[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2276":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"view_count":31,"doi":32,"paper":33,"created_at":57},2276,"PT-GNN: A physiological topology-aware graph neural network for multimodal early detection of cucumber downy mildew using hyperspectral and chlorophyll fluorescence sensing","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112433","PT-GNN: A physiological topology-aware graph neural network for multimodal early detection of cucumber downy mildew using hyperspectral and chlorophyll fluorescence sensing。Computers and Electronics in Agriculture","PT-GNN：一种生理拓扑感知图神经网络，利用高光谱和叶绿素荧光传感进行黄瓜霜霉病的多模态早期检测。",null,"Computers and Electronics in Agriculture","2026-09-12T00:00:00Z","论文",10,false,81,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,9,1,"提出生理拓扑感知图神经网络融合高光谱与叶绿素荧光实现黄瓜霜霉病早期检测，方法新颖且发表于农业信息领域核心期刊，具备较强专业参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","农业人工智能","黄瓜","病害检测","高光谱遥感",0,"10.1016\u002Fj.compag.2026.112433",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":31,"oa_url":9,"card":50,"direction":54,"ingested_from":56},"W7212310174",[36,39,41,43,45,47],{"name":37,"orcid":38},"Yibin Li","https:\u002F\u002Forcid.org\u002F0000-0002-5906-5074",{"name":40,"orcid":9},"Zonghuan Han",{"name":42,"orcid":9},"Yong Wang",{"name":44,"orcid":9},"Wei Gao",{"name":46,"orcid":9},"Yiding Zhang",{"name":48,"orcid":49},"Lingxian Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-8665-7075",{"tldr":51,"method":52,"finding":53,"direction":54,"opportunity":55},"提出生理拓扑感知图神经网络PT-GNN，融合高光谱与叶绿素荧光实现黄瓜霜霉病早期检测。","构建生理拓扑图神经网络，融合高光谱与叶绿素荧光多模态传感数据。","PT-GNN能有效利用生理拓扑关系，提升黄瓜霜霉病早期检测精度。","农业遥感与作物表型","可探索生理拓扑图构建的通用性，迁移至其他作物病害及多模态传感器融合场景。","openalex","2026-09-13T23:30:01.409569Z"]