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

Authors:
M. Mohebbi;J. Barouei;M. R. Akbarzadeh-T;A. R. Rowhanimanesh;M. B. Habibi-Najafi;M. Yavarmanesh
Affiliations:
Department of Food Science and Technology, Ferdowsi University, Iran;Food Science and Technology Research Group, Academic Centre for Education, Culture and Research, Mashhad Branch, Iran;Department of Electrical Engineering, Ferdowsi University, Iran;Department of Electrical Engineering, Ferdowsi University, Iran;Department of Food Science and Technology, Ferdowsi University, Iran;Department of Food Science and Technology, Ferdowsi University, Iran
Venue:
Computers and Electronics in Agriculture
Year:
2008

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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^(R) 0.5L (0.00, 0.05, 0.10, 0.15, 0.20 and 0.25v/w%) at 30, 40 and 50^oC 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.