International Journal of Irrigation and Water Management

International Journal of Irrigation and Water Management ISSN 5423-5294 Vol. 3 (12), pp. 001-008, December, 2016. © International Scholars Journals

Full Length Research Paper

Neural network approach for modeling the mass transfer of potato slices during osmotic dehydration using genetic algorithm

M. R. Amiryousefi* and M. Mohebbi

Department of Food Science and Technology, Ferdowsi University of Mashhad, P. O. Box: 91775-1163, Mashhad, Iran.

Accepted 08 July, 2016

Abstract

In this study, an approach for designing a neural network based on genetic algorithm has been used to model mass transfer during osmotic dehydration of potato slices. The experimental data were obtained through a complete randomized design with different osmotic solutions (5, 10 and 15% w/w) and potato to solution ratios (1:6, 1:8 and 1:10) at varying temperatures (30, 40 and 60°C) and the best model obtained with optimization of a multi-layer perceptron neural network had a mean absolute error of 0.260, 0.516 and 0.137 for moisture content, water loss and solid gain of osmotically dehydrated slices respectively.

Key words: Osmotic dehydration, potato, neural network, genetic algorithm, modeling, mass transfer.