期刊
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE
卷 51, 期 12, 页码 3712-3721出版社
SPRINGER INDIA
DOI: 10.1007/s13197-013-0941-y
关键词
Mango ginger; Through-flow dryer; Diffusion; Artificial neural network; Thin layer drying
Mango ginger (Curcuma amada) was dried in a through-flow dryer system at different temperatures (40-70 A degrees 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 x 10(-10) m(2)/s to 12.5 x 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.
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