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平台等联合攻关，依托巴西家庭农业场景开展技术验证与成果转化，打造智慧农业南南合作标杆。\n\n近日，江苏省农业科学院与巴西农牧业研究公司(Embrapa)、南京农业大学、国机数科、国际民众合作协会共同签署合作谅解备忘录，携手共建“中国—巴西人工智能应用合作中心”，以科技创新赋能全球粮食安全与农业现代化。江苏省农科院党委委员、副院长孙洪武出席签约仪式并作主旨发言。\n\n孙洪武重点介绍了江苏省农科院在科技服务与国际合作方面的工作成效。他建议合作各方应落实好人员互访、专家考察、联合研讨等任务，聚焦中小型智能农机、农业AI平台、作物生长模型等方向开展联合攻关，建设好智慧农机服务中心示范点，搭建好人员交流桥梁，携手推进合作中心建设，为深化中巴农业科技合作、保障全球粮食安全、推动农业现代化贡献力量。\n\n巴西农牧业研究公司总裁席尔维娅·马苏鲁哈介绍，Embrapa是拉美地区最大的国家级公立农业科研机构，巴西家庭农户占比超七成，热带农业种植与生产场景丰富，拥有成熟的农业试点研发体系。她期待深度依托合作中心，与包括江苏省农业科学院在内的中方单位深化协作，开展田间技术验证、农业数据共享与技术成果转化，打造金砖农业合作标杆案例。\n\n中国—巴西人工智能应用合作中心将深度整合产学研优势资源，以巴西家庭农业实际应用场景为需求牵引，以中方智慧农业先进技术为重要支撑，推进中巴双方在联合科研攻关、示范基地建设、人才交流培养等方面实现双向赋能、双向落地，探索形成可复制、可推广的智慧农业南南合作新模式。\n\n引用： 共建中国—巴西人工智能应用合作中心 助力智慧农业南南合作 江苏省农业科学院 [引用日期：2026年10月8日]\n\n本文系转载，转发此文目的在于促进信息交流，不存在盈利性目的，此文观点与本站立场无关，不承担任何责任，不做任何投资和交易根据。如无意侵犯媒体或个人知识产权请告知我们，我们将在第一时间做删除处理。\n\n上一篇：混动争锋、沃野竞技！200马力及以上混合动力拖拉机田间实地试验验证活动即将举行","农业商情网 2026-10-08","2026-10-08T00:00:00Z",73,{"impact":157,"substance":17,"depth":18,"authority":45,"freshness":85,"relevant":21,"comment":201},"省级科研机构牵头的中巴智慧农业国际合作，聚焦智能农机与农业AI平台，具行业示范价值，但属签约启动阶段、落地成果尚待观察。",[203],{"name":197,"url":194},[27,29,105,205,206],"南南合作","中巴合作",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":210},{"candidates":211,"agricultural_evidence":46},[212,216,220],{"code":32,"score":53,"supported":46,"title":213,"abstract":214,"tags":215},[],[48],[105],{"code":72,"score":53,"supported":46,"title":217,"abstract":218,"tags":219},[],[27],[27],{"code":52,"score":21,"supported":14,"title":221,"abstract":222,"tags":223},[],[],[29],[225,226],"江苏省农科院 Embrapa 人工智能","农业人工智能 中巴合作 南南合作 智慧农业","江苏省农科院Embrapa人工智能-4768","2026-10-13T00:08:35.638471Z",{"id":230,"title":231,"url":232,"summary":233,"summary_zh":234,"content":8,"source_name":235,"source_url":232,"published_at":236,"category":237,"cover_url":8,"hotness":238,"is_selected":14,"score":239,"score_detail":240,"sources":243,"tags":248,"primary_topic":253,"secondary_topics":258,"classification":265,"search_phrases":313,"slug":316,"view_count":21,"doi":317,"paper":318,"created_at":330},4573,"APPLICATION OF ARTIFICIAL INTELLIGENCE AND AUTOMATION TECHNOLOGIES IN MODERN AGRICULTURAL MACHINERY","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23255982","The rapid development of artificial intelligence (AI), robotics, computer vision, Internet of Things (IoT), satellite navigation, remote sensing, and autonomous control systems is transforming the design and operation of modern agricultural machinery. Agricultural machinery is increasingly evolving from conventional mechanical equipment into intelligent cyber-physical systems capable of sensing field conditions, processing large volumes of data, making operational decisions, and executing agricultural tasks with limited human intervention. This article examines the application of artificial