Modeling and optimization of viscosity in enzyme-modified cheese by fuzzy logic and genetic algorithm
Document Type
Article
Publication Title
Computers and Electronics in Agriculture
Abstract
In the food industry, there is an increasing emphasis on the need for an economic and an additional cheese flavor to prepared food. In this paper a Genetic Fuzzy Rule Base System (GFRS) for modeling of viscosity in enzyme-modified cheese (EMC) is described based on experimental data. Using data obtained via measurement of viscosity in EMC prepared with different dosage of a commercial bacterial neutral proteinase, Neutrase® 0.5L (0.00, 0.05, 0.10, 0.15, 0.20 and 0.25 v/w%) at 30, 40 and 50 °C with 100, 200 and 300 RPM in a viscometer, it is concluded that construction of an optimized fuzzy model for the evaluation of viscosity in EMC is a reliable procedure. This may help manufacturers to control the viscosity of EMS in processing units by selecting the appropriate combinations of potential manufacturing parameters. © 2008 Elsevier B.V. All rights reserved.
First Page
260
Last Page
265
DOI
10.1016/j.compag.2008.01.010
Publication Date
7-1-2008
Recommended Citation
Mohebbi, M., Barouei, J., Akbarzadeh-T, M., Rowhanimanesh, A., Habibi-Najafi, M., & Yavarmanesh, M. (2008). Modeling and optimization of viscosity in enzyme-modified cheese by fuzzy logic and genetic algorithm. Computers and Electronics in Agriculture, 62 (2), 260-265. https://doi.org/10.1016/j.compag.2008.01.010