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

IR@CSIR-CFTRI

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Relation http://ir.cftri.com/11690/
http://dx.doi.org/10.1007/s13197-013-0941-y
 
Title Hot air drying characteristics of mango ginger: Prediction
of drying kinetics by mathematical modeling and artificial
neural network.
 
Creator Krishna Murthy, T. P.
Manohar, B.
 
Subject 30 Spices/Condiments
02 Drying and Dehydration
 
Description 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.
 
Date 2014
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Identifier http://ir.cftri.com/11690/1/Journal%20of%20Food%20Science%20and%20Technology%2C%20Vol.%2051%2C%20No.12%2C%202014%2C%203712.pdf
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