智能农业技术在杂草管理中的应用研究进展OA

In recent years,global agriculture has faced multiple challenges,including increasing food demand,decreasing labor force,and environmental degradation.Among them,weed infestation,as one of the key factors constraining crop yield and farmland management efficiency,urgently calls for more efficient and sustainable management approaches.Traditional weed management methods heavily rely on manual labor and chemical herbicides,which are inefficient and have negative environmental impacts.Smart agriculture,by in-tegrating modern technologies such as the Internet of Things(IoT),deep learning,drones and robots,offers an efficient and environmentally friendly solution for weed detection and identification.This paper reviewed the advancements in weed management through smart agriculture technologies,specifically focusing on the appli-cation of deep learning in weed detection,drone-based field monitoring,and autonomous operations of intelli-gent weeding robots.Despite their significant performance in improving operational efficiency and reducing her-bicide use,these technologies still face challenges in large-scale deployment,such as environmental complexi-ty,high costs,and insufficient model generalizability.Future research should focus on enhancing model gener-alization,reducing equipment costs,and improving the efficiency of multimodal data integration to promote the widespread adoption and sustainable development of smart agricultural technologies.