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Design and testing of a RealSense-based variable spraying control system for field kale.

Yahui Luo1, Wen Li1, Pin Jiang1

  • 1College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.

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Summary

A new variable spray control system using binocular vision and YOLOv8n technology precisely targets kale, reducing pesticide waste by up to 26.58% and improving application efficiency for better pest control.

Keywords:
atomization deposition densitybinocular vision sensorimproved YOLOv8n algorithmpulse width modulationvariable spraying

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Area of Science:

  • Agricultural Engineering
  • Robotics and Automation
  • Computer Vision

Background:

  • Traditional upland gap sprayers suffer from high pesticide dosage, low efficiency, and poor pest control.
  • Pesticide waste is a significant issue in conventional spraying methods.
  • Precision agriculture requires advanced technologies for targeted application.

Purpose of the Study:

  • To design and evaluate a variable spray control system for precise pesticide application on kale.
  • To address the limitations of traditional spraying methods in terms of efficiency and waste.
  • To improve pest and disease control while optimizing pesticide utilization.

Main Methods:

  • Developed a variable spray control system integrating binocular vision sensors and pulse-width modulation (PWM) technology.
  • Utilized an improved target detection model based on YOLOv8n for real-time kale identification.
  • Conducted flow on/off tests for solenoid valve duty cycle and evaluated spraying effects through field tests.

Main Results:

  • The YOLOv8n model achieved 88.7% detection accuracy for field-grown kale.
  • Variable spraying reduced the coefficient of variation in atomized deposition density by 0.2% compared to constant spraying.
  • Pesticide savings reached a maximum of 26.58%, with strong linear correlation between theoretical and actual flow rates (max error 4.1%).

Conclusions:

  • The developed variable spray control system effectively achieves precise pesticide application guided by binocular vision sensors.
  • The system demonstrates significant improvements in pesticide utilization and pest control efficacy for kale.
  • This technology offers a feasible and efficient solution for field pest control, reducing environmental impact.