snedecor, G.W., Cochran, W.G. (1967). Statistical Methods. The Iowa State University Press, Ames, Iowa.

van Boekel, M.A.J.S. (2008). Kinetic modeling of food quality: A critical review. Comprehensive Review in Food Science and Food Safety, 7: 144–158.

Holman, J.P., Holman, B.K. (2018). What Every Engineer Should Know About Excel. Second Edition. CRC Press. Taylor & Francis Group.

Jaiswal, A.K., Khandelwal, A. (2007). Computer based numerical and statistical techniques. New Age International Publishers.

Brown, A.M. (2001). A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet. Computer Methods and Programs in Biomedicine, 65: 191–200.

Martín, M., de Juan, L.M. (2020) EXCEL® for Chemical Engineering. In: Martín, M. (Ed.) Introduction to Software for Chemical Engineers. pp.27-91. Second Edition. CRC Press.

Mínguez-Mosquera, M.I., Gandul-Rojas, B. (1994). Mechanism and kinetics of carotenoid degradation during the processing of green table olives. Journal of Agriculture and Food Chemistry, 42: 1551–1554.

Geeraerd, A.H., Valdramidis, V.P., Van Impe, J.F. (2005). GInaFiT, a freware tool to assess non-log-linear microbial survivor curves. International Journal of Food Microbiology, 102: 95-105.

Kemmer, G., Keller, S. (2010). Nonlinear least-squares data fitting in Excel spreadsheets. Nature Protocols, 5: 267–281.

Yurdakul, M., Leylak, C., Buzrul, S. (2020). Gıda bilimlerinde Excel kullanımı 2: Doğrusal olmayan regresyon. Food and Health, 6: 199–212.

Motulsky, H.J., Ransnas, L.A. (1987). Fitting curves to data using nonlinear regression: a practical and nonmathematical review. The FASEB Journal, 1(5): 365–374.

Kronthaler, F. (2023). Statistics Applied with Excel. Data Analysis is (not) an Art. Springer-Verlag GmbH.

Baranyi, J., Roberts, T.A. (1994). A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology, 23: 277–294.

Buchanan, R.L., Whiting, R.C., Damert, W.C. (1997). When is simple good enough: a comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves. Food Microbiology, 14: 313–326.

Peleg, M. (2006). Advanced Quantitative Microbiology for Food and Biosystems: Models for Predicting Growth and Inactivation. Boca Raton, FL, CRC Press.

Peleg, M., Corradini, M.G. (2011). Microbial growth curves: What the models tell us and what they cannot. Critical Reviews in Food Science and Nutrition, 51: 917–945.

Öksüz, H., Buzrul, S. (2020). Monte Carlo analysis for microbial growth curves. Journal of Microbiology, Biotechnology and Food Sciences, 10: 418–423.

Öksüz, H., Buzrul, S. (2021). Mikroorganizmaların büyüme eğrilerini tanımlamak için Excel tabanlı, kullanıcı dostu, ücretsiz bir araç: ÖK-BUZ GRoFiT. Tekirdağ Ziraat Fakültesi Dergisi 18: 521–532.

Özçelik, F., Halkman, A.K., Bağder-Elmacı, S. (2019). Mikroorganizma gelişmesi. In: Halkman, A.K. (Ed.) Gıda Mikrobiyolojisi.Başak Mtabaacılık ve Tanıtım Hizmetleri Ltd., Ankara, ISBN: 978-605-245-683-5, pp. 23–60. Bölüm 2.

Zwietering, M.H., Jongenburger, I., Rombouts, F.M., Van’t Riet. K. (1990). Modelling of the bacterial growth curve. Applied and Environmental Microbiology, 56: 1875–1881.

Buzrul, S. (2007). Gıdalarda etkisizleştirilen mikroorganizmaların tanımlanması 1: Doğrusal taslam ve eksiklikleri. Dünya Gıda Dergisi, 8: 61–64.

Buzrul, S. (2022). The Weibull model for microbial inactivation. Food Engineering Reviews, 14: 45–61.

