ArticleAnnals of botany2020
Estimation of maize plant height and leaf area index dynamics using an unmanned aerial vehicle with oblique and nadir photography.
Article in Annals of botany, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Beyond high-throughput: leveraging plant phenotyping to improve understanding and prediction of plant growth through process-based models.The New phytologist · 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
- Multi-sensor phenotyping of yield and yield stability for genotype selection in durum wheat.Plant phenomics (Washington, D.C.) · 2026Article
- Improved Multi-Stage Rice Above-Ground Biomass Estimation Using Wavelet-Texture-Fused Vegetation Indices from UAV Remote Sensing.Plants (Basel, Switzerland) · 2025Article
- Field phenotyping for soybean density tolerance using time-series prediction and dynamic modeling.Plant phenomics (Washington, D.C.) · 2025Article
- Genetic resolution of multi-level plant height in common wheat using the 3D canopy model from ultra-low altitude unmanned aerial vehicle imagery.Plant phenomics (Washington, D.C.) · 2025Article
- Comparative Analysis of TLS and UAV Sensors for Estimation of Grapevine Geometric Parameters.Sensors (Basel, Switzerland) · 2024Article
- An integrated method for phenotypic analysis of wheat based on multi-view image sequences: from seedling to grain filling stages.Frontiers in plant science · 2024Article
- Comparing Nadir and Oblique Thermal Imagery in UAV-Based 3D Crop Water Stress Index Applications for Precision Viticulture with LiDAR Validation.Sensors (Basel, Switzerland) · 2023Article
- The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field.Plant phenomics (Washington, D.C.) · 2023Article
- UAV-based individual plant detection and geometric parameter extraction in vineyards.Frontiers in plant science · 2023Article
- Estimation of cotton canopy parameters based on unmanned aerial vehicle (UAV) oblique photography.Plant methods · 2022Article
- Retrieving rice (Frontiers in plant science · 2022Article
- Evaluation of important phenotypic parameters of tea plantations using multi-source remote sensing data.Frontiers in plant science · 2022Article
- Why Do Big Data and Machine Learning Entail the Fractional Dynamics?Entropy (Basel, Switzerland) · 2021Article
- The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines.Plant phenomics (Washington, D.C.) · 2021Article
- Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology.Annals of botany · 2020Review
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsHigh-throughput phenotyping is a limitation in plant genetics and breeding due to large-scale experiments in the field. Unmanned aerial vehicles (UAVs) can help to extract plant phenotypic traits rapidly and non-destructively with high efficiency. The general aim of this study is to estimate the dynamic plant height and leaf area index (LAI) by nadir and oblique photography with a UAV, and to compare the integrity of the established three-dimensional (3-D) canopy by these two methods.
methodsImages were captured by a high-resolution digital RGB camera mounted on a UAV at five stages with nadir and oblique photography, and processed by Agisoft Metashape to generate point clouds, orthomosaic maps and digital surface models. Individual plots were segmented according to their positions in the experimental design layout. The plant height of each inbred line was calculated automatically by a reference ground method. The LAI was calculated by the 3-D voxel method. The reconstructed canopy was sliced into different layers to compare leaf area density obtained from oblique and nadir photography. KEY
resultsGood agreements were found for plant height between nadir photography, oblique photography and manual measurement during the whole growing season. The estimated LAI by oblique photography correlated better with measured LAI (slope = 0.87, R2 = 0.67), compared with that of nadir photography (slope = 0.74, R2 = 0.56). The total number of point clouds obtained by oblique photography was about 2.7-3.1 times than those by nadir photography. Leaf area density calculated by nadir photography was much less than that obtained by oblique photography, especially near the plant base.
conclusionsPlant height and LAI can be extracted automatically and efficiently by both photography methods. Oblique photography can provide intensive point clouds and relatively complete canopy information at low cost. The reconstructed 3-D profile of the plant canopy can be easily recognized by oblique photography.
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