Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning

Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning

Abstract Background The need for rapid in-field measurement of key traits contributing to yield over many thousands of genotypes is a major roadblock in crop breeding. Recently, leaf hyperspectral reflectance data has been used to train machine learning models using partial least squares regression...

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Bibliographic Details
Main Authors: Robert T. Furbank, Viridiana Silva-Perez, John R. Evans, Anthony G. Condon, Gonzalo M. Estavillo, Wennan He, Saul Newman, Richard Poiré, Ashley Hall, Zhen He
Format: Article
Language:English
Published: BMC 2021-10-01
Series:Plant Methods
Subjects:
Wheat
Photosynthesis
Machine learning
Deep learning
Hyperspectral reflectance
Online Access:https://doi.org/10.1186/s13007-021-00806-6

Internet

https://doi.org/10.1186/s13007-021-00806-6

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