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Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network.

Krishna Murthy, T. P. and Manohar, B. (2014) Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network. Journal of Food Science and Technology, 51 (12). pp. 3712-3721. ISSN 0022-1155

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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 × 10−10m2/s to 12.5 × 10−10m2/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.

Item Type: Article
Uncontrolled Keywords: Mango ginger . Through-flow dryer . Diffusion . Artificial neural network . Thin layer drying
Subjects: 600 Technology > 08 Food technology > 30 Spices/Condiments
600 Technology > 08 Food technology > 06 Preservation and Storage > 02 Drying and Dehydration
Divisions: Food Engineering
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 09 Jan 2015 11:33
Last Modified: 28 Sep 2018 10:27
URI: http://ir.cftri.com/id/eprint/11690

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