ArticlePlant methods2021
Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.).
Article in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 28 citations in OpenAlex.
- Intraspecific variation in mycorrhiza-associated traits predicts plant responses to resource limitation.Mycorrhiza · 2026Article
- Integrating morphological and molecular characterization to reveal genetic diversity and breeding potential in Turkish local alfalfa (Medicago sativa L.) populations.Scientific reports · 2026Article
- Response of root morphology and anatomy of two alfalfa cultivars with contrasting root system architecture to phosphorus deficiency under drought stress.Frontiers in plant science · 2026Article
- Effect of phosphorus deficiency on biomass and root system architecture in diverseFrontiers in plant science · 2026Article
- Regulation of alfalfa growth, water and nitrogen utilization and distribution in arid region of Northwest China by optimizing irrigation method.Frontiers in plant science · 2025Article
- Thriving in a salty future: morpho-anatomical, physiological and molecular adaptations to salt stress in alfalfa (Medicago sativa L.) and other crops.Annals of botany · 2024Review
- Multi-locus genome-wide association study reveal genomic regions underlying root system architecture traits in Ethiopian sorghum germplasm.The plant genome · 2024Article
- The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review.Plant phenomics (Washington, D.C.) · 2024Review
- Phenotyping Alfalfa (Plant phenomics (Washington, D.C.) · 2024Article
- Exploring root system architecture and anatomical variability in alfalfa (Medicago sativa L.) seedlings.BMC plant biology · 2023Article
- OMICS in Fodder Crops: Applications, Challenges, and Prospects.Current issues in molecular biology · 2022Review
- Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.).Plant phenomics (Washington, D.C.) · 2022Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundThe root system architecture (RSA) of alfalfa (Medicago sativa L.) affects biomass production by influencing water and nutrient uptake, including nitrogen fixation. Further, roots are important for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous selection for a greater number of branched and fibrous roots significantly increased alfalfa biomass yield. However, phenotyping root systems of mature alfalfa plant is labor-intensive, time-consuming, and subject to environmental variability and human error. High-throughput and detailed phenotyping methods are needed to accelerate the development of alfalfa germplasm with distinct RSAs adapted to specific environmental conditions and for enhancing productivity in elite germplasm. In this study methods were developed for phenotyping 14-day-old alfalfa seedlings to identify measurable root traits that are highly heritable and can differentiate plants with either a branched or a tap rooted phenotype. Plants were grown in a soil-free mixture under controlled conditions, then the root systems were imaged with a flatbed scanner and measured using WinRhizo software.
resultsThe branched root plants had a significantly greater number of tertiary roots and significantly longer tertiary roots relative to the tap rooted plants. Additionally, the branch rooted population had significantly more secondary roots > 2.5 cm relative to the tap rooted population. These two parameters distinguishing phenotypes were confirmed using two machine learning algorithms, Random Forest and Gradient Boosting Machines. Plants selected as seedlings for the branch rooted or tap rooted phenotypes were used in crossing blocks that resulted in a genetic gain of 10%, consistent with the previous selection strategy that utilized manual root scoring to phenotype 22-week-old-plants. Heritability analysis of various root architecture parameters from selected seedlings showed tertiary root length and number are highly heritable with values of 0.74 and 0.79, respectively.
conclusionsThe results show that seedling root phenotyping is a reliable tool that can be used for alfalfa germplasm selection and breeding. Phenotypic selection of RSA in seedlings reduced time for selection by 20 weeks, significantly accelerating the breeding cycle.
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