[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2156":3,"related-2156":106},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":81,"slug":84,"view_count":85,"doi":86,"paper":87,"created_at":105},2156,"“十五五”视野下三峡柑橘文化与产业的协同发展","https:\u002F\u002Fdoi.org\u002F10.54254\u002F3049-7825\u002F2026.36653","三峡地区是中国柑橘核心原产区与柑橘文化重要发祥地，兼具独特文化资源与领先产业基础，形成文化与产业双重优势。本文以三峡宜昌全域为研究样本，系统梳理当地柑橘文化资源与产业发展基底，分析秭归等地在文化符号品牌化嵌入、文化空间实体化嵌入、文化活动仪式化嵌入，以及脐橙产业全链开发、农文旅联动拓展等方面的实践经验，揭示文化嵌入与产业共生相互赋能的协同机制。在此基础上，对接《加快农业农村现代化“十五五”规划》关于科技农业、绿色农业、质量农业、品牌农业的战略部署，提出三峡柑橘产业在种业振兴与智慧农业升级、精深加工全价值利用、农文旅深度融合、区域公用品牌矩阵构建四个方向的发展路径，以期为宜昌及长江流域同类库区特色果业的文化赋能转型提供参考。",null,"Ren wen she hui fa zhan.","2026-09-10T00:00:00Z","论文",10,false,65,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},16,18,17,6,8,1,"以宜昌全域为样本系统梳理柑橘文化嵌入与产业共生机制，并对接“十五五”规划提出四条发展路径，兼具案例深度与政策参考价值，但来源权威性一般。",[24],{"name":9,"url":6},[26,27,28,29,30,31],"智慧农业","十五五规划","种业振兴","区域公用品牌","农文旅融合","三峡柑橘",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"B2","fruit","果树","\u002Ftopic\u002Fhorticulture\u002Ffruit","B",[],{"status":40,"locked":13,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,59,64,71,76],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},11,true,[49],"柑橘",[49],[],{"code":53,"score":54,"supported":47,"title":55,"abstract":56,"tags":58},"F1",4,[],[57],"种业",[28],{"code":60,"score":54,"supported":47,"title":61,"abstract":62,"tags":63},"I1",[],[26],[26],{"code":65,"score":66,"supported":47,"title":67,"abstract":68,"tags":70},"J2",3,[],[69],"农业农村现代化",[],{"code":72,"score":21,"supported":13,"title":73,"abstract":74,"tags":75},"E5",[],[],[29],{"code":77,"score":21,"supported":13,"title":78,"abstract":79,"tags":80},"J1",[],[],[27],[82,83],"区域公用品牌 农文旅融合 十五五规划 三峡柑橘","区域公用品牌 农文旅融合","区域公用品牌农文旅融合十五五规划三峡柑橘-2156",2,"10.54254\u002F3049-7825\u002F2026.36653",{"doi":86,"openalex_id":88,"authors":89,"venue":9,"cited_by_count":96,"oa_url":8,"card":97,"direction":103,"ingested_from":104},"W7212108476",[90,92,94],{"name":91,"orcid":8},"鸿宇 李",{"name":93,"orcid":8},"远来 陈",{"name":95,"orcid":8},"夏 张",0,{"tldr":98,"method":99,"finding":100,"direction":101,"opportunity":102},"以三峡宜昌为样本，梳理柑橘文化与产业协同机制并提出四条发展路径。","案例研究，分析秭归文化嵌入与脐橙全链开发经验。","文化嵌入与产业共生相互赋能，形成文化与产业双重优势。","数字乡村与农业信息化","可探究智慧农业升级中文化品牌数字化与农文旅数据融合的协同机制。","智慧农业 \u002F 农业物联网","openalex","2026-09-11T23:30:20.544739Z",{"total":19,"page":21,"page_size":19,"items":107},[108,187,237,287,325,397],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":8,"content":113,"source_name":114,"source_url":8,"published_at":115,"category":116,"cover_url":8,"hotness":12,"is_selected":13,"score":117,"score_detail":118,"sources":123,"tags":125,"primary_topic":130,"secondary_topics":131,"classification":132,"search_phrases":181,"slug":184,"view_count":185,"doi":8,"paper":8,"created_at":186},3406,"广东新技术在乡村找'跑道'——'铁柱2号'冬瓜占广东同类品种40%以上，荔枝AI诊断准确率达95%以上","https:\u002F\u002Fepaper.nfnews.com\u002Fnfdaily\u002Fhtml\u002F202609\u002F22\u002Fcontent_10182068.html","南方日报深度报道：广东省农科院蔬菜所'铁柱2号'冬瓜开创'铁心'冬瓜新类型，累计推广面积约300万亩、占广东同类品种40%以上；茂名荔枝产业大数据平台完成DeepSeek本地化部署，病虫害诊断准确率提升至95%以上、平均诊断时间从数小时缩短至5秒以内；河源东源县柳城镇下坝村万绿智慧无人农场由中国工程院院士罗锡文团队指导打造1500亩无人化核心区，亩产提升至500公斤以上；全省植保无人机保有量约9000架，日作业能力约440万亩。","一粒种子，如何从实验室走向万亩良田？