Modeling and optimization of viscosity in enzyme-modified cheese by fuzzy logic and genetic algorithm

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 obta...

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Bibliographic Details
Published in:Computers and electronics in agriculture 2008-07, Vol.62 (2), p.260-265
Main Authors: Mohebbi, M., Barouei, J., Akbarzadeh-T, M.R., Rowhanimanesh, A.R., Habibi-Najafi, M.B., Yavarmanesh, M.
Format: Article
Language:English
Subjects:
algorithms
Biological and medical sciences
Cheese
cheeses
EMC (enzyme-modified cheese)
Food industries
Fundamental and applied biological sciences. Psychology
Fuzzy
fuzzy logic
Genetic algorithm
Milk and cheese industries. Ice creams
Modeling
Optimization
Viscosity
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Summary: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.
ISSN:0168-1699
1872-7107
DOI:10.1016/j.compag.2008.01.010