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Proceedings Paper

The research development of hyperspectral imaging in apple nondestructive detection and grading
Author(s): Di Feng; Jian-wei Ji; Li Zhang; Si-jia Liu; You-wen Tian
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Paper Abstract

Hyperspectral imaging is a new technology for nondestructive detection of fruit which developed rapidly in recent years. It can get the image and spectral information of the detected object from "three-dimensional", can also reflect the internal and external qualities simultaneously, is a new efficient grading method for fruit. This article induces system types by introducing the hardware structure, determine light source and scanning mode which apply to apple grading. We describe detecting process of apple external and internal indicators according to two directions in apple grading. For internal quality detection, we generalize the methods of image enhancement and image segmentation. For quality indicator detection, we elaborate the process of system calibration and spectral preprocessing, also we discuss the significance of optimal band selection, classify the methods of prediction model establishment and evaluation. Then we summarize the domestic and foreign research results of several main indicators of apple grading, the external quality including color, size, slight injury and contamination, and the internal quality including soluble solids content (SSC), firmness and bruise. We illustrate accuracy, modeling methods, research progress of all indicators and express personal comments for the research progress of single indicator. Finally, this article proposes the deficiency, research direction and application prospect of hyperspectral imaging in apple nondestructive detection and grading.

Paper Details

Date Published: 25 October 2016
PDF: 9 pages
Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 101560V (25 October 2016); doi: 10.1117/12.2246537
Show Author Affiliations
Di Feng, Shenyang Agricultural Univ. (China)
Jian-wei Ji, Shenyang Agricultural Univ. (China)
Li Zhang, Consultant (China)
Si-jia Liu, Shenyang Agricultural Univ. (China)
You-wen Tian, Shenyang Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 10156:
Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology

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