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Related Concept Videos

Light Acquisition02:16

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.

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Related Experiment Video

Updated: Jul 16, 2026

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&ndash;Environment Interactions
15:30

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

Three-Dimensional Crop Phenotyping for Crop Protection: Reconstruction Routes, Decision Pathways, and Digital-Twin

Fanguo Zeng1, Lin Yuan1, Ouguan Xu1

  • 1School of Computer Science and Technology, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China.

Plants (Basel, Switzerland)
|July 15, 2026
PubMed
Summary

Three-dimensional (3D) crop phenotyping offers valuable data for crop protection, but its practical application requires linking 3D traits to actionable decisions. High-fidelity 3D models must mature into feedback-aware digital twins for effective deployment.

Keywords:
3D crop phenotyping3D reconstructioncrop protectiondecision supportdigital twin maturity

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Area of Science:

  • Agricultural Science
  • Computer Vision
  • Plant Science

Background:

  • Three-dimensional (3D) crop phenotyping captures detailed plant structure.
  • Its utility in crop protection is conditional on providing decision-relevant information beyond traditional methods.
  • A framework is needed to assess 3D phenotyping's maturity for crop protection applications.

Purpose of the Study:

  • To review and synthesize evidence on 3D crop phenotyping for crop protection.
  • To evaluate the maturity of 3D approaches across various protection tasks.
  • To identify priorities for advancing 3D phenotyping towards validated decision support systems.

Main Methods:

  • A reconstruction-trait-task-maturity framework was used for literature synthesis.
  • Evidence was examined across disease assessment, pest interpretation, pesticide application, and digital twin development.
  • The review analyzed reconstruction routes, 3D traits, decision pathways, and maturity levels.

Main Results:

  • Strongest evidence for 3D phenotyping in crop protection comes from canopy-based pesticide dose adjustment and spray deposition prediction.
  • Disease, stress, and architecture-aware modeling show promise but with heterogeneous evidence.
  • Many current 3D methods and digital twin frameworks lack validated links to practical protection decisions and outcomes.

Conclusions:

  • High-fidelity 3D reconstruction does not equate to decision-support maturity.
  • Protection-oriented digital twins require integration of crop geometry, models, decision rules, and field outcomes.
  • Further research must focus on validated links between 3D measurements and crop protection outcomes for deployment.