IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i4p301-d528207.html
   My bibliography  Save this article

The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed Testing and Research

Author

Listed:
  • Anders Krogh Mortensen

    (Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Forsøgsvej 1, 4200 Slagelse, Denmark)

  • René Gislum

    (Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Forsøgsvej 1, 4200 Slagelse, Denmark)

  • Johannes Ravn Jørgensen

    (Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Forsøgsvej 1, 4200 Slagelse, Denmark)

  • Birte Boelt

    (Department of Agroecology, Faculty of Technical Sciences, Aarhus University, Forsøgsvej 1, 4200 Slagelse, Denmark)

Abstract

The objective of seed testing is to provide high-quality seeds in terms of high varietal identity and purity, germination capacity, and seed health. Across the seed industry, it is widely acknowledged that quality assessment needs an upgrade and improvement by inclusion of faster and more cost-effective techniques. Consequently, there is a need to develop and apply new techniques alongside the classical testing methods, to increase efficiency, reduce analysis time, and meet the needs of stakeholders in seed testing. Multispectral imaging (MSI) and near-infrared spectroscopy (NIRS) are both quick and non-destructive methods that attract attention in seed research and in the seed industry. This review addresses the potential benefits and challenges of using MSI and NIRS for seed testing with a comprehensive focus on applications in physical and physiological seed quality as well as seed health.

Suggested Citation

  • Anders Krogh Mortensen & René Gislum & Johannes Ravn Jørgensen & Birte Boelt, 2021. "The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed Testing and Research," Agriculture, MDPI, vol. 11(4), pages 1-18, April.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:301-:d:528207
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/4/301/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/4/301/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlos Henrique Queiroz Rego & Fabiano França-Silva & Francisco Guilhien Gomes-Junior & Maria Heloisa Duarte de Moraes & André Dantas de Medeiros & Clíssia Barboza da Silva, 2020. "Using Multispectral Imaging for Detecting Seed-Borne Fungi in Cowpea," Agriculture, MDPI, vol. 10(8), pages 1-12, August.
    2. Martina Vrešak & Merete Halkjaer Olesen & René Gislum & Franc Bavec & Johannes Ravn Jørgensen, 2016. "The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-10, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alan G. Taylor & Masoume Amirkhani & Hank Hill, 2021. "Modern Seed Technology," Agriculture, MDPI, vol. 11(7), pages 1-6, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrew Ogolla Egesa & Maria Teresa Davidson & Héctor E. Pérez & Kevin Begcy, 2024. "Biochemical and Physical Screening Using Optical Oxygen-Sensing and Multispectral Imaging in Sea Oats Seeds," Agriculture, MDPI, vol. 14(6), pages 1-16, May.
    2. Alan G. Taylor & Masoume Amirkhani & Hank Hill, 2021. "Modern Seed Technology," Agriculture, MDPI, vol. 11(7), pages 1-6, July.
    3. Carlos Henrique Queiroz Rego & Fabiano França-Silva & Francisco Guilhien Gomes-Junior & Maria Heloisa Duarte de Moraes & André Dantas de Medeiros & Clíssia Barboza da Silva, 2020. "Using Multispectral Imaging for Detecting Seed-Borne Fungi in Cowpea," Agriculture, MDPI, vol. 10(8), pages 1-12, August.
    4. Xingpeng Li & Hongzhe Jiang & Xuesong Jiang & Minghong Shi, 2021. "Identification of Geographical Origin of Chinese Chestnuts Using Hyperspectral Imaging with 1D-CNN Algorithm," Agriculture, MDPI, vol. 11(12), pages 1-19, December.
    5. Frédéric Kosmowski & Tigist Worku, 2018. "Evaluation of a miniaturized NIR spectrometer for cultivar identification: The case of barley, chickpea and sorghum in Ethiopia," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:4:p:301-:d:528207. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.