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Plant Tissues

Plant Tissues

Plants are multicellular eukaryotes with tissue systems made of various cell types that carry out specific functions. Different tissues work together to perform a unique function and form an organ. Organs working together form organ systems. Vascular plants have two distinct organ systems: a shoot system and a root system. The shoot system consists of two portions: the vegetative (non-reproductive) parts of the plant, such as the leaves and the stems, and the reproductive parts of the plant,...

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Updated: Apr 13, 2026

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

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Published on: April 5, 2013

A 3D reconstruction platform for complex plants using OB-NeRF.

Sixiao Wu¹, Changhao Hu¹, Boyuan Tian¹

¹China College of Engineering/Key Laboratory of Agricultural Equipment for the Middle and Lower Reaches of the Yangtze River, Ministry of Agriculture, Huazhong Agricultural University, Wuhan, China.

Frontiers in Plant Science

|March 25, 2025

Summary

This summary is machine-generated.

This study introduces a fast and accurate 3D plant reconstruction platform using Object-Based NeRF (OB-NeRF). The system significantly reduces reconstruction time and enhances precision for agricultural digital twins and high-throughput phenotyping.

Keywords:

3D reconstruction digital twins mesh neural radiance fields plant phenotyping

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Area of Science:

Agricultural Science
Computer Vision
3D Reconstruction

Background:

3D reconstruction enhances high-throughput phenotyping and digital twin development in agriculture.
Existing 3D reconstruction platforms face challenges with cost, speed, workflow complexity, and automation.

Purpose of the Study:

To develop an efficient and automated 3D reconstruction platform for complex plants.
To overcome limitations of existing 3D reconstruction methods in terms of speed, cost, and automation.

Main Methods:

A video acquisition system and keyframe extraction were implemented.
Zhang Zhengyou's calibration and Structure from Motion (SfM) were used for camera pose estimation.
Object-Based NeRF (OB-NeRF) with a novel ray sampling strategy was employed for fine-scale plant reconstruction.

Main Results:

The OB-NeRF platform achieved high-quality 3D plant reconstruction in 250 seconds.
OB-NeRF demonstrated superior performance in PSNR evaluation and reduced reconstruction time compared to NeRF and other methods.
The reconstructed 3D models showed high fidelity, with R² values of 0.9933, 0.9881, and 0.9883 for plant height, leaf length, and leaf width, respectively.

Conclusions:

The developed 3D reconstruction platform offers a robust solution for agricultural digital twins and high-throughput phenotyping.
The OB-NeRF algorithm significantly improves reconstruction efficiency and quality without background segmentation.
Optimized camera poses and automated localization enhance the precision and applicability of the 3D models.