13
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview

      , , , , ,
      Sensors
      MDPI AG

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Near-infrared (800–2500 nm; NIR) spectroscopy coupled to hyperspectral imaging (NIR-HSI) has greatly enhanced its capability and thus widened its application and use across various industries. This non-destructive technique that is sensitive to both physical and chemical attributes of virtually any material can be used for both qualitative and quantitative analyses. This review describes the advancement of NIR to NIR-HSI in agricultural applications with a focus on seed quality features for agronomically important seeds. NIR-HSI seed phenotyping, describing sample sizes used for building high-accuracy calibration and prediction models for full or selected wavelengths of the NIR region, is explored. The molecular interpretation of absorbance bands in the NIR region is difficult; hence, this review offers important NIR absorbance band assignments that have been reported in literature. Opportunities for NIR-HSI seed phenotyping in forage grass seed are described and a step-by-step data-acquisition and analysis pipeline for the determination of seed quality in perennial ryegrass seeds is also presented.

          Related collections

          Most cited references137

          • Record: found
          • Abstract: not found
          • Article: not found

          Review of the most common pre-processing techniques for near-infrared spectra

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Remote sensing of foliar chemistry

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The reflectance at the 950–970 nm region as an indicator of plant water status

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                SENSC9
                Sensors
                Sensors
                MDPI AG
                1424-8220
                March 2022
                March 03 2022
                : 22
                : 5
                : 1981
                Article
                10.3390/s22051981
                35271127
                fd766e12-4999-4fa3-93e4-1e78e02869a0
                © 2022

                https://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article