[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2965":3,"related-2965":85},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":37,"classification":38,"search_phrases":80,"slug":83,"view_count":22,"doi":8,"paper":8,"created_at":84},2965,"农业农村部召开\"十五五\"果菜茶高质量发展推进会","https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL77FKJAJ0518QV0R.html","近日农业农村部在贵州修文召开\"十五五\"果菜茶高质量发展推进会。会议指出水果、蔬菜、茶叶是改善居民膳食结构的重要\"菜篮子\"产品，\"十五五\"期间要落实《加快农业农村现代化\"十五五\"规划》要求，牢固树立践行大食物观，推动水果蔬菜茶叶供应均衡、品类丰富、质量安全。",null,"[![Image 14](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL77FKJAJ0518QV0R.html)](javascript:void(0))\n\n[网易首页](https:\u002F\u002Fwww.163.com\u002F \"网易首页\")\n\n[应用](https:\u002F\u002Fwww.163.com\u002F#f=topnav)\n\n*   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[举报](https:\u002F\u002Fwww.163.com\u002Fspecial\u002F0077jt\u002Ftipoff.html?title=%E4%B8%80%E5%91%A8%E8%8C%B6%E4%BA%8B%EF%BD%9C%E6%94%BF%E7%AD%96%E7%AD%91%E7%89%A2%E4%BA%A7%E4%B8%9A%E6%A0%B9%E5%9F%BA%EF%BC%8C%E8%B5%9B%E4%BA%8B%E5%B1%95%E4%BC%9A%E6%BF%80%E6%B4%BB%E5%B8%82%E5%9C%BA%E6%B4%BB%E5%8A%9B)\n\n[](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL77FKJAJ0518QV0R.html#post_comment_area \"快速发贴\")[0](https:\u002F\u002Fcomment.tie.163.com\u002FL77FKJAJ0518QV0R.html \"点击查看跟贴\")\n\n分享至\n*   [](javascript:;)\n*   [](javascript:;)\n*   [](javascript:;)\n\n[](javascript:; \"关闭\")\n\n![Image 17: Scan me!](blob:http:\u002F\u002Flocalhost\u002F2704d6e5bb2bfd65815753d4668c3652)\n\n用微信扫码二维码\n\n分享至好友和朋友圈\n\n![Image 18](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2Fa34aec5ap00tlm3h0000ed200u0002ng00u0002n.png&thumbnail=660x2147483647&quality=80&type=jpg)\n\n![Image 19](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2Fb73fbb2fj00tlm3h00016d200u0007mg02jm00n8.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n![Image 20](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F45b911f6j00tlm3h2001jd200u0004wg00u0004w.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**产业发展**\n\n**事件1**\n\n**贵州修文**\n\n**❒ 农业农村部部署“十五五”果菜茶产业高质量发展工作**\n\n近日，农业农村部在贵州修文召开“十五五”果菜茶高质量发展推进会。会议指出，水果、蔬菜、茶叶是改善居民膳食结构的重要“菜篮子”产品。“十五五”期间，要认真落实《加快农业农村现代化“十五五”规划》要求，牢固树立和践行大食物观，突出优质安全导向，推动水果、蔬菜、茶叶供应均衡、品类丰富、质量安全，多元化供给与消费需求更加适配。\n\n来源：农业农村部\n\n**事件2**\n\n**❒ 国家卫健委呼吁：大家多喝白开水、淡茶水**\n\n9月14日，“开局起步‘十五五’”系列主题新闻发布会在北京举行。会议期间，介绍推动健康中国建设取得决定性进展有关情况。其中，国家卫健委发言人指出：“提倡大家要多喝白开水、多喝淡茶水，这实际上是既经济、又健康的。”\n\n来源：健康中国\n\n**事件3**\n\n![Image 21](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2Fd5364b7aj00tlm3h300bad200u000l5g00y000ny.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 3个茶叶示范区入选国家地理标志保护示范区创建对象名单**\n\n9月15日，国家知识产权局发布2026年国家地理标志保护示范区创建对象名单。其中，安吉白茶、日照绿茶、凤庆滇红茶等茶叶国家地理标志保护示范区入选。此举将推动各地茶产业在标准化保护、品牌价值提升、联农带农增收等方面迈上新台阶。\n\n来源：国家知识产权局\n\n**事件4**\n\n**❒ 2项茶相关“十四五”国家农作物育种联合攻关成果发布**\n\n9月11日，国家农作物育种联合攻关办公室发布“十四五”国家农作物育种联合攻关成果。其中，包含一项茶叶突破品种选育性成果：天然茉莉香型茶树新品种春闺，主攻特殊香型茶树品种选育难题；一项育种技术创新类成果：茶树液相育种芯片TEA5K，重点解决精准育种难题，定向培育优质茶，树新品种，育种周期可以缩短5年左右。\n\n来源：全国农技推广\n\n**事件5**\n\n**❒ 2026年秋冬茶树增产提质科学施肥指导意见发布**\n\n9月16日，农业农村部科学施肥专家指导组联合全国农技推广发布《2026年秋冬茶树增产提质科学施肥指导意见》，明确六大核心施肥原则，按茶类、产区、产量细分精准用肥方案，优化基肥追肥时序与农机配合操作，为全国茶区秋冬茶园管理提供标准化指引，助力茶农降本增效，筑牢来年春茶的产量与品质根基。\n\n来源：农业农村部科学施肥专家指导组\n\n**品牌活动**\n\n**事件6**\n\n**云南澜沧**\n\n**❒ “何以中国·千年茶道——世界遗产景迈山”网络主题宣传活动启动**\n\n9月13日，“何以中国·千年茶道——世界遗产景迈山”网络主题宣传活动在云南澜沧启动。启动仪式上，嘉宾围绕茶文化创新传播、茶产业高质量发展作主题分享。活动期间，“古道漫时光”参访活动、“茶藏古今·道通天下”2026年（第六届）景迈山论坛等系列活动陆续举行。此次活动，旨在讲好中国茶故事，推动景迈山文化保护传承与协同发展。\n\n来源：普洱发布\n\n**事件7**\n\n**浙江淳安**\n\n**❒ “坚持‘三茶’统筹 推动乡村共富”座谈会举行**\n\n9月18日，“坚持‘三茶’统筹 推动乡村共富”座谈会在浙江淳安举行。现场，参会嘉宾交流五年来“三茶”统筹发展实践成果，共议乡村共富。代表们认为应坚守初心、守正创新，推动“三茶 ”走深走实，为推进乡村全面振兴、实现共同富裕作出更大贡献。\n\n来源：潮新闻\n\n**事件8**\n\n**山东济南**\n\n**❒ “青联乡村四季行”暨闽鲁青年话“三茶”主题交流活动举办**\n\n9月13日，“青联乡村四季行”暨闽鲁青年话“三茶”主题交流活动在山东济南举办。本次活动是“茶香齐鲁·有福来兮-福建青年企业家山东行”的核心环节，活动现场，闽鲁两省嘉宾共叙山海情谊，共话青年合作，共谋“三茶”发展。