Evaluation of the air-borne ultrasound on fluidized bed drying of shelled corn: Effectiveness, grain quality, and energy consumption

Abdoli, Bahareh and Zare, Dariush and Jafari, Abdolabbas and Chen, Guangnan (2018) Evaluation of the air-borne ultrasound on fluidized bed drying of shelled corn: Effectiveness, grain quality, and energy consumption. Drying Technology. pp. 1-18. ISSN 0737-3937

Abstract

The objective of the study was to investigate the influence of high power ultrasound on a laboratory-scale fluidized bed shelled corn dryer. The drying time, moisture content variation, specific energy consumption, and quality parameters including ultimate compressive strength, toughness, shrinkage and color of corn kernels were investigated. Furthermore, artificial neural network (ANN) simulation models were developed for predicting the drying variables. Machine vision techniques were used to determine color and shrinkage as qualitative indices. Results showed that the lower frequencies had better penetrations at lower temperatures and cause a significant reduction in drying time. In addition, the ultrasound application led to reduction of ultimate compressive strength and toughness of the dried samples although ultrasound has nonthermal character as the subsidiary factor, it plays an important role in shrinkage and color specification. Based on error analysis results, the prediction capability of ANN model is found to be reasonable for the developed models. Application of ultrasound significantly decreased the specific energy consumption of drying process at the optimal drying condition.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published online 05 Feb 2018. Permanent restricted access to ArticleFirst version in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 19 Feb 2018 00:48
Last Modified: 14 May 2018 23:59
Uncontrolled Keywords: drying kinetics; machine vision; quality attributes; ultrasound-assisted fluidized bed dryer
Fields of Research : 09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
Socio-Economic Objective: B Economic Development > 82 Plant Production and Plant Primary Products > 8204 Summer Grains and Oilseeds > 820401 Maize
Identification Number or DOI: 10.1080/07373937.2018.1423568
URI: http://eprints.usq.edu.au/id/eprint/33711

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