ArticleJournal of experimental botany2017
Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.
Article in Journal of experimental botany, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Early Plant Development as a Systems-Level Trait: Integrating Omics, Artificial Intelligence, and Emerging Biotechnologies.Plants (Basel, Switzerland) · 2026Review
- Root system architecture and drought adaptation: emerging tools and genetic insights.Frontiers in plant science · 2026Review
- Silicon as a Strategy to Mitigate Abiotic Stresses and Improve Physiological Performance and Grain Yield of Maize Grown Under Tropical Climate Conditions.Plants (Basel, Switzerland) · 2025Article
- Genotypic Variability in Root Morphology in a Diverse Wheat Genotypes Under Drought and Low Phosphorus Stress.Plants (Basel, Switzerland) · 2024Article
- From phenotyping to genetic mapping: identifying water-stress adaptations in legume root traits.BMC plant biology · 2024Review
- Regulation of root growth and elongation in wheat.Frontiers in plant science · 2024Review
- Spatial and Texture Analysis of Root System distribution with Earth mover's Distance (STARSEED).Plant methods · 2023Article
- Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.Plant phenomics (Washington, D.C.) · 2023Review
- Omics resources and omics-enabled approaches for achieving high productivity and improved quality in pea (Pisum sativum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- Genetic Variability ofFrontiers in plant science · 2021Article
- A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean.Frontiers in plant science · 2021Article
- Root Response to Drought Stress in Rice (International journal of molecular sciences · 2020Review
- Mechanisms of High Concentration Valine-Mediated Inhibition of Peach Tree Shoot Growth.Frontiers in plant science · 2020Article
- Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon.Frontiers in plant science · 2020Article
- The platformPlant methods · 2020Article
- Characterization of Cover Crop Rooting Types from Integration of Rhizobox Imaging and Root Atlas Information.Plants (Basel, Switzerland) · 2019Article
- Three-Dimensional Time-Lapse Analysis Reveals Multiscale Relationships in Maize Root Systems with Contrasting Architectures.The Plant cell · 2019Article
- Building a future with root architecture.Journal of experimental botany · 2018Article
- Seeking stable traits to characterize the root system architecture. Study on 60 species located at two sites in natura.Annals of botany · 2018Article
- Hyperspectral imaging: a novel approach for plant root phenotyping.Plant methods · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research.
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