活动现场还设置茶文化展示环节，通过茶艺展演、茶品品鉴等沉浸式体验，让参会嘉宾近距离感受闽茶的独特韵味。\n\n来源：福建省青年企业家协会\n\n**事件9**\n\n**云南昆明**\n\n**❒ 2026年云台中秋茶话会举办**\n\n9月16日，2026年云台中秋茶话会在云南昆明举办。此次茶话会分为观看专题片、嘉宾致辞、文化交流、中秋晚宴四个阶段。两岸嘉宾共同回顾云台青年交流交往成果，围绕传承中华优秀传统文化、深化云台交流合作、增进同胞血脉亲情等先后发言，表达了对两岸团圆、民族复兴的共同期盼。\n\n来源：今日台湾\n\n**事件10**\n\n**河南郑州**\n\n![Image 22](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2Ffa1a4713j00tlm3h5017jd200u000k0g00zk00np.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 政和白茶郑州招商推介活动举办**\n\n9月18日，政和白茶郑州招商推介活动在河南郑州举办。活动现场，开展政和白茶产业优势推介、河南市场招商政策发布等环节；活动期间，政和茶企走访国香茶城、胖东来茶叶超市等地，与相关企业负责人座谈交流，为政和白茶深耕中原市场、扩大品牌影响力筑牢基础，推动茶产业互利共赢与高质量发展。\n\n来源：中国茶叶流通协会\n\n**事件11**\n\n**福建福州**\n\n**❒ “质量赋能茉莉香·三茶融合链新篇”——2026年福州市仓山区“质量月”系列活动暨茉莉花茶产业链高质量发展讲堂举办**\n\n9月14日，“质量赋能茉莉香·三茶融合链新篇”——2026年福州市仓山区“质量月”系列活动暨茉莉花茶产业链高质量发展讲堂在福建福州举办。本次活动从文化传承、质量管控、市场拓展、科技创新等角度，为产业强链补链延链提供了有益思路，推动产业链供应链优化升级，促进茉莉花茶产业建圈强链。\n\n来源：福州市场监管\n\n**事件12**\n\n**福建福安**\n\n![Image 23](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F3bb6827cj00tlm3h600o2d200n700d9g00n700d9.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 2026年坦洋工夫品牌推介暨产销对接会举办**\n\n9月12日，2026年坦洋工夫品牌推介暨产销对接会在福建福安举办。活动现场，设置品牌推介、颁奖、重点合作项目签约等环节，汇聚沪闽茶界资源深化产销协作，助力百年坦洋工夫拓展上海及海外市场，推动福安茶产业高质量升级。\n\n来源：福安市茶产业发展中心\n\n**事件13**\n\n**安徽黄山**\n\n**❒ 2026年全国行业职业技能竞赛第八届全国茶业职业技能竞赛安徽分赛区茶叶加工（精制）项目开赛**\n\n9月12日，2026年全国行业职业技能竞赛第八届全国茶业职业技能竞赛安徽分赛区茶叶加工（精制）项目在安徽黄山开赛。赛事设置理论知识考核、实操技能比拼两大核心环节，考察选手制茶全流程技艺。以赛育才，挖掘培育优秀制茶技能人才，为徽茶产业提质升级筑牢人才根基。\n\n来源：屯溪融媒\n\n**事件14**\n\n**四川成都**\n\n**❒ 2026年成都市茶艺师技能竞赛举办**\n\n9月16日，2026年成都市茶艺师技能竞赛在四川成都举办。赛事设置理论测试、规定茶艺与茶席设计三大模块进行比拼。为进一步放大赛事效应，主办方特设全民品茗环节，邀请中外游客与市民走进赛场，近距离品鉴十五强选手的匠心之作。此次赛事依托成都深厚的市井文化底蕴，推动茶艺职业化进阶、拉动茶旅消费升级的重要实践。\n\n来源：封面新闻\n\n**事件15**\n\n**福建大田**\n\n**❒ 2026年大田县美人茶斗茶赛举办**\n\n9月12日，2026年大田县美人茶斗茶赛在福建大田举办。由大田县美人茶生产企业、合作社、家庭农场及茶农选送的82个茶样同台比拼，以标准化审评助推美人茶品质再升级。经初赛、复赛、决赛三轮角逐，最终评出特等奖1名、一等奖3名、二等奖21名。本次斗茶赛的举办进一步打通“赛茶-评茶-学茶-卖茶”链条，以赛促学、以赛提质。\n\n来源：大田融媒\n\n**事件16**\n\n**湖南长沙、云南昆明**\n\n**❒ 全国多地茶博会举办**\n\n近日，全国多地举办茶博会。9月11日-14日，2026第十八届湖南茶业博览会在湖南长沙举办。展区设置产销对接、茶养疗愈体验、国风茶文化互动等多元环节，全方位推动湘茶产业升级；9月18日-20日，2026云南茶博会暨新茶饮生活方式展在云南昆明举办。展会将茶产业展示与新茶饮潮流场景相结合，为茶企搭建对接交流平台，打通传统茶业与新茶饮消费场景的联结渠道，推动云南茶产业融合消费升级，为到场观众打造沉浸式的茶生活体验空间。\n\n来源：湖南茶博会、云南茶博会\n\n**事件17**\n\n**浙江杭州**\n\n![Image 24](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2Fd67989ebj00tlm3h7002ud200u000k0g01hc00zk.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 话剧《南方有嘉木》新闻发布会暨专家研讨会举办**\n\n9月16日，话剧《南方有嘉木》新闻发布会暨专家研讨会在浙江杭州举办。现场以雅集为概念打造沉浸式茶空间，设置品茶点茶环节，活动现场，嘉宾共同完成《南方有嘉木》项目启动仪式。该剧11月25日-26日将在杭州首演，助力江南茶文化与舞台艺术深度融合传播。\n\n来源：杭州文广旅游发布\n\n**事件18**\n\n**肯尼亚内罗毕**\n\n![Image 25](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F4a8df358j00tlm3h70039d200u000hgg00u000hg.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 第七届非洲茶叶大会举办**\n\n9月16-18日，第七届非洲茶叶大会在肯尼亚内罗毕举办。中国食品土畜进出口商会抹茶专业委员会应邀出席此次活动，并分享我国抹茶产业的实践经验。期间还与多国国际茶行业组织等交流，研讨全球茶产业最新发展情况、行业热点及消费趋势，进一步加强产业互通，深化全链条务实联动。\n\n来源：食土商会茶叶专业委员会\n\n**事件19**\n\n**福建漳州**\n\n![Image 26](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F2dda4440j00tlm3h8002xd200u000k0g00zk00np.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ “千年明月照古今·功夫茶里话中秋”品鉴交流活动举办**\n\n9月19日，“千年明月照古今·功夫茶里话中秋”品鉴交流活动在福建漳州举办。活动现场，闽粤两地茶界专家、非遗传承人共话中秋茶俗与功夫茶非遗传承。此次活动依托企业茶文化平台与制茶创新成果，探讨功夫茶破圈路径，助力闽粤台茶文化交流，推动区域茶产业协同高质量发展。\n\n来源：国晟义发\n\n**茶业股市**\n\n**事件20**\n\n![Image 27](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F569c4e31j00tlm3h80027d200u000qsg00u000qs.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**❒ 本周茶业股市播报**\n\n截至9月18日收盘，当前市值前5的茶相关股票，分别为农夫山泉（4341.14亿港元）、蜜雪集团（737.98亿港元）、康师傅控股（660.70亿港元）、古茗（535.14亿港元）、统一企业中国（551.75亿港元）。（ * 统计范围为传统茶、新茶饮企业股票，农夫山泉、康师傅控股、统一企业中国等以瓶装茶饮料业务为核心营收之一的企业，也涵盖其中）\n\n来源：百度股市通\n\n**本文内容由“说茶传媒”汇总整理，转载请注明来源**\n\n责编 \u002F 简竹筠\n\n编委 \u002F 王妙容\n\n![Image 28](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F9b5c46e9j00tlm3h80012d200u0009ag01fn00fy.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n![Image 29](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F9609881ap00tlm3h8001jd200u0003gg014n004n.png&thumbnail=660x2147483647&quality=80&type=jpg)\n\n**每日茶事：**2026年秋冬茶树增产提质科学施肥指导意见发布\n\n![Image 30](https:\u002F\u002Fnimg.ws.126.net\u002F?url=http%3A%2F%2Fdingyue.ws.126.net%2F2026%2F0919%2F19f4195fj00tlm3h9003nd200u00089g01hc00eo.jpg&thumbnail=660x2147483647&quality=80&type=jpg)\n\n特别声明：以上内容(如有图片或视频亦包括在内)为自媒体平台“网易号”用户上传并发布，本平台仅提供信息存储服务。\n\nNotice: The content above (including the pictures and videos if any) is uploaded and posted by a user of NetEase Hao, which is a social media platform and only provides 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310](https:\u002F\u002Fwww.163.com\u002Fdy\u002Farticle\u002FL76J84DR053469RG.html?f","说茶TV·网易","2026-09-14T02:00:00Z","政策",10,false,59,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},26,13,9,6,5,1,"部委层面“十五五”果菜茶产业部署，方向性政策信号明确，但正文实质条款与数据有限，时效略滞后。",[25],{"name":10,"url":6},[27,28,29,30,31],"十五五规划","高质量发展","大食物观","特色产业","果菜茶",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},"B","horticulture","园艺作物","\u002Ftopic\u002Fhorticulture",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"partial","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":47,"reason":79},[44,52,58,64,69,74],{"code":45,"score":46,"supported":47,"title":48,"abstract":49,"tags":51},"B1",3,true,[],[50],"蔬菜",[],{"code":53,"score":46,"supported":47,"title":54,"abstract":55,"tags":57},"B3",[],[56],"茶叶",[],{"code":59,"score":46,"supported":47,"title":60,"abstract":61,"tags":63},"J2",[],[62],"农业农村现代化",[],{"code":65,"score":22,"supported":14,"title":66,"abstract":67,"tags":68},"E2",[],[],[29],{"code":70,"score":22,"supported":14,"title":71,"abstract":72,"tags":73},"G4",[],[],[30],{"code":75,"score":22,"supported":14,"title":76,"abstract":77,"tags":78},"J1",[],[],[27],"一级领域明确，二级方向需要细分",[81,82],"农业农村部 十五五 果菜茶","果菜茶 高质量发展 推进会","农业农村部十五五果菜茶-2965","2026-09-20T00:02:59.385997Z",{"total":20,"page":22,"page_size":20,"items":86},[87,156,201,279,374,427],{"id":88,"title":89,"url":90,"summary":91,"summary_zh":8,"content":92,"source_name":93,"source_url":8,"published_at":94,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":95,"score_detail":96,"sources":102,"tags":104,"primary_topic":109,"secondary_topics":110,"classification":111,"search_phrases":151,"slug":154,"view_count":138,"doi":8,"paper":8,"created_at":155},1338,"池州市印发《人工智能产业发展行动方案(2026-2028)》：聚焦九华黄精、竹业、池州鳜鱼等\"人工智能+\"现代农业","https:\u002F\u002Fwww.chizhou.gov.cn\u002FOpennessContent\u002Fshow\u002F1752209.html","方案围绕九华黄精、竹业、池州鳜鱼、富硒、食用菌、茶叶等特色主导产业，以 AI 技术赋能农业全产业链，推动\"数字皖农\"从示范试点走向全域覆盖；以 AI 和数字技术赋能乡村治理和便民服务，缩小城乡\"数字鸿沟\"。","池政办〔2026〕14 号\n\n各 县、区人民政府，江南新兴产业集中区、九华山风景区、开发区、平天湖风景区管委会，市政府各部门、各直属机构：\n\n《池州市人工智能产业发展行动方案（2026-2028 年）》业经市政府 第 61 次 常务会议审议通过，现印发给你们，请认真贯彻落实。\n\n池州市人民政府办公室\n\n2026 年 8 月 20 日\n\n（此件公开发布）\n\n池州市人工智能产业发展行动方案（2026-2028 年）\n\n为贯彻落实 安徽省加快发展人工智能产业部署，推进全市人工智能 产业 高质量发展，力争 到 2028 年底，全市人工智能产业规模突破 135 亿元，拥有规模以上工业企业 80 家，培育产值 1 亿元以上企业 30 家，人工智能创新应用场景数量达到 180 个以上，特 制定本方案。\n\n一、实施底层能力强基行动\n\n**（一）****加强新型基础设施建设。**鼓励多路线、多模式建设一批城市算力基础设施，创新智能算力基础设施运营模式，鼓励发展标准化、可扩展的算力云服务。优化升级网络基础设施，合理规划千兆、万兆光网，有序推进 5G 网络向 5G-A 升级演进，前瞻布局 6G 网络。推动公共基础设施物联网感知建设，夯实 数智化发展底座。（责任单位：市数据资源局、市工业和信息化局、电信池州分公司、移动池州分公司、联通池州分公司）\n\n**（二）筑牢半导体产业发展根基。**锚定大尺寸晶圆制造、第三代半导体、先进封测、部件材料配套等细分领域，推进差异化发展，力争在人工智能芯片领域开辟特色发展新赛道。（责任单位：市发展改革委）\n\n**（三）加快行业垂类模型引育。**利用现有通用基础大模型，打造具有池州辨识度、行业竞争力的行业垂类模型。围绕先进制造、现代服务业、现代农业、政务服务等领域，依托重点企业应用场景，做精做强一批具有行业特色的专用模型。（责任单位：市科技局、市工业和信息化局、市发展改革委、市农业农村局、市数据资源局，有关市直部门）\n\n**（四）深化数据资源开发利用。**深化“数据要素×”行动，推进数据产权登 记。加快数据资产化进程，推动合规入账入表与市场化流通，拓宽数据产权登记凭证质押融资等应用场景，释放数据要素价值。培育数据标注产业，建设公共领域、重点行业高质量训练数据集。鼓励企业通过可信数据空间共享和使用产业链上下游企业数据，支持在商贸物流、医疗健康、现代农业等领域建设企业、行业可信数据空间。培育数据企业，提升数据产业整体竞争力。