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Article

Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

The plant genome - 1 Nov 2016

Cuevas Jaime, Crossa José, Soberanis Víctor, Pérez-Elizalde Sergio, Pérez-Rodríguez Paulino, Campos Gustavo de Los, Montesinos-López O A, Burgueño Juan

Abstract excerpt

In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an...

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PMID: 27902799
DOI: 10.3835/plantgenome2016.03.0024

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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