期刊
FOOD SCIENCE AND TECHNOLOGY INTERNATIONAL
卷 20, 期 1, 页码 13-22出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1082013212469614
关键词
drying; kinetics; thyme; neural networks
资金
- 'Ministerio de Educacion y Ciencia' in Spain, CONSOLIDER INGENIO [CSD2007-00016]
The drying kinetics of thyme was analyzed by considering different conditions: air temperature of between 40? and 70?, and air velocity of 1m/s. A theoretical diffusion model and eight different empirical models were fitted to the experimental data. From the theoretical model application, the effective diffusivity per unit area of the thyme was estimated (between 3.68 x 10(-5) and 2.12 x 10 (-4)s(-1)). The temperature dependence of the effective diffusivity was described by the Arrhenius relationship with activation energy of 49.42kJ/mol. Eight different empirical models were fitted to the experimental data. Additionally, the dependence of the parameters of each model on the drying temperature was determined, obtaining equations that allow estimating the evolution of the moisture content at any temperature in the established range. Furthermore, artificial neural networks were developed and compared with the theoretical and empirical models using the percentage of the relative errors and the explained variance. The artificial neural networks were found to be more accurate predictors of moisture evolution with VAR99.3% and ER8.7%.
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