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Article

Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data.

G3 (Bethesda, Md.) - 9 Feb 2023

Costa-Neto Germano, Crespo-Herrera Leonardo, Fradgley Nick, Gardner Keith, Bentley Alison R, Dreisigacker Susanne, Fritsche-Neto Roberto, Montesinos-López Osval A, Crossa Jose

Abstract excerpt

Linking high-throughput environmental data (enviromics) to genomic prediction (GP) is a cost-effective strategy for increasing selection intensity under genotype-by-environment interactions (G × E). This study developed a data-driven approach based on Environment-Phenotype Association (EPA) aimed at recycling important G × E information from historical breeding data. EPA was developed in two applications: (1)...

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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: 36454213
DOI: 10.1093/g3journal/jkac313
PMCID: PMC9911085

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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