intelligence and automation technologies in tractors, harvesters, sprayers, robotic platforms, unmanned aerial vehicles, and other agricultural machinery. The study is based on a systematic analysis of scientific publications, international institutional reports, and documented agricultural technology adoption data. Particular attention is given to autonomous navigation, machine vision, precision spraying, variable-rate application, crop monitoring, yield prediction, robotic weeding, harvesting, and safety systems. Evidence from the United States demonstrates substantial growth in precision-agriculture adoption: automated guidance systems were used on more than half of the acreage planted to several major crops, while in 2023 guidance autosteering was used by 52 percent of midsize farms and 70 percent of large-scale crop-producing farms. Scientific literature also demonstrates the growing role of machine learning in yield estimation, nitrogen management, disease detection, and robotic perception. However, high acquisition costs, inadequate rural connectivity, data governance issues, cybersecurity, technical complexity, and safety risks remain significant barriers. The study concludes that AI-enabled agricultural machinery can contribute to higher operational efficiency, more precise input application, reduced operator fatigue, improved resource management, and greater agricultural sustainability, provided that technological development is accompanied by appropriate infrastructure, human-capacity development, interoperability standards, and safety regulation.","人工智能（AI）、机器人技术、计算机视觉、物联网（IoT）、卫星导航、遥感及自主控制系统的快速发展，正在深刻改变现代农业机械的设计与运行方式。农业机械正日益从传统机械设备演变为智能信息物理系统，能够感知田间条件、处理海量数据、做出作业决策，并在有限人工干预下执行农业任务。本文探讨了人工智能与自动化技术在拖拉机、联合收割机、喷雾机、机器人平台、无人机及其他农业机械中的应用。研究基于对科学文献、国际机构报告及已记录的农业技术采用数据的系统分析。重点关注自主导航、机器视觉、精准喷雾、变量施用、作物监测、产量预测、机器人除草、收获及安全系统。来自美国的证据表明，精准农业的采用率大幅增长：自动导航系统已应用于多种主要作物一半以上的种植面积，而2023年，52%的中型农场和70%的大型作物生产农场使用了导航自动转向技术。科学文献也表明，机器学习在产量估算、氮素管理、病害检测和机器人感知中的作用日益增强。然而，高昂的购置成本、农村网络连接不足、数据治理问题、网络安全、技术复杂性及安全风险仍是重要障碍。研究结论认为，在技术发展的同时配套适当的基础设施、人力能力建设、互操作性标准和安全监管，人工智能赋能的农业机械能够有助于提高作业效率、实现更精准的投入施用、减轻操作人员疲劳、改善资源管理并增强农业可持续性。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-09T00:00:00Z","论文",25,81,{"impact":157,"substance":241,"depth":17,"authority":100,"freshness":20,"relevant":21,"comment":242},20,"系统梳理AI与自动化在农机领域应用的综述性论文，含美国精准农业采纳率等实证数据，对智慧农业主题聚合有较高参考价值。",[244,245],{"name":235,"url":232},{"name":246,"url":247},"International Bulletin of Engineering and Technology","https:\u002F\u002Finternationalbulletins.com\u002Fintjour\u002Findex.php\u002Fibet\u002Farticle\u002Fview\u002F2468",[27,29,249,250,251,252],"农业机器人","农业物联网","精准农业","自动驾驶农机",{"code":52,"slug":254,"name":255,"path":256,"parent_code":257},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[259,260],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":261,"slug":262,"name":263,"path":264,"parent_code":257},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":39,"locked":14,"version":40,"method":41,"evidence":266},{"candidates":267,"agricultural_evidence":46},[268,277,283,290,297,302,308],{"code":52,"score":17,"supported":46,"title":269,"abstract":271,"tags":276},[270],"artificial