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Multimodal deep learning methods enhance genomic prediction of wheat breeding.

G3 (Bethesda, Md.) - 2 May 2023

Montesinos-López Abelardo, Rivera Carolina, Pinto Francisco, Piñera Francisco, Gonzalez David, Reynolds Mathew, Pérez-Rodríguez Paulino, Li Huihui, Montesinos-López Osval A, Crossa Jose

Abstract excerpt

While several statistical machine learning methods have been developed and studied for assessing the genomic prediction (GP) accuracy of unobserved phenotypes in plant breeding research, few methods have linked genomics and phenomics (imaging). Deep learning (DL) neural networks have been developed to increase the GP accuracy of unobserved phenotypes while simultaneously accounting for the complexity of...

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Deep Learning
Genomics
Genotype
Models, Genetic
Phenotype

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PMID: 36869747
DOI: 10.1093/g3journal/jkad045
PMCID: PMC10151399

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