HAL (France)
open access
Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding
Genomic selection (GS) is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV) in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Ensemble-based genomic prediction for maize flowering time improves prediction accuracy and reveals novel insights into trait genetic variation.#258457
- GWAS and Candidate Gene Prediction of Elemental Accumulation Traits in Rice Using a Multiparental Population#976236
- Precision in Rice Variety Classification using Stacking-Based Ensemble Learning#997396
- OryzaG3: A Single-species Genomic Foundation Model Pretrained on Rice Pangenome#307217
- Breeding for Resilient Cereals: Integrating Molecular Networks and Trait-Based Selection to Improve Nitrogen and Water Use Efficiencies.#434569
Record · ID 1219233
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive