APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS IN DRYING OF FRUITS AND VEGETABLES : A REVIEW

Abstract

Fruits and vegetables play an important role in the diet of human beings and economic development of a country. They are cheapest and most available sources of important proteins, vitamins, minerals and essential amino acids. Considering the perishable nature of fruits and vegetables it is necessary to preserve them and drying is one such method to do it. The drying of fruits and vegetables is a complex operation that demands much energy and time. Due to this complexity, the use of drying mathematical models in estimating the drying kinetics, the behaviour and the energy needed in the drying of fruits and vegetables becomes indispensable. Numerous mathematical models, empirical and semi-empirical, have been proposed to estimate the drying characteristics of fruits and vegetables. But these models are generally solutions of simultaneous heat and mass transfer differential equations and the final result may be very complicated and difficult to use in actual drying systems. This article present a comprehensive review on the applications of artificial neural networks and genetic algorithms in drying of fruits and vegetables. The paper starts with the drying of fruits and vegetables, the introduction of basic theoretical knowledge of ANN and GA. Then summarize their application on modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physicochemical properties of dried fruits and vegetables. Conclusively, opportunities and limitations of ANN and GA technique in are outlined to provide more ideas for research and development in this field.