\n\n一片深海，如何将传统渔排升级为“数智牧场”？\n\n近日，以“创业兴村·向新而行”为主题的“农行杯”广东省第五届农村创业大赛总决赛在广州举行。经过现场路演和答辩，“AI超级蛋白工厂——医用蛋白‘宁德时代’”“合成生物技术赋能红景天富民工程”分别获得乡村新产业、农产品加工赛道一等奖，将代表广东参加2026年全国农村创业大赛。\n\n“感觉我们不是农业大赛，像科技大赛。”广东省第五届农村创业大赛总决赛专家评委组长曾准在点评中表示，本届比赛更加突出科技引领。人工智能、合成生物、智慧农业、种业创新……从获奖项目中可以窥见，新技术、新业态正深度融入农业生产和乡村产业发展之中。\n\n这场农村创业大赛，也是广东农业转型的缩影。透过赛场内外，可以清晰看到一条从科技创新到成果转化，再到农业新质生产力培育的完整路径。在广东推进“百县千镇万村高质量发展工程”的过程中，农业科技创新与产业创新实现深度融合，科技“关键变量”正在持续转化为乡村振兴的“最大增量”。\n\n“十五五”规划纲要明确提出，加快农业农村现代化，扎实推进乡村全面振兴，统筹发展科技农业、绿色农业、质量农业、品牌农业。科技创新是驱动乡村全面振兴的重要引擎，要加快科技成果高效转化，将科技创新关键变量转化为乡村全面振兴的最大增量，为实现共同富裕筑牢坚实根基。\n\n●南方日报记者 王悦阳\n\n大湾区的合成生物技术\n\n种到了高原\n\n禾虫是一种生长在沿海滩涂和咸淡水交汇稻田中的环节动物，在粤菜菜系中被视为滋补佳品，但传统养殖长期依赖自然条件，规模小、产量不稳定。乡村新产业赛道一等奖项目“AI超级蛋白工厂——医用蛋白‘宁德时代’”，通过育种创新、立体养殖设施和AI养殖系统，推动传统禾虫养殖向智能化、规模化发展，并进一步开发其蛋白价值。\n\n农产品加工赛道一等奖项目“合成生物技术赋能红景天富民工程”，则将合成生物技术应用于红景天育苗、种植和加工全链条。“我们把大湾区的合成生物创新技术种到了高原。”项目负责人陈绍强介绍，目前团队已在云南发展千亩以上种植基地，并通过提供种苗、技术和保底收购等方式与当地农户合作。\n\n人工智能也在重构农产品流通环节。获得乡村新产业赛道二等奖的“羊羊鲜供·粤港澳大湾区AI数智供应链创新平台”，将大模型应用于生鲜供应链。项目负责人刘洋2024年到清远连州创业，一年多跑了5万多公里，走访田间和市场，希望通过供应链改造减少流通损耗、提高效率，“让种菜的人赚到钱，让买菜的人安心买好菜”。\n\n传统特色产业同样在谋新求变。龙川县“车田山水豆腐”项目通过设备和加工工艺改造推动标准化生产，香云纱、沉香、水产加工等项目也通过技术、产品和经营模式创新拓展产业发展空间。\n\n广东省农村创业大赛自2021年创办以来已举办5届，累计吸引600余个项目参赛，孵化培育240多个优秀农村创业典型项目，持续发挥“以赛促学、以赛促创、以赛促融”作用。从赛场竞技到资源对接，从发现项目到培育人才，大赛已成为展示乡村产业创新成果、汇聚农村创业资源的重要平台。\n\n然而，正如曾准所言，技术最终要转化为产品和产业竞争力。科技成果转化是连接科技创新与农业农村现代化的关键桥梁，打通从技术突破到产业应用的“最后一公里”。\n\n那么，这些技术在广东大地上找到了怎样的“跑道”？\n\n智慧无人农场\n\n亩产提升至500公斤以上\n\n在广东，一批批农业新品种、新技术、新装备正在加速进入生产一线，直接推动生产、加工、流通、服务等环节的效率跃升。实验室中、创业大赛上涌现的科技“变量”，正在真实的产业场景中接受检验、完成转化。\n\n种业是农业的“芯片”。在广东，育种创新正在从实验室走向田间地头，游向深远海。\n\n广东海水鱼类苗种产量连续多年稳居全国首位，占全国超50%的比重。在潮州饶平，万佳水产与中山大学合作开展海鮸鱼全雄育种，通过分子标记辅助育种技术，将经济价值更高的雄性海鮸鱼比例大幅提升。“2023年以前，饶平的种苗长期依赖外地。”万佳水产董事长郑镇雄说，目前万佳水产已成功培育出海鮸鱼苗，年产苗约3000万尾，种苗实现本地化供应。\n\n在蔬菜领域，广东省农业科学院蔬菜研究所研究员谢大森和团队培育的“铁柱2号”冬瓜开创“铁心”冬瓜新类型，解决了黑皮冬瓜运输损耗高、发芽率低的产业痛点，累计推广面积约300万亩，占广东同类品种40%以上，是我国当前推广面积最大的黑皮冬瓜品种。一个品种的突破，带动的是整个冬瓜产业的标准化和商品化水平提升。\n\n新品种解决的是“种什么”，新技术解决的则是“怎么种”。在广东，新技术在广东农业中的应用正在从“单点试用”走向“系统嵌入”。\n\n在茂名，荔枝产业大数据平台完成人工智能大模型DeepSeek本地化部署，病虫害诊断从人工经验判断转向AI秒级分析，准确率提升至95%以上，生产效率提升30%，平均诊断时间从数小时缩短至5秒以内。在河源东源县柳城镇下坝村的万绿智慧无人农场，由中国工程院院士罗锡文团队指导打造的1500亩无人化核心区，配备无人驾驶旋耕机、插秧机、收割机等智能农机，已全面实现“耕、种、管、收”全流程云端远程操控，亩产提升至500公斤以上。\n\n广东多丘陵山地，六成以上耕地散落在山岭之间，大型农机进不去，传统人工耕作又苦又累。新装备的突破，正在改写这一困局。\n\n在茂名高州分界镇，果农谭锦威的荔枝园已扩至上千亩。他购入两架农业无人机后，600多亩果园中400亩需要深度作业的都靠无人机完成，谭锦威感叹：“两天就能打完一轮药，没有无人机，根本不敢种这么多。”在潮州凤凰山海拔近千米的高山茶园，23岁的“茶二代”韦镇辉组建了一支十几人的“00后”飞手团队，用农业无人机参与植保、飞防、施肥、吊送，服务凤凰镇及周边200多户茶农，累计覆盖茶园达5万亩。\n\n据广东省农业农村厅数据，全省植保无人机保有量约9000架，日作业能力约440万亩，登记在册的病虫害专业化防治服务组织1755个，从业人员约1.8万人。\n\n在海洋领域，新装备的迭代速度同样令人瞩目。近年来，湛江相继建成投入养殖的“海威”系列、“恒燚1号”等多个大型养殖平台，全省占比38%的养殖重器矩阵在此破浪——从半潜式到桁架式，从固定式到自航式，多品类多型号的“湛江造”重器持续领跑广东深远海装备发展。\n\n广东发挥雄厚的船舶与海工装备制造基础优势，推动“格盛1号”“伏羲一号”“湛江湾一号”等一批大型智能化养殖平台相继投产，相关技术和产品辐射主要沿海省份。截至8月2日，2026年全省已新建重力式网箱920个、桁架类网箱5个。\n\n从一粒种子到一片深海，从手机里的AI助手到高山上的无人机，新品种、新技术、新装备在广东的真实场景中释放出实实在在的产业价值。\n\n但一个更深层的问题随之浮现：这些技术场景为什么能在广东率先“跑通”？