title: Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network.
abstract: Mango ginger (Curcuma amada) was dried in a through-flow dryer system at different temperatures (40-70 °C) and air velocities (0.84 - 2.25 m/s) to determine the effect of drying on drying rate and effective diffusivity. As the temperature and air velocity increased, drying time significantly decreased. Among the ten different thin layer drying models considered to determine the kinetic drying parameters, semi empirical Midilli et al., model gave the best fit for all drying conditions. Effective moisture diffusivity varied from 3.7 × 10(-10) m(2)/s to 12.5 × 10(-10) m(2)/s over the temperature and air velocity range of study. Effective moisture diffusivity regressed well with Arrhenius model and activation energy of the model was found to be 32.6 kJ/mol. Artificial neural network modeling was also employed to predict the drying behaviour and found suitable to describe the drying kinetics with very high correlation coefficient of 0.998.
authors.affiliation: Department of Food Engineering, CSIR - Central Food Technological Research Institute, Mysore, 570020 India.
authors.forename: Thirupathihalli Pandurangappa Krishna
authors.initials: TP
authors.lastname: Murthy
authors.affiliation: Department of Food Engineering, CSIR - Central Food Technological Research Institute, Mysore, 570020 India.
authors.forename: Balaraman
authors.initials: B
authors.lastname: Manohar
keywords: Artificial neural network; Diffusion; Mango ginger; Thin layer drying; Through-flow dryer