•  Persian
    • Persian
    • English
  •   ورود
  • دانشگاه فردوسی مشهد
  • |
  • مرکز اطلاع‌رسانی و کتابخانه مرکزی
    • Persian
    • English
  • خانه
  • انواع منابع
    • مقاله مجله
    • کتاب الکترونیکی
    • مقاله همایش
    • استاندارد
    • پروتکل
    • پایان‌نامه
  • راهنمای استفاده
View Item 
  •   کتابخانه دیجیتال دانشگاه فردوسی مشهد
  • Fum
  • Articles
  • ProfDoc
  • View Item
  •   کتابخانه دیجیتال دانشگاه فردوسی مشهد
  • Fum
  • Articles
  • ProfDoc
  • View Item
  • همه
  • عنوان
  • نویسنده
  • سال
  • ناشر
  • موضوع
  • عنوان ناشر
  • ISSN
  • شناسه الکترونیک
  • شابک
جستجوی پیشرفته
JavaScript is disabled for your browser. Some features of this site may not work without it.

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

نویسنده:
محبت محبی
,
جواد بارویی
,
محمدرضا اکبرزاده توتونچی
,
علیرضا روحانی منش
,
محمدباقر حبیبی نجفی
,
مسعود یاورمنش
,
Mohebbat Mohebbi
,
Mohammad Reza Akbarzadeh Totonchi
,
Alireza Rowhanimanesh
,
Mohammad B Habibi Najafi
,
Masoud Yavarmanesh
سال
: 2008
چکیده: 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.
یو آر آی: http://libsearch.um.ac.ir:80/fum/handle/fum/3370360
کلیدواژه(گان): cheese- EMC-Fuzzy- Genetic algorithm- Modelling-Optimization- Viscosity
کالکشن :
  • ProfDoc
  • نمایش متادیتا پنهان کردن متادیتا
  • آمار بازدید

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

Show full item record

contributor authorمحبت محبیen
contributor authorجواد باروییen
contributor authorمحمدرضا اکبرزاده توتونچیen
contributor authorعلیرضا روحانی منشen
contributor authorمحمدباقر حبیبی نجفیen
contributor authorمسعود یاورمنشen
contributor authorMohebbat Mohebbifa
contributor authorMohammad Reza Akbarzadeh Totonchifa
contributor authorAlireza Rowhanimaneshfa
contributor authorMohammad B Habibi Najafifa
contributor authorMasoud Yavarmaneshfa
date accessioned2020-06-06T13:49:09Z
date available2020-06-06T13:49:09Z
date issued2008
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/3370360?locale-attribute=fa
description abstractIn 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.en
languageEnglish
titleModelling and optimization of viscosity in enzyme-modified cheese by fuzzy logic and genetic algorithmen
typeJournal Paper
contenttypeExternal Fulltext
subject keywordscheese- EMC-Fuzzy- Genetic algorithm- Modelling-Optimization- Viscosityen
journal titleComputers and Electronics in Agriculturefa
pages260-265
journal volume62
journal issue0
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1008942.html
identifier articleid1008942
  • درباره ما
نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
DSpace software copyright © 2019-2022  DuraSpace