Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper-spectral image data

Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper-spectral image data

Abstract Background Modern agriculture uses hyperspectral cameras that provide hundreds of reflectance data at discrete narrow bands in many environments. These bands often cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra. With the bands, vegetation indic...

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Bibliographic Details
Main Authors: Abelardo Montesinos-López, Osval A. Montesinos-López, Jaime Cuevas, Walter A. Mata-López, Juan Burgueño, Sushismita Mondal, Julio Huerta, Ravi Singh, Enrique Autrique, Lorena González-Pérez, José Crossa
Format: Article
Language:English
Published: BMC 2017-07-01
Series:Plant Methods
Subjects:
Hyper-spectral data
Genomic information
Genotype × environment interaction
Band × environment interaction
Vegetation indices
Prediction accuracy
Online Access:http://link.springer.com/article/10.1186/s13007-017-0212-4

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http://link.springer.com/article/10.1186/s13007-017-0212-4

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