（责任单位：市数据资源局、市财政局、市发展改革委、市工业和信息化局、市市场监管局、市投控集团）\n\n二、实施应用赋能拓展行动\n\n**（五）强化人工智能场景创新应用。**重点在制造、商贸、物流、文化、交通、医疗、教育、农业、养老等领域谋划建设重大应用场景，鼓励创建省级人工智能应用典型案例、创新项目、优秀应用，形成一批标志性创新应用场景。（责任单位：市科技局、市发展改革委、市工业和信息化局、市数据资源局、市商务局，有关市直部门）\n\n**（六）“人工智能+”先进制造。**聚焦我市重点链主产业和未来产业，制定 AI 赋能“一业一方案”；聚焦高端化、智能化、绿色化三大方向，推动多模态大模型深度融入产业核心环节，促进 制造业转型升级；开展“AI+机器人”行动，推广智能质检、预测性维护、智能供应链、快速研发设计等技术；谋划布局具身智能、低空经济等产业，发挥我市轻量化材料、半导体、高端装备制造等多元场景应用优势。（责任单位：市发展改革委、市工业和信息化局）\n\n**（七）“人工智能+”现代农业。**围绕九华黄精、竹业、池州鳜鱼、富硒、食用菌、茶叶等特色主导产业，以 AI 技术赋能农业全产业链，推动“数字皖农”建设从示范试点走向全域覆盖，助力池州农业从“传统种养”向“智慧农业”转型。以 AI 和数字技术赋能乡村治理和便民服务，缩小城乡“数字鸿沟”，助力和美乡村建设。（责任单位：市农业农村局）\n\n**（八）“人工智能+”文旅康养。**统筹推进环九华山、主城区、沿秋浦河、环升金湖四大休闲度假康养片区 AI 赋能协同发展。将人工智能技术融入文旅康养产业，创设“AI+文旅”应用场景，创新培育数字沉浸体验、数智康养产品开发、低空经济融合新业态。加强人工智能在文旅管理中的应用，赋能 A 级旅游景区等场所的安全生产。（责任单位：市文化和旅游局）\n\n**（九）“人工智能+”教育教学。**探索人工智能与教育领域的融合创新，重点推进智能备课系统、智能教学平台、数字教师、AI 助教、自主学习系统建设。深入推进人工智能在教、学、管、研、评等方面的应用。实施教师人工智能素养提升专项计划，构建“线上与线下相融合”的培养体系。（责任单位：市教育和体育局）\n\n**（十）“人工智能+”医疗卫生。**深化“智联网医院”应用，依托医疗自然语言理解、医疗诊断治疗方案推荐等技术，提高诊疗效率、精度和服务能力。推进全市二级及以上公立医院电子病历和智慧医院建设，加强医院智慧服务与管理水平。推进 AI 医学影像辅助诊断在全市医疗机构的应用，提高诊断准确性和时效性。拓展智慧医疗应用场景，打造“智医助理”池州模式。（责任单位：市卫生健康委）\n\n**（十一）“人工智能+”城市治理。**迭代升级城市智能预警中枢，推动智能政务、应急处置、公共安全治理等方面的创新应用，打造新型智慧城市。建立跨部门协同的智能管理平台，聚焦城市级交通调度、线网优化等，打造一批典型应用场景；打造 12345 热线数据智能应用，探索构建“池州政务”智能体。推进人工智能在城市管理、应急处置等方面的应用，以 AI 技术推动“好房子、好小区、好社区、好城区”建设，全面提升城市功能品质活力和安全韧性水平。（责任单位：市数据资源局、市政府办公室、市公安局、市住房城乡建设局、市城市管理局、市应急管理局）\n\n**（十二）“人工智能+”其他。**加快 推进人工智能在 养老、司法、自然资源和规划、生态环境、林业、水利、人力资源和社会保障、市场监管、金融等领域应用。（责任单位：市民政局、市司法局、市自然资源和规划局、市生态环境局、市林业局、市水利局、市人力资源社会保障局、市市场监管局、人行池州市分行，有关市直部门）\n\n三、实施产业基础夯实行动\n\n**（十三）优化人工智能产业布局。**建立差异化特色化发展的人工智能创新格局。贵池区重点发展 AI 赋能新材料、智能制造、智慧农业、低空经济产业；东至县重点推进传统产业“智改数转网联绿色”智能化改造和产业链优化升级；石台县重点发展“AI+文旅”“AI+康养”等产业；青阳县重点发展轻量化材料、新能源电池在 AI 产品中的应用；江南新兴产业集中区重点发展 AI 在商业航天、具身智能中的应用；九华山风景区 围绕 打造世界级旅游景区和世界级文化胜地，重点发展 AI 文旅 新业态及示范场景打造；市经开区 布局 AI 芯片 产业；平天湖风景区重点发展数字文创等赛道。（责任单位：各县区人民政府、管委会）\n\n**（十四）育强人工智能企业。**建立人工智能企业培育机制，按“初创科技型企业-科技型中小企业-高新技术企业-专精特新企业-专精特新‘小巨人’企业-科技领军企业（上市培育企业）”梯次培育，壮大 人工智能 产业 创新主体。支持半导体、机器人、智能物流、智能政务等领域的人工智能企业，培育赋能行业解决方案供应商、数据服务商、人工智能服务商以及数据要素型企业。（责任单位：市科技局、市工业和信息化局）\n\n**（十五）大力招引人工智能企业。**完善人工智能产业链招商图谱 和人工智能场景清单，建立动态更新的强链、补链、延链企业库。聚焦细分赛道，采用以算引商、以数招商、定向招商、场景招商等方式，招引一批人工智能产业链关键环节、拥有自主核心技术的企业。（责任单位：市新质生产力促进服务中心）\n\n**（十六）完善创新平台体系。**坚持以平天湖科创湾为引领，打造 AI“研发+孵化+中试+产业化”全链条创新载体。围绕具身智能、半导体等前沿领域，完善省重点实验室、产业技术工程化中心、企业研发（技术）中心、科技成果转化概念验证中心、科技成果转化中试基地、制造业中试平台、科技型企业孵化器等全链条创新平台体系，加快科技成果从实验室走向产业化应用。推进与香港科技大学、上海交通大学、安徽工程大学 等高校院所的 产学研合作，围绕具身智能、先进材料、半导体领域共建产业创新平台。抢抓上海（长三角）国际科创中心扩围机遇，发挥池州（上海）科创中心平台作用，提升质效，招引人工智能领域项目和人才（团队）。（责任单位：市科技局、市新质生产力促进服务中心、市发展改革委、市工业和信息化局）\n\n四、实施发展生态构建行动\n\n**（十七）加大金融政策支持。**积极向上争取国家、省级专项资金支持，用好省人工智能池州子基金、天使基金，引导多元社会资本支持人工智能产业发展。统筹池州市新兴产业引导基金、本地科创基金等各类 基 金，加强对人工智能关键产业链项目的资金支持，精准服务企业发展需求。（责任单位：市科技局、市新质生产力促进服务中心、市投控集团）\n\n**（十八）强化高端人才供给。**通过实施重大科技项目、建设高能级科创平台等方式，吸引和汇聚一批国内外高水平创新团队。依托“万马奔池”计划，精准引进高层次人才团队。以人工智能技术应用为契机，创造更多 AI 训练师、AI 系统测试工程师、数据标注师等新职业岗位。鼓励企业与在池高校联合建设产业学院、研发中心、实训基地等，深度开展企业和高校人才交流互派。（责任单位：市委人才工作局、市人力资源社会保障局、市教育和体育局、市科技局）\n\n**（十九）提升全社会人工智能素养。**开展覆盖全学段、面向全社会的通识教育，承办省级以上人工智能展会、论坛等 各类活动，提升全民人工智能素养。强化人工智能教育培训，在党校主体班次开设人工智能课程，提升干部数字化素养与智能应用能力。开展数字化管理、智能化升级等新技能培训，培养一批人工智能专业技术人才。（责任单位：市科协、市教育和体育局、市科技局、市人力资源社会保障局、市委组织部、市委党校）\n\n**（二十）探索建立新型生产关系。**深化数据要素市场化配置改革，落实 完善公共数据授权运营和价格形成机制。探索城市“智能空间”复合开发模式，适应人工智能轻型生产、轻型研发等特征，探索建设智能产业综合体。围绕网络安全、数据安全、科技伦理等领域建立风险防控应对机制。加强人工智能产业市场监管和知识产权保护，营造公平、健康、有序的人工智能产业市场环境。（责任单位：市数据资源局、市发展改革委、市投控集团、市委网信办、市公安局、市科技局、市市场监管局）\n\n加强全市人工智能高质量发展工作统筹，由市科技局协调推进人工智能产业各项工作。各县区 政府、管委会 和 市 有关 部门要 立足行业和区域特点，强化政策支持和协同联动，推动各项任务落地落实。强化典型示范引领，注重总结工作中的好经验好做法，充分利用各类媒体加强宣传推广，营造加快“人工智能+”创新应用的浓厚氛围。