Modeling and Optimization of Electrodialytic Desalination of Fish Sauce Using Artificial Neural Networks and Genetic Algorithm
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Author list: Chindapan N., Sablani S.S., Chiewchan N., Devahastin S.
Publisher: Springer
Publication year: 2013
Journal: Food and Bioprocess Technology (1935-5130)
Volume number: 6
Issue number: 10
Start page: 2695
End page: 2707
Number of pages: 13
ISSN: 1935-5130
eISSN: 1935-5149
Languages: English-Great Britain (EN-GB)
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Abstract
Electrodialysis (ED) has been proposed as a means to reduce sodium ion concentration in fish sauce. However, no information is so far available on the optimum condition to operate the ED process. Artificial neural network (ANN)-based models were therefore developed to predict the ED performance and changes in selected quality attributes of ED-treated fish sauce; optimum operating condition of the process was then determined via multi-objective optimization using genetic algorithm (MOGA). The optimal ANN models were able to predict the ED performance with R 2 = 0.995, fish sauce basic characteristics with R 2 = 0.992, and the concentrations of total aroma compounds and total amino acids, flavor difference, and saltiness of the treated fish sauce with R 2 = 0.999. Through the use of MOGA, the optimum condition of the ED process was the use of an applied voltage of 6.3 V and the maintenance of the residual salt concentration of the treated fish sauce of 14.3 % (w/w). ฉ 2012 Springer Science+Business Media, LLC.
Keywords
Low-sodium product, Process performance
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