Hyperspectral imaging and 3D technologies for plant phenotyping: From satellite to close-range sensing
•Plant phenotyping using hyperspectral and 3D sensing are thoroughly reviewed.•Remote sensing has a longe history and related methods have been well developed.•Close-rang hyperspectral and 3D sensing of plants are still in their infant stages.•Accurate 3D modelling of plants is a bottleneck of close...
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Veröffentlicht in: | Computers and electronics in agriculture 2020-08, Vol.175, p.105621, Article 105621 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Plant phenotyping using hyperspectral and 3D sensing are thoroughly reviewed.•Remote sensing has a longe history and related methods have been well developed.•Close-rang hyperspectral and 3D sensing of plants are still in their infant stages.•Accurate 3D modelling of plants is a bottleneck of close-range hyperspectral and 3D-based plant phenotyping.•The fusion of hyperspectral images and 3D data would be a further research direction.
High-throughput phenotyping technologies in controlled environments or field conditions have proven to be extremely useful in unravelling key quantitative traits of plants for breeding. Among many plant phenotyping methods, hyperspectral imaging (HSI) and three-dimensional (3D) sensing are the fastest growing and promising approaches for measuring multiple plant parameters. There are many types of HSI and 3D sensors available with each being designed for a specific purpose. Also, the same sensor could be set up and calibrated in different ways to measure different plant parameters on various platforms. This review aims to guide the use of HSI and 3D sensing technologies for plant phenotyping. It first introduces the preliminary knowledge of HSI and 3D sensing for plant phenotyping. In addition, it provides the detail of plant phenotyping using different HSI and 3D sensors on various platforms with different scales. Lastly, the problems and challenges of close-range HSI and 3D modelling of plants are discussed and potential solutions are suggested. |
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ISSN: | 0168-1699 1872-7107 |
DOI: | 10.1016/j.compag.2020.105621 |