An integrated energy and quality approach to optimization of green peas drying in a hot air infrared-assisted vibratory bed dryer. (December 2015)

• Record Type: Journal Article
• Authors: Barzegar, Maryam; Zare, Dariush; Stroshine, Richard L.
• Is Part Of: Journal of food engineering. Volume 166(2015:Dec.)
• Page Start: 302
• Page End: 315
• Publication Date: 2015-12
• Subjects: Hot air-infrared drying -- Artificial neural network -- Green peas -- Vibratory bed -- Machine vision; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2015.06.026
• Languages: English
• ISSNs: 0260-8774

Abstract

Highlights: Drying processes of green peas was optimized based on both energy and product quality attributes. The ANN modeling was capable to predict quality aspects of green peas during drying. The specific energy consumptions was calculated for several drying conditions. Abstract: In this study, the drying behavior of a small spherical product, green peas, from moisture content of 75.34 ± 0.53 (%w.b.) to 20.02 ± 0.14 (%w.b.), was investigated in a hot air infrared-assisted vibratory bed dryer. The quality of dried product, including roundness, shrinkage and color, was assessed using machine vision techniques. The experiments were conducted using drying air temperatures of 30, 40, and 50 °C, infrared radiation intensity levels of 2000, 4000, and 9000 W m −2 as well as no radiation (control), green pea depths of 1, 2, and 3 layers, and two modes: vibratory and fixed bed. The specific energy consumption (SEC) of drying was also measured. The results showed that drying time and SEC decreased significantly in the vibratory bed ( p < 0.01). In addition, the original quality of dried green peas was better maintained in the infrared-assisted vibratory bed dryer. Finally, drying time, shrinkage, roundness, color and moisture content of green peas were simulated for vibratory bed mode using Artificial Neural Network.