[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"daily-2026-09-24":3},{"date":4,"title":5,"highlights":6,"content":13,"items":14},"2026-09-24","农业农村日报：智慧农业提速 数字乡村赋能县域共富",[7,8,9,10,11,12],"专家解读智慧农业与小农户衔接路径：农机北斗终端累计推广超350万台套，社会化服务组织将智能农机、无人机植保转化为小农户点单即享的标准化服务。","《数字乡村高质量发展行动计划（2026—2030年）》解读发布，智慧农业聚焦增产增效，农业社会化服务成为数智技术落地的重要依托。","乐清粮油三熟种植制度改革入选2026年全国农村改革试验区拓展试验任务，油-稻-稻、麦-稻-稻模式三季合计补贴最高达740元\u002F亩。","2026世界农业科技创新大会在京开幕，我国农业科技进步贡献率超64%，农作物耕种收综合机械化率达76.7%。","研究显示人工智能显著提升农业新质生产力，数字乡村试点政策促进县域共同富裕，两条路径均获大样本面板数据实证支持。","2026年中国农民丰收节全国主场活动落地湖北襄阳，襄阳粮食产量占全省近五分之一，实现22连丰，展示鄂北粮仓智慧种地转型。","本期聚焦智慧农业与数字乡村建设：政策解读明确十五五推进人工智能与农业融合，农机北斗终端规模化推广超350万台套；乐清粮油三熟改革、襄阳丰收节主场展示地方实践；多篇论文实证人工智能驱动农业新质生产力、数字乡村促进县域共富，并涵盖农业大数据、雷达测产等前沿技术。\n\n---\n*本日报内容整理自公开来源，学术论文元数据来自 OpenAlex 等开放接口；外文资料已译为中文，翻译与摘要仅供参考；引用与决策请以官方原文与正式出版物为准。*",[15,51,80,116,144,165,194,218,257,282,322,345,385,412,453],{"id":16,"title":17,"url":18,"summary":19,"summary_zh":20,"content":21,"source_name":22,"source_url":20,"published_at":23,"category":24,"cover_url":20,"hotness":25,"is_selected":26,"score":27,"score_detail":28,"sources":36,"tags":38,"search_phrases":45,"slug":48,"view_count":49,"doi":20,"paper":20,"created_at":50},3289,"专家解读：乘数而上向智而行——大力发展智慧农业 加快建设数字乡村 智慧农业与小农户有机衔接","https:\u002F\u002Fwww.thepaper.cn\u002FnewsDetail_forward_34116699","专家解读文章指出：近年来农机北斗终端实现快速规模化推广，截至2025年底累计推广超350万台套。各类农业社会化服务组织加速布点，通过集采智能装备、统一调度作业、提供菜单式服务，将智能农机、无人机植保、精准施肥等先进技术和装备转化为小农户点单即享的标准化服务。十五五时期是基本实现农业农村现代化的关键时期，《加快农业农村现代化十五五规划》明确要推进人工智能运用和智慧农业发展；农业大模型、智能装备加速在生物育种、农情监测、生产管理、动植物疫病识别与防控、产量预测等场景落地。",null,"习近平总书记高度重视数字乡村建设和智慧农业发展，作出重要指示强调，“瞄准农业现代化主攻方向，提高农业生产智能化、经营网络化水平，帮助广大农民增加收入”“要用好现代信息技术，创新乡村治理方式，提高乡村善治水平”。2019年，中共中央办公厅、国务院办公厅印发了《数字乡村发展战略纲要》。此后，中央一号文件连续八年对推进数字乡村和智慧农业作出重要部署。各地区各有关部门持续推进数字技术与农业生产、乡村生活日益融合，数字乡村建设和智慧农业发展取得重要阶段性成效。近日，国家互联网信息办公室、农业农村部联合发布《中国数字乡村发展报告（2019—2025年）》（以下简称《报告》），系统总结了七年来我国数字乡村发展的成就和经验。《报告》立足新形势新要求，展示了以信息基础设施为底座、数据资源体系为核心、智慧农业与乡村数字经济为重点、数字文化与数字治理为支撑、信息服务与智慧美丽乡村为拓展、政策机制与人才队伍为保障的体系化发展路径。该《报告》不仅为全面了解发展成效、科学谋划“十五五”数字乡村发展蓝图提供了重要参考，也积极回应各方关切，向国际社会展示了我国借助数字技术推动农业与乡村治理数智化转型的经验。回顾七年历程，智慧农业作为数字乡村建设的重要内容，已由试点探索转向快速起步、由点状突破迈向系统推进，正乘“数”而上，向“智”而行，为推进农业农村现代化提供有力支撑。\n\n一、智慧农业正从“盆景”走向“风景”\n\n数字乡村涵盖乡村经济、治理、文化、服务等多个维度，内涵丰富。《报告》提出，智慧农业是“农业新质生产力的重要内容，是乡村产业数字化的关键着力点”。智慧农业为数字乡村高质量发展提供了坚实的产业支撑，成为推动数字乡村发展的关键动能。《报告》显示，七年的探索推进和快速发展，推动智慧农业实现了“四个跨越”。\n\n第一，智慧农业基础设施实现从“基础覆盖”到“深化赋能”的跨越。完善的网络基础设施为智慧农业在田间地头、池塘圈舍的落地拓展提供了基础支撑。截至2025年底，农村地区互联网普及率达69.5%，较2018年底提升31.1个百分点。传统基础设施数字化为智慧农业提供了更加坚实的硬件底座和场景支撑，农村水利、农田、电网、公路及寄递物流等持续升级完善。农业数据资源日益丰富，为智慧农业落地应用提供了基础资源和创新引擎，“天空地一体化”监测网络等新型基础设施加快建设，全国农产品批发市场价格信息等涉农数据开发利用不断深入。\n\n第二，关键技术装备实现从“基础”到“核心”的跨越。智能农机装备研发应用取得重要进展，新一代信息技术与农业装备深度融合，正推动农业生产方式从“靠天吃饭”向“知天而作”加速转变。产学研用相衔接的智慧农业创新体系加快形成，支撑取得一批关键智慧农业技术装备创新成果。《报告》显示，截至2025年底，累计建设智慧农业创新中心、分中心34个，智慧农业创新应用项目116个，104项关键智慧农业技术和62项整机智能装备研发取得突破。智慧农业技术装备质量管控更加严格、应用推广不断拓展，布局建设国家农机装备产业计量测试中心，强化农机装备产业计算测试技术研究与应用。\n\n第三，主要产业数字化实现从“单点试验”到“面上推广”的跨越。大田种植领域，天空地一体化农情感知与数据驱动模式初步构建，实现水稻、小麦、玉米苗情长势动态监测。截至2025年底，累计推广应用各类农机北斗终端超350万台套，农用无人机保有量超过30万架、年作业面积突破4.6亿亩。智能农机共享租赁加速普及。畜禽养殖领域，精准饲喂、环境控制、行为分析等智能技术广泛应用于生猪养殖和家禽立体高效养殖中。全国659个动物防疫通道纳入信息化管理，动物检疫监督更加智能化、便捷化和高效化。渔业领域，数字技术持续赋能多元化养殖模式，智能化网箱设备、投料机器人等智能装备加速迭代，海洋养殖智能化水平不断提升。\n\n第四，粮食安全保障实现从“人工管控”到“数智赋能”的跨越。粮食安全是“国之大者”，数智技术正在为其构筑起坚实保障。在耕地保护方面，“三区三线”等“一张图”相关基础数据库进一步完善，让“藏粮于地”有了更坚实的数据底座，助力守牢18亿亩耕地红线。在种业振兴方面，中国种业大数据平台建成运行，全国农作物种质资源信息平台已上线58.8万份国家级库圃种质资源信息，为育种创新提供了坚实的资源基础。在防灾减损领域，气象预警信息全面接入全国123万个应急广播终端并在16个省份386个市县试行开展“闪信”技术应用，以气象预警为先导的应急响应联动机制更加健全。在仓储方面，借助数字化仓储技术，粮库储粮周期内综合损耗率控制在1%以内，支撑节粮减损效果明显。从种到收、从田间到粮仓，数智技术正在全链条赋能国家粮食安全保障体系。\n\n二、智慧农业发展需要坚定走好符合国情农情的路子\n\n七年来，在信息革命加速农业深刻变革的进程中，智慧农业加快发展、数字乡村建设深入推进，推动农业成为更有奔头的产业、农村成为更加宜居宜业的家园，为网络强国、农业强国建设贡献了重要力量。回顾七年实践，我们进一步深化了对智慧农业发展的规律性认识。\n\n一是政府引导与市场机制协同发力。党中央、国务院印发的《加快建设农业强国规划（2024—2035年）》、农业农村部印发的《关于大力发展智慧农业的指导意见》《全国智慧农业行动计划（2024—2028年）》等文件构建了智慧农业“四梁八柱”。七年来，从智慧农业创新中心布局到创新应用项目建设实施，从主推技术遴选、典型案例推介到智慧农业创新大赛，政府的“有形之手”在搭建平台、降低门槛、推动产业化等方面发挥了重要作用。同时，平台经济等推动拓展创业空间，返乡青年、家庭农场、农民合作社和农村个体商户以平台化方式进入市场、链接消费和重构经营模式，农村电商、数字服务等新业态加速发展，市场的“无形之手”进一步增强了智慧农业发展的动力活力。\n\n二是技术创新与农情农艺深度结合。农业不同于工业、农村不同于城市，发展智慧农业、建设数字乡村必须坚持问题导向、应用导向，走适宜化、低成本、易操作的技术路线。近年来，农机北斗终端实现快速规模化推广，在于其有效契合了播种、收获等关键环节的实际生产需求，让农民“用得上、用得起、用得好”。\n\n三是智慧农业与小农户有机衔接。“大国小农”的基本国情农情决定了智慧农业要实现大规模落地应用，必须坚持让小农户共享数字红利的现实路径。各类农业社会化服务组织加速布点，通过集采智能装备、统一调度作业、提供“菜单式”服务，将智能农机、无人机植保、精准施肥等先进技术和装备转化为小农户“点单即享”的标准化服务，有效破解小农户“买不起、用不好”的难题。以社会化服务为纽带，智慧农业正成为促进小农户与现代农业发展有机衔接的重要手段。\n\n三、奋力推进“十五五”时期智慧农业建设\n\n“十五五”时期是基本实现农业农村现代化的关键时期。展望未来五年，数字乡村将加快迈向数智乡村，智慧农业建设将进入创新发展、落地见效的关键阶段。《加快农业农村现代化“十五五”规划》明确，要“推进人工智能运用和智慧农业发展”。这要求我们既要总结运用好实践中积累形成的宝贵经验，又要准确把握未来数智技术和农业发展新趋势。\n\n当前，人工智能等数智技术加速演进，深刻重塑农业发展的底层逻辑，为智慧农业发展带来了前所未有的新机遇。一是数据产业加快培育，释放要素价值潜能。数据从支撑农业农村发展的辅助性工具，逐步发展为具有独立价值、可市场化运营的新型生产要素，其基础资源和创新引擎作用日渐显现，数智技术加速内化成为农业农村领域的发展动能，要抓实数据这个根本，进一步加快“统筹部署农业农村数据基础设施”“发展农业农村领域数据产业”。二是应用场景全链拓展，场景驱动成为重要引擎。农业大模型、智能装备加速在生物育种、农情监测、生产管理、动植物疫病识别与防控、产量预测等场景落地，场景驱动技术迭代的效能日益凸显，要打造丰富多样的应用场景，“加快农业人工智能应用场景拓展”。三是新兴产业加快培育，拓展农业发展新空间。智能设计育种、新能源农机、农业低空经济等先导性产业规模化发展，开辟智慧农业高质量发展全新赛道，要从智能育种等产业急需领域做起，加快“培育发展乡村新产业新业态”。\n\n《报告》的发布既是阶段性总结，更是新征程的动员。面向“十五五”，我们要坚决贯彻党中央、国务院关于大力推进“人工智能+”农业的部署要求，在基础设施上强基固本，在关键技术装备上聚力攻坚，在产业数智化上扩面提效，在粮食安全保障上筑牢数字防线，加快推动智慧农业从“点上突破”迈向“面上成势”，从“量的积累”转向“质的跃升”。以智慧农业的创新发展，推动数字乡村高质量发展，为加快农业农村现代化、扎实推进乡村全面振兴注入更加澎湃的数智动能。\n\n作者：李韶民 农业农村部信息中心副主任\n\n原标题：《专家解读｜乘“数”而上 向“智”而行——大力发展智慧农业 加快建设数字乡村》\n\n[阅读原文](https:\u002F\u002Fmp.weixin.qq.com\u002Fs?__biz=Mzg2ODA4MDIwNg==&mid=2247812104&idx=2&sn=0d26f89082d00b4df0d545a746ae8920&chksm=cf86c6565a4df065b13c07ba7a865f15b705b1f5daea9595cb732f4e76ca7a07f6080524f4d7&scene=7)","澎湃新闻 2026年09月23日","2026-09-23T00:00:00Z","报道",10,true,93,{"impact":29,"substance":30,"depth":31,"authority":32,"freshness":33,"relevant":34,"comment":35},28,24,18,14,9,1,"农业农村部信息中心专家对《中国数字乡村发展报告（2019—2025年）》的系统解读，含大量权威数据与“十五五”方向判断，政策参考价值高。",[37],{"name":22,"url":18},[39,40,41,42,43,44],"数字乡村","智慧农业","农业人工智能","十五五规划","粮食安全","农业社会化服务",[46,47],"中国数字乡村发展报告 2019-2025","智慧农业 小农户 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程源 乐清融媒记者 孔丽琴）","温州市人民政府 2026年09月20日","2026-09-20T00:15:00Z",87,{"impact":61,"substance":62,"depth":31,"authority":63,"freshness":64,"relevant":34,"comment":65},26,23,13,7,"国家级农村改革试验区拓展任务落地乐清，粮油三熟制在品种、政策、农机、经营方式上均有实质数据与机制创新，值得进入每日精选。",[67],{"name":57,"url":54},[69,70,71,72,73,74],"农业保险","农事服务中心","粮油三熟","农村改革试验区","种植制度改革","无人驾驶插秧机",[76,77],"乐清 粮油三熟 种植制度改革","浙油早1号 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农作物耕种收综合机械化率达76.7%","http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html","9月17日，2026世界农业科技创新大会在北京平谷开幕。来自30余个国际组织、科研机构和企业商会的近300位嘉宾围绕农食系统绿色健康转型主题开展研讨。统计数据显示，目前我国农业科技进步贡献率超过64%，农作物自主选育品种种植面积占比超95%，农作物耕种收综合机械化率达到76.7%。开幕式上《农食一体、农医联动，农食系统绿色健康转型的平谷方案》《联合国粮食及农业组织FAO创新报告》等6项技术方案和国际报告成果集中亮相。","[![Image 2](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html)](javascript:void(0))\n\n![Image 3](http:\u002F\u002Fwww.news.cn\u002F2022newhomepro\u002Fmobile\u002Fimages\u002Flogo.png)_手机版_\n\n[网站无障碍](javascript:void(0))\n\n[![Image 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海内外专家学者在京热议农食系统绿色健康转型-新华网 \n\n![Image 8](http:\u002F\u002Fwww.news.cn\u002Fdetail2020\u002Fimages\u002Fewm.png)\n\n[](http:\u002F\u002Fservice.weibo.com\u002Fshare\u002Fshare.php?url=http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html&title=%E6%B5%B7%E5%86%85%E5%A4%96%E4%B8%93%E5%AE%B6%E5%AD%A6%E8%80%85%E5%9C%A8%E4%BA%AC%E7%83%AD%E8%AE%AE%E5%86%9C%E9%A3%9F%E7%B3%BB%E7%BB%9F%E7%BB%BF%E8%89%B2%E5%81%A5%E5%BA%B7%E8%BD%AC%E5%9E%8B)\n\n![Image 9](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fzxcode_20260918df69e04f86804a63a0b6c16e9c688891.jpg)\n\n![Image 10](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html)\n\n![Image 11](http:\u002F\u002Fwww.news.cn\u002Fpolitics\u002Fnewpage2020\u002Fimages\u002Fqrcode-app.png)\n\n[新华网北京频道](http:\u002F\u002Fbj.news.cn\u002F)>[新闻](https:\u002F\u002Fwww.news.cn\u002F)> 正文\n\n_2026_ 09\u002F18 08:39:53\n\n来源：新华网 \n\n# 海内外专家学者在京热议农食系统绿色健康转型\n\n[Audio 2](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html)\n\n字体： 小 中 大\n\n分享到：[](javascript:void(0))[](http:\u002F\u002Fservice.weibo.com\u002Fshare\u002Fshare.php?url=http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html&title=%E6%B5%B7%E5%86%85%E5%A4%96%E4%B8%93%E5%AE%B6%E5%AD%A6%E8%80%85%E5%9C%A8%E4%BA%AC%E7%83%AD%E8%AE%AE%E5%86%9C%E9%A3%9F%E7%B3%BB%E7%BB%9F%E7%BB%BF%E8%89%B2%E5%81%A5%E5%BA%B7%E8%BD%AC%E5%9E%8B)[](javascript:void(0))[](javascript:void(0))\n\n![Image 12](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fzxcode_20260918df69e04f86804a63a0b6c16e9c688891.jpg)\n\n![Image 13](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html)\n\n![Image 14](http:\u002F\u002Fwww.news.cn\u002Fpolitics\u002Fnewpage2020\u002Fimages\u002Fqrcode-app.png)\n\n# 海内外专家学者在京热议农食系统绿色健康转型\n\n 2026-09-18 08:39:53  来源：新华网 \n\n9月17日，2026世界农业科技创新大会在北京平谷开幕。来自30余个国际组织、科研机构和企业商会的近300位嘉宾，围绕“农食系统绿色健康转型”主题，聚焦粮食安全、绿色低碳、AI农业、营养健康等议题开展研讨，共绘可持续发展新图景。\n\n与会专家表示，当前，日常食物消费需求正从“吃得饱”向“吃得好、吃得营养健康”加快转变，保障粮食安全、促进绿色发展成为国际社会的共同课题。\n\n统计数据显示，目前我国农业科技进步贡献率超过64%，农作物自主选育品种种植面积占比超95%，农作物耕种收综合机械化率达到76.7%，科技创新成为引领农业发展的重要引擎。\n\n开幕式上，《农食一体、农医联动，农食系统绿色健康转型的平谷方案》《联合国粮食及农业组织FAO创新报告》等6项技术方案和国际报告成果集中亮相。\n\n![Image 15](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002F20260918df69e04f86804a63a0b6c16e9c688891_20260918762d75ecda1541ceb3c823948479bdae.jpg)\n9月17日，在2026世界农业科技创新大会配套的博览会上拍摄的中科院自动化研究所的一款智能采摘机器人采摘演示。新华社记者 鞠焕宗 摄\n\n中国农业大学党委书记钟登华表示，多年来，中国农业大学深度参与全球粮食安全治理，聚焦生物育种、环境生态、营养健康等领域开展科技创新，在节水农业、数字农业、保护性耕作等领域形成了国际先进的技术体系。\n\n加蓬共和国农业部长帕科姆·科西表示，农业绿色健康转型要构建面向未来的发展模式，将农业生产力与可持续发展协同推进，还要持续推动农业科技创新触及农民、惠及农民。\n\n与会外国嘉宾表示，期待与中国在智慧农业、智能装备、现代种业、产学研融合等领域开展更深层次、更宽领域合作，携手助力世界粮食安全与农食系统绿色健康转型。\n\n本次大会由中国农业大学、北京市农业农村局、北京市平谷区人民政府、国际农业研究磋商组织联合主办，大会将持续至9月19日。（记者余佩璇、鲍赫）\n\n[【纠错】](javascript:void(0);)\n\n![Image 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22](http:\u002F\u002Fbj.news.cn\u002F20260918\u002F1b30f3cd4eef43e98c3ffe684b545903\u002F202609181b30f3cd4eef43e98c3ffe684b545903_d834da59fb4c4eacab48b7a30e61c86b.jpg)](http:\u002F\u002Fbj.news.cn\u002F20260918\u002F1b30f3cd4eef43e98c3ffe684b545903\u002Fc.html)[2026世界农业科技创新大会在北京平谷举办](http:\u002F\u002Fbj.news.cn\u002F20260918\u002F1b30f3cd4eef43e98c3ffe684b545903\u002Fc.html)  \n*   [![Image 23](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F26849b06f39644b6b47016aada5a404c\u002F2026091726849b06f39644b6b47016aada5a404c_2026091763c0613432414252b485780fc2954b8f.jpg)](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F26849b06f39644b6b47016aada5a404c\u002Fc.html)[2026年北马启动报名 赛事规模3.2万人](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F26849b06f39644b6b47016aada5a404c\u002Fc.html)  \n*   [![Image 24](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F01ee3b6094b14a0796119a2e9643a1a6\u002F2026091701ee3b6094b14a0796119a2e9643a1a6_20260917d3d2fa154ed141e8817c45c614f7859e.jpg)](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F01ee3b6094b14a0796119a2e9643a1a6\u002Fc.html)[校馆弦歌｜北京大学图书馆 传承红色基因 以文化人](http:\u002F\u002Fbj.news.cn\u002F20260917\u002F01ee3b6094b14a0796119a2e9643a1a6\u002Fc.html)  \n\nCopyright © 2000 - 2026 XINHUANET.com All Rights Reserved.