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

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.).

The plant genome - 1 Jun 2024

Dhakal Anup, Poland Jesse, Adhikari Laxman, Faryna Ethan, Fiedler Jason, Rutkoski Jessica E, Arbelaez Juan David

Abstract excerpt

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling...

Read the complete abstract on PubMed

Topics

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

Share to Avena
Share to Edible Grain
Share to Genome, Plant

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genomics

Share to Phenotype

Share to Plant Breeding

Share to Quantitative Trait Loci

Share to Selection, Genetic

Source

Open in PubMed Open full text

Identifiers

PMID: 38764287
DOI: 10.1002/tpg2.20457
PMCID: PMC12807195

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.).PMID 38764287Read ↗

Effectiveness of low-density high-throughput marker platform and easy-to-measure traits for genomic prediction of biomass yield in oat (Avena sativa L.).Semantic proximity Read ↗

Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).Semantic proximity Read ↗

Exploring morphological traits related to potential milling yield based on image-analysis.Semantic proximity Read ↗

A genetic framework for grain size and shape variation in wheat.Semantic proximity Read ↗

Archetypes of inflorescence: genome-wide association networks of panicle morphometric, growth, and disease variables in a multiparent oat population.Semantic proximity Read ↗

Genome-wide association study identifies key quantitative trait loci (QTL) for fruit morphometric traits in avocado (Persea spp.).Semantic proximity Read ↗

Genome-wide association mapping for grain and forage quality traits in a subtropical oat germplasm collection adapted to highland regions of Eastern AfricaSemantic proximity Read ↗

Genome-wide association for grain morphology in synthetic hexaploid wheats using digital imaging analysis.Semantic proximity Read ↗

Genomic prediction of biological shape: elliptic Fourier analysis and kernel partial least squares (PLS) regression applied to grain shape prediction in rice (Oryza sativa L.).Semantic proximity Read ↗

Open RGB imaging workflow for morphological and morphometric analysis of fruits using deep learning: a case study on almonds.Semantic proximity Read ↗

The potentialities of omics resources for millet improvement.Semantic proximity Read ↗

Genome-wide association study and genomic prediction of fruit weight in spinach.Semantic proximity Read ↗

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