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

Author

Listed:
  • Abdul Momin

    (Agricultural Engineering Technology, School of Agriculture, Tennessee Tech University, Cookeville, TN 38505, USA)

  • Naoshi Kondo

    (Laboratory of Biosensing Engineering, Graduate School of Agriculture, Kyoto University, Kitashirakawa, Kyoto 6068267, Japan)

  • Dimas Firmanda Al Riza

    (Department of Biosystems Engineering, Faculty of Agricultural Technology, Universitas Brawijaya, Jl. Veteran, Malang 65145, Indonesia)

  • Yuichi Ogawa

    (Laboratory of Biosensing Engineering, Graduate School of Agriculture, Kyoto University, Kitashirakawa, Kyoto 6068267, Japan)

  • David Obenland

    (USDA Agricultural Research Service, San Joaquin Valley Agricultural Sciences Center, 9611 S. Riverbend Ave., Parlier, CA 93648, USA)

Abstract

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.

Suggested Citation

  • Abdul Momin & Naoshi Kondo & Dimas Firmanda Al Riza & Yuichi Ogawa & David Obenland, 2023. "A Methodological Review of Fluorescence Imaging for Quality Assessment of Agricultural Products," Agriculture, MDPI, vol. 13(7), pages 1-14, July.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:7:p:1433-:d:1198450
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    References listed on IDEAS

    as
    1. Zhen Ma & João Manuel R.S. Tavares & Renato Natal Jorge & T. Mascarenhas, 2010. "A review of algorithms for medical image segmentation and their applications to the female pelvic cavity," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 13(2), pages 235-246.
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