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

Genomic prediction models for traits differing in heritability for soybean, rice, and maize.

BMC plant biology - 26 Feb 2022

Kaler Avjinder S, Purcell Larry C, Beissinger Timothy, Gillman Jason D

Abstract excerpt

BACKGROUND: Genomic selection is a powerful tool in plant breeding. By building a prediction model using a training set with markers and phenotypes, genomic estimated breeding values (GEBVs) can be used as predictions of breeding values in a target set with only genotype data. There is, however, limited information on how prediction accuracy of genomic prediction can be optimized. The objective of this study was...

Read the complete abstract on PubMed

Topics

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

Share to Genetic Markers
Share to Genome, Plant
Share to Glycine max

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Linkage Disequilibrium

Share to Models, Genetic

Share to Plant Breeding

Share to Zea mays

Source

Open in PubMed Open full text

Identifiers

PMID: 35219296
DOI: 10.1186/s12870-022-03479-y
PMCID: PMC8881851

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. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Genomic prediction models for traits differing in heritability for soybean, rice, and maize.PMID 35219296Read ↗

GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection.Semantic proximity Read ↗

Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait.Semantic proximity Read ↗

Accuracy of genotypic value predictions for marker-based selection in biparental plant populations.Semantic proximity Read ↗

Genomic prediction vs. gene-based crop models: a case study on rice trait prediction.Semantic proximity Read ↗

Integrating genomic predictions into an applied Central European wheat breeding program.Semantic proximity Read ↗

Performance of Bayesian and BLUP alphabets for genomic prediction: analysis, comparison and results.Semantic proximity Read ↗

Comprehensive analytical and empirical evaluation of genomic prediction across diverse accessions in maize.Semantic proximity Read ↗

Genomic prediction in CIMMYT maize and wheat breeding programs.Semantic proximity Read ↗

Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters.Semantic proximity Read ↗

Genomic prediction of agronomic traits in wheat using different models and cross-validation designs.Semantic proximity Read ↗

Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.).Semantic proximity Read ↗

Genomic Prediction Paves Way for the Identification of Multiple Rust Resistant Genotypes in Bread Wheat (Triticum aestivum).Semantic proximity Read ↗

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