答案指向制度设计和政策推力。\n\n政策为技术落地“架桥铺路”\n\n农村科技特派员制度是广东打通技术落地“最后一公里”的关键一招。\n\n9月，潮州市饶平县东山镇的万亩茶园迎来秋茶采摘。驻东山镇科技特派员、华南农业大学张凌云教授团队穿梭于茶园、车间，指导茶农采茶做茶。“作为广东科技特派员，我长期扎根东山镇，把实验室的研究成果真正应用到茶叶生产过程中，帮助农户提高种茶制茶的技艺。”张凌云介绍，针对低档茶原料经济效益不高、所制茶类单一等问题，团队创新性地将单丛乌龙茶工艺改良为全发酵单丛红茶工艺，为低档茶原料开辟了新销路。\n\n从种业到技术再到装备，广东的政策体系正在系统性地为技术落地“架桥铺路”。\n\n广东省委农村工作会议明确提出，因地制宜、抓紧抓实“粤强种芯”“粤强农装”“粤强智农”工程，不断提升农业科技创新效能，大力发展农业新质生产力。在种业领域，全省系统收集保存农业种质资源36.8万份，位居全国前列；“拎包入住”式的现代化海洋牧场种业创新中心吸引全国63个顶尖科研团队入驻，针对41个适养品种开展联合攻关。在装备领域，广东陆续出台一系列政策推动低空经济高质量发展，支持农业无人机广泛应用于农林植保等综合场景应用。\n\n金融“活水”则为技术装备从实验室走向产业提供了关键支撑。\n\n近年来，广东印发了《广东省现代化海洋牧场设施设备险实施方案》，将设施设备纳入政策性保险范围，各级财政补贴保费75%，养殖主体保费自担25%，降低养殖主体生产风险。现代化海洋牧场养殖险养殖主体自担比例从40%降低至20%，减轻养殖主体负担。\n\n与此同时，农村创业大赛本身也是一种推动科技成果及时转化的制度设计。\n\n总决赛当天，中国农业银行广东省分行为参赛项目进行重点客户授信；仲恺农业工程学院科研团队与广东车田山水豆腐食品科技有限公司、广东马岭观花生态园有限公司等签订科技项目结对协议，围绕技术攻关、产品研发开展合作。从赛场竞技到资源对接，从发现项目到培育人才，“以赛促创”逐渐成为“百千万工程”助推广东农业加速变革的重要抓手。\n\n站在“十五五”开局之年新起点上，广东以“百千万工程”为总指引，以机制创新推动技术落地，以场景应用驱动新一轮的科技创新和成果转化，扎实推动乡村产业全面振兴，加快书写农业农村现代化的时代答卷。","南方日报 2026-09-22","2026-09-22T00:00:00Z","报道",76,{"impact":119,"substance":120,"depth":18,"authority":12,"freshness":121,"relevant":21,"comment":122},22,20,7,"以广东农村创业大赛为切口，系统呈现种业、AI诊断、无人农场、深远海装备与政策金融配套，数据与案例扎实，具省级产业参考价值。",[124],{"name":114,"url":111},[26,126,28,127,128,129],"农业人工智能","科技特派员","植保无人机","深远海养殖",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":133},{"candidates":134,"agricultural_evidence":47},[135,140,146,152,158,163,167,172,176],{"code":33,"score":46,"supported":47,"title":136,"abstract":138,"tags":139},[137],"荔枝",[137],[],{"code":141,"score":54,"supported":47,"title":142,"abstract":143,"tags":145},"F4",[],[144],"植保",[128],{"code":147,"score":66,"supported":47,"title":148,"abstract":149,"tags":151},"B1",[],[150],"蔬菜",[],{"code":153,"score":66,"supported":47,"title":154,"abstract":155,"tags":157},"F6",[],[156],"无人农场",[],{"code":159,"score":21,"supported":13,"title":160,"abstract":161,"tags":162},"D2",[],[],[129],{"code":53,"score":21,"supported":13,"title":164,"abstract":165,"tags":166},[],[],[28],{"code":168,"score":21,"supported":13,"title":169,"abstract":170,"tags":171},"G1",[],[],[127],{"code":60,"score":21,"supported":13,"title":173,"abstract":174,"tags":175},[],[],[26],{"code":177,"score":21,"supported":13,"title":178,"abstract":179,"tags":180},"I2",[],[],[126],[182,183],"铁柱2号 冬瓜 广东","荔枝AI 病虫害诊断 茂名","铁柱2号冬瓜广东-3406",5,"2026-09-25T00:09:30.408382Z",{"id":188,"title":189,"url":190,"summary":191,"summary_zh":8,"content":192,"source_name":193,"source_url":8,"published_at":194,"category":116,"cover_url":8,"hotness":12,"is_selected":13,"score":195,"score_detail":196,"sources":200,"tags":202,"primary_topic":205,"secondary_topics":206,"classification":207,"search_phrases":232,"slug":235,"view_count":121,"doi":8,"paper":8,"created_at":236},3387,"从会种粮到'慧'种粮——中联重科岳麓智慧农场、常州艾宝机器人、温氏华系种猪、牧原智能猪舍AI兽医集体亮相","https:\u002F\u002Fnews.cyol.com\u002Fgb\u002Fkeji\u002Farticles\u002F2026-09\u002F23\u002Fcontent_v6vKznCP2x.html","中联重科岳麓智慧农场'天空地人机'协同智慧作业模式搭载多光谱相机巡田无人机最高飞120米、20分钟完成整片地块巡检，长势图精度达3米×3米网格；常州艾宝机器人四臂采摘猕猴桃机器人经第三方检测适合山坡丘陵地形，一台机器能节约7至8个人工；温氏股份、德康农牧'华系种猪育种技术与核心种源创制及应用'项目获国家科学技术进步奖一等奖；牧原股份智能化猪舍AI兽医全天候值守。","◎记者 刘立 王乔琪\n\n又是一年丰收季。