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Automatic root measurement: a lightweight method for measuring pea root length.

Haoyu Jiang1, Chenhan Hu2, Luxu Tian3

  • 1College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, 210031, China.

Plant Methods
|December 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a lightweight automatic root measurement (ARM) model for efficient pea root length analysis. The ARM model enhances crop stress resistance research and supports sustainable agriculture.

Keywords:
Cost-effective deploymentInstance segmentationPea seedsRoot length measurementStress-resistant crop breeding

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Area of Science:

  • Agricultural Science
  • Plant Biology
  • Computer Vision

Background:

  • Climate change increases extreme weather events, impacting crop yield and stability.
  • Developing stress-resistant crops is crucial for sustainable agriculture and food security.
  • Root length is a key trait for water/nutrient absorption and stress tolerance, but measurement is a bottleneck.

Purpose of the Study:

  • To develop an efficient and cost-effective automated system for measuring root length.
  • To address limitations of manual measurement and high-cost existing automated models.
  • To support high-throughput phenotyping in crop breeding and agricultural research.

Main Methods:

  • Developed a seed germination image acquisition system and a pea root dataset.
  • Utilized the YOLOv8-Seg-n instance segmentation model for a lightweight automatic root measurement (ARM) model.
  • Applied feature distillation, structured pruning, and post-processing for root length calculation.

Main Results:

  • The ARM model has 1.81M parameters, 8.3 GFLOPs, 4.2MB file size, and achieves 70.4 FPS.
  • Achieved high performance with mAP@0.5 of 90.3% and AProot of 81.2%, showing strong correlation with manual measurements (R² = 0.993).
  • Demonstrated practical application potential through time-series analysis of pea root length under drought conditions.

Conclusions:

  • The ARM model provides an efficient, cost-effective solution for high-throughput root length measurement in peas.
  • It balances accuracy, speed, and computational requirements, showing broad potential in agriculture and breeding.
  • Offers critical technical support for food security and enhancing crop stress resistance.