\n\n如果内容不能正常显示：请安装pdf软件， 或下载本PDF文档 [[点击下载](https:\u002F\u002Fwww.chizhou.gov.cn\u002Fdownload?siteId=1&id=707664)]。","池州市人民政府 · 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人工智能+ 数字皖农 智慧农业","农业人工智能 人工智能+","农业人工智能人工智能+数字皖农智慧农业-1338","2026-09-02T00:05:03.287161Z",{"id":157,"title":158,"url":159,"summary":160,"summary_zh":8,"content":8,"source_name":161,"source_url":8,"published_at":162,"category":163,"cover_url":8,"hotness":13,"is_selected":14,"score":164,"score_detail":165,"sources":167,"tags":169,"primary_topic":174,"secondary_topics":175,"classification":176,"search_phrases":195,"slug":198,"view_count":199,"doi":8,"paper":8,"created_at":200},5352,"顺昌县委副书记县长周华健来福建农科院推进院县合作 聚焦柑橘食用菌竹业","https:\u002F\u002Fwww.faas.cn\u002Fcms\u002Fhtml\u002Ffjsnykxy\u002F2026-10-16\u002F1616650934.html","10 月 14 日,顺昌县委副书记、县长周华健一行来访福建农科院并开展座谈交流。院党委书记、院长余文权表示,省农科院将充分发挥人才、科研成果等方面优势,紧扣顺昌柑橘、食用菌、竹业等特色产业发展实际,聚焦品种改良、绿色栽培、产后加工、成果转化、人才培育等重点环节。双方一致表示将进一步夯实合作基础,强化科技赋能,携手推动院县合作取得更多实效。","福建省农业科学院 2026-10-14","2026-10-14T00:00:00Z","报道",48,{"impact":13,"substance":99,"depth":100,"authority":99,"freshness":20,"relevant":22,"comment":166},"县级政府与省级农科院对接的地方合作动态，有具体产业方向但无新政策或数据，属常规工作通稿，不宜进每日精选。",[168],{"name":161,"url":159},[122,170,171,172,173],"科技赋能","柑橘","院县合作","竹产业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":177},{"candidates":178,"agricultural_evidence":47,"reason":79},[179,184,188],{"code":180,"score":99,"supported":47,"title":181,"abstract":182,"tags":183},"B2",[171],[171],[171],{"code":119,"score":99,"supported":47,"title":185,"abstract":186,"tags":187},[122],[122],[122],{"code":189,"score":190,"supported":47,"title":191,"abstract":192,"tags":194},"G1",4,[],[193],"成果转化",[170],[196,197],"顺昌县 福建农科院 院县合作","顺昌 柑橘 食用菌 竹业","顺昌县福建农科院院县合作-5352",0,"2026-10-20T02:47:44.598431Z",{"id":202,"title":203,"url":204,"summary":205,"summary_zh":8,"content":8,"source_name":206,"source_url":8,"published_at":207,"category":208,"cover_url":8,"hotness":13,"is_selected":14,"score":209,"score_detail":210,"sources":214,"tags":216,"primary_topic":220,"secondary_topics":221,"classification":222,"search_phrases":265,"slug":268,"view_count":190,"doi":8,"paper":269,"created_at":278},4199,"A digital framework for smart greenhouse tomato cultivation（智能温室番茄种植的数字化框架）","https:\u002F\u002Fwh.nstl.gov.cn\u002Fpaper_detail.html?id=c531f437ff2bcc18494127a2b1b452ec","Guo Jianjun、Zhang Beibei、Zhou Piao、Xu Yudian、Luo Shangwen、Ji Jingyu、Zhuo Yuhan、Xu Xin、Lin Linjun（仲恺农业工程学院）。针对传统温室番茄栽培中管理滞后、信息化程度低、劳动力依赖度高的问题，构建了一套融合物联网（IoT）、大数据分析、人工智能（AI）和数字孪生技术的综合数字系统。该系统能实时采集并处理温室环境数据、作物生长数据，集成专家经验知识库，通过模型驱动决策优化灌溉、施肥、病虫害防控等关键生产环节，实现温室番茄种植的精细化管理和提质增效。","Smart Agricultural Technology 2026","2026-10-01T00:00:00Z","论文",77,{"impact":211,"substance":98,"depth":212,"authority":18,"freshness":19,"relevant":22,"comment":213},18,17,"核心期刊论文，融合IoT、AI与数字孪生的温室番茄数字化框架，方法新颖且具产业应用价值，值得入选每日精选。",[215],{"name":206,"url":204},[105,106,217,218,219],"数字孪生","智能温室","番茄种植",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":223},{"candidates":224,"agricultural_evidence":47,"reason":79},[225,231,238,245,249,255,261],{"code":45,"score":98,"supported":47,"title":226,"abstract":229,"tags":230},[227,228],"番茄","tomato",[227],[219],{"code":232,"score":98,"supported":47,"title":233,"abstract":236,"tags":237},"B7",[234,235],"温室","greenhouse",[234],[218],{"code":239,"score":20,"supported":47,"title":240,"abstract":241,"tags":244},"I5",[],[242,243],"物联网","IoT",[],{"code":147,"score":21,"supported":47,"title":246,"abstract":247,"tags":248},[],[217],[217,105],{"code":250,"score":46,"supported":47,"title":251,"abstract":252,"tags":254},"F3",[],[253],"施肥",[],{"code":256,"score":46,"supported":47,"title":257,"abstract":258,"tags":260},"H3",[],[259],"灌溉",[],{"code":137,"score":22,"supported":14,"title":262,"abstract":263,"tags":264},[],[],[106],[266,267],"仲恺农业工程学院 智能温室 番茄","数字孪生 温室 番茄种植","仲恺农业工程学院智能温室番茄-4199",{"doi":8,"openalex_id":8,"authors":270,"venue":8,"cited_by_count":199,"oa_url":8,"card":271,"direction":275,"ingested_from":277},[],{"tldr":272,"method":273,"finding":274,"direction":275,"opportunity":276},"构建融合IoT、大数据、AI与数字孪生的智能温室番茄种植数字化框架。","集成物联网实时采集环境与作物数据，结合专家知识库与AI模型驱动决策。","实现灌溉、施肥、病虫害防控的精细化管理，降低劳动力依赖并提质增效。","智慧农业 \u002F 农业物联网","可探索数字孪生模型与作物生长机理耦合的实时闭环调控及跨温室迁移验证。","agent","2026-10-05T00:04:56.224544Z",{"id":280,"title":281,"url":282,"summary":283,"summary_zh":284,"content":8,"source_name":285,"source_url":282,"published_at":286,"category":208,"cover_url":8,"hotness":13,"is_selected":14,"score":287,"score_detail":288,"sources":292,"tags":294,"primary_topic":299,"secondary_topics":300,"classification":301,"search_phrases":340,"slug":343,"view_count":46,"doi":344,"paper":345,"created_at":373},3350,"Precision agriculture for water saving: The case of processing tomato and table grape","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fppp3.70253","Societal Impact Statement Agriculture faces increasing pressure to produce high‐quality food while reducing water use under intensifying climate change and water scarcity. This study compared sensor‐based precision irrigation, drone monitoring, and near‐infrared spectroscopy with conventional farmer management in table grape and processing tomato production systems. Precision agriculture improved crop water status, photosynthetic performance, yield, and marketable quality, while reducing irrigation by 8%–15% in table grape and approximately 15% in processing tomato. These findings support wider adoption of integrated digital tools through targeted incentives and farmer training, offering a scalable strategy to strengthen long‐term water security, farm resilience, and sustainable food production globally. Summary The study aimed to evaluate the effectiveness of precision agriculture (PA) technologies, specifically sensor‐based irrigation and drones, on table grape (cv. Allison ) and processing tomato (cv. Taylor ) production compared to traditional farming methods (control). The research involved field experiments in two locations in the Puglia region, southeastern Italy, in 2023 and 2024. For table grape and processing tomato, two different irrigation managements (PA vs. Control\u002FFarmer) were compared, monitoring physiological, morphological, yield, and quality parameters. For processing tomato, drone imagery, and ground measurements were also conducted. Predictive models for fruit ripeness and quality traits of both species were also developed using near‐infrared (NIR) spectroscopy data, preprocessing techniques, and PLS regression. For table grape, the PA vines showed greater water potential stability, more uniform stomatal conductance, and higher chlorophyll content, resulting in higher and more consistent production with 8%–15% water savings. For processing tomato, PA management improved plant vegetative indicators, total and marketable yields, and reduced water consumption by approximately 15%. Three out of four calibrated models using NIR showed predictive performance suitable for future practical applications. The findings highlight the potential of PA to improve water resource utilization, crop development, yield, and fruit quality, contributing to more sustainable agricultural systems in regions facing water scarcity and climate change. Moreover, this work demonstrates how sensor‐driven irrigation of the two crops (with more equilibrated plants) directly influenced high‐accuracy predictive modelling. The integration of environmental sensors (for irrigation) and optical sensors (for quality) will represent the core of modern smart farming.","社会影响声明 在气候变化加剧和水资源短缺的背景下，农业面临着在生产高质量食品的同时减少用水量的日益增大的压力。本研究在鲜食葡萄和加工番茄生产系统中，将基于传感器的精准灌溉、无人机监测和近红外光谱技术与传统农户管理进行了比较。精准农业改善了作物水分状况、光合性能、产量和商品品质，同时在鲜食葡萄中减少了8%–15%的灌溉用水，在加工番茄中减少了约15%。这些发现支持通过有针对性的激励措施和农户培训来更广泛地采用集成数字工具，为增强全球长期水资源安全、农场韧性和可持续食品生产提供了一种可推广的策略。