High-throughput analysis of leaf physiological and chemical traits with VIS–NIR–SWIR spectroscopy: a case study with a maize diversity panel

Abstract Background Hyperspectral reflectance data in the visible, near infrared and shortwave infrared range (VIS–NIR–SWIR, 400–2500 nm) are commonly used to nondestructively measure plant leaf properties. We investigated the usefulness of VIS–NIR–SWIR as a high-throughput tool to measure six leaf...

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Main Authors: Yufeng Ge, Abbas Atefi, Huichun Zhang, Chenyong Miao, Raghuprakash Kastoori Ramamurthy, Brandi Sigmon, Jinliang Yang, James C. Schnable
格式: Artigo
語言:Inglês
出版: BMC 2019-06-01
叢編:Plant Methods
主題:
Hyperspectral
Plant phenotyping
Partial least squares regression
Support vector regression
Machine learning
Vegetation indices
在線閱讀:http://link.springer.com/article/10.1186/s13007-019-0450-8
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