田野之间，沉甸甸的果实背后，农业生产逻辑正在发生深刻变化。\n\n今年5月，国务院印发的《加快农业农村现代化“十五五”规划》明确提出：“推进人工智能运用和智慧农业发展。加快农业人工智能技术创新、应用场景拓展和产业生态营造。”\n\n近期，上海证券报记者在对部分农业种养殖龙头企业和农业展会的调研中发现，从种子实验室到果园大田，智能化工具正在把农业从经验驱动推向数据驱动。AI不再只是实验室概念，它正从育种、田间种植延伸到畜牧水产全链条，改写着传统农业依靠经验、看天吃饭的旧模式。\n\n**以AI打磨农业“芯片”**\n\n种业被称作农业的“芯片”。记者在采访中发现，快速发展的AI技术，正在缩短育种探索的漫长周期。\n\n在近日举办的全国种子双交会上，中种集团展台上一台ELISA蛋白全自动分析检测工作站设备吸引不少参会者驻足。据工作人员介绍，传统育种蛋白检测多采用人工、半自动化操作，通量低、稳定性差，而这台设备针对生物育种性状鉴定、蛋白定量筛查场景，可实现实验全流程无人自动化运行，日检测通量比人工高5倍以上，成本降低50%，且完全国产化。\n\n记者在采访中发现，AI正在把复杂的农业科研数据转化成通俗直观的结论。育种不再完全依靠科研人员肉眼观察记录，而是由仪器采集数据，AI完成解析筛选。\n\n上海泽泉科技股份有限公司研发的花粉活力仪可以应用于玉米、小麦、果树、大豆杂交育种项目，帮助科研人员精准把握授粉窗口，稳定后代品质。公司副总经理张凯峰对记者说：“过去做大豆、玉米、小麦等杂交育种，收集花粉之后，不知道花粉活性。我们的设备可以对每一粒花粉活性做量化测定，活性不达标的花粉直接淘汰。随着科技的普及，我相信，未来这些智能设备都会逐步下沉到普通农户。”\n\n一位农业专家对记者表示，AI并非颠覆传统育种，而是对育种体系的升级赋能。智能育种的核心，是依靠高通量设备获取标准化的基因组、表型组数据，依托算法挖掘基因与性状之间的关联，推动育种从过去依赖经验的“试错筛选”，转向数据驱动的“精准设计”，助力我国种业向育种4.0阶段迈进。\n\n**“空天地一体化”重构农业生产模式**\n\n在位于湖南长沙的中联重科岳麓智慧农场，中联智慧农业打造的“天空地人机”协同智慧作业模式，正在改写大田管护方式。\n\n以往人工巡查四五百亩稻田，要耗费一至两小时。中联智慧农业这套搭载多光谱相机的巡田无人机最高可飞120米，20分钟就能完成整片地块巡检，变焦可达100多倍，捕捉到虫害、长势异常等疑点便低空补拍核验。影像实时回传云端后，AI算法输出水稻长势图，精度可达3米乘以3米网格，明确标注地块补水、补肥位置与用量。\n\n天上完成巡查，地上设备随即落地执行。中联智慧农业部署的物联网灌排设备、微型气象站同步采集风、雨、光照数据，农户通过手机软件就能查看农事日历、操控田间设备。这种“按数据决策”的模式，改变了传统农业“凭经验跑田”的粗放管理方式。\n\n除了天上飞的无人机，地上走的机器人也开始应用到更多农业生产场景。\n\n在北京平谷的2026世界农业科技创新大会上，常州艾宝机器人有限公司研发的猕猴桃采摘机器人吸引了不少观众。公司工程师赵炳宇向记者介绍，这款四臂采摘机器人，经第三方机构检测，适合山坡丘陵地形，一台机器能够节约7至8个人工。现阶段设备尚处在定制阶段，已有3家企业完成定制采购。\n\n“我们主要从事AI智能水果采摘机器人研发，已突破多臂协同、视觉感知、自主导航等关键技术，已经推出苹果、葡萄、猕猴桃采摘等系列产品，目的就是推动采摘机器人从技术示范走向生产落地。”赵炳宇说。\n\n**农牧业智能化驶入快车道**\n\n中国是全球最大的猪肉消费国，年消费猪肉超过5000万吨。庞大的产业规模背后，是管理规模大、场景复杂的生猪养殖体系。如今，人工智能正加速渗透进这个最传统的行业。\n\n畜牧种业是畜牧业的“芯片”，在很长一段时间，国内要从海外进口种猪，还要高价采购海外生猪基因芯片，支付高昂的知识产权费。通常一头外引种猪的综合成本高达3万元至5万元。\n\n这一局面如今已被打破。日前，温氏股份、德康农牧等作为主要完成单位参与的“华系种猪育种技术与核心种源创制及应用”项目，荣获国家科学技术进步奖一等奖。该项目通过基因组选择、表型精准测定等技术创新，构建了华系种猪自主育种体系，创制了具有自主知识产权的核心种猪群体，标志着我国生猪核心种源实现高标准自主可控，彻底打破国外长期垄断格局。\n\n在河南，畜牧业龙头企业牧原股份的智能化猪舍里，AI兽医已投入全天候值守。\n\n“过去发现猪不吃食，饲养员找兽医、翻手册、凭经验判断，平均响应时间需要个把小时；现在从发现异常到推荐用药的闭环，仅需数秒。”牧原股份技术负责人介绍，名为“小牧助手”的AI应用，融合企业30余年养殖知识与全产业链330万套智能装备每日产生的20亿条数据，被封装为可嵌入日常流程的AI智能体。目前，牧原与阿里云合作共建的养猪大模型“猪小牧”已向全行业开放共享，助力行业高质量发展。\n\n此外，类似变革正在更多养殖场景中铺开。比如在水产养殖领域，广西防城港东兴市红树林农业有限公司的养殖基地引入AI“厂长”，集成AI算法、高清水下摄像头与传感器网络，24小时实时采集虾群数据，自动调控水阀与投料，每日精准投喂300余次。目前，该基地一年可养对虾5茬，年产量35万至40万公斤。\n\n【责任编辑：母建鑫】","中青在线 2026-09-23","2026-09-23T00:00:00Z",85,{"impact":197,"substance":119,"depth":17,"authority":198,"freshness":121,"relevant":21,"comment":199},26,12,"紧扣十五五规划AI+农业主线，覆盖育种、种植、养殖全链条，案例与数据扎实，具行业风向标价值。",[201],{"name":193,"url":190},[26,126,203,28,204],"智能农机","智慧养殖",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":208},{"candidates":209,"agricultural_evidence":47},[210,215,219,224,228],{"code":33,"score":66,"supported":47,"title":211,"abstract":212,"tags":214},[],[213],"猕猴桃",[],{"code":53,"score":21,"supported":13,"title":216,"abstract":217,"tags":218},[],[],[28],{"code":220,"score":21,"supported":13,"title":221,"abstract":222,"tags":223},"F5",[],[],[203],{"code":60,"score":21,"supported":13,"title":225,"abstract":226,"tags":227},[],[],[26],{"code":177,"score":21,"supported":13,"title":229,"abstract":230,"tags":231},[],[],[126],[233,234],"中联重科 