摘要 本研究旨在评估精准农业（PA）技术，特别是基于传感器的灌溉和无人机，在鲜食葡萄（品种Allison）和加工番茄（品种Taylor）生产中相较于传统耕作方法（对照）的有效性。研究于2023年和2024年在意大利东南部普利亚地区的两个地点进行了田间试验。对于鲜食葡萄和加工番茄，比较了两种不同的灌溉管理方式（PA vs. 对照\u002F农户），监测了生理、形态、产量和品质参数。对于加工番茄，还进行了无人机影像采集和地面测量。研究还利用近红外（NIR）光谱数据、预处理技术和PLS回归，开发了两种作物果实成熟度和品质性状的预测模型。对于鲜食葡萄，PA处理的葡萄藤表现出更强的水势稳定性、更均匀的气孔导度和更高的叶绿素含量，从而实现了更高且更稳定的产量，并节约了8%–15%的用水。对于加工番茄，PA管理改善了植株营养指标、总产量和商品产量，并减少了约15%的耗水量。使用NIR校准的四个模型中有三个显示出适合未来实际应用的预测性能。研究结果凸显了PA在改善水资源利用、作物发育、产量和果实品质方面的潜力，有助于在水资源短缺和气候变化地区构建更可持续的农业系统。此外，本研究还表明，两种作物的传感器驱动灌溉（使植株更加均衡）……","Plants People Planet","2026-09-23T00:00:00Z",81,{"impact":211,"substance":289,"depth":211,"authority":290,"freshness":19,"relevant":22,"comment":291},22,14,"意大利田间试验证实传感器与无人机精准灌溉可节水8%–15%并提升产量品质，对缺水地区智慧农业推广有实证参考价值。",[293],{"name":285,"url":282},[105,295,296,297,298],"农业遥感","精准灌溉","节水农业","近红外光谱",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":302},{"candidates":303,"agricultural_evidence":47,"reason":79},[304,310,314,320,328,335],{"code":147,"score":97,"supported":47,"title":305,"abstract":307,"tags":309},[306],"precision agriculture",[308,306],"精准农业",[105],{"code":45,"score":290,"supported":47,"title":311,"abstract":312,"tags":313},[228],[227,228],[],{"code":180,"score":290,"supported":47,"title":315,"abstract":317,"tags":319},[316],"grape",[318,316],"葡萄",[],{"code":256,"score":321,"supported":47,"title":322,"abstract":323,"tags":327},11,[],[259,324,325,326],"水资源","irrigation","water resource",[296,297],{"code":329,"score":20,"supported":47,"title":330,"abstract":331,"tags":334},"H7",[],[332,333],"气候变化","climate change",[],{"code":336,"score":22,"supported":14,"title":337,"abstract":338,"tags":339},"I3",[],[],[295],[341,342],"加工番茄 精准灌溉 节水","鲜食葡萄 无人机 灌溉","加工番茄精准灌溉节水-3350","10.1002\u002Fppp3.70253",{"doi":344,"openalex_id":346,"authors":347,"venue":285,"cited_by_count":199,"oa_url":282,"card":367,"direction":275,"ingested_from":372},"W7214079746",[348,351,354,356,358,361,364],{"name":349,"orcid":350},"Giuseppe Ferrara","https:\u002F\u002Forcid.org\u002F0000-0002-2129-6723",{"name":352,"orcid":353},"Alessandro Pesole","https:\u002F\u002Forcid.org\u002F0009-0007-1292-4517",{"name":355,"orcid":8},"Rita De Marco",{"name":357,"orcid":8},"Sara Bisceglie",{"name":359,"orcid":360},"Giovanni Popeo","https:\u002F\u002Forcid.org\u002F0009-0003-6796-3880",{"name":362,"orcid":363},"Simone Pascuzzi","https:\u002F\u002Forcid.org\u002F0000-0002-6699-3485",{"name":365,"orcid":366},"Luigi Tedone","https:\u002F\u002Forcid.org\u002F0000-0003-4398-3820",{"tldr":368,"method":369,"finding":370,"direction":275,"opportunity":371},"对比传感器精准灌溉、无人机与近红外光谱和传统管理在葡萄与番茄上的节水增产效果。","意大利普利亚两年田间试验，传感器灌溉、无人机监测与NIR光谱PLS建模。","精准农业改善水分与光合状态，葡萄节水8%–15%、番茄约15%，并提高产量与品质。","可探索多源传感与NIR模型跨品种跨区域迁移，并量化农户采纳激励与培训的长期节水效益。","openalex","2026-09-24T23:30:10.070697Z",{"id":375,"title":376,"url":377,"summary":378,"summary_zh":8,"content":8,"source_name":379,"source_url":8,"published_at":380,"category":208,"cover_url":8,"hotness":13,"is_selected":14,"score":209,"score_detail":381,"sources":383,"tags":385,"primary_topic":389,"secondary_topics":390,"classification":391,"search_phrases":415,"slug":418,"view_count":46,"doi":8,"paper":419,"created_at":426},3247,"From Phenotyping to Supervised Agentic Decision Support: A Review of Sensing and Artificial Intelligence for Greenhouse Strawberry Cultivation（从表型到监督智能体决策支持：温室草莓栽培的传感与人工智能综述）","https:\u002F\u002Fm2.mtmt.hu\u002Fapi\u002Fpublication\u002F37426142","MDPI Horticulturae 12(7) 765 发表综述：温室草莓栽培越来越依赖传感技术、人工智能和决策支持基础设施，但其在园艺上的价值取决于异构测量能否转化为生物学上有意义的作物状态和实际管理决策。本综述综合草莓表型、多模态传感、AI作物状态解释和监督智能体协调，提出表型到行动的温室草莓栽培框架。综述研究表明，通过成像、光谱、环境、根区和建模方法在测量和解释营养、生殖、果实品质、压力和环境作物状态方面取得实质性进展。然而，大部分文献仍强调测量精度、模型性能或基础设施能力，而较少研究验证AI输出是否改善作物响应、管理决策、工作流、资源使用或生产结果。