Design of and Experiment with Physical Perception Pineapple Targeted Flower Forcing-Spraying Control System

Induction in pineapples requires the targeted delivery of specific chemical solutions into the plant’s central core to enable batch management, a task currently reliant on manual operation. This study addressed this challenge by analyzing the physical characteristics of pineapple plants and establishing a perception-based mathematical model for core position localization. An integrated hardware–software system was developed, complemented by a human–machine interface for real-time operational monitoring. Comprehensive experiments were conducted to evaluate the spraying accuracy, nozzle response time, and prototype performance. The results demonstrate that the actuation system—comprising solenoid valves, pumps, and flowmeters—achieved an average spraying error of 2.72%. The average nozzle opening/closing time was 0.111 s; with a standard operating speed of 0.5 m/s, a delay compensation distance of 55.5 mm was implemented. In human–machine comparative trials, the automated system outperformed manual spraying in both efficiency and stability, with average errors of 7.1% and 6.4%, respectively. The system reduced chemical usage by over 67,500 mL per hectare while maintaining a miss-spray rate of 5–6%. Both two-tailed tests revealed extremely significant differences (p < 0.001). These findings confirm that the developed solution meets the operational requirements for pineapple floral induction, offering significant improvements in precision and resource efficiency.