Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Multi-trait genomic-enabled prediction enhances accuracy in multi-year wheat breeding trials.

G3 (Bethesda, Md.) - 27 Sept 2021

Montesinos-López Abelardo, Runcie Daniel E, Ibba Maria Itria, Pérez-Rodríguez Paulino, Montesinos-López Osval A, Crespo Leonardo A, Bentley Alison R, Crossa José

Abstract excerpt

Implementing genomic-based prediction models in genomic selection requires an understanding of the measures for evaluating prediction accuracy from different models and methods using multi-trait data. In this study, we compared prediction accuracy using six large multi-trait wheat data sets (quality and grain yield). The data were used to predict 1 year (testing) from the previous year (training) to assess...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Genomics
Share to Genotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Models, Genetic

Share to Phenotype

Share to Plant Breeding

Share to Selection, Genetic

Share to Triticum

Source

Open in PubMed Open full text

Identifiers

PMID: 34568924
DOI: 10.1093/g3journal/jkab270
PMCID: PMC8496321

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.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Multi-trait genomic-enabled prediction enhances accuracy in multi-year wheat breeding trials.PMID 34568924Read ↗

Genome-based prediction of multiple wheat quality traits in multiple years.Semantic proximity Read ↗

Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat.Semantic proximity Read ↗

Use of multiple traits genomic prediction, genotype by environment interactions and spatial effect to improve prediction accuracy in yield data.Semantic proximity Read ↗

Genomic selection for multi-trait crop improvement in wheat (Triticum aestivum L.): a practical modeling approach.Semantic proximity Read ↗

Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones.Semantic proximity Read ↗

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).Semantic proximity Read ↗

Multi-trait Genomic Prediction Model Increased the Predictive Ability for Agronomic and Malting Quality Traits in Barley (Hordeum vulgare L.).Semantic proximity Read ↗

Multitrait genomic prediction method in approximate genome-based kernel model.Semantic proximity Read ↗

Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data.Semantic proximity Read ↗

Genomic Prediction with Pedigree and Genotype × Environment Interaction in Spring Wheat Grown in South and West Asia, North Africa, and Mexico.Semantic proximity Read ↗

Genomic Prediction from Multi-Environment Trials of Wheat Breeding.Semantic proximity Read ↗

Improving wheat grain yield genomic prediction accuracy using historical data.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.