综述区分数据采集传感技术与AI解释预测方法，并研究作物状态信息如何与实际温室决策相连接。","MDPI Horticulturae","2026-09-21T00:00:00Z",{"impact":211,"substance":98,"depth":212,"authority":18,"freshness":19,"relevant":22,"comment":382},"系统梳理温室草莓从表型感知到智能体决策支持的研究进展，指出AI输出缺乏生产结果验证这一关键缺口，对智慧园艺研究有参考价值。",[384],{"name":379,"url":377},[105,106,386,387,388],"决策支持","温室草莓","多模态传感",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":392},{"candidates":393,"agricultural_evidence":47,"reason":79},[394,401,405,411],{"code":45,"score":395,"supported":47,"title":396,"abstract":399,"tags":400},19,[397,398],"草莓","strawberry",[397],[],{"code":232,"score":395,"supported":47,"title":402,"abstract":403,"tags":404},[234,235],[234],[],{"code":137,"score":211,"supported":47,"title":406,"abstract":409,"tags":410},[407,408],"artificial intelligence","decision support",[],[106,386],{"code":147,"score":22,"supported":14,"title":412,"abstract":413,"tags":414},[],[],[105],[416,417],"温室草莓 人工智能 决策支持","草莓表型 多模态传感","温室草莓人工智能决策支持-3247",{"doi":8,"openalex_id":8,"authors":420,"venue":8,"cited_by_count":199,"oa_url":8,"card":421,"direction":275,"ingested_from":277},[],{"tldr":422,"method":423,"finding":424,"direction":275,"opportunity":425},"综述温室草莓从表型感知到监督智能体决策支持的传感与AI技术，提出表型到行动框架。","综合草莓表型、多模态传感、AI状态解释与监督智能体协调的文献综述。","感知与AI解释进展显著，但少有研究验证AI输出是否真正改善作物响应与管理决策。","可研究AI决策输出对温室草莓实际管理、资源利用与产量结果的闭环验证与效果评估。","2026-09-23T00:04:33.259764Z",{"id":428,"title":429,"url":430,"summary":431,"summary_zh":8,"content":8,"source_name":432,"source_url":8,"published_at":433,"category":208,"cover_url":8,"hotness":13,"is_selected":14,"score":287,"score_detail":434,"sources":436,"tags":438,"primary_topic":442,"secondary_topics":443,"classification":444,"search_phrases":472,"slug":475,"view_count":20,"doi":476,"paper":477,"created_at":484},2852,"面向边缘部署的温室串番茄采摘机器人:YOLOv8n-BiFPN-WIoU+ROS分布式控制——Frontiers in Plant Science","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fplant-science\u002Farticles\u002F10.3389\u002Ffpls.2026.1926482\u002Ffull","论文提出了一种可在边缘部署的温室串番茄采摘机器人,集成YOLOv8n-BiFPN-WIoU视觉检测模型与基于ROS的分布式控制架构。BiFPN加权特征融合结构增强了跨尺度特征表示,WIoU改进了部分遮挡和重叠目标的定位稳健性。在独立测试集上,该模型Precision达88.534%、Recall 89.377%、F1 88.954%、mAP@0.5为92.338%、mAP@0.5:0.95为71.368%,相比基线YOLOv8n分别提升2.143、2.779、2.460、4.587和5.675个百分点。视觉检测器与ROS机器人系统集成,协调目标感知、轨道站点间运动和机械臂操作。","Frontiers in Plant Science","2026-09-14T00:00:00Z",{"impact":211,"substance":289,"depth":211,"authority":290,"freshness":19,"relevant":22,"comment":435},"方法改进与实测指标扎实、面向边缘部署的温室串番茄采摘机器人研究，对智慧农业具参考价值，但属细分技术进展，未达产业级突破。",[437],{"name":432,"url":430},[105,106,439,440,441],"边缘计算","串番茄","采摘机器人",{"code":33,"slug":34,"name":35,"path":36,"parent_code":8},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":445},{"candidates":446,"agricultural_evidence":47,"reason":79},[447,452,456,460,464,468],{"code":448,"score":99,"supported":47,"title":449,"abstract":450,"tags":451},"F6",[441],[441],[441],{"code":45,"score":321,"supported":47,"title":453,"abstract":454,"tags":455},[227],[227],[],{"code":232,"score":321,"supported":47,"title":457,"abstract":458,"tags":459},[234],[234],[],{"code":147,"score":22,"supported":14,"title":461,"abstract":462,"tags":463},[],[],[105],{"code":137,"score":22,"supported":14,"title":465,"abstract":466,"tags":467},[],[],[106],{"code":239,"score":22,"supported":14,"title":469,"abstract":470,"tags":471},[],[],[439],[473,474],"农业人工智能 采摘机器人 智慧农业 边缘计算","农业人工智能 采摘机器人","农业人工智能采摘机器人智慧农业边缘计算-2852","10.3389\u002Ffpls.2026.1926482\u002Ffull",{"doi":476,"openalex_id":8,"authors":478,"venue":8,"cited_by_count":199,"oa_url":8,"card":479,"direction":275,"ingested_from":277},[],{"tldr":480,"method":481,"finding":482,"direction":275,"opportunity":483},"提出边缘部署的温室串番茄采摘机器人，融合改进YOLOv8n检测与ROS分布式控制。","YOLOv8n结合BiFPN加权特征融合与WIoU损失，集成ROS分布式控制架构","模型mAP@0.5达92.338%，较基线YOLOv8n提升4.587个百分点，可完成采摘。","可探索轻量化模型在更多边缘设备上的泛化部署，及多机器人协同采摘调度优化。","2026-09-18T00:03:30.570025Z"]