Modeling and optimization for prediction of moisture content, drying rates and moisture ratio

Abstract

There were needs to develop some preservation technique to enhance the shelf life of Paneer because it is highly perishable in nature at ambient conditions. Drying can be one of the methods to increase shelf life of paneer. This study was undertaken to dry 1.5 cm3 paneer at 62, 72 and 82℃temperatures and 10, 14 and 18 kPa absolute pressures with superheated steam. Moisture content, drying rate and moisture ratio data were generated by conducting the experiments in low pressure superheated steam dryer. These data were used to develop Artificial Neural Network (ANN) models. Optimized ANN models were developed for rapid and more accurate prediction of moisture content with two hidden layers and seven nurons having R2 0.9991, drying rate with two hidden layers and nine nurons having R2 0.9846 and moisture ratio with two hidden layers and seven nurons having R2 0.9991 in drying, based on two hidden layers and one to nine neurons in each hidden layer. Measured values of moisture content, drying rate and moisture ratio were predicted with an R2＞0.98. System equation has been developed to predict moisture content, drying rate and moisture ratio at any given conditions.

Key words: Artificial Neural Network(ANN), moisture content, drying rate, moisture ratio, optimization
DOI: 10.3965/j.issn.1934-6344.2009.01.058-064

Citation: Shivmurti Shrivastav, B. K. Kumbhar. Modeling and optimization for prediction of moisture content, drying rates and moisture ratio. Int J Agric & Biol Eng, 2009; 2(1): 58－64.