Deep Kernel for Genomic and Near Infrared Predictions in Multi-environment Breeding Trials

Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear unbiased predictor (GBLUP or GB) kernel, and the Gaussian kernel (GK). In genera...

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Hlavní autoři:	Jaime Cuevas, Osval Montesinos-López, Philomin Juliana, Carlos Guzmán, Paulino Pérez-Rodríguez, José González-Bucio, Juan Burgueño, Abelardo Montesinos-López, José Crossa
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Oxford University Press 2019-09-01
Edice:	G3: Genes, Genomes, Genetics
Témata:	Genomic based prediction Genomic Best Unbiased Predictor (GBLUP, GB linear and non-linear kernel methods) near infrared (NIR) high-throughput phenotype single-environment model deep learning genomic × environment interaction model Genomic Prediction GenPred Shared Data Resources
On-line přístup:	http://g3journal.org/lookup/doi/10.1534/g3.119.400493
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