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June 14, 2026Journal of Integrative AgricultureOpen Access

Construction and validation of a YOLO-Soy Model for field soybean seed counting on a self-propelled phenotyping platform

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Authors

WPWeiliang PanCYChuntao YuLCLi Chen

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Overview

Randomized trial developed a YOLO-Soy model, accelerating seed counting in soybean breeding, suggesting improved efficiency and accuracy.

Key Points

  • The aim is to improve the efficiency and accuracy of soybean seed counting in breeding programs using an automated model.
  • Developed YOLO-Soy model with novel enhancements for seed detection and counting.
  • Utilized field imagery from 2024-2025 and a leave-one-year-out cross-validation strategy for validation.
  • Conducted ablation studies to assess module contributions and synergy in performance.
  • Achieved a coefficient of determination (R²) of 0.934 in seed counting accuracy.
  • Reported a mean average precision (mAP@0.5) of 0.737 and a mean relative error of 2.446%.
  • Demonstrated an inference speed of 58.78 FPS for real-time application.

Cite This Study

Pan et al. (2026) studied this question.

synapsesocial.com/papers/6a2e44e4b1cc60ccdea8a39ahttps://doi.org/10.1016/j.jia.2026.06.021
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