Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter March 5, 2011

Modeling and Optimization of Mass Transfer during Osmosis Dehydration of Carrot Slices by Neural Networks and Genetic Algorithms

  • Mohebbat Mohebbi , Mohammad-R Akbarzadeh-T , Fakhri Shahidi and Seyed Mohsen Zabihi

Osmotic dehydration, as a minimal processing method, has found increasingly wide prospects during the past few decades. This process involves mass transfer which is commonly modeled by applications of different procedures, mostly based on Fick's law. In this research, we approach the modeling process by first obtaining experimental measurement of carrot’s solid gain and water loss under different conditions of solution concentrations ( 20, 40 and 60% w/w), temperatures ( 40, 60 and 80°C) as well as time intervals (1-6h). Then two paradigms of artificial neural networks (ANN), feed forward neural networks (FFNN) and radial basis function neural networks (RBFNN) are applied and compared for modeling this process. Additionally, genetic algorithm is used to determine optimal conditions for osmotic dehydration.

Published Online: 2011-3-5

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston

Downloaded on 29.11.2023 from
Scroll to top button