A 3D stem diameter measurement method for field maize at jointing stage: combining RLRSA-PointNet++ and structural
Jing Zhou1, Yijia Tang1, Mingren Cui1
1College of Information Technology, Jilin Agricultural University, Changchun, China.
Frontiers in Plant Science
|January 28, 2026
Summary
This study introduces a novel 3D method for measuring maize stem diameter, improving accuracy in precision agriculture. The approach enhances lodging resistance assessment and yield prediction for maize crops.
Area of Science:
- Agricultural Engineering
- Computer Vision
- Plant Science
Background:
- Accurate maize stem diameter measurement is vital for lodging resistance and yield prediction in precision agriculture.
- Existing manual and 2D methods are subjective, time-consuming, and lack 3D structural information.
- A need exists for automated, accurate 3D stem diameter measurement.
Purpose of the Study:
- To develop and validate an automated 3D stem diameter measurement method for maize plants.
- To improve the accuracy and reliability of stem diameter measurements during the critical jointing stage.
- To provide a foundation for advanced maize growth monitoring and phenotypic analysis.
Main Methods:
- Generated 3D point clouds of maize stems using multi-view image reconstruction.
- Improved PointNet++ network with Relative Position Encoding, Local Group Rearrangement, and Self-Attention for precise stem segmentation.
- Applied structural feature fitting, including principal axis analysis and ellipse fitting, for diameter estimation.
Main Results:
- Achieved high accuracy in complex field conditions.
- Reported a Mean Absolute Error (MAE) of 1.27 mm for major-axis diameter (R² = 0.87).
- Reported an MAE of 1.38 mm for minor-axis diameter (R² = 0.82).
Conclusions:
- The proposed 3D method overcomes limitations of traditional measurement techniques.
- Offers a robust and accurate solution for maize stem diameter measurement at the jointing stage.
- Supports intelligent maize growth monitoring, lodging resistance analysis, and 3D trait extraction.
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