The effect of rotor airflow from plant protection UAV on pesticide application in rice

Multi-rotor plant protection drones are extensively utilized in rice field operations. However, the airflow generated by the rotors not only disturbs the rice canopy but also affects the deposition of pesticide droplets. The investigation of the impact of rotor wind fields on the protection of rice crops has the potential to enhance the effectiveness of operations of this nature. The present study firstly acquired aerial imagery of plant protection drone operations via the utilization of aerial photography, and subsequently employed machine vision technology to investigate the disturbance patterns of rotor wind fields on rice canopies. Notably, there is currently no effective experimental method to observe the disturbance of rice canopies caused by the wind field generated by plant protection drone rotors, and machine vision processing is proven to be an effective approach, which is a key innovation of this study. This study innovatively adopts an integrated experimental–numerical approach, a distinct advancement over existing Unmanned Aerial Vehicle (UAV) spraying and airflow research that typically focuses on single experimental or simulation methods. Aerial photography and machine vision were used to explore canopy disturbance patterns, while reverse engineering combined with thrust tests and numerical simulations verified rotor model precision and analyzed droplet deposition. Core findings show that flight speeds of 3–4 m/s enable effective overlap between canopy disturbance and droplet deposition zones, achieving optimal plant protection effects; higher speeds cause droplet drift and zone misalignment, reducing efficacy. In addition, this study explores the spray deposition of plant protection drones based on numerical simulation methods, and assists in judging the effect of plant protection operations through the coincidence of droplet deposition and canopy disturbance zones. This integrated approach and related findings provide a reliable technical basis for optimizing UAV flight parameters, and have certain reference significance for the technical research and development of plant protection drones and the setting of operation parameters.