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

Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield.

The plant genome - 1 Sept 2025

García-Barrios Guillermo, Robles-Zazueta Carlos A, Montesinos-López Abelardo, Montesinos-López Osval A, Reynolds Matthew P, Dreisigacker Susanne, Carrillo-Salazar José A, Acevedo-Siaca Liana G, Guerra-Lugo Margarita, Thompson Gilberto, Pecina-Martínez José A, Crossa José

Abstract excerpt

Genomic selection is an extension of marker-assisted selection by leveraging thousands of molecular markers distributed across the genome to capture the maximum possible proportion of the genetic variance underlying complex traits. In this study, genomic prediction models were developed by integrating phenological, physiological, and high-throughput phenotyping traits to predict grain yield in bread wheat...

Topics

Join the communities discussing this publication.

Droughts
Genome, Plant
Genomics
Genotype
Models, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Stress, Physiological

Source

Open in PubMed Open full text

Identifiers

PMID: 40904125
DOI: 10.1002/tpg2.70110
PMCID: PMC12409263

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

0

discussions

0

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Integration of physiological and remote sensing traits for improved genomic prediction of wheat yield.PMID 40904125Read ↗

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat.Semantic proximity Read ↗

Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat.Semantic proximity Read ↗

Combining High-Throughput Phenotyping and Genomic Information to Increase Prediction and Selection Accuracy in Wheat Breeding.Semantic proximity Read ↗

Improving genomic prediction in wheat with random regression models with genotype-specific phenology-driven environmental covariates.Semantic proximity Read ↗

Enhancing prediction accuracy of grain yield in wheat lines adapted to the southeastern United States through multivariate and multi-environment genomic prediction models incorporating spectral and thermal information.Semantic proximity Read ↗

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

Spectral-genomic chain-model approach enhances the wheat yield component prediction under the Mediterranean climate.Semantic proximity Read ↗

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology.Semantic proximity Read ↗

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.Semantic proximity Read ↗

Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi-kernel genomic prediction models integrating secondary traits and environmental covariates.Semantic proximity Read ↗

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

Phenomic selection in wheat breeding: identification and optimisation of factors influencing prediction accuracy and comparison to genomic selection.Semantic proximity Read ↗

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