\n\n制作单位：新华网股份有限公司 版权所有：新华网股份有限公司\n\n![Image 25](http:\u002F\u002Fbj.news.cn\u002F20260918\u002Fdf69e04f86804a63a0b6c16e9c688891\u002Fc.html)\n\n 海内外专家学者在京热议农食系统绿色健康转型","新华网北京频道 2026年09月18日","2026-09-18T00:00:00Z",{"impact":61,"substance":91,"depth":203,"authority":204,"freshness":173,"relevant":34,"comment":205},16,15,"央媒报道的世界农业科技大会动态，含农业科技进步贡献率超64%、机械化率76.7%等权威数据，具备全国性影响与信息增量，值得进入每日精选。",[207],{"name":200,"url":197},[40,209,210,211,212],"农业机械化","国际合作","农业科技进步","农食系统",[214,215],"WAFI 世界农业科技创新大会","农业科技进步贡献率 64%","WAFI世界农业科技创新大会-3294","2026-09-24T00:03:57.340049Z",{"id":219,"title":220,"url":221,"summary":222,"summary_zh":223,"content":20,"source_name":224,"source_url":221,"published_at":225,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":171,"score_detail":226,"sources":228,"tags":230,"search_phrases":236,"slug":239,"view_count":49,"doi":240,"paper":241,"created_at":256},3266,"Research on the impact effects of RCEP on China’s aquatic product trade: an analysis based on the GTAP model","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1904058","The implementation of the Regional Comprehensive Economic Partnership (RCEP) will reshape the regional industrial landscape and exert a significant influence on aquatic product trade. Drawing upon the officially signed agreement text, this study constructs a Global Trade Analysis Project (GTAP) model to examine the combined effects of RCEP-mandated tariff reductions and trade facilitation measures on China’s aquatic product trade. The findings reveal that RCEP effectively reduces regional trade costs, with the average tariff rate on aquatic products among member countries declining from 6.60 to 0.72%, representing a reduction of 89.10%. Concurrently, average import clearance time improves by 37.84%, while average export clearance time improves by 19.42%. The implementation of RCEP shifts China’s aquatic product sector from a domestically oriented pattern toward an export-oriented one. The agreement expands the overall scale of aquatic product trade, with both import and export values projected to increase; however, the growth rate of imports substantially outpaces that of exports. In terms of trading partners, intra-RCEP trade growth far exceeds the growth of trade with non-RCEP economies. Furthermore, following the conclusion of RCEP, the improvement in the terms of trade for aquatic products generates a positive welfare effect. The overall impact of RCEP on China’s aquatic product trade represents the combined outcome of trade creation, trade diversion, and trade displacement effects. In this context, promoting the sustainable development of aquatic product trade under the RCEP framework is significant for developing the regional economy and enhancing the long-term resilience of trade.","《区域全面经济伙伴关系协定》（RCEP）的实施将重塑区域产业格局，并对水产品贸易产生重要影响。本研究依据正式签署的协定文本，构建全球贸易分析模型（GTAP），考察RCEP框架下关税削减与贸易便利化措施对中国水产品贸易的叠加效应。研究发现，RCEP有效降低了区域贸易成本，成员国间水产品平均关税税率从6.60%降至0.72%，降幅达89.10%；同时，平均进口通关时间改善37.84%，平均出口通关时间改善19.42%。RCEP的实施推动中国水产品部门由以内需为主转向出口导向。该协定扩大了水产品贸易总体规模，进出口额均预计增长，但进口增速显著快于出口。从贸易伙伴来看，RCEP区域内贸易增长远超与区域外经济体的贸易增长。此外，RCEP生效后，水产品贸易条件改善产生了正向福利效应。RCEP对中国水产品贸易的总体影响是贸易创造、贸易转移与贸易替代效应共同作用的结果。在此背景下，推动RCEP框架下水产品贸易可持续发展，对发展区域经济和增强贸易长期韧性具有重要意义。","Frontiers in Sustainable Food Systems","2026-09-22T00:00:00Z",{"impact":91,"substance":62,"depth":31,"authority":63,"freshness":33,"relevant":34,"comment":227},"基于GTAP模型的RCEP对中国水产品贸易影响研究，数据详实、结论明确，对农业贸易政策有参考价值。",[229],{"name":224,"url":221},[231,232,233,234,235],"RCEP","农产品贸易","水产贸易","GTAP模型","贸易便利化",[237,238],"RCEP 中国 水产品贸易","GTAP 水产品 关税","RCEP中国水产品贸易-3266","10.3389\u002Ffsufs.2026.1904058",{"doi":240,"openalex_id":242,"authors":243,"venue":224,"cited_by_count":49,"oa_url":221,"card":249,"direction":253,"ingested_from":255},"W7214022970",[244,247],{"name":245,"orcid":246},"Yu Sun","https:\u002F\u002Forcid.org\u002F0000-0002-7059-177X",{"name":248,"orcid":20},"Yani Zhu",{"tldr":250,"method":251,"finding":252,"direction":253,"opportunity":254},"用GTAP模型评估RCEP关税削减与贸易便利化对中国水产品贸易的影响。","基于RCEP协定文本构建GTAP模型，模拟关税削减与通关时间变化。","RCEP使中国水产品由内需导向转为出口导向，进口增速远超出口，区内贸易增长显著。","其他","可延伸研究RCEP下中国水产品贸易的可持续性与供应链韧性，结合数字贸易与智慧渔业。","openalex","2026-09-23T23:30:07.413243Z",{"id":258,"title":259,"url":260,"summary":261,"summary_zh":20,"content":262,"source_name":263,"source_url":20,"published_at":23,"category":24,"cover_url":20,"hotness":25,"is_selected":88,"score":264,"score_detail":265,"sources":268,"tags":270,"search_phrases":277,"slug":280,"view_count":49,"doi":20,"paper":20,"created_at":281},3305,"广东写好土特产大文章——粤字号农业品牌产品905个入库 全省农业企业品牌总价值超2500亿元","https:\u002F\u002Fepaper.nfnews.com\u002Fnfdaily\u002Fhtml\u002F202609\u002F23\u002Fcontent_10182158.html","南方日报报道：广东省以粤字号农业品牌培育为基础，以12221市场营销体系打通产销；全省农业企业品牌总价值已超过2500亿元，全省入库粤字号农业品牌目录区域公用品牌123个、创新培优实践点290个、产品品牌905个。农业无人机吊起一篮重达200斤的茶青，不到1分钟就到达山下加工厂。广州市从化区与广东省农科院、华南农业大学合作攻关的荔枝超低温冻眠锁鲜技术实现了鲜荔枝的周年供应。