Abstract
Developing drought-resistant alfalfa (Medicago sativa L.) that maintains high biomass yield is a key breeding goal to enhance productivity in water-limited areas. In this study, 424 alfalfa breeding families were analyzed to identify molecular markers associated with biomass yield under drought stress and to predict high-merit plants. Biomass yield was measured from 18 harvests from 2020 to 2023 in a field trial with deficit irrigation. A total of 131 significant markers were associated with biomass yield, with 80 markers specifically linked to yield under drought stress; among these, 19 markers were associated with multiple harvests. Finally, genomic best linear unbiased prediction (GBLUP) was employed to obtain predictive accuracies (PAs) and genomic estimated breeding values (GEBVs). Removing low-informative SNPs [SNPs with p-values > 0.05 from the additive Genome-Wide Association (GWAS) model] for GBLUP increased PA by 47.3%. The high number of markers associated with yield under drought stress and the highest PA (0.9) represent a significant achievement in improving yield under drought stress in alfalfa.
| Original language | English (US) |
|---|---|
| Article number | 608 |
| Journal | International journal of molecular sciences |
| Volume | 26 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 2025 |
Bibliographical note
Publisher Copyright:© 2025 by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Keywords
- GWAS
- alfalfa
- drought stress
- genomic prediction
- yield
PubMed: MeSH publication types
- Journal Article
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