[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2733":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":8,"category":10,"cover_url":8,"hotness":11,"is_selected":12,"score":13,"score_detail":14,"sources":22,"tags":24,"view_count":30,"doi":8,"paper":31,"created_at":40},2733,"Non-Destructive Sensing and Modeling for Biomass Estimation and Yield Prediction of Protected Vegetables——综述","https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F18\u002F1980","江苏大学Xiaodong Zhang等综述了设施蔬菜生物量与产量无损感知与建模研究进展,聚焦叶菜与果菜类设施栽培,总结了生物量与产量指标及地面真实测量方法,比较了RGB成像、三维视觉、光谱感知和环境数据的特点,综述了叶菜生物量估算、连续生长监测、收获预测以及果菜花果感知、果品计数、单果质量估算、分阶段收获产量预测等进展。",null,"Agriculture (MDPI) 2026年第16卷18期","论文",10,false,68,{"impact":15,"substance":16,"depth":17,"authority":18,"freshness":19,"relevant":20,"comment":21},16,20,17,13,2,1,"系统梳理设施蔬菜生物量与产量无损感知建模进展，方法覆盖RGB、三维视觉与光谱，专业参考价值较高，但属综述且时效性弱，适合主题聚合而非每日精选。",[23],{"name":9,"url":6},[25,26,27,28,29],"智慧农业","农业人工智能","产量预测","设施蔬菜","无损感知",0,{"doi":8,"openalex_id":8,"authors":32,"venue":8,"cited_by_count":30,"oa_url":8,"card":33,"direction":37,"ingested_from":39},[],{"tldr":34,"method":35,"finding":36,"direction":37,"opportunity":38},"综述设施蔬菜生物量与产量无损感知与建模研究进展。","综述RGB成像、三维视觉、光谱感知及环境数据等方法。","总结了叶菜与果菜生物量估算、生长监测和产量预测的技术进展。","智慧农业 \u002F 农业物联网","多模态感知融合与跨品种泛化模型是设施蔬菜无损估产的研究空白。","agent","2026-09-17T00:04:40.596719Z"]