广货行天下2026广东荔枝嘉年华举办以来，省市县各级累计开展农产品营销宣传推介、促消费活动300余场，带动线上线下促销金额超16亿元。","●南方日报记者 王悦阳 彭琳 黄进\n\n秋分，正是梅州蜜柚上市时节。漫山翠绿间，蜜柚压弯枝头，果农穿行树下，剪刀“咔嚓”一声，沉甸甸的柚子落入篮中。采摘下的蜜柚经分拣、贴标、装箱，满载着秋日的甜蜜发往全国各地。\n\n汕头锦沣农机专业合作社的稻米加工车间里，一派五谷丰登的丰收景象。低温烘干、碾磨、色选……工人忙着把刚收好的早稻制成大米，销往全国各地。\n\n再把目光转向2026年“中国农民丰收节”广东主场活动所在地湛江，特呈岛海域的湛江恒兴深海网箱养殖产业园内，深海网箱里不时跃起一条条金鲳鱼。\n\n近年来，广东深入实施“百县千镇万村高质量发展工程”（以下简称“百千万工程”），锚定建设农业强省目标，大力发展岭南特色农产品，扎实做好粤字号“土特产”文章，加快构建粮经饲统筹、农林牧渔并举、产加销贯通、农文旅融合的现代乡村产业体系。\n\n产业蝶变\n\n将“土特产”培育成大产业\n\n乡村振兴，产业为基。\n\n去年，广东出台《关于现代农业产业集群培育行动方案（2025年—2027年）》，提出在全省重点培育一批千亿、百亿与十亿元级的现代农业产业集群。\n\n从湛江的霞山渔人码头乘船出发，半小时疾驰后抵达特呈岛海域的湛江恒兴深海网箱养殖产业园，这里也是全省首个深海网箱产业园。\n\n“这批鱼是今年4月投的苗，到现在5个多月，很快就能起网了。”船停靠在网箱旁，恒兴集团渔业公司生产技术经理林东宁站在网箱栈道上，熟练地抓起一袋饲料撒入水中，原本平静的海面瞬间“沸腾”起来。\n\n近年来，湛江加快培育省级金鲳鱼良种场，从源头破解优质苗种供给的瓶颈，同时大力发展深海养殖。全市深海网箱数量超3650个、大型养殖平台达13个，均占全省60%以上。\n\n因海而兴，向海图强。作为海洋大省，广东海洋渔业成为粤字号“土特产”的一张亮丽名片。2025年，全省水产品总产量997.15万吨，居全国首位。全省水产品总产量、海水鱼养殖产量、鱼虾苗种产量、渔业产值等主要指标连续多年全国第一。预计到2027年全省年海水养殖总产量达440万吨、2030年提升至500万吨、2035年冲刺620万吨，一个万亿级现代化海洋牧场正在加快形成。\n\n9月下旬，走进茂名高州根子镇柏桥村强村公司，一款冻眠荔枝正在上架销售。剥开冻眠荔枝，晶莹的果肉饱满水润，口感和鲜果并无太多差异。柜台上，荔枝干、荔枝酒、荔枝饼等各类荔枝深加工产品整齐陈列，完整勾勒出一颗荔枝从鲜果向多元消费品转化的轨迹。\n\n“我们强村公司由柏桥村村集体100%占股，去年强村公司整体营收突破320万元，荔农人均收入突破5.9万元，村集体收入高达538.26万元。”柏桥村党总支书记何清表示，即便遇上荔枝中小年，依托冻眠产品、深加工与定制化销售，柏桥依然实现销售额逆势上扬，稳住荔农的钱袋子。\n\n世界荔枝看中国，中国荔枝看广东。依靠加工链延伸以及低温冻眠锁鲜技术，岭南荔枝实现了从“一季鲜”到“四季甜”。今年全省荔枝产量130万吨、总产值突破210亿元，实现了减产不减收。\n\n包括荔枝在内，广东计划重点培育粮食、蔬菜、岭南水果等10个千亿级现代农业产业集群、20个百亿元产业集群以及超200个十亿级地方特色产业，构建起“千亿引领、百亿支撑、十亿筑基”的发展格局。\n\n科技赋能\n\n全省农科进步贡献率超74%\n\n科技，已成为广东农业经济增长的重要驱动力。全省农业科技进步贡献率已超74%，连续多年位居全国第一；主要农作物良种覆盖率达98%以上；水稻耕种收综合机械化率达80%以上。\n\n种源是农业的“芯片”。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。\n\n长期以来，广东马铃薯种薯面临“北薯南调”的瓶颈，为了啃下这块硬骨头，广东省农业科学院团队一头扎进适配南方气候的品种培育研究，建起了广东马铃薯种质资源库，收集保存超过1000份优异种质，通过杂交育种、分子标记辅助选择等技术，成功培育出近20个优良品种。这些品种不仅适应了广东的水土，也填补了广东自主培育马铃薯品种的空白，让市场有了更多选择。\n\n科技成果最终要落到田间地头，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\n在潮州饶平县，驻东山镇科技特派员、华南农业大学教授张凌云团队穿梭于茶园、车间，指导茶农采茶做茶。“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。”张凌云介绍。\n\n产业链科技含量的提高，正在打破农产品“丰产不丰收”的困境。\n\n荔枝“一日色变、二日香变、三日味变”，保鲜曾是千年难题。如今，多项保鲜、加工技术的研发推广，实现了荔枝“全年卖、卖全球”。由广州市从化区与广东省农科院、华南农业大学合作攻关的荔枝超低温冻眠锁鲜技术，实现了鲜荔枝的周年供应，有效解决荔枝大年滞销的问题；荔枝深加工产品的开发则解决了荔枝加工品类单一、附加值低等问题，极大提高荔枝产业附加值。\n\n“农业的现代化关系到农村现代化的成色。”广东省农业农村厅相关负责人表示，科技的力量正贯穿广东农业的每一个环节，农业不再只是“看天吃饭”的传统行当，而是有硬核科技支撑的现代产业。\n\n品牌成势\n\n905个“粤字号”产品品牌入库\n\n产业振兴是乡村振兴的基础，品牌建设则是产业升级的“金钥匙”。\n\n广东以“粤字号”农业品牌培育为基础，以“12221”市场营销体系打通产销，以“媒体+”赋能放大营销声量，以“广货行天下”推动农产品出省出海，切实发挥农业品牌在推动农业产业高质量发展中的重要作用，驱动各地特色优势产业转型升级。\n\n9月秋茶采摘季，海拔千米的潮州凤凰山高山茶园，弥漫着独特的馥郁芳香。农业无人机吊起一篮重达200斤的茶青，越过崎岖山路，不到1分钟就到达山下的加工厂。\n\n这捧“飞”出大山的凤凰单丛茶，正是“粤字号”品牌培优工程落地生根的缩影。广东历来重视农业品牌培育工作，全省农业企业品牌总价值已超过2500亿元，全省入库“粤字号”农业品牌目录区域公用品牌123个、创新培优实践点290个、产品品牌905个。\n\n在“广货行天下”的助力下，一大批优质广货跨越山海、走向全国、链接全球，农特产品的品牌溢价能力得到实质性提升。\n\n5月，“广货行天下”2026广东荔枝嘉年华在广州举行，来自全省9个地市的20多家企业展销新鲜荔枝、荔枝新茶饮等产品，平台、采购商、贸易商、加工企业等代表齐聚现场，商讨推动广东荔枝销售全国。\n\n2026年以来，省市县各级累计开展“广货行天下”农产品营销宣传推介、促消费活动300余场，服务超5000家次企业开展广货农产品展示展销，带动线上线下促销金额超16亿元。\n\n市场拓展的同时，“媒体+”赋能行动也为品牌持续注入传播力与连接力。\n\n“来自我们阳西程村的金蚝，肉质肥厚、鲜甜无渣。”8月28日，“阳西优品”山海好货直播间里，程村金蚝、墨鱼饼、红心鲜鸭蛋等阳西特色产品轮番亮相。该活动由南方日报与阳江市阳西融媒联合打造，以“媒体+产业+品牌+市场”为核心，推动阳西本地特色农副产品融湾出海，提升品牌影响力。\n\n2025年7月，省委农办、省委宣传部联合印发《“媒体+”赋能“百千万工程”农产品市场体系建设行动方案（2025—2027年）》。这是全国首个省级层面出台的“媒体+”赋能乡村振兴的政策文件。一年来，全省各地各部门积极拥抱“媒体+”，各大主流媒体主动作为，市场力量、社会机构广泛参与，助力广东“土特产”破圈热销。\n\n记者获悉，《广东省农产品品牌建设五年行动方案》正在征求意见，即将出台。\n\n“百千万工程”实施以来，广东从品牌培优、市场拓展到媒体赋能，推动“粤字号”产品完成从“土特产”到“金字招牌”的系统跃升。农产品品牌建设，必将在推动农业高质量发展中发挥更为突出的作用。","南方日报 2026年09月23日",84,{"impact":30,"substance":91,"depth":31,"authority":266,"freshness":33,"relevant":34,"comment":267},11,"省级官媒对广东农业品牌、海洋牧场与科技赋能的系统性综述，数据翔实、信源多元，具备进入每日精选的价值。",[269],{"name":263,"url":260},[271,272,273,274,275,276],"种业振兴","荔枝保鲜","农业品牌","土特产","海洋牧场","粤字号",[278,279],"粤字号 农业品牌 905个","广东 荔枝 超低温冻眠锁鲜","粤字号农业品牌905个-3305","2026-09-24T00:03:59.728684Z",{"id":283,"title":284,"url":285,"summary":286,"summary_zh":287,"content":20,"source_name":288,"source_url":285,"published_at":23,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":264,"score_detail":289,"sources":291,"tags":293,"search_phrases":298,"slug":301,"view_count":49,"doi":302,"paper":303,"created_at":321},3255,"Grape yield estimation using on-the-fly MIMO millimeter-wave radar at operational field speed: A variety-dependent proof of concept","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112395","Accurate pre-harvest grape yield estimation is a critical challenge in precision viticulture, yet current optical approaches (RGB cameras, LiDAR) are fundamentally limited by foliage occlusion and sensitivity to ambient lighting conditions. This paper presents a ground-based grape yield estimation system using a dual 77 GHz Multiple-Input Multiple-Output (MIMO) Frequency-Modulated Continuous-Wave (FM-CW) radar mounted on a rover operating at an average speed of 1.0 m\u002Fs (3.7 km\u002Fh), matching practical vineyard tractor speeds. Unlike prior radar-based studies conducted in static or slow-moving setups, the proposed pipeline achieves continuous 3D reconstruction of vinerows through digital beamforming in the elevation plane, combined with an IMU-fused Kalman filter for point cloud stabilization on irregular terrain. An experimental campaign was conducted on 136 km of scanned vinerows across seven grape varieties and three phenological growth stages (BBCH 75–89) in a commercial vineyard in