A Methodological Review of Fluorescence Imaging for Quality Assessment of Agricultural Products

被引：10
作者：
Momin, Abdul [1 ]
Kondo, Naoshi [2 ]
Al Riza, Dimas Firmanda [3 ]
Ogawa, Yuichi [2 ]
Obenland, David [4 ]
机构：
[1] Tennessee Technol Univ, Agr Engn Technol, Sch Agr, Cookeville, TN 38505 USA
[2] Kyoto Univ, Grad Sch Agr, Lab Biosensing Engn, Kitashirakawa, Kyoto 6068267, Japan
[3] Univ Brawijaya, Fac Agr Technol, Dept Biosyst Engn, Jl Vet, Malang 65145, Indonesia
[4] USDA Agr Res Serv, San Joaquin Valley Agr Sci Ctr, 9611 S Riverbend Ave, Parlier, CA 93648 USA
来源：
AGRICULTURE-BASEL | 2023年 / 13卷 / 07期
关键词：
agricultural products; citrus; quality; machine vision; fluorescence; image processing; MACHINE VISION; FOOD QUALITY; HYPERSPECTRAL REFLECTANCE; AUTOMATIC DETECTION; COMMON DEFECTS; APPLE FRUIT; CITRUS; SYSTEM; CLASSIFICATION; INSPECTION;
D O I：
10.3390/agriculture13071433
中图分类号：
S3 [农学（农艺学）];
学科分类号：
0901 ;
摘要：
Currently, optical imaging techniques are extensively employed to automatically sort agricultural products based on various quality parameters such as size, shape, color, ripeness, sugar content, and acidity. This methodological review article examined different machine vision techniques, with a specific focus on exploring the potential of fluorescence imaging for non-destructive assessment of agricultural product quality attributes. The article discussed the concepts and methodology of fluorescence, providing a comprehensive understanding of fluorescence spectroscopy and offering a logical approach to determine the optimal wavelength for constructing an optimized fluorescence imaging system. Furthermore, the article showcased the application of fluorescence imaging in detecting peel defects in a diverse range of citrus as an example of this imaging modality. Additionally, the article outlined potential areas for future investigation into fluorescence imaging applications for the quality assessment of agricultural products.
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页数：14
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