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

Precision PWM variable spray technology and target detection, identification, and localization technology are key to solving the pesticide waste associated with traditional constant application methods and to improving pesticide utilization for achieving precise application. To address the problems of high pesticide dosage, low application efficiency, and poor kale pest and disease control in traditional upland gap sprayers, a variable spray control system was designed in the study. The system utilizes binocular vision sensors to detect kale targets in the field in real time and achieves accurate pesticide application through pulse-width modulation technology. An improved target detection model based on YOLOv8n is presented, with experimental results showing a detection accuracy of up to 88.7% for field-grown kale. The system was also tested for accuracy-responsive variable spraying in recognition detection tasks, with a 0.2% reduction in the central atomized deposition density coefficient of variation (CV) compared to constant spraying. A flow on/off test model was designed for the solenoid valve duty cycle, determining the correlation decision coefficient for spraying. The correlation coefficient of the flow model exceeded 0.9958 when the duty cycle was in the range of 20-90%, and the actual and theoretical flow rates at the spray terminals were strongly linearly correlated, with a maximum error of only 4.1%. The spraying effect of the system was evaluated through field tests. The results show that the theoretical spray volume of the variable spray control system aligns well with the actual spray volume. In field atomization deposition tests, compared with constant-rate spraying, the target center atomization density in variable spraying mode reached 34.42%. Although droplet deposition and coverage around the crop were slightly reduced, pest and disease control around kale remained effective. In addition, the variable-rate spraying control system further improved pesticide utilization, with a maximum pesticide savings of 26.58%. This study demonstrates the feasibility of binocular vision sensor-guided spraying operations in field environments and provides a reference for its application in field pest control.