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.

引用

页数：14

共 102 条

[1] Al Riza D.F., 2021, P 4 INT SEMINAR PHOT, V11789, p117890I
[2] Mango (Mangifera indica cv. Sein Ta Lone) ripeness level prediction using color and textural features of combined reflectance-fluorescence images
Al Riza, Dimas Firmanda
Rulin, Chen
Tun, Naw Thwe Thwe
Yi, Phyu Phyu Lei
Thwe, Aye Aye
Myint, Khin Thida
Kondo, Naoshi
[J]. JOURNAL OF AGRICULTURE AND FOOD RESEARCH, 2023, 11
[3] Combined fluorescence-transmittance imaging system for geographical authentication of patchouli oil
Al Riza, Dimas Firmanda
Widodo, Slamet
Purwanto, Y. Aris
Kondo, Naoshi
[J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2019, 218 : 155 - 160
[4] Multispectral inspection of citrus in real-time using machine vision and digital signal processors
Aleixos, N
Blasco, J
Navarrón, F
Moltó, E
[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 33 (02) : 121 - 137
[5] RGB imaging system for monitoring quality changes of seedless watermelon during storage
Ali, M. Mohd
Hashim, N.
Khairunniza-Bejo, S.
Shamsudin, R.
Sembak, W. N. F. H. Wan
[J]. III INTERNATIONAL CONFERENCE ON AGRICULTURAL AND FOOD ENGINEERING, 2017, 1152 : 361 - 366
[6] [Anonymous], 2013, ENG AGR ENV FOOD, DOI [DOI 10.1016/S1881-8366(13)80004-3, DOI 10.1016/S1881-8366(13)80020-1]
[7] [Anonymous], 2008, P ASABE ANN INT M SP
[8] [Anonymous], UN BREAK HYP BARR
[9] Near-infrared hyperspectral imaging for grading and classification of pork
Barbin, Douglas
Elmasry, Gamal
Sun, Da-Wen
Allen, Paul
[J]. MEAT SCIENCE, 2012, 90 (01) : 259 - 268
[10] CHANGES IN NEODIOSMIN LEVELS DURING THE DEVELOPMENT OF CITRUS-AURANTIUM LEAVES AND FRUITS - POSTULATION OF A NEODIOSMIN BIOSYNTHETIC-PATHWAY
BENAVENTEGARCIA, O
CASTILLO, J
CONESA, JAD
[J]. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, 1993, 41 (11) : 1916 - 1919

← 1 2 3 4 5 6 7 8 9 10 →