Combined infrared and hot air drying (IR-HAD) of sweet potato explored using a multiphase model: application of reaction engineering approach. Issue 8 (15th June 2022)

• Record Type: Journal Article
• Authors: Chia, Zhi Bin; Putranto, Aditya; Chen, Xiao Dong; Onwude, Daniel Iroemeha
• Is Part Of: Drying technology. Volume 40:Issue 8(2022)
• Page Start: 1629
• Page End: 1638
• Publication Date: 2022-06-15
• Subjects: Drying -- reaction engineering approach -- food -- process intensification -- fruits and vegetables -- food drying -- heat and mass transfer; Drying -- Periodicals; Desiccation; 660.28426
• DOI: 10.1080/07373937.2022.2066118
• Languages: English
• ISSNs: 0737-3937

Abstract

Abstract: For better understanding of transport phenomena, local evaporation rate and water vapor concentration should be taken into consideration when predicting drying behavior. However, to the best of our knowledge, there is no model which explicitly represents this. Predictive modeling of combined infrared-heating and hot air drying (IR-HAD) is useful to assist in designing new dryer units and manufacturing the products with desirable quality. As the quality changes are basically local phenomena, the model should be able to capture the local evaporation rate. In this study, for the first, time, spatial reaction engineering approach (S-REA) was developed and used to describe infrared-heating drying of the food materials by using the reaction engineering approach (REA) to represent local evaporation rate. Benchmarks against the single-phase approach and the results showed that the S-REA gave high accuracy toward the experimental data ( R 2 = 0.978–0.999). The S-REA successfully provided reasonable predictions of two-dimensional (2 D) profiles of moisture content, concentration of water vapor and temperature. This highlights the accuracy of the REA framework to describe the local evaporation rate during the infrared-heating. The REA-based predicted variables can then be applied to project the local quality parameters for quality assurance in food processing. The model is also ready to be used to audit energy demands in drying systems.