期刊
DRYING TECHNOLOGY
卷 39, 期 3, 页码 418-431出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/07373937.2020.1818254
关键词
Potato cubes; drying kinetics; physicochemical properties; artificial neural network (ANN); hot air drying based on temperature and humidity control (TH-HAD)
资金
- National Key Research and Development Program of China [2017YFD0400905]
- basic scientific research program for public welfare scientific research institutes in Xinjiang Uygur Autonomous Region [KY2019027]
In current work, air impingement drying (AID), infrared-assisted hot air-drying (IR-HAD), and hot air drying based on temperature and humidity control (TH-HAD) drying technologies were employed to drying potato cubes and their effects on drying kinetics, color, ascorbic acid content, rehydration ratio, microstructure, and specific energy consumption (SEC) were explored. Besides, artificial neural network (ANN) was used to predict changes in moisture ratio during the drying process. Results indicated that TH-HAD had the shortest drying time, followed by IR-HAD and AID. The effective moisture diffusivity (D-eff) of potato under TH-HAD, IR-HAD and AID were 1.35 x 10(-9), 1.18 x 10(-9), and 0.90 x 10(-9)m(2)/s, respectively. TH-HAD contributed to excellent physicochemical properties of dried potato when compared to samples dried by IR-HAD and AID. Overall, TH-HAD provided higher ascorbic acid content, better rehydration ability, brighter color, and had lower specific energy consumption (SEC). The microstructure well explained the difference of rehydration ratio and drying kinetics under different drying methods. The ANN models with the optimal topology could predict the moisture ratio under different drying methods with satisfactory accuracy. The current findings indicate that TH-HAD is a promising drying technology for potato cubes and has the potential to be applied in commercial scale.
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