岳麓智慧农场","温氏 华系种猪","中联重科岳麓智慧农场-3387","2026-09-25T00:09:27.645047Z",{"id":46,"title":238,"url":239,"summary":240,"summary_zh":8,"content":241,"source_name":242,"source_url":8,"published_at":243,"category":116,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":244,"sources":247,"tags":249,"primary_topic":252,"secondary_topics":253,"classification":254,"search_phrases":282,"slug":285,"view_count":12,"doi":8,"paper":8,"created_at":286},"2026上海马陆葡萄文化节启用智能采摘、巡检机器人，单机每小时可摘250串","https:\u002F\u002Fso.html5.qq.com\u002Fpage\u002Freal\u002Fsearch_news?docid=70000021_3336a660a8f98652","第二十六届上海马陆葡萄文化节启幕，今年马陆葡萄种植面积约3900亩、品种60余个、预计总产值超1亿元。开幕式上\"未来果园\"智能采摘、巡检机器人正式启用：采摘机器人融合多模态感知、深度学习与柔性控制，单串采摘耗时不足3秒、成功率超90%、单机每小时可摘250串、支持24小时作业；巡检机器人单日覆盖超50亩、效率为人工5倍。同时上线\"小田管家\"AI智能体，结合气象、土壤、生长大数据自动生成标准化农事方案、用药指导和排产规划。开幕式还签署长三角葡萄产业一体化发展倡议书，推动品种研发、智慧种植、品质管控、品牌运营等环节资源互通。","累累似玉垂青蔓，颗颗如珠映碧空。7月26日，2026年长三角葡萄产业高质量发展交流会暨第二十六届上海马陆葡萄文化节启幕。\n\n据悉，今年马陆葡萄种植总面积约3900亩，品种达60余个，预计总产量约4600吨，预计总产值超1亿元。马葡1号、喜乐、早茉莉、京蜜、胭脂红、瑞都红玉、蜜宝儿、绿宝石等为当前热销的早熟品种，售价与去年基本持平。\n\n![Image 1](http:\u002F\u002Fqqpublic.qpic.cn\u002Fqq_public\u002F0\u002F28-926864804-2D6BD9D516F00E741B307358F344A4EC\u002F0?fmt=jpg&size=284&h=600&w=900&ppv=1)\n\n值得一提的是，开幕式上，马陆葡萄“未来果园”智能采摘、巡检机器人启用。智能设备的落地，让传统葡萄种植管理模式开始革新。\n\n机器人摘葡萄 单机每小时可采摘250串\n\n马陆葡萄产业底蕴深厚，自1981年起开始种植，至今已有40余年的发展历史。作为上海特色农产品产业标杆，马陆葡萄产业规模、品种体系持续完善。\n\n品种持续迭代的背后，是数字科技的全方位赋能。今年，马陆葡萄持续深耕“未来果园”建设，以数字化、智能化赋能传统农业迭代升级，落地全周期智慧种植管理体系，让现代农业科技扎根葡乡田间。\n\n![Image 2](http:\u002F\u002Fqqpublic.qpic.cn\u002Fqq_public\u002F0\u002F28-2436894883-DB1C4C496F69FF4EC5A5F2F1174E8F4C\u002F0?fmt=jpg&size=308&h=506&w=900&ppv=1)\n\n智能设备的落地，革新了传统葡萄种植管理模式。其中，葡萄园巡检机器人彻底颠覆传统人工巡查模式，告别“人海战术”，可实现田间全天候无人值守作业，自主完成长势监测、病虫害排查、田间异常预警等核心工作，单日巡检覆盖面积超50亩，巡检效率较人工提升5倍，无论烈日还是深夜均可精准值守，实现果园管理数字化、常态化、精细化。\n\n专为马陆葡萄定制的采摘机器人更是突破行业技术壁垒，融合多模态感知、深度学习算法与柔性控制技术，攻克葡萄柔性抓取、无损切割等核心难题，单串葡萄采摘耗时不足3秒，采摘成功率超90%，单机每小时可采摘250串，支持24小时不间断作业，有效破解采摘季用工短缺、人力成本偏高的行业痛点，让智慧种植落地见效。\n\n与此同时，马陆葡萄产业智能管控体系全面升级，全新上线的机器人管理平台可实现两类机器人的统一调度、实时监控、数据溯源与智能分析。配套打造的“小田管家”AI智能体深度融合数十年本土种植经验，结合气象、土壤、作物生长大数据，自动生成标准化农事方案、用药指导与排产规划，变传统经验种植为数据化、精准化、科学化种植，为葡萄稳产提质、产业增效筑牢数字根基，全力打造上海都市现代农业智慧样板。\n\n![Image 3](http:\u002F\u002Fqqpublic.qpic.cn\u002Fqq_public\u002F0\u002F28-3474761988-4428796A41BA4333810E641B7FE98838\u002F0?fmt=jpg&size=382&h=600&w=900&ppv=1)\n\n以葡萄为媒 丰富农文旅融合内涵\n\n以葡萄为媒，马陆持续推动农文旅深度融合，开幕式上，马陆葡萄艺术村推介片发布，推介片展现了千亩葡萄园的生态风光、乡村与艺术深度融合的景观，勾勒马陆葡萄艺术村的生态之美、人文之美、创意之美，全方位呈现艺术村集生态观光、采摘体验、艺术研学、休闲度假于一体的复合型文旅目的地魅力，进一步擦亮“葡香”马陆文旅名片。\n\n立足自身全链条产业优势和深厚品牌积淀，马陆葡萄积极打破地域壁垒、赋能区域联动发展。开幕式上，举行推进长三角葡萄产业一体化发展倡议书签字仪式。长三角各地葡萄产业代表共同签约，搭建跨区域产业交流合作平台，推动品种研发、智慧种植、品质管控、品牌运营、文旅融合、市场流通等领域资源互通、优势互补、成果共享，合力规范产业标准、提升产区品质、打造区域特色品牌，共同推动长三角葡萄产业规模化、标准化、品牌化、智能化协同发展，助力长三角乡村产业振兴一体化建设。