Analysing the penetration and droplet deposition characteristics in the canopy of fruit trees is critical for optimising the operational parameters of air-assisted spraying equipment, achieving precise application of chemicals, and improving the effectiveness of fruit tree pest and disease control. We used a mobile LIDAR system to detect the tree canopy characteristics and optical porosity and conduct wind tunnel experiments to investigate the interaction between the tree canopy, the airflow field, and the droplet penetration ratio in the canopy of fruit trees. The results show that the relative wind velocity decreases rapidly during canopy penetration, and that the minimum value occurs at the back of the canopy. The smaller the optical porosity, the greater the reduction in wind velocity is. The quadratic exponential regression model had the highest coefficient of determination (R²) (0.9672) and the lowest root mean square error (RMSE) (5.56%). This paper provides information on optimising the spraying parameters, improving the pesticide utilisation rate, and selecting the optimum spraying conditions and application parameters.

This study developed and evaluated a LiDAR-based variable-rate orchard sprayer to address the inefficiency of traditional constant-rate application. The system dynamically adjusts pesticide output in real-time using a canopy volume calculation model and an adaptive delayed-spray mechanism, synchronized with LiDAR scans and travel speed. Experimental results demonstrated effective performance: the canopy volume estimation achieved a low overall error of 2.84%, enabling precise spray decision-making. The dosage control system showed an average error of 8.78%, and the adaptive system responded within 160 ms, distinguishing target gaps as small as 75 mm. Deposition tests confirmed uniform coverage within the canopy and minimal drift. The system proves to be a practical solution for significantly reducing pesticide use, operational costs, and environmental impact, marking a substantial advancement in precision orchard management.

Airflow regulation is essential for optimizing pesticide deposition in orchard spraying. This study developed an airflow attenuation model for a five-port air-assisted sprayer by integrating jet dynamics with crown resistance characteristics. The tree crown was modeled as a porous medium with calibrated resistance coefficients, and airflow attenuation was described using momentum conservation theorems, with initial conditions derived from jet decay profiles at the outlet. Validation included free-space airflow measurements and field trials in three fruit tree species. In free-space tests, the model showed a maximum relative error of 22.31% and a mean error of 12.26%. Field tests yielded a maximum error of 25.92%, with mean errors of 14.85% and 15.76% at 2300 and 2800 rpm, respectively. The model provides a theoretical basis for intelligent airflow control aimed at improving deposition and reducing drift.