intelligence",[272,273,274,270,275],"机器学习","计算机视觉","machine learning","computer vision",[29],{"code":32,"score":158,"supported":46,"title":278,"abstract":280,"tags":282},[279],"agricultural 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o'g'li",{"tldr":324,"method":325,"finding":326,"direction":327,"opportunity":328},"系统综述AI与自动化技术在现代农机中的应用现状、效益与障碍。","系统分析科学文献、国际机构报告及美国精准农业采用数据。","AI农机可提升效率与可持续性，但成本、连接性、数据治理与安全仍是主要障碍。","智慧农业 \u002F 农业物联网","可研究低成本AI农机方案、农村连接与数据治理标准，及人机协同安全监管框架。","openalex","2026-10-10T23:30:13.826410Z",{"id":332,"title":333,"url":334,"summary":335,"summary_zh":8,"content":8,"source_name":336,"source_url":8,"published_at":337,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":338,"score_detail":339,"sources":341,"tags":343,"primary_topic":347,"secondary_topics":348,"classification":349,"search_phrases":386,"slug":389,"view_count":21,"doi":8,"paper":8,"created_at":390},4469,"佳家农农服APP服务佳木斯及周边超6万农户 覆盖耕地超700万亩","https:\u002F\u002Ffinance.people.com.cn\u002FBIG5\u002Fn1\u002F2026\u002F1005\u002Fc1004-40809500.html","佳木斯国家农高区联合中国科学院打造的智慧农业服务平台佳家农农服APP上线一年多，已免费服务佳木斯及周边超6万农户、覆盖耕地超700万亩；农户使用平台可实现亩均增产约3%、农资购买成本降低约10%；黑龙江全省农作物耕种收综合机械化率超99%，高性能播种机、乘坐式水稻插秧机、玉米收获机等先进适用农机保有量稳定增长，植保无人机保有量全国第一。","人民日报 2026-10-05","2026-10-05T00:00:00Z",77,{"impact":157,"substance":241,"depth":18,"authority":18,"freshness":298,"relevant":21,"comment":340},"央媒报道的农高区智慧农业平台落地数据扎实，服务规模与增产降本成效具体，具备行业参考价值。",[342],{"name":336,"url":334},[26,27,344,345,346],"植保无人机","农业社会化服务","农服APP",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":350},{"candidates":351,"agricultural_evidence":46},[352,356,361,365,371,377,382],{"code":32,"score":85,"supported":46,"title":353,"abstract":354,"tags":355},[],[48,175],[],{"code":303,"score":53,"supported":46,"title":357,"abstract":358,"tags":360},[],[359],"植保",[344],{"code":72,"score":53,"supported":46,"title":362,"abstract":363,"tags":364},[],[27],[27],{"code":366,"score":60,"supported":46,"title":367,"abstract":368,"tags":370},"A1",[],[369],"水稻",[],{"code":372,"score":60,"supported":46,"title":373,"abstract":374,"tags":376},"A3",[],[375],"玉米",[],{"code":378,"score":21,"supported":14,"title":379,"abstract":380,"tags":381},"G2",[],[],[345],{"code":77,"score":21,"supported":14,"title":383,"abstract":384,"tags":385},[],[],[26],[387,388],"佳家农农服APP 佳木斯","佳木斯农高区 智慧农业平台","佳家农农服APP佳木斯-4469","2026-10-09T00:04:56.878115Z",{"id":392,"title":393,"url":394,"summary":395,"summary_zh":8,"content":396,"source_name":397,"source_url":8,"published_at":337,"category":12,"cover_url":8,"hotness":13,"is_selected":46,"score":398,"score_detail":399,"sources":404,"tags":406,"primary_topic":409,"secondary_topics":410,"classification":417,"search_phrases":437,"slug":440,"view_count":60,"doi":8,"paper":8,"created_at":441},4256,"人民论坛实评：当秋收遇上AI 智慧农机迭代重塑农耕","https:\u002F\u002Fwww.rmlt.com.cn\u002F2026\u002F1005\u002F756557.shtml","人民论坛评论文章：今年秋收AI从实验室走进田间地头成为新农具。