ArticleFrontiers in plant science2024
Multi-trait modeling and machine learning discover new markers associated with stem traits in alfalfa.
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Disentangling direct and pleiotropic SNP effects in alfalfa (Medicago sativa L.) using causal graph learning.Scientific reports · 2026Article
- UAV image-derived canopy traits for predicting alfalfa fall dormancy and forage yield in Mediterranean environments.Frontiers in plant science · 2026Article
- BIGapp: A user-friendly genomic tool kit identified quantitative trait loci for creeping rootedness in alfalfa (Medicago sativa L.).The plant genome · 2025Article
- Pre-breeding in alfalfa germplasm develops highly differentiated populations, as revealed by genome-wide microhaplotype markers.Scientific reports · 2025Article
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7 authors.
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Abstract
Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h
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