文献类型： 外文期刊
作者： Wang, Yunfei 1 ; Jia, Weidong 1 ; Ou, Mingxiong 1 ; Wang, Xuejun 3 ; Dong, Xiang 1 ;
作者机构： 1.Jiangsu Univ, Sch Agr Engn, Zhenjiang 212013, Peoples R China
2.Jiangsu Univ, Key Lab Plant Protect Engn, Minist Agr & Rural Affairs, Zhenjiang 212013, Peoples R China
3.Chinese Acad Agr Mechanizat Sci Grp Co Ltd, Beijing 100083, Peoples R China
关键词： orchard canopy; sensor technologies; variable-rate spraying; canopy perception; multimodal data fusion
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 16 期
页码：
收录情况： SCI
摘要： With the advancement of precision agriculture, variable-rate spraying (VRS) technology has demonstrated significant potential in enhancing pesticide utilization efficiency and promoting environmental sustainability, particularly in orchard applications. As a critical medium for pesticide transport, the dynamic structural characteristics of orchard canopies exert a profound influence on spraying effectiveness. This review systematically summarizes recent progress in the dynamic perception and modeling of orchard canopies, with a particular focus on key sensing technologies such as LiDAR, Vision Sensor, multispectral/hyperspectral sensors, and point cloud processing techniques. Furthermore, it discusses the construction methodologies of static, quasi-dynamic, and fully dynamic canopy modeling frameworks. The integration of canopy sensing technologies into VRS systems is also analyzed, including their roles in spray path planning, nozzle control strategies, and precise droplet transport regulation. Finally, the review identifies key challenges-particularly the trade-offs between real-time performance, seasonal adaptability, and modeling accuracy-and outlines future research directions centered on multimodal perception, hybrid modeling approaches combining physics-based and data-driven methods, and intelligent control strategies.
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