湖北枣阳农机手收割机北斗智能终端将行距误差控制在厘米级别；湖南衡阳烘干中心2.4万个传感器为20多个稻谷品种量身定制烘干曲线；浙江粮仓平台覆盖232家收储企业6750个仓房。十五五规划纲要提出农作物耕种收综合机械化率提高到80%以上。","湖北枣阳的农机手，靠着收割机的北斗智能终端，把行距误差控制在厘米级别；湖南衡阳的烘干中心里，2.4万个传感器，为20多个稻谷品种“量身定制”烘干曲线……今年秋收，AI从实验室走进田间地头，成为百姓身边的“新农具”。\n\n习近平总书记强调，中国式现代化离不开农业农村现代化。不同于传统农耕模式，伴随AI助手、北斗终端、智能烘干、数字仓储等科技装备全面落地，深度融入粮食收割、烘干、储运、加工全链条，智慧农机迭代升级、数字技术深耕田野，正是我国现代农业高质量发展的缩影。\n\nAI助手的意义，不只是让农民“少流汗”，更在于让每一粒粮食“颗粒归仓”。湖南衡阳角山米业的智慧粮食系统进入3.0版本后，较去年上一代系统出米率提升1%，整精米率提升3%以上。减损就是增产，提质就是增收。智慧农业的价值，首先体现在“减损增效”的硬账本上。\n\n智慧农业的想象力，远不止于效率的提升。以往农民种地是“看天吃饭、凭手感烘干”，而现在是靠数据“系统识别品种、自动派仓、变温烘干”。从“人脑决策”转向“人机协同”，从“粗放管理”转向“精准施策”。“浙江粮仓”平台，打通收、储、运、管全链数据，覆盖全省232家收储企业、6750个仓房，这种系统性的数字化改造，让粮食从田间到仓库的每一步都“有迹可循”。\n\n目前，我国人工智能在农业领域的应用取得显著成效，但仍面临瓶颈。这主要表现在：一是成本门槛高。一台搭载北斗终端的收割机、一套智慧粮食系统，投入动辄数十万甚至上百万，对中小农户而言，存在“看得见、用不起”的困境。同时，后续运维、流量、软件升级等隐性成本不低，投入回报周期偏长，也在一定程度上抑制购置和使用意愿。二是“数据孤岛”现象仍存。各地平台各建各的，标准不一、接口不通，农机数据、粮库数据难以共享，数据权属、隐私安全和收益分配机制有待健全。三是操作技术转型， 一时跟不上机器的迭代。一些农民面对智能设备仍手足无措，设备更新了，技能跟不上，再好的AI也成了“摆设”。为此，既要有基础设施、智慧农机等“硬投入”，也需优化数据治理、培训指导等“软服务”，让人工智能扎根田间地头。\n\n“十五五”规划纲要对“强化农业科技和装备支撑”作出部署，提出“农作物耕种收综合机械化率提高到80%以上”的目标。针对成本门槛，加大农机购置补贴力度，探索智慧农业设备“共享租赁”“按需付费”等模式，降低中小农户的使用门槛；针对“数据孤岛”，加快制定统一的数据标准、接口规范和安全规则，实现数据共享；针对人才短板，把培训送到田间地头，依托农技站、合作社和龙头企业开展场景化教学，带动更多农民跨越“数字鸿沟”。\n\n智慧农业不是“替代农民”，而是“赋能农民”，让农民从繁重体力劳动中解放出来，成为“会种地”更“慧种地”的新型农民。为此，看待智慧农业发展，还需用辩证眼光。既看到其提效减损的巨大潜力，也正视其落地生根的现实障碍；既拥抱技术进步，也守住“为农服务”的初心。\n\n让AI在田埂上生根发芽，需要的不仅是算法的迭代，更是政策、人才、基础设施的协同发力。当农民在秋收时节收获的不仅是沉甸甸的稻谷，还有实实在在的获得感，“智慧农业”才算踏踏实实落了地。","人民论坛网 2026-10-05",88,{"impact":400,"substance":401,"depth":17,"authority":402,"freshness":19,"relevant":21,"comment":403},26,21,14,"央媒评论系统梳理AI秋收落地成效与成本、数据孤岛、人才三大瓶颈，兼具政策高度与产业细节，值得精选。",[405],{"name":397,"url":394},[27,29,164,407,408],"北斗终端","数字粮仓",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[411],{"code":412,"slug":413,"name":414,"path":415,"parent_code":416},"J4","seasonal-agriculture","农时与节庆活动","\u002Ftopic\u002Fpolicy\u002Fseasonal-agriculture","J",{"status":39,"locked":14,"version":40,"method":41,"evidence":418},{"candidates":419,"agricultural_evidence":46},[420,424,429,433],{"code":32,"score":17,"supported":46,"title":421,"abstract":422,"tags":423},[48],[48,175,281],[164],{"code":412,"score":124,"supported":46,"title":425,"abstract":427,"tags":428},[426],"秋收",[426],[],{"code":72,"score":21,"supported":14,"title":430,"abstract":431,"tags":432},[],[],[27],{"code":52,"score":21,"supported":14,"title":434,"abstract":435,"tags":436},[],[],[29],[438,439],"浙江粮仓 数字收储","北斗智能终端 收割机","浙江粮仓数字收储-4256","2026-10-06T00:04:59.998793Z"]