Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling

• Main Authors: Vali Rasooli Sharabiani, Mohammad Kaveh, Roozbeh Abdi, Mariusz Szymanek, Wojciech Tanaś
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-04-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-88270-z

Abstract Two different drying methods were applied for dehydration of apple, i.e., convective drying (CD) and microwave drying (MD). The process of convective drying through divergent temperatures; 50, 60 and 70 °C at 1.0 m/s air velocity and three different levels of microwave power (90, 180, and 360 W) were studied. In the analysis of the performance of our approach on moisture ratio (MR) of apple slices, artificial neural networks (ANNs) was used to provide with a background for further discussion and evaluation. In order to evaluate the models mentioned in the literature, the Midilli et al. model was proper for dehydrating of apple slices in both MD and CD. The MD drying technology enhanced the drying rate when compared with CD drying significantly. Effective diffusivity (Deff) of moisture in CD drying (1.95 × 10−7–4.09 × 10−7 m2/s) was found to be lower than that observed in MD (2.94 × 10−7–8.21 × 10−7 m2/s). The activation energy (Ea) values of CD drying and MD drying were 122.28–125 kJ/mol and 14.01–15.03 W/g respectively. The MD had the lowest specific energy consumption (SEC) as compared to CD drying methods. According to ANN results, the best R2 values for prediction of MR in CD and MD were 0.9993 and 0.9991, respectively.