Effects of different drying methods on drying kinetics, physicochemical properties, microstructure, and energy consumption of potato (Solanum tuberosum L.) cubes

• Published in: Drying technology Vol. 39; no. 3; pp. 418 - 431
• Main Authors: Wang, Hui, Liu, Zi-Liang, Vidyarthi, Sriram K., Wang, Qing-Hui, Gao, Lei, Li, Bo-Rui, Wei, Qing, Liu, Yan-Hong, Xiao, Hong-Wei
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 16.09.2020; Taylor & Francis Ltd
• Subjects: air; Air drying; artificial neural network (ANN); Artificial neural networks; Ascorbic acid; Color; Cubes; Drying; Drying agents; drying kinetics; energy; Energy consumption; hot air drying based on temperature and humidity control (TH-HAD); humidity; Humidity control; Kinetics; Microstructure; Moisture control; moisture diffusivity; neural networks; Physicochemical properties; Potato cubes; Potatoes; rehydration; Solanum tuberosum; specific energy; temperature; Topology; Vegetables
• ISSN: 0737-3937; 1532-2300; 1532-2300
• DOI: 10.1080/07373937.2020.1818254

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 × 10 −9 , 1.18 × 10 −9 , and 0.90 × 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.