Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Light Acquisition

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.

Plant Breeding and Biotechnology

Plant Breeding and Biotechnology

Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.

Dihybrid Crosses

Dihybrid Crosses

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Synthetic-augmented multimodal deep learning fuses dual-angle RGB images and phenology to unlock genotype-informative canopy structural trait in wheat.

Plant phenomics (Washington, D.C.)·2026

Same author

Machine Learning-Enabled Intelligent Technologies Across the Grape and Wine Value Chain: From Vineyard Sensing to Winemaking Optimization.

Comprehensive reviews in food science and food safety·2026

Same author

Precise mapping of high-temperature adult-plant stripe rust resistance gene Yr52 in wheat.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2026

Same author

A compact, flexible time-resolved single photon detection system based on an active quenched SPAD by FPGA tri-state gates.

Optics express·2026

Same author

Stochastic and deterministic processes shape microbiota and flavors of strong-flavor Daqu made from different wheat varieties during fermentation.

Food research international (Ottawa, Ont.)·2026

Same author

Effect of Yiqi Fumai injection improves exercise tolerance in patients with chronic heart failure: A prospective, open-label, randomized, controlled clinical trial.

QJM : monthly journal of the Association of Physicians·2026

Search research articles

Related Experiment Video

Updated: Jul 2, 2026

High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

Published on: January 9, 2026

Synchronized UAV multi-angle inversion of canopy structure parameters in wheat breeding materials.

Zhiwen Mi¹, Jinya Su², Qifan Chen¹

¹College of Mechanical and Electronic Engineering, Northwest A&F University, Key Laboratory of Agricultural Internet of Things, Yangling, 712100, Shaanxi, China.

Plant Phenomics (Washington, D.C.)

|July 1, 2026

Summary

Multi-angle UAV sensing significantly improves estimates of wheat canopy structure, including leaf inclination distribution (LIDFa) and leaf area index (LAI). This advancement offers valuable insights for crop breeding and management.

Keywords:

Fractional vegetation cover Leaf area index Leaf inclination distribution parameter Reflectance anisotropy Semi-empirical BRDF model Unmanned aerial vehicle (UAV)

More Related Videos

Computer Vision-Based Biomass Estimation for Invasive Plants

Computer Vision-Based Biomass Estimation for Invasive Plants

Published on: February 9, 2024

Related Experiment Videos

Last Updated: Jul 2, 2026

High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

Published on: January 9, 2026

Computer Vision-Based Biomass Estimation for Invasive Plants

Computer Vision-Based Biomass Estimation for Invasive Plants

Published on: February 9, 2024

Area of Science:

Agricultural remote sensing
Plant canopy structure analysis
UAV-based photogrammetry

Background:

Accurate estimation of canopy structure parameters like leaf inclination distribution (LIDFa), leaf area index (LAI), and fractional vegetation cover (FCover) is crucial for crop breeding.
The added value of multi-angular Unmanned Aerial Vehicle (UAV) sensing over traditional nadir-only methods for these estimations is not well understood.

Purpose of the Study:

To develop and evaluate a UAV-based multi-angular inversion framework for deriving high-resolution canopy structure parameters.
To compare the retrieval performance of multi-angle versus nadir-only sensing strategies for LIDFa, LAI, and FCover using transfer learning.

Main Methods:

Developed a UAV framework to derive bidirectional reflectance factors (BRF) from oblique photogrammetry.
Fitted a kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model to characterize reflectance anisotropy.
Employed transfer learning (CNN, Random Forest) to compare multi-angle vs. nadir-only retrieval accuracy across cultivars and dates.

Main Results:

BRDF model simulations showed strong agreement with airborne BRF data (R² > 0.80).
Multi-angle observations significantly improved LAI (R² = 0.59 vs. 0.38) and LIDFa (R² = 0.46 vs. 0.37) retrieval accuracy compared to nadir-only.
High accuracy was achieved for FCover with both methods (R² ≥ 0.73), with marginal gains from multi-angle sensing.

Conclusions:

Kernel-driven BRDF modeling effectively captures spectral anisotropy in dense wheat canopies.
Multi-angular UAV sensing offers a distinct advantage for retrieving complex structural parameters like LAI and LIDFa.
Optimal viewing configurations are trait-dependent, favoring forward scattering angles (15°-45° zenith).