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

Plant Methods

Volumn 13, Issue 1, 2017, Pages

  Montesinos López, Abelardo ^a   Montesinos López, Osval A ^b   Cuevas, Jaime ^c   Mata López, Walter A ^b   Burgueño, Juan ^d   Mondal, Sushismita ^d   Huerta, Julio ^d   Singh, Ravi ^d   Autrique, Enrique ^d   González Pérez, Lorena ^d   Crossa, José ^d  

^a UNIVERSITY OF GUADALAJARA   (Mexico)

^b UNIVERSIDAD DE COLIMA   (Mexico)

^c UNIVERSIDAD DE QUINTANA ROO   (Mexico)

^d INTERNATIONAL MAIZE AND WHEAT IMPROVEMENT CENTER CIMMYT   (Mexico)

Author keywords

Band environment interaction; Bayesian functional regression; Fourier regression; Genomic information; Genotype environment interaction; Hyper spectral data; Prediction accuracy; Spline regression; Vegetation indices

Indexed keywords

EID: 85026240057     PISSN: None     EISSN: 17464811     Source Type: Journal    
DOI: 10.1186/s13007-017-0212-4     Document Type: Article

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