Title : ( Optimization of slicing sugar beet for improving the purity of diffusion juice using response surface methodology and genetic algorithm )
Authors: MARYAM NAGHIPOUR , Mohammad Hossein Aghkhani , Abbas Rohani , Khalil Behzad , Armaghan Kosari Moghaddam ,Access to full-text not allowed by authors
Abstract
The purity is accounted for one of the main characteristics of sugar beet juice in the sugar production process. In this regard, in the paper, the impact of slicing parameters including blade type, slicing angle from 0 to 90°, slicing thickness from 3 to 6 mm, and preheating duration from 3 to 15 min was studied on juice purity using Response Surface Methodology (RSM). The Genetic Algorithm (GA) technique was also employed to find the optimum values of variables to reach the highest juice purity. The results indicated that the quadratic model was the best model to predict juice purity. The Findings presented that as cossette thickness and slicing angle increased, the juice purity was improved. Optimization of the quadratic model by GA showed the best cossette thickness was 6 mm for both blades. The results of optimization indicated that 92.25 and 94.45% juice purities could be obtained from optimum conditions.
Keywords
blade; cossette; genetic algorithm; purity; response surface methodology; sugar beet@article{paperid:1086556,
author = {NAGHIPOUR, MARYAM and Aghkhani, Mohammad Hossein and Rohani, Abbas and Behzad, Khalil and Kosari Moghaddam, Armaghan},
title = {Optimization of slicing sugar beet for improving the purity of diffusion juice using response surface methodology and genetic algorithm},
journal = {International Journal of Food Engineering},
year = {2021},
volume = {17},
number = {10},
month = {October},
issn = {2194-5764},
pages = {827--836},
numpages = {9},
keywords = {blade; cossette; genetic algorithm; purity; response surface methodology; sugar beet},
}
%0 Journal Article
%T Optimization of slicing sugar beet for improving the purity of diffusion juice using response surface methodology and genetic algorithm
%A NAGHIPOUR, MARYAM
%A Aghkhani, Mohammad Hossein
%A Rohani, Abbas
%A Behzad, Khalil
%A Kosari Moghaddam, Armaghan
%J International Journal of Food Engineering
%@ 2194-5764
%D 2021