\n\n![Image 4](http:\u002F\u002Fqqpublic.qpic.cn\u002Fqq_public\u002F0\u002F28-957210179-0E4267C219D9234A4A33F46D12E8F57A\u002F0?fmt=jpg&size=535&h=600&w=900&ppv=1)\n\n下一步，马陆镇将持续深耕“未来果园”建设，深化品牌标准化体系建设，做强农文旅融合业态，深化长三角产业协同，持续放大国家地理标志、上海品牌双重优势，以特色产业赋能乡村提质增效，持续打造可复制、可推广的乡村振兴马陆样板。\n\n来源：新民晚报 作者：杨洁","新民晚报 · 2026-07-26","2026-07-26T00:00:00Z",{"impact":17,"substance":120,"depth":245,"authority":12,"freshness":85,"relevant":21,"comment":246},15,"报道上海马陆葡萄文化节启用智能采摘巡检机器人，展示智慧农业落地成效，但时效性已过，影响限于地方产业。",[248],{"name":242,"url":239},[26,250,251,30],"农业机器人","葡萄产业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":255},{"candidates":256,"agricultural_evidence":47},[257,262,267,273,278],{"code":33,"score":198,"supported":47,"title":258,"abstract":260,"tags":261},[259],"葡萄",[259],[251],{"code":153,"score":54,"supported":47,"title":263,"abstract":264,"tags":266},[],[265],"采摘机器人",[250],{"code":268,"score":66,"supported":47,"title":269,"abstract":270,"tags":272},"H2",[],[271],"土壤",[],{"code":177,"score":66,"supported":47,"title":274,"abstract":275,"tags":277},[],[276],"深度学习",[],{"code":60,"score":21,"supported":13,"title":279,"abstract":280,"tags":281},[],[],[26],[283,284],"农业机器人 农文旅融合 智慧农业 葡萄产业","农业机器人 农文旅融合","农业机器人农文旅融合智慧农业葡萄产业-11","2026-07-27T05:05:33.346692Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":8,"content":292,"source_name":293,"source_url":8,"published_at":294,"category":116,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":295,"sources":298,"tags":300,"primary_topic":303,"secondary_topics":304,"classification":305,"search_phrases":320,"slug":323,"view_count":96,"doi":8,"paper":8,"created_at":324},5516,"上海农科院葡萄团队赴银川参加第47届世界葡萄与葡萄酒大会","https:\u002F\u002Fwww.saas.sh.cn\u002Fhzjl\u002Fgjhz\u002Fcontent_57128","10月12日至16日第47届世界葡萄与葡萄酒大会在银川举办，智慧农业研究中心葡萄团队负责人奚晓军研究员作专题报告，阐明疏穗与环剥处理对果实糖、花青素及脱落酸积累的源库调控机制。团队还观摩酿酒葡萄AI综合作业机器人成果展示，与研发单位围绕葡萄智慧装备与果园智能化管理深入交流。","2026年10月12-16日，第47届世界葡萄与葡萄酒大会在银川举办，智慧农业研究中心葡萄团队负责人奚晓军研究员一行赴会交流。团队围绕“提升葡萄种植生产韧性与可持续发展能力”主题，向全球同行展示最新科研成果。\n\n会上，奚晓军作“Changes in sugar, anthocyanin and ABA accumulation in response to cluster thinning and girdling in ‘Jumeigui’grape”专题报告。报告围绕葡萄疏穗与环剥处理开展研究，阐明源库比对果实糖、花青素及脱落酸积累的调控机制，为葡萄优质栽培技术提供理论支撑，报告内容引发国内外园艺专家广泛研讨。参会期间，团队前往银川国际会展中心观摩酿酒葡萄 AI 综合作业机器人成果展示，详细了解该装备在葡萄园智能作业方面的技术特点与应用前景，并与研发单位围绕葡萄智慧装备研发、果园智能化管理等方向开展深入交流。\n\n本次参会是葡萄团队持续推进科研国际化、对标国际前沿开展研究的重要实践。","上海市农业科学院 2026-10-19","2026-10-19T00:00:00Z",{"impact":16,"substance":18,"depth":296,"authority":296,"freshness":19,"relevant":21,"comment":297},13,"国际学术会议交流并涉及葡萄AI作业机器人观摩，有实质科研内容与行业参考价值，但属团队参会动态，影响面有限。",[299],{"name":293,"url":290},[26,203,259,301,302],"栽培技术","国际交流",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":306},{"candidates":307,"agricultural_evidence":47},[308,312,316],{"code":33,"score":198,"supported":47,"title":309,"abstract":310,"tags":311},[259],[259],[259],{"code":60,"score":54,"supported":47,"title":313,"abstract":314,"tags":315},[],[26],[26],{"code":220,"score":21,"supported":13,"title":317,"abstract":318,"tags":319},[],[],[203],[321,322],"上海农科院 葡萄 银川","世界葡萄与葡萄酒大会 