Gascony, France. Statistical features extracted from 3D radar echo level images are used to train a Support Vector Regressor (SVR) evaluated in cross-validation. The primary out-of-sample result is a cross-validation Mean Absolute Error (CV MAE) of 31.2% on the full multi-variety dataset without any defoliation, achieved against certified wine-vat bulk weights as the ground truth reference. This figure should be contextualized against the ∼ 24–25% discrepancy observed between portable field weighing plates and vat-certified weights across the same dataset, and against manual pre-harvest estimation errors routinely exceeding 30% in viticultural practice. A sensitivity analysis over physical parameters reveals that grape variety is the dominant −and limiting- source of performance heterogeneity: CV MAE ranges from 7% for Tannat to 69% for Baco, demonstrating that a single global model is insufficient for multi-variety deployment and that variety-specific calibration is a necessary condition for operational use. These results are best understood as an architectural proof of concept: the primary contribution is the demonstration that MIMO digital beamforming removes the speed bottleneck of prior mechanically-scanned radar systems, enabling gapless 3D vinerow reconstruction at practical field speeds. The yield estimation results provide a first quantitative characterization of the system’s sensing capability and its variety-dependent limitations and establish a baseline for future variety-specific model development.","准确的采前葡萄产量估测是精准葡萄栽培中的一项关键挑战，然而当前的光学方法（RGB相机、LiDAR）从根本上受到冠层遮挡和对环境光照条件敏感性的限制。本文提出了一种地基葡萄产量估测系统，采用双77 GHz多输入多输出（MIMO）调频连续波（FM-CW）雷达，搭载于以平均速度1.0 m\u002Fs（3.7 km\u002Fh）行驶的移动平台上，与实际葡萄园拖拉机作业速度相匹配。与先前在静态或慢速移动装置中进行的雷达研究不同，所提出的处理流程通过仰角平面上的数字波束成形实现葡萄行连续三维重建，并结合IMU融合卡尔曼滤波器在不规则地形上实现点云稳定。在法国加斯科尼的一个商业葡萄园中，对七个葡萄品种和三个物候生长期（BBCH 75–89）的136 km扫描葡萄行进行了实验。从三维雷达回波强度图像中提取的统计特征用于训练支持向量回归器（SVR），并通过交叉验证进行评估。主要样本外结果为：在完整多品种数据集上、未进行任何去叶处理的情况下，交叉验证平均绝对误差（CV MAE）为31.2%，以认证酒罐散装重量作为地面真值参考。该数值应结合以下背景加以理解：在同一数据集上，便携式田间称重板与酒罐认证重量之间观察到约24–25%的差异，而葡萄栽培实践中人工采前估测误差通常超过30%。对物理参数的敏感性分析表明，葡萄品种是性能异质性的主要——也是限制性——来源：CV MAE从Tannat的7%到Baco的69%不等，表明单一全局模型不足以支持多品种部署，品种特异性校准是实际应用的必要条件。这些结果最好被理解为一种架构层面的概念验证：主要贡献在于证明了MIMO数字波束成形消除了先前机械扫描雷达系统的速度瓶颈，从而能够在实际田间速度下实现无间隙三维葡萄行重建。产量估测结果首次定量表征了该系统的感知能力及其品种依赖性局限，并为未来","Computers and Electronics in Agriculture",{"impact":31,"substance":62,"depth":92,"authority":32,"freshness":25,"relevant":34,"comment":290},"首次在实用田间车速下用MIMO毫米波雷达实现葡萄产量预估，136公里商业园数据与品种依赖性结论具参考价值。",[292],{"name":288,"url":285},[40,294,295,296,297],"精准农业","葡萄","产量预估","毫米波雷达",[299,300],"MIMO 毫米波雷达 葡萄 产量预估","葡萄园 雷达 三维重建","MIMO毫米波雷达葡萄产量预估-3255","10.1016\u002Fj.compag.2026.112395",{"doi":302,"openalex_id":304,"authors":305,"venue":288,"cited_by_count":49,"oa_url":285,"card":315,"direction":319,"ingested_from":255},"W7214043753",[306,309,312],{"name":307,"orcid":308},"Etienne Dedic","https:\u002F\u002Forcid.org\u002F0000-0002-1414-019X",{"name":310,"orcid":311},"Dominique Henry","https:\u002F\u002Forcid.org\u002F0000-0002-6016-140X",{"name":313,"orcid":314},"H. Aubert","https:\u002F\u002Forcid.org\u002F0000-0002-6113-0648",{"tldr":316,"method":317,"finding":318,"direction":319,"opportunity":320},"用双77GHz MIMO雷达在1m\u002Fs车速下重建葡萄藤行并估算产量，验证品种依赖性。","双77GHz MIMO FMCW雷达、数字波束成形、IMU卡尔曼滤波、SVR，1","全品种交叉验证MAE为31.2%，但品种间差异大（Tannat 7%至Baco 69%），需按品种校","农业遥感与作物表型","可研究品种自适应建模与迁移学习，解决多品种部署时单一模型失效问题，并融合光学与雷达数据。","2026-09-23T23:30:01.516727Z",{"id":323,"title":324,"url":325,"summary":326,"summary_zh":20,"content":327,"source_name":328,"source_url":20,"published_at":329,"category":24,"cover_url":20,"hotness":25,"is_selected":88,"score":330,"score_detail":331,"sources":334,"tags":336,"search_phrases":340,"slug":343,"view_count":49,"doi":20,"paper":20,"created_at":344},3285,"2026年中国农民丰收节全国主场活动落地襄阳——9-23 农历秋分全国主场启幕 鄂北粮仓慧种地转型全面展示","https:\u002F\u002Fhubei.gov.cn\u002Fhbfb\u002Fszsm\u002F202609\u002Ft20260922_6019905.shtml","9月23日第九个中国农民丰收节全国主场活动在湖北襄阳枣阳市环城街道东郊村举办，主题丰收开新局实干促振兴。这是中国农民丰收节设立以来全国主场首次落地鄂北。襄阳粮食播种面积稳定在1190万亩、粮食产量占全省近五分之一，22连丰；累计建成高标准农田657万亩，培育省部级以上农业创新平台104个。襄阳以科技、绿色、质量、品牌四个农业作答：襄州区全省首个无人化试验示范农场1100亩配套智慧农机162台套实现稻油稻麦全程无人化作业；8000多台农机具安装北斗智能驾驶系统；一管四控数字化平台带动亩增产5%以上；水肥一体化滴灌预计全生育期节水30%、节肥20%、亩增产35%以上；2025年东郊村人均可支配收入30123元；枣阳皇桃品牌价值达147亿元。","襄阳市襄州区龙王镇孙庙村，金灿灿的晚稻迎来收割季，农机下田抢收稻谷。从 “汗水农业” 迈向 “智慧农业”，鄂北粮仓襄阳持续稳固百亿斤粮食产能，喜迎第九个中国农民丰收节。（刘曙松 摄）\n\n9月23日，第九个中国农民丰收节全国主场活动将在枣阳启幕。\n\n这场国家级丰收盛典首次落地湖北，为何选址襄阳？\n\n粮食播种面积稳定在1190万亩、全省唯一百亿斤粮食产能大市、实现“二十二连丰”……\n\n这份丰收答卷背后，一场从“汗水农业”向“智慧农业”的深刻转型，正在重新定义鄂北粮仓的成色。\n\n襄阳以数字赋能重塑农业生产方式的探索，正是湖北践行大农业观、大食物观，加快建设现代农业强省的生动缩影。\n\n**智能装备：从“会种地”到“慧种地”**\n\n秋收时节，位于襄州区的全省首个无人化试验示范农场，一台台大马力拖拉机驶过田野，驾驶室却空无一人。\n\n依托北斗监测及自动驾驶系统，这些农机沿着预设轨迹直线行进、精准调头，无需人工操控，便有条不紊完成田间作业。\n\n农场负责人杭世伟介绍，该项目依托汇吉兴农机专业合作社建设，以北斗导航技术为支撑，无人农场面积共1100亩，配套各类智慧农机162台套，成功实现稻油、稻麦“耕种管收”全程无人化作业。\n\n在枣阳市熊集镇连片稻田里，3台联合收割机匀速穿梭作业，收割、脱粒、清选、秸秆粉碎还田一气呵成，田边运粮车同步接力转运，实现粮食收运全程不落地。\n\n“今年种了200多亩优质稻，亩产预计超过1600斤，智能化种地既省心又高产。”种粮大户杜小伟满心欢喜。\n\n9月以来，熊集镇调配200余台加装北斗定位系统的农机设备投入秋收一线，通过规范低留茬、控速度作业标准，全镇机收损失率控制在3%以内。\n\n“装了北斗定位的收割机，调好参数就能精细化收割，大幅减少落粒损耗，一亩地能多收几十斤粮食。”农机手张浩说。\n\n从“会种地”到“慧种地”，一字之变，反映的是襄阳农业机械化、智能化装备体系的全面升级。\n\n目前，襄阳农机总动力达834.99万千瓦，主要农作物机械化作业率达90.07％，两项指标均稳居全省第一。\n\n**精准调控：从“凭经验”到“靠数据”**\n\n9月20日，枣阳市东郊村千亩高标准农田里，连片水稻长势正旺。\n\n稻田上空，植保无人机掠过，十几分钟就完成一亩地的“一喷多促”作业。\n\n“以前，施肥全凭感觉，现在无人机一飞，手机里就有了‘处方’，省事还省肥。”