• Spectroscopy and Spectral Analysis
  • Vol. 40, Issue 9, 2713 (2020)
SUN Jing-tao1、2, LUO Yi-jia1, SHI Xue-wei1, MA Ben-xue3, WANG Wen-xia3, and DONG Juan1、*
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2020)09-2713-08 Cite this Article
    SUN Jing-tao, LUO Yi-jia, SHI Xue-wei, MA Ben-xue, WANG Wen-xia, DONG Juan. Research Progress on Non-Destructive Detection Technology for Grape Quality[J]. Spectroscopy and Spectral Analysis, 2020, 40(9): 2713 Copy Citation Text show less

    Abstract

    Grape is rich in nutrients and has therapeutic effects, making it one of the most popular fruits for consumers. However, the quality of grape degrades due to their vulnerability in the process of growth, picking and storage, which seriously affects the purchasing desire of consumers and the selling price of grape. Therefore, detecting grape quality is crucial for improving the commercial value of grape. Traditional testing methods have the disadvantages of destroying samples, time-consuming and labor-intensive, high cost. However, non-destructive testing methods, which mainly adopt machine vision technology, near-infrared spectroscopy technology and high spectral imaging technology, have developed rapidly due to their advantages of non-destructive, rapid and accurate, and have formed a relatively perfect method system. At present, non-destructive testing technology is widely used in grape quality testing. The national and international latest researches of using machine vision, near-infrared spectroscopy and hyperspectral imaging technology in the detection of grape, including prediction of external quality (fruit size, surface color and bunch size) and internal quality (varieties, sugar, titratable acid, anthocyanins and total phenols, diseases and pesticide residues, etc.), were summarized. Finally, the existing problems and the prospects were analyzed, which provide a reference for the development of non-destructive testing technology of grape and the work of related scientific researchers.
    SUN Jing-tao, LUO Yi-jia, SHI Xue-wei, MA Ben-xue, WANG Wen-xia, DONG Juan. Research Progress on Non-Destructive Detection Technology for Grape Quality[J]. Spectroscopy and Spectral Analysis, 2020, 40(9): 2713
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