奚晓军","上海农科院葡萄银川-5516","2026-10-22T00:07:04.061911Z",{"id":326,"title":327,"url":328,"summary":329,"summary_zh":330,"content":8,"source_name":331,"source_url":328,"published_at":332,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":117,"score_detail":333,"sources":336,"tags":338,"primary_topic":342,"secondary_topics":343,"classification":344,"search_phrases":370,"slug":373,"view_count":96,"doi":374,"paper":375,"created_at":396},5401,"A HIERARCHICAL DISTRIBUTED EDGE AI FRAMEWORK FOR REAL-TIME APPLE LEAF DISEASE CLASSIFICATION","https:\u002F\u002Fdoi.org\u002F10.22190\u002Ffuacr260506002g","The application of artificial intelligence (AI) in agriculture has transformed crop management, particularly in the detection of plant diseases. Apple trees, a key agricultural commodity, are vulnerable to various diseases, which can severely impact crop yields. Traditional disease detection methods, often reliant on manual inspections, are time-consuming and prone to error. In response, this study proposes a novel two-stage edge AI framework for apple leaf disease classification that integrates RGB imagery with distributed edge computing. The first stage performs binary classification to distinguish between healthy and diseased leaves, achieving an F1 score of 95.50%. This optimization is achieved by utilizing lightweight models on edge devices, thereby enhancing computational efficiency. The second stage employs a consensus-based multiclass classification approach, achieving a 96.44% F1 score in identifying specific diseases. This dual-stage system, supported by an edge AI architecture, ensures real-time disease detection while minimizing resource consumption and enhancing scalability in large-scale agricultural environments. The full system achieved a 95.50% accuracy and F1 score on the special dataset. The results demonstrate the system’s efficacy in controlled laboratory conditions, offering a promising solution for precise, real-time agricultural monitoring. This study underscores the potential of distributed edge AI systems for scalable and efficient disease detection in precision agriculture.","人工智能（AI）在农业中的应用已深刻改变了作物管理方式，尤其是在植物病害检测方面。苹果树作为重要的农业经济作物，易受多种病害侵袭，严重影响作物产量。传统的病害检测方法通常依赖人工检查，耗时且易出错。为此，本研究提出了一种新颖的两阶段边缘AI框架，用于苹果叶片病害分类，该框架将RGB图像与分布式边缘计算相结合。第一阶段执行二分类以区分健康叶片与患病叶片，F1分数达到95.50%。该优化通过在边缘设备上采用轻量级模型实现，从而提升了计算效率。第二阶段采用基于共识的多类分类方法，在识别具体病害方面F1分数达到96.44%。该双阶段系统在边缘AI架构的支持下，实现了实时病害检测，同时最大限度地降低了资源消耗，并增强了在大规模农业环境中的可扩展性。完整系统在专用数据集上达到了95.50%的准确率和F1分数。结果表明，该系统在受控实验室条件下具有有效性，为精准、实时的农业监测提供了一种有前景的解决方案。本研究凸显了分布式边缘AI系统在精准农业中实现可扩展且高效病害检测的潜力。","Facta Universitatis Series Automatic Control and Robotics","2026-10-18T00:00:00Z",{"impact":17,"substance":334,"depth":18,"authority":198,"freshness":20,"relevant":21,"comment":335},21,"该研究提出两级边缘AI框架，在苹果叶片病害识别上取得95%以上F1值，方法新颖、数据可靠，对精准农业实时监测有参考价值，但尚处实验室验证阶段，产业影响有限。",[337],{"name":331,"url":328},[26,126,339,340,341],"边缘计算","作物病害识别","苹果病害",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":345},{"candidates":346,"agricultural_evidence":47},[347,353,359,365],{"code":33,"score":17,"supported":47,"title":348,"abstract":350,"tags":352},[349],"apple",[35,351,349],"苹果",[341],{"code":60,"score":121,"supported":47,"title":354,"abstract":355,"tags":358},[],[356,357],"精准农业","precision