Droplet Penetration Model Based on Canopy Porosity for Spraying Applications

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 (R-2) (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.

Automated summary

The study examines the interaction between the canopy of fruit trees, the airflow field, and the droplet penetration ratio using a mobile LIDAR system and wind tunnel experiments. The results show that wind velocity decreases during canopy penetration, with the lowest value at the back of the canopy. A quadratic exponential regression model is found to be the most accurate in predicting the droplet penetration ratio. This research provides valuable information for optimizing spraying parameters and improving pesticide utilization.