Title: Mathematical and neural network modelling of the adsorption characteristics of dried African catfish (clarias gariepenus)

Authors: Rufus Rotimi Dinrifo

Addresses: Department of Agricultural and Bio-Environmental Engineering, School of Engineering, Lagos State Polytechnic, Ikorodu, Lagos Nigeria

Abstract: Moisture adsorption isotherms of dried fillets of African catfish (Clarias gariepenus) were determined at 23, 30 and 45°C in the range 0.11 to 0.93 of water activity, using the standard gravimetric static method. The data obtained from the experiments were fitted to four popular mathematical models [the Brunauer, Emmett and Teller (BET), Oswin, Henderson and the modified Guggenheim-Anderson-De Boer (GAB)] and to a set of artificial neural network (ANN) models. The modified GAB outperformed the other mathematical models [with coefficient of determination R2 = 0.96, mean relative error (MRE) = 6.64%] but the ANNs were more accurate (with the best giving R2 = 0.988 and MRE = 3.56%) in predicting the moisture adsorption isotherms of the dried catfish. The knowledge of the adsorption isotherms would be very useful in the design of packages, prediction of storage stability and for calculating moisture changes that may occur during storage.

Keywords: African catfish; water activity; adsorption; isotherm; equilibrium moisture content; EMC; mathematical models; artificial neural network; ANN.

DOI: 10.1504/IJPTI.2016.10004627

International Journal of Postharvest Technology and Innovation, 2016 Vol.5 No.3, pp.187 - 199

Accepted: 04 Nov 2015
Published online: 18 Apr 2017 *

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