种粮大户张启胜说。\n\n这套“处方”，来自多光谱无人机巡田。\n\n枣阳市农业技术推广中心农艺师郭贵东介绍，智慧农田平台根据多光谱测量结果生成苗情分布图，按照不同长势等级，采取变量作业，实现肥料精准追施、病虫精准防治，效率是人工的50倍。\n\n在位于襄州区的湖北绿神农业科技有限公司稻麦轮作“超吨粮”基地，农田遥感监测平台全天候采集分析作物长势、土壤墒情、病虫害等数据，并提出农田管理意见。有了“数字大脑”，近3000亩农田仅需7个人管理，每亩地增产8%、降本380元。\n\n如今，襄阳已建成高标准农田670.3万亩，占永久基本农田的79.2%。建成后的高标准农田，粮食亩均综合产能普遍提升10%至20%，每亩节本增效200元至500元。\n\n“襄阳把物联网和大数据用到种地上，这不仅是良法，更是现代化农业的标配。”今年7月，全国粮油生产政策宣贯暨夏种夏管生产现场会在襄阳召开，与会代表实地观摩后纷纷点赞。\n\n从“凭经验”到“靠数据”，襄阳用数字技术把每一寸耕地的潜力都“吃干榨净”，让丰收从偶然变成必然。\n\n**全链保障：从“丰收在田”到“丰收在手”**\n\n粮食丰收，不仅看田里的长势，更看能不能稳稳收进仓里。\n\n今夏，襄阳遭遇连阴雨天气，3.6万台农机、4万余名农机手昼夜抢收，479处烘干点、1658台烘干机满负荷运转，全市夏粮总产39.944亿斤，较去年增加260万斤。\n\n烘得干，粮才安。\n\n在位于襄城区的襄阳绿谷农业开发有限公司粮食烘干车间，刚运到的湿稻谷经输送、烘干、清杂、出仓，不到20个小时，水分便控制在国标13.5%以下，损耗从传统晾晒的5%以上降至1%以下。\n\n运营部负责人朱兵说：“随来随卸、随卸随烘，这个秋收季已烘干入库水稻近400吨。”\n\n襄阳积极推广“共享烘干”模式，依托乡镇农事服务中心和大型合作社为小农户提供代烘服务，避免“雨天收粮、霉变损失”的风险。\n\n储得好，价才稳。\n\n在老河口华粮粮食储备有限公司，仓内每处粮堆的温度、湿度、虫害情况在电脑屏幕上实时跳动。\n\n总经理张海涛介绍，仓储管理、轮换出入库等环节已实现全程信息化、智能化。\n\n让每一粒粮食都住进“智慧空调房”，物联网技术正重构襄阳各大粮库的仓储模式。从“靠天晒粮”到“随到随烘”、从“大堆存放”到“智慧储粮”，襄阳以环环相扣的全链保障，把“丰收在田”稳稳变成“丰收在手”。\n\n放眼荆楚田野，这样的蝶变，正为新时代“鱼米之乡”写下生动注脚。\n\n粮食总产连续13年站稳500亿斤台阶，淡水产品产量连续30年稳居全国第一，林下经济经营面积超过2800万亩、综合产值超775亿元……湖北正依托山水林田的丰厚家底，以更大担当端稳端牢“中国饭碗”。（张源）\n\n编辑：汪 丽\n\n责编：李 茜\n\n审核：陈 勇\n\n姚 盼","湖北省人民政府门户网站 2026年09月22日","2026-09-22T01:06:00Z",83,{"impact":61,"substance":332,"depth":151,"authority":152,"freshness":93,"relevant":34,"comment":333},20,"国家级丰收节主场首次落地湖北，系统展示襄阳从智能装备、精准调控到全链保障的智慧农业转型，数据与信源扎实，值得进入每日精选。",[335],{"name":328,"url":325},[39,40,337,338,339,43],"无人农场","北斗导航","高标准农田",[341,342],"襄阳 中国农民丰收节 主场","襄阳 无人农场 北斗","襄阳中国农民丰收节主场-3285","2026-09-24T00:03:56.561075Z",{"id":346,"title":347,"url":348,"summary":349,"summary_zh":350,"content":20,"source_name":288,"source_url":348,"published_at":225,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":330,"score_detail":351,"sources":353,"tags":355,"search_phrases":359,"slug":362,"view_count":49,"doi":363,"paper":364,"created_at":384},3257,"Blueberry flow and mass estimation from harvester conveyor videos via foundation-model-assisted labeling and vision-based sensing","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112432","Despite rising labor costs and growing labor shortages, adoption of machine harvesting in fresh market blueberry production has been limited by issues such as high rates of bruising and the significant loss of fruits on the ground. Machine settings strongly affect fruit quality and harvesting performance, yet they are manually configured based on operator experience, with no real-time performance feedback. Towards addressing these limitations, this paper presents a sensing proof-of-concept for analyzing berry flow through the harvester by estimating the pixel-wise proportion of blue vs green berries and volumetric flow rate from overhead RGB-D images of the harvester’s conveyor. An automated labeling pipeline combining a domain-specific YOLOv8 patch detector with SAM2-based mask generation was developed to generate a realistic large-scale berry dataset from unlabeled images captured during commercial over-the-row blueberry harvesting operations. Compared to a baseline SegFormer model trained on a smaller dataset of manually annotated images, our fine-tuned SegFormer – trained and validated on the large-scale automatically generated dataset – achieves superior performance, with green berry IoU improving from 0.377 to 0.817 and recall increasing from 0.414 to 0.911. A scene-level YOLOv8-l detection model trained and evaluated on the same dataset achieves mAP(50-95) of 0.966 and 0.898 for blue and green berries, respectively. Both models’ performance is further confirmed by an independent evaluation on a manually annotated subset of the validation images. We also compared two approaches for predicting harvest yields across five machine-setting trials: a depth-based method using the RGB-D sensor and a detection-based method using only RGB images, achieving R 2 = 0.989 and R 2 = 0.894 , respectively, against ground-truth load cell measurements from these trials. To support future research, we publicly release our datasets and models.","尽管劳动力成本上升且劳动力短缺日益加剧，但鲜食蓝莓生产中机器采收的采用仍受到果实瘀伤率高和落地果实损失严重等问题的限制。机器设置对果实品质和采收性能有很大影响，但目前仍依赖操作人员经验进行手动配置，且没有实时性能反馈。针对这些局限，本文提出了一种传感概念验证方法，通过估计采收机传送带上方RGB-D图像中蓝莓与绿果的逐像素比例以及体积流量，来分析通过采收机的果实流。我们开发了一种自动标注流程，将领域特定的YOLOv8小块检测器与基于SAM2的掩膜生成相结合，从商业跨行蓝莓采收作业期间采集的无标注图像中生成逼真的大规模蓝莓数据集。与在较小规模人工标注图像数据集上训练的基线SegFormer模型相比，我们经过微调的SegFormer——在大规模自动生成数据集上训练和验证——取得了更优性能，绿果IoU从0.377提升至0.817，召回率从0.414提升至0.911。在同一数据集上训练和评估的场景级YOLOv8-l检测模型，对蓝莓和绿果分别达到0.966和0.898的mAP(50-95)。两个模型的性能还通过在验证图像人工标注子集上的独立评估得到进一步确认。我们还比较了在五次机器设置试验中预测采收产量的两种方法：使用RGB-D传感器的基于深度的方法和使用仅RGB图像的基于检测的方法，相对于这些试验中来自称重传感器的真实测量值，分别达到R² = 0.989和R² = 0.894。