Cerf, O. (1977). A review. Tailing of survival curves of bacterial spores. Journal of Applied Bacteriology, 42: 1–19.

Linton, R.H., Carter, W.H., Pierson, M.D., Hackney, C.R. (1995). Use of modified Gompertz equation to model non-linear survival curves for Listeria monocytogenes Scott A. Journal of Food Protection, 9: 946–954.

Peleg, M. (2000). Microbial survival curves – the reality of flat shoulders and absolute thermal death times. Food Research International, 33: 531–538.

Peleg, M. (2006). Advanced quantitative microbiology for foods and biosystems: Models for predicting growth and inactivation. Boca Raton, FL, CRC Press.

van Boekel, M.A.J.S. (2002). On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells. International Journal of Food Microbiology, 74: 139–159.

Ritchie, R.J., Prvan, T. (1996). Current statistical methods for estimating the Km and Vmax of Michaelis-Menten kinetics. Biochemical Education, 24: 196–206.

Sanchez, L., Peiro, J.M., Castillo, H., Perez, M.D., Ena J.M., Calvo, M. (1992). Kinetic parameters for denaturation of bovine milk lactoferrin. Journal of Food Science 57: 873–879.

Tayyab, S., Quamar, S. (1992). A look into enzyme kinetics: Some introductory experiments. Biochemical Education, 20: 116–118.

Buzrul, S. (2023). α-Laktalbumin’in ısıl denatürasyonunun iki farklı modelle tanımlanması. Akdeniz Mühendislik Dergisi, 1: 23–32.

Marangoni, A.G. (2017). Kinetic Analysis of Food Systems. Springer International Publishing.

Özilgen, M. (2011). Handbook of Food Process Modeling and Statistical Quality Control with Extensive MATLAB Applications. Second Edition. Taylor and Francis Group.

van Boekel, M.A.J.S. (2021). Kinetics of heat-induced changes in foods: A workflow proposal. Journal of Food Engineering, 306: 110634.

van Boekel, M.A.J.S. (2022). Kinetics of heat-induced changes in dairy products: Developments in data analysis and modelling techniques. International Dairy Journal, 126: 105187.

van Boekel, M.A.J.S. (1996). Statistical aspects of kinetic modeling for food science problems. Journal of Food Science, 61: 477–485, 489.

van Boekel, M.A.J.S. (2021). To pool or not to pool: That is the question in microbail kinetics. International Journal of Food Microbiology, 354: 109283.

van Boekel, M.A.J.S., Roux, S. (2022). Multilevel modeling in food science: A case study on heat-induced ascorbic acid degradation kinetics. Food Research International, 158: 111565.

Dolan, K.D., Mishra, D.K. (2013). Parameter estimation in food science. Annual Reviews in Food Science and Technology, 4: 401–422.

Buzrul, S. (2021). Microsoft® Excel’de Monte Carlo benzetimi: Gıda bilimlerinde kullanılan doğrusal olmayan regresyon için model parametrelerinin güven aralıklarının belirlenmesi. Akademik Gıda, 19: 291–299.

Lambert, R.J.W., Mytilinaios, I., Maitland, L., Brown, A.M. (2012). Monte Carlo simulation of parameter confidence intervals for non-linear regression analysis of biological data using Microsoft Excel. Computer Methods and Programs in Biomedicine, 107: 155–163.

Mínguez-Mosquera, M.I., Gandul-Rojas, B., Mínguez-Mosquera, J. (1994). Mechanism and kinetics of the degradation of chlorophylls during the processing of green table olives. Journal of Agricultural and Food Chemistry, 42: 1089–1095.

Öksüz, H.B., Buzrul, S. (2020). Monte Carlo analysis for microbial growth curves. Journal of Microbiology, Biotechnology and Food Science, 10: 418–423.

van Boekel, M.A.J.S. (2008). Kinetic modeling of reactions in foods. Boca Raton FL, CRC Press.

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21 Mart 2024

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