Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4759179 | Computers and Electronics in Agriculture | 2017 | 7 Pages |
Abstract
Deciduous-calyx pears of Korla fragrant pear (Pyrus sinkiangensis Yu) have a significant economic value in Xinjiang Uygur Autonomous Region, China. This study developed a non-destructive method based on hyperspectral imaging using a combination of existing analytical techniques to differentiate the deciduous-calyx pear (DCF) and persistent-calyx pear (PCF). The degrees of circularity of DCP and PCP were extracted according to its morphological characteristic; similarly, the reflectance spectra of DCP and PCP were obtained by hyperspectral imaging technology. Successive projections algorithm (SPA) combined with support vector machine (SVM) established a classification model. The DCF and PCF could be differentiated by SPA-SVM model with accuracy of 93.3% and 96.7% respectively. Our findings suggest that hyperspectral imaging can be applied to non-destructively differentiate pears, and meet the packaging standards.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Haijiang Hu, Leiqing Pan, Ke Sun, Sicong Tu, Ye Sun, Yingying Wei, Kang Tu,