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

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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Bibliographic Details
Main Authors: Jaime Cuevas, Osval Montesinos-López, Philomin Juliana, Carlos Guzmán, Paulino Pérez-Rodríguez, José González-Bucio, Juan Burgueño, Abelardo Montesinos-López, José Crossa
Format: Article
Language:English
Published: Oxford University Press 2019-09-01
Series:G3: Genes, Genomes, Genetics
Subjects:
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
Online Access:http://g3journal.org/lookup/doi/10.1534/g3.119.400493

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http://g3journal.org/lookup/doi/10.1534/g3.119.400493

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