为支持未来研究，我们公开了数据集和模型。",{"impact":31,"substance":62,"depth":92,"authority":32,"freshness":33,"relevant":34,"comment":352},"该研究提出基于基础模型辅助标注与视觉传感的蓝莓流量与产量估计方法，方法新颖、数据规模大且公开数据集与模型，对智慧农业与农业机器人领域有较高参考价值。",[354],{"name":288,"url":348},[40,41,356,357,358],"农业机器人","机器视觉","蓝莓采收",[360,361],"蓝莓采收 机器视觉 产量估计","蓝莓收获机 传送带 视觉检测","蓝莓采收机器视觉产量估计-3257","10.1016\u002Fj.compag.2026.112432",{"doi":363,"openalex_id":365,"authors":366,"venue":288,"cited_by_count":49,"oa_url":348,"card":379,"direction":191,"ingested_from":255},"W7214013690",[367,369,371,373,376],{"name":368,"orcid":20},"A. M. Aahad",{"name":370,"orcid":20},"Pico Sankari",{"name":372,"orcid":20},"Wei Q. Yang",{"name":374,"orcid":375},"Siniša Todorović","https:\u002F\u002Forcid.org\u002F0000-0001-5793-5921",{"name":377,"orcid":378},"Joseph R. Davidson","https:\u002F\u002Forcid.org\u002F0000-0003-4388-2210",{"tldr":380,"method":381,"finding":382,"direction":191,"opportunity":383},"用收割机传送带RGB-D视频估计蓝莓流量与质量，并公开数据集和模型。","YOLOv8+SAM2自动标注，SegFormer分割，RGB-D深度与检测法估","自动标注使绿果IoU从0.377升至0.817，深度法估产R²达0.989。","可延伸至收割机参数实时闭环调控，用视觉反馈优化机器设置以减损提质。","2026-09-23T23:30:01.713624Z",{"id":386,"title":387,"url":388,"summary":389,"summary_zh":20,"content":20,"source_name":390,"source_url":20,"published_at":122,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":391,"score_detail":392,"sources":394,"tags":396,"search_phrases":400,"slug":403,"view_count":49,"doi":20,"paper":404,"created_at":411},3323,"基于空间分辨光谱的鲜食玉米含水率和硬度MaMoNet检测模型——融合Mamba状态空间模型与多门专家混合机制","https:\u002F\u002Fk.sina.com.cn\u002Farticle_5953466437_162dab0450670bdama.html","《智慧农业（中英文）》2026年第4期。许敏、赵鑫、陈艳萍、朱启兵、黄敏（江南大学\u002F江苏省农科院）以带苞叶鲜食玉米为研究对象，构建多通道可见光-近红外空间分辨光谱采集系统，获取玉米样本的多通道光谱数据，并提出一种融合Mamba状态空间模型与多门专家混合(MMoE)机制的多任务预测网络——MaMoNet(Mamba-MMoE Network)。MaMoNet在测试集上玉米籽粒含水率预测的决定系数R²达到了0.91，硬度预测R²达到了0.89，均优于对比模型。消融实验进一步证明Mamba模块在建模光谱长程依赖关系方面具有显著优势，以及MMoE机制能够有效缓解多任务学习中任务间特征竞争问题。","《智慧农业（中英文）》2026年第4期",81,{"impact":31,"substance":91,"depth":31,"authority":32,"freshness":33,"relevant":34,"comment":393},"核心期刊论文，方法新颖且指标可靠，对农产品无损检测有实质参考价值。",[395],{"name":390,"url":388},[40,41,397,398,399],"鲜食玉米","光谱检测","多任务学习",[401,402],"江南大学 鲜食玉米 含水率","MaMoNet 玉米 硬度","江南大学鲜食玉米含水率-3323",{"doi":20,"openalex_id":20,"authors":405,"venue":20,"cited_by_count":49,"oa_url":20,"card":406,"direction":319,"ingested_from":114},[],{"tldr":407,"method":408,"finding":409,"direction":319,"opportunity":410},"提出MaMoNet网络，用空间分辨光谱检测鲜食玉米含水率和硬度。","多通道可见光-近红外空间分辨光谱，融合Mamba与MMoE多任务网络。","含水率R²达0.91、硬度R²达0.89，优于对比模型，Mamba与MMoE均有效。","可探索Mamba在多作物多品质指标无损检测中的泛化性及田间在线部署。","2026-09-24T00:04:02.557420Z",{"id":413,"title":414,"url":415,"summary":416,"summary_zh":417,"content":20,"source_name":418,"source_url":415,"published_at":225,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":391,"score_detail":419,"sources":421,"tags":423,"search_phrases":427,"slug":430,"view_count":49,"doi":431,"paper":432,"created_at":452},3277,"Downscaling of SMAP Soil Moisture Based on the Transformer Algorithm in Anhui Province","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs18193272","Soil moisture (SM) is critical for climate, water, and agriculture, but Soil Moisture Active Passive (SMAP) passive microwave products have coarse resolution, limiting regional applications. This study develops an SM downscaling framework based on Transformer and its variants (PatchTST and iTransformer), integrating multi-source satellite and groundwater data to generate 1 km daily SM products (2015–2022). Compared with Random Forest (RF), Long Short-Term Memory (LSTM), and Convolutional Neural Network–LSTM (CNN-LSTM), Transformer and its variants achieve superior accuracy and generalization. Validated against in situ measurements and SMCI1.0, the Transformer-downscaled SM product achieved the best accuracy with ubRMSE = 0.0372 m3\u002Fm3 and RMSE = 0.0591 m3\u002Fm3. The downscaled SM dataset not only captured finer spatial details but also preserved the spatial patterns and seasonal dynamics of the original SMAP product and showed good responsiveness to precipitation events. Feature importance analysis revealed that, aside from precipitation, the diurnal land surface temperature difference had a greater impact on SM than individual daytime or nighttime land surface temperature, ranking just below vegetation indices and soil texture factors, while groundwater level showed higher importance than elevation and surface temperature. This study confirms the effectiveness of Transformer-based models for SM spatial downscaling, providing a novel framework integrating remote sensing and deep hydrological information to generate accurate 1 km SM products.","土壤水分（SM）对气候、水资源和农业至关重要，但土壤水分主动被动（SMAP）被动微波产品分辨率较粗，限制了区域应用。本研究构建了一个基于Transformer及其变体（PatchTST和iTransformer）的土壤水分降尺度框架，融合多源卫星和地下水数据，生成1 km日尺度土壤水分产品（2015—2022年）。与随机森林（RF）、长短期记忆网络（LSTM）和卷积神经网络—长短期记忆网络（CNN-LSTM）相比，Transformer及其变体取得了更高的精度和泛化能力。利用站点实测数据和SMCI1.0进行验证，Transformer降尺度土壤水分产品精度最优，ubRMSE = 0.0372 m³\u002Fm³，RMSE = 0.0591 m³\u002Fm³。降尺度土壤水分数据集不仅捕捉到了更精细的空间细节，还保留了原始SMAP产品的空间格局和季节动态，并对降水事件表现出良好的响应。特征重要性分析表明，除降水外，昼夜地表温差对土壤水分的影响大于单独的白天或夜间地表温度，其重要性仅次于植被指数和土壤质地因子，而地下水埋深的重要性高于高程和地表温度。