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Article

Machine learning for genomic and pedigree prediction in sugarcane.

The plant genome - 1 Sept 2024

Inamori Minoru, Kimura Tatsuro, Mori Masaaki, Tarumoto Yusuke, Hattori Taiichiro, Hayano Michiko, Umeda Makoto, Iwata Hiroyoshi

Abstract excerpt

Sugarcane (Saccharum spp.) plays a crucial role in global sugar production; however, the efficiency of breeding programs has been hindered by its heterozygous polyploid genomes. Considering non-additive genetic effects is essential in genome prediction (GP) models of crops with highly heterozygous polyploid genomes. This study incorporates non-additive genetic effects and pedigree information using machine...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 38923818
DOI: 10.1002/tpg2.20486
PMCID: PMC12806984

Provenance

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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