ArticleFrontiers in plant science2021
High Throughput Field Phenotyping for Plant Height Using UAV-Based RGB Imagery in Wheat Breeding Lines: Feasibility and Validation.
Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
35 citing papers in PubMed, 106 citations in OpenAlex.
- 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
- Accelerating iron biofortification in millets: progress, challenges, and future prospects.Planta · 2026Review
- Ground Mobile Robots for High-Throughput Plant Phenotyping: A Review from the Closed-Loop Perspective of Perception, Decision, and Action.Plants (Basel, Switzerland) · 2026Review
- Editorial: Utilizing machine learning with phenotypic and genotypic data to enhance effective breeding in agricultural and horticultural crops.Frontiers in plant science · 2026Article
- Bridging scales: integrated multi-omics and deep phenotyping for climate resilience in crop plants.Frontiers in plant science · 2026Review
- Multitask ST-LSTM model based on UAV hyperspectral remote sensing for wheat yield prediction.Frontiers in plant science · 2026Article
- UAV-LiDAR high-throughput time-series phenotyping and genome-wide association analysis reveal the genetic basis of plant height in peanut (Plant phenomics (Washington, D.C.) · 2025Article
- Climate-Resilient Crops: Integrating AI, Multi-Omics, and Advanced Phenotyping to Address Global Agricultural and Societal Challenges.Plants (Basel, Switzerland) · 2025Review
- Bridging Intuition and Data: A Unified Bayesian Framework for Optimizing Unmanned Aerial Vehicle Swarm Performance.Entropy (Basel, Switzerland) · 2025Article
- Combining UAV multisensor field phenotyping and genome-wide association studies to reveal the genetic basis of plant height in cotton (Plant phenomics (Washington, D.C.) · 2025Article
- Plant Detection in RGB Images from Unmanned Aerial Vehicles Using Segmentation by Deep Learning and an Impact of Model Accuracy on Downstream Analysis.Journal of imaging · 2025Article
- Integrating UAV multispectral imaging and proximal sensing for high-precision cereal crop monitoring.PloS one · 2025Article
- Plant height measurement using UAV-based aerial RGB and LiDAR images in soybean.Frontiers in plant science · 2025Article
- Unlocking regeneration potential: harnessing morphogenic regulators and small peptides for enhanced plant engineering.The Plant journal : for cell and molecular biology · 2025Review
- Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.The Plant journal : for cell and molecular biology · 2024Article
- Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- All-organic transparent plant e-skin for noninvasive phenotyping.Science advances · 2024Article
- Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.Frontiers in plant science · 2024Review
- High-Throughput Yield Prediction of Diallele Crossed Sugar Beet in a Breeding Field Using UAV-Derived Growth Dynamics.Plant phenomics (Washington, D.C.) · 2024Article
- Drone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans (Plant phenomics (Washington, D.C.) · 2024Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plant height (PH) is an essential trait in the screening of most crops. While in crops such as wheat, medium stature helps reduce lodging, tall plants are preferred to increase total above-ground biomass. PH is an easy trait to measure manually, although it can be labor-intense depending on the number of plots. There is an increasing demand for alternative approaches to estimate PH in a higher throughput mode. Crop surface models (CSMs) derived from dense point clouds generated via aerial imagery could be used to estimate PH. This study evaluates PH estimation at different phenological stages using plot-level information from aerial imaging-derived 3D CSM in wheat inbred lines during two consecutive years. Multi-temporal and high spatial resolution images were collected by fixed-wing (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.