Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classificat...

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Bibliographic Details
Main Authors: Michael C. Tross, Marcin W. Grzybowski, Talukder Z. Jubery, Ryleigh J. Grove, Aime V. Nishimwe, J. Vladimir Torres‐Rodriguez, Guangchao Sun, Baskar Ganapathysubramanian, Yufeng Ge, James C. Schnable
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Plant Phenome Journal
Online Access:https://doi.org/10.1002/ppj2.20106
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