ArticlePlant phenomics (Washington, D.C.)2025
Genetic resolution of multi-level plant height in common wheat using the 3D canopy model from ultra-low altitude unmanned aerial vehicle imagery.
Article in Plant phenomics (Washington, D.C.), 2025. 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.
- Temporal GWAS and QTL mapping of UAV-derived digital canopy height reveals stage-specific genetic effects in bread wheat.Plant phenomics (Washington, D.C.) · 2026Article
- Integrating 3D phenotyping and functional-structural plant models for crop ideotype breeding.Nature communications · 2026Review
- InspectGaussian: Large-scale coarse-to-fine Gaussian reconstruction for orchard inspection robots.Plant phenomics (Washington, D.C.) · 2026Article
- Balancing accuracy, completeness, and efficiency for rice 3D reconstruction through CBAM-UNet-based multi-view segmentation and camera configuration optimization.Frontiers in plant science · 2026Article
- Editorial: Leveraging phenotyping and crop modeling in smart agriculture.Frontiers in plant science · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
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Abstract
In quantitative genomic analysis of wheat plant height (PH), the average height of a few representative plants is typically used to represent the PH of the entire plot, which overlooks the variation in height among other plants. Extracting different height quantiles from canopy point clouds can address this limitation. For this purpose, low-cost UAV cross-circling oblique (CCO) imaging, combined with structure-from-motion (SfM) and multi-view stereopsis (MVS), was employed to generate precise canopy point clouds for 262 F5 recombinant inbred lines (Zhongmai 578 × Jimai 22) across seven environments. Multi-level 3D-PH measurements were extracted from six height quantiles, revealing a strong correlation (mean
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