agriculture",[26],{"code":360,"score":121,"supported":47,"title":361,"abstract":362,"tags":364},"I5",[],[339,363],"edge computing",[339],{"code":177,"score":185,"supported":47,"title":366,"abstract":367,"tags":369},[],[368],"artificial intelligence",[340,126],[371,372],"苹果叶片病害 边缘AI","分布式边缘计算 病害分类","苹果叶片病害边缘AI-5401","10.22190\u002Ffuacr260506002g",{"doi":374,"openalex_id":376,"authors":377,"venue":331,"cited_by_count":96,"oa_url":328,"card":390,"direction":395,"ingested_from":104},"W7222964752",[378,381,384,387],{"name":379,"orcid":380},"Milan Grujev","https:\u002F\u002Forcid.org\u002F0009-0002-3211-6844",{"name":382,"orcid":383},"Dragan H. Stojanovic","https:\u002F\u002Forcid.org\u002F0000-0003-4893-3814",{"name":385,"orcid":386},"Miloš Ilić","https:\u002F\u002Forcid.org\u002F0000-0002-9696-2874",{"name":388,"orcid":389},"Aleksandar Milosavljević","https:\u002F\u002Forcid.org\u002F0000-0003-3057-7727",{"tldr":391,"method":392,"finding":393,"direction":103,"opportunity":394},"提出两级边缘AI框架，用RGB图像实时分类苹果叶片病害。","分布式边缘计算+轻量模型，先二分类再共识多分类。","两级系统准确率与F1均达95.50%，多分类F1为96.44%。","仅在受控实验室验证，可延伸至田间复杂光照与多作物泛化及边缘能耗优化。","农业人工智能与决策模型","2026-10-20T23:30:33.830748Z",{"id":398,"title":399,"url":400,"summary":401,"summary_zh":8,"content":8,"source_name":402,"source_url":8,"published_at":403,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":404,"score_detail":405,"sources":407,"tags":409,"primary_topic":413,"secondary_topics":414,"classification":415,"search_phrases":426,"slug":429,"view_count":96,"doi":8,"paper":430,"created_at":438},5297,"高志永团队《基于特征优选与优化算法的干热河谷区柑橘蒸腾模拟》","https:\u002F\u002Fwww.sohu.com\u002Fa\u002F1087305323_122014422","《智慧农业(中英文)》2026年第8卷第4期刊载云南农业大学吴明清、高志永等团队论文,以10年生柑橘树为研究对象收集2020—2022年树干液流与环境因子数据;针对干热河谷加快建设智慧灌区背景下传统机理模型参数需求高、对部分参数高度敏感且误差来源复杂等难题,提出基于特征优选与优化算法的蒸腾模拟方法,可为优化灌区水分调控与配水策略提供决策支撑。","智慧农业(中英文)(2026,8(4))","2026-10-13T00:00:00Z",72,{"impact":16,"substance":334,"depth":18,"authority":296,"freshness":185,"relevant":21,"comment":406},"核心期刊论文，方法有创新且数据规模扎实，对干热河谷智慧灌区水分调控有决策参考价值，但属细分领域研究，时效性一般。",[408],{"name":402,"url":400},[26,410,49,411,412],"云南","智慧灌区","蒸腾模拟",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":13,"version":41,"method":42,"evidence":416},{"candidates":417,"agricultural_evidence":47},[418,422],{"code":33,"score":198,"supported":47,"title":419,"abstract":420,"tags":421},[49],[49],[49],{"code":60,"score":54,"supported":47,"title":423,"abstract":424,"tags":425},[],[26],[26],[427,428],"云南农业大学 柑橘 蒸腾模拟","干热河谷 智慧灌区","云南农业大学柑橘蒸腾模拟-5297",{"doi":8,"openalex_id":8,"authors":431,"venue":8,"cited_by_count":96,"oa_url":8,"card":432,"direction":103,"ingested_from":437},[],{"tldr":433,"method":434,"finding":435,"direction":103,"opportunity":436},"用特征优选与优化算法模拟干热河谷区柑橘蒸腾。","基于2020—2022年树干液流与环境因子数据构建特征优选与优化算法模型。","该方法可降低机理模型参数依赖与敏感性，提升蒸腾模拟精度。","可探索将蒸腾模拟嵌入智慧灌区实时配水决策，研究多树种迁移与边缘部署。","agent","2026-10-19T00:07:48.135945Z"]