ANN modeling for diffusivity of mushroom and vegetables using a fluidized bed dryer--颗粒学报PARTICUOLOGY

Jena, S., & Sahoo, A. (2013). ANN modeling for diffusivity of mushroom and vegetables using a fluidized bed dryer. Particuology, 11(5), 607–613. https://doi.org/10.1016/j.partic.2012.07.015

ANN modeling for diffusivity of mushroom and vegetables using a fluidized bed dryer

Subasini Jena, Abanti Sahoo^*

Chemical Engineering Department, National Institute of Technology, Rourkela 769008, Orissa, India

10.1016/j.partic.2012.07.015

Volume 11, Issue 5, October 2013, Pages 607-613

Received 27 September 2011, Revised 10 July 2012, Accepted 28 July 2012, Available online 9 May 2013.

E-mail: abantisahoo@gmail.com; asahu@nitrkl.ac.in

Highlights

• Effective diffusivity, activation energy and mass transfer coefficients were studied.

• Regression analysis and ANN analysis were used to study parameter effects.

• ANN modeling was found to be suitable for assessing the correlations obtained.

• Drying kinetics of mushroom and other vegetables were compared.

Abstract

Drying characteristics in terms of diffusivity were studied for mushrooms and different vegetables in a fluidized bed dryer. Drying characteristics with falling rate regime were computed for all the samples. Effective diffusivity of each sample was calculated. Mass transfer coefficients were determined. Mass transfer kinetics for drying of different samples was also found out. Correlations for the diffusivity of samples were developed by relating the experimentally observed data with the different system parameters on the basis of regression analysis. The developed correlations for effective moisture diffusivity of the samples are validated by artificial neural network (ANN) modeling. Finally calculated values of diffusivity obtained through both the methods are compared with the experimentally measured values which show a very good approximation thereby indicating the wide applicability of the developed correlations for industrial uses.

Graphical abstract

Keywords

Activation energy; Effective diffusivity; Drying rate; Mass transfer kinetics; Regression analysis; Artificial neural network

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