本研究证实了基于Transformer的模型在土壤水分空间降尺度中的有效性，为融合遥感和深层水文信息生成准确的1 km土壤水分产品提供了一种新框架。","Remote Sensing",{"impact":31,"substance":91,"depth":31,"authority":32,"freshness":33,"relevant":34,"comment":420},"基于Transformer的SMAP土壤水分1km降尺度研究，方法新颖、验证充分，对区域农业旱情监测有实用价值。",[422],{"name":418,"url":415},[40,41,424,425,426],"深度学习","遥感","土壤墒情",[428,429],"SMAP 土壤水分 降尺度","Transformer 土壤水分 安徽","SMAP土壤水分降尺度-3277","10.3390\u002Frs18193272",{"doi":431,"openalex_id":433,"authors":434,"venue":418,"cited_by_count":49,"oa_url":415,"card":447,"direction":319,"ingested_from":255},"W7208807695",[435,437,439,441,443,445],{"name":436,"orcid":20},"Yuyang Fan",{"name":438,"orcid":20},"Jianwei Ma",{"name":440,"orcid":20},"Mengmeng Li",{"name":442,"orcid":20},"Changqing Ke",{"name":444,"orcid":20},"Bin Cheng",{"name":446,"orcid":20},"Zheng Duan",{"tldr":448,"method":449,"finding":450,"direction":319,"opportunity":451},"基于Transformer及变体融合多源卫星与地下水数据，将SMAP土壤湿度降尺度至1km日尺度。","Transformer、PatchTST、iTransformer，融合多源卫星","Transformer降尺度产品精度最优（ubRMSE=0.0372），保留原产品时空格局并响应降水","可探索Transformer降尺度产品在区域干旱监测、灌溉决策及作物估产中的耦合应用。","2026-09-23T23:30:19.132307Z",{"id":454,"title":455,"url":456,"summary":457,"summary_zh":458,"content":20,"source_name":224,"source_url":456,"published_at":23,"category":87,"cover_url":20,"hotness":25,"is_selected":88,"score":391,"score_detail":459,"sources":461,"tags":463,"search_phrases":467,"slug":470,"view_count":49,"doi":471,"paper":472,"created_at":492},3263,"Identifying drought-responsive candidate genes in root and shoot tissues of wheat (Triticum aestivum L.) through RNA sequencing, cluster analysis, weighted gene co-expression network analysis, and machine learning models","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1952456","Drought stress severely affects the growth, development, and yield formation of wheat. However, the differentiated regulatory mechanisms of wheat roots and shoots during drought adaptation remain to be further analyzed. Therefore, this study used RNA-seq datasets of roots and shoots from multiple wheat varieties, combined with differential expression analysis, Gene Ontology (GO) enrichment analysis, clustering analysis, weighted gene co-expression network analysis (WGCNA), and machine learning were used to characterize drought-responsive transcriptional changes. Differential expression analysis identified 90 and 3,991 differentially expressed genes (DEGs) in roots under DS1 and DS2 respectively, compared with 34 and 1,940 DEGs in shoots. Functional enrichment analysis indicated that root DEGs were mainly involved in root growth, cell wall remodeling, water transport, and osmotic adjustment processes, whereas shoot DEGs are mainly enriched in processes related to stomatal regulation, photosynthesis, lipid metabolism, and oxidative stress responses. WGCNA identified 18 and 19 co-expression modules in roots and shoots, respectively, among which the yellow module was significantly correlated with the response to drought stress in root and shoot tissues. To further screen drought-responsive candidate genes from these modules, we compared multiple machine learning models. The XGBoost model achieved the highest and AUC in both roots and shoots. Combined with SHAP feature contribution analysis, 30 drought-responsive candidate genes with high discriminatory power were identified separately in roots and shoots. Analysis of cis -acting elements in candidate gene promoters revealed abundant drought- and stress-responsive elements, including MYB, G-box, ABRE, MYC, MBS, and LTR. MYB (183 in roots and 164 in shoots), G-box (168 and 98), and ABRE (148 and 86) were particularly abundant, and several candidate genes contained more than five ABRE copies in their promoters, suggesting potential involvement in ABA-mediated drought responses. This study reveals the different transcriptional response processes of wheat roots and shoots under drought stress, and identifies key co-expression modules and core candidate genes through WGCNA combined with XGBoost and SHAP analysis. These findings provide a basis for understanding organ-specific molecular responses to drought stress and offer potential targets for improving drought tolerance in wheat.","干旱胁迫严重影响小麦的生长发育和产量形成。然而，小麦根系和地上部在干旱适应过程中的差异化调控机制仍有待深入解析。因此，本研究利用多个小麦品种根系和地上部的RNA-seq数据集，结合差异表达分析、基因本体（GO）富集分析、聚类分析、加权基因共表达网络分析（WGCNA）和机器学习方法，表征干旱响应转录变化。差异表达分析在DS1和DS2条件下分别鉴定出根系中90个和3,991个差异表达基因（DEGs），而地上部中分别为34个和1,940个DEGs。功能富集分析表明，根系DEGs主要参与根系生长、细胞壁重塑、水分运输和渗透调节过程，而地上部DEGs主要富集于气孔调控、光合作用、脂质代谢和氧化胁迫响应相关过程。WGCNA在根系和地上部中分别鉴定出18个和19个共表达模块，其中黄色模块与根系和地上部组织对干旱胁迫的响应显著相关。为进一步从这些模块中筛选干旱响应候选基因，我们比较了多种机器学习模型。XGBoost模型在根系和地上部中均取得了最高的AUC。结合SHAP特征贡献分析，分别在根系和地上部中鉴定出30个具有高判别力的干旱响应候选基因。候选基因启动子中的顺式作用元件分析揭示了丰富的干旱和胁迫响应元件，包括MYB、G-box、ABRE、MYC、MBS和LTR。其中MYB（根系183个，地上部164个）、G-box（168个和98个）和ABRE（148个和86个）尤为丰富，且多个候选基因的启动子中含有超过5个ABRE拷贝，表明其可能参与ABA介导的干旱响应。本研究揭示了小麦根系和地上部在干旱胁迫下不同的转录响应过程，并通过WGCNA结合XGBoost和SHAP分析鉴定了关键共表达模块和核心候选基因。这些发现为理解干旱胁迫的器官特异性分子响应提供了基础，并为提高小麦耐旱性提供了潜在靶点。",{"impact":31,"substance":91,"depth":31,"authority":63,"freshness":25,"relevant":34,"comment":460},"该研究结合多组学与机器学习挖掘小麦抗旱候选基因，方法新颖、数据扎实，对分子育种有参考价值，值得进入每日精选。",[462],{"name":224,"url":456},[41,271,464,465,466],"基因挖掘","作物育种","小麦抗旱",[468,469],"小麦 抗旱基因 RNA测序","小麦 根系 地上部 干旱响应","小麦抗旱基因RNA测序-3263","10.3389\u002Ffsufs.2026.1952456",{"doi":471,"openalex_id":473,"authors":474,"venue":224,"cited_by_count":49,"oa_url":456,"card":487,"direction":191,"ingested_from":255},"W7214062209",[475,477,480,482,484],{"name":476,"orcid":20},"Tianle Ji",{"name":478,"orcid":479},"Baoyue Cui","https:\u002F\u002Forcid.org\u002F0009-0000-5881-9682",{"name":481,"orcid":20},"Jinjie Yin",{"name":483,"orcid":20},"Xianyong Meng",{"name":485,"orcid":486},"Jun Yan","https:\u002F\u002Forcid.org\u002F0000-0001-6883-8529",{"tldr":488,"method":489,"finding":490,"direction":191,"opportunity":491},"通过RNA-seq、WGCNA和XGBoost-SHAP分析，鉴定小麦根和茎中响应干旱的候选基因。","RNA-seq、差异表达、WGCNA、XGBoost与SHAP特征分析。","根和茎干旱响应机制不同，各鉴定出30个候选基因，启动子富含MYB、G-box和ABRE元件。","可结合多组学与深度学习构建器官特异性干旱调控网络，并开展候选基因功能验证。","2026-09-23T23:30:07.062126Z"]