Predicting the drying kinetics of salted codfish (Gadus Morhua): semi‐empirical, diffusive and neural network models

Abstract

This work aims to compare the accuracy of several drying modelling techniques namely semi-empirical, diffusive and artificial neural network (ANN) models as applied to salted codfish (Gadus Morhua). To this end, sets of experimental data were collected to adjust parameters for the models. Modelling of codfish drying was performed by resorting to Page and Thompson semi-empirical models and to a Fick diffusion law. The ANN employed a neural network multilayer 'feed-forward', consisting of one input layer, with four neurons, one hidden layer, formed by five neurons and one output layer with a convergence criterion for training purposes. The simulations showed good results for the ANN (correlation coefficient between 0.987 and 0.999) and semi-empirical models (correlation coefficient ranging from 0.992 to 0.997 for Page's model, and from 0.993 to 0.996 for Thompson's model), while improvements were required to obtain better predictions by the diffusion model (correlation coefficients ranged from 0.864 to 0.959).

Empirical and diffusion models to describe water transport into chickpea (Cicer arietinum L.)

“…In literature, the use and the comparison among empirical models to describe drying processes are very common (Ghazanfari et al ., ; Ganesapillai et al ., ; Roberts et al ., ; Boeri et al ., ). In our paper, the comparison between the two empirical models (Page and the model proposed here) indicates that both well describe drying and soaking processes of chickpea.…”

“…For grains, the usual boundary condition for the diffusion equation is of the first kind (Boeri et al ., ; Mundada et al ., ; Yildirim et al ., ). Thus, for a homogeneous and isotropic sphere of radius R (m), assuming constant thermo‐physical properties, with initial and equilibrium moisture content given by X i and X eq (dry basis, db), respectively, the solution X ( r , t ) of the diffusion equation is given by (Luikov, ; Crank, ): where X ( r , t ) is the moisture content (kg water per kg grain dry weight) at the position r (m) from the centre of the sphere at time t (s), and D (m 2 s −1 ) is the effective mass diffusivity.…”

“…For grains, the usual boundary condition for the diffusion equation is of the first kind (Boeri et al, 2011;Mundada et al, 2011;Yildirim et al, 2011). Thus, for a homogeneous and isotropic sphere of radius R (m), assuming constant thermo-physical properties, with initial and equilibrium moisture content given by X i and X eq (dry basis, db), respectively, the solution X(r, t) of the diffusion equation is given by (Luikov, 1968;Crank, 1992):…”

“…To describe water transport kinetics through a diffusion model, the initial and boundary conditions must be known. In the literature, for grains, the usual boundary condition is of the first kind (Silva et al ., , ; Vega‐Gálvez et al ., ; Boeri et al ., ; Mundada et al ., ; Yildirim et al ., ), but third kind is also found in some papers as, for instance, in Silva et al . ().…”

“…Generally, to describe water transport inside food, a mathematical model is used and, among them, the following can be cited: models based on Darcy's laws (Pinheiro et al, 1998); empirical models (Turhan et al, 2002;Akpinar & Bicer, 2005;Ghazanfari et al, 2006;Sutar & Prasad, 2007;Ganesapillai et al, 2008;Roberts et al, 2008;Silva et al, 2008;Vega-Ga´lvez et al, 2008;Hii et al, 2009;Diamante et al, 2010;Kaleta & Go´rnicki, 2010;Bantle et al, 2011); and diffusion models (Vega-Ga´lvez et al, 2008;Silva et al, 2009Silva et al, , 2010Silva et al, , 2012Boeri et al, 2011;Mundada et al, 2011;Yildirim et al, 2011). To describe water transport kinetics through a diffusion model, the initial and boundary conditions must be known.…”