Improvement of kiwifruit drying using computer vision system (CVS) and ALM clustering method. Issue 6 (26th April 2017)

• Record Type: Journal Article
• Authors: Nadian, Mohammad Hossein; Abbaspour‐Fard, Mohammad Hossein; Sadrnia, Hassan; Golzarian, Mahmood Reza; Tabasizadeh, Mohammad; Martynenko, Alex
• Is Part Of: Drying technology. Volume 35:Issue 6(2017)
• Page Start: 709
• Page End: 723
• Publication Date: 2017-04-26
• Subjects: Clustering -- hot air -- infrared -- kiwifruit -- online monitoring; Drying -- Periodicals; Desiccation; 660.28426
• DOI: 10.1080/07373937.2016.1208665
• Languages: English
• ISSNs: 0737-3937

Abstract

ABSTRACT: The objective of this work was to improve kiwifruit drying with respect to quality. The drying of kiwifruit slices was studied with hot air drying (HAD) and hybrid hot air-infrared drying (HID) at 50, 60, and 70°C, air velocity of 0.5, 1.0, and 1.5 m/s and thickness of 3, 5, and 7 mm using full factorial design. Shrinkage and color changes of kiwifruit slices were monitored in real time with a computer vision system (CVS). The drying treatments were ranked based on desirability function, using the combination of minimal color change, minimal shrinkage, and drying time as decision criteria. The proper conditions of kiwifruit drying were determined by average linkage method clustering as: temperature, 70°C; thickness, 3 mm; air velocity, 1.5 m/s (HAD) or 0.5 m/s (HID). Finally, a hybrid approach with HID at the first stage and HAD at the second stage of drying was proposed as a reasonable compromise between drying time and product quality.