A Review of Multiscale Interaction Mechanisms of Wind-Leaf-Droplet Systems in Orchard Spraying

文献类型： 外文期刊

第一作者： Wang, Yunfei

作者： Wang, Yunfei;Zhang, Zhenlei;Shi, Ruohan;Dai, Shiqun;Jia, Weidong;Ou, Mingxiong;Dong, Xiang;Dai, Shiqun;Jia, Weidong;Ou, Mingxiong;Dong, Xiang;Yan, Mingde

作者机构：

关键词： orchard spraying; key spray variables; wind-leaf-droplet interaction; data-driven modeling

期刊名称：SENSORS （ 影响因子：3.5； 五年影响因子：3.7 ）

ISSN：

年卷期： 2025 年 25 卷 15 期

页码：

收录情况： SCI

摘要： The multiscale interactive system composed of wind, leaves, and droplets serves as a critical dynamic unit in precision orchard spraying. Its coupling mechanisms fundamentally influence pesticide transport pathways, deposition patterns, and drift behavior within crop canopies, forming the foundational basis for achieving intelligent and site-specific spraying operations. This review systematically examines the synergistic dynamics across three hierarchical scales: Droplet-leaf surface wetting and adhesion at the microscale; leaf cluster motion responses at the mesoscale; and the modulation of airflow and spray plume diffusion by canopy architecture at the macroscale. Key variables affecting spray performance-such as wind speed and turbulence structure, leaf biomechanical properties, droplet size and electrostatic characteristics, and spatial canopy heterogeneity-are identified and analyzed. Furthermore, current advances in multiscale modeling approaches and their corresponding experimental validation techniques are critically evaluated, along with their practical boundaries of applicability. Results indicate that while substantial progress has been made at individual scales, significant bottlenecks remain in the integration of cross-scale models, real-time acquisition of critical parameters, and the establishment of high-fidelity experimental platforms. Future research should prioritize the development of unified coupling frameworks, the integration of physics-based and data-driven modeling strategies, and the deployment of multimodal sensing technologies for real-time intelligent spray decision-making. These efforts are expected to provide both theoretical foundations and technological support for advancing precision and intelligent orchard spraying systems.

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