[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3215":3,"related-3215":37},{"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":23,"tags":25,"search_phrases":31,"slug":34,"view_count":35,"doi":8,"paper":8,"created_at":36},3215,"秋分逢丰收节 机器人成主角！浙江田野正被AI\"接管\"——浙江农科院数字农业研究所研发AI眼镜+害虫识别小程序","https:\u002F\u002Fwww.cztv.com\u002FnewsDetail\u002F904714","9-22 新蓝网专题报道：在湖州德清县农博家庭农场，种植大户王菊仙戴上一副AI眼镜，对着诱杀害虫的黄板轻轻一扫，\"镜片上、手机端，种类、数量、位置等数据瞬间显现\"。这套由浙江省农科院数字农业研究所研发的设备，正将虫害防控从\"事后补救\"推向\"提前预警\"。在湖州吴兴丰盛湾水产种业，\"云眸\"沼虾养殖AI系统能在3-5秒内捕捉沼虾触须末端细微影像，自动生成比对图谱，一旦发现活动异常即刻标记预警，自动投料机器人与水下传感器联动精准计算投喂量，饲料利用率提升12%-15%、巡塘人力节省六成、养殖效益整体提高10%以上。在杭州余杭区径山镇，无人驾驶拖拉机搭载北斗导航系统自主作业。在杭州临平区田立方未来农场，450亩无人智慧农场示范区配套200余个田间传感器和4个物联网微基站，可根据土壤饱和度和实时水位自动确定浇灌量，一亩地一季油菜花可节水约1000吨。浙江省农业农村厅数据显示，截至目前浙江已累计建成数字农业工厂729家、未来农场63家。",null,"![Image 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33010602002235号](http:\u002F\u002Fwww.beian.gov.cn\u002Fportal\u002FregisterSystemInfo?recordcode=33010602002235) | 信息网络传播视听节目许可证号：1107197\n\n[互联网新闻信息服务许可证号：33120170002](https:\u002F\u002Fwww.cztv.com\u002Fxuke) | 网络文化经营许可证号：浙网文(2023)1495-044号\n\n 地址：浙江省杭州市莫干山路111号 邮政编码：310005 邮箱：cztv@zmg.com.cn\n\n 网上有害信息举报专区 12321网络不良与垃圾信息举报受理中心 网络违法犯罪举报网站 网络举报APP下载 \n\n 违法和不良信息公开举报电话：12377、0571-81089789 有害信息举报邮箱：jubao@12377.cn 涉未成年人有害信息举报电话: 0571-81089789 \n\n[点播](https:\u002F\u002Fwww.cztv.com\u002Fvideo)\n\n[直播](https:\u002F\u002Fwww.cztv.com\u002FliveTV)\n\n[点播](https:\u002F\u002Fwww.cztv.com\u002Fradio)\n\n[直播](https:\u002F\u002Fwww.cztv.com\u002FliveRadio)","新蓝网","2026-09-22T00:00:00Z","报道",10,false,60,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":20,"relevant":21,"comment":22},16,14,12,9,1,"省级官媒报道浙江农科院数字农业研究所AI眼镜与害虫识别小程序落地，属智慧农业细分进展，时效性强但正文信息量有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字农业","智慧农业","农业人工智能","智能农机","害虫识别",[32,33],"浙江农科院 数字农业研究所 AI眼镜","浙江 害虫识别 小程序","浙江农科院数字农业研究所AI眼镜-3215",0,"2026-09-23T00:04:29.218317Z",{"total":38,"page":21,"page_size":38,"items":39},6,[40,66,103,149,192,214],{"id":41,"title":42,"url":43,"summary":44,"summary_zh":8,"content":45,"source_name":46,"source_url":8,"published_at":47,"category":12,"cover_url":8,"hotness":13,"is_selected":48,"score":49,"score_detail":50,"sources":55,"tags":57,"search_phrases":61,"slug":64,"view_count":35,"doi":8,"paper":8,"created_at":65},3210,"【光明论坛】藏粮于地、藏粮于技 扎实推进乡村全面振兴——农业新质生产力引领\"十五五\"种植业高质量发展","https:\u002F\u002Fepaper.gmw.cn\u002Fgmrb\u002Fhtml\u002Fcontent\u002F202609\u002F23\u002Fcontent_25817.html","9-23 光明日报\"光明论坛\"刊文解读农业农村部近日印发的《全国种植业发展\"十五五\"规划》：规划在深入实施藏粮于地、藏粮于技战略的同时，专门就\"发挥农业新质生产力引领作用\"作出部署。种植业科技战略正由以良田、良种、良机、良法集成为主，向数据、算法、智能装备与生物技术深度融合拓展。2025年全国粮食总产量达14298亿斤、增长1.2%，单位面积产量增长1.1%，单产提升是增产的主要来源；农作物耕种收综合机械化率达76.7%，农业科技进步贡献率超过64%；农用无人机保有量超过30万架，年作业面积突破4.6亿亩。规划首次提出以精准监测、AI决策、自主作业为重点发展智慧种植，推动无人机、具身机器人等先进装备与传统植保深度融合。","**【光明论坛】**\n\n习近平总书记指出，建设农业强国，利器在科技，关键靠改革。近日，农业农村部印发《全国种植业发展“十五五”规划》，在深入实施藏粮于地、藏粮于技战略的同时，专门就“发挥农业新质生产力引领作用”作出部署。这表明，种植业科技战略正由以良田、良种、良机、良法集成为主，向数据、算法、智能装备与生物技术深度融合拓展。以新质生产力引领科技战略升级是未来五年种植业高质量发展的重要路径。\n\n实施藏粮于地、藏粮于技战略并非抽象概念，它实实在在体现在产量、装备和技术水平的变化里。相关数据显示，2025年全国粮食总产量达14298亿斤，比上年增长1.2%，其中单位面积产量增长1.1%，单产提升是增产的主要来源；农作物耕种收综合机械化率达76.7%，农业科技进步贡献率超过64%；农用无人机保有量超过30万架，年作业面积突破4.6亿亩，农机北斗终端设备应用超过220万台（套），智慧农场、智能育秧工厂等智能化场景不断涌现。《“十四五”全国种植业发展规划》把“坚持创新驱动，转型升级”作为基本原则，把“增强科技支撑”列入保障措施，智能化内容散见于相关章节，提出“探索应用智慧农业技术”。新规划则将发挥农业新质生产力引领作用单列为一个部分，与增强供给保障能力、推进绿色转型、增强防灾减灾救灾能力并列，科技由“支撑”走向“引领”，这是这份规划最鲜明的亮点。\n\n科技引领具体体现在五个方面的部署上。在品种上，把抗赤霉病小麦、耐密宜机收玉米、高油高产大豆等列为选育重点，向突破性品种要产量；在技术上，强调集成推广引领性技术，并把提高技术到位率和覆盖率作为推广要求；在装备上，一手抓大型高端智能农机，一手抓丘陵山区轻简高效农机，让不同地形都有合用的机具；在投入品上，在种植业五年规划中首次提出运用基因编辑、核酸干扰等前沿手段创制核糖核酸农药等新型产品；在场景上，首次提出以精准监测、AI决策、自主作业为重点发展智慧种植，推动无人机、具身机器人等先进装备与传统植保深度融合，并提出培育无人农机操作员等专业技术人员。这些部署与2026年中央一号文件促进人工智能与农业发展相结合的要求相衔接，也服务于国务院《加快农业农村现代化“十五五”规划》提出的“到2030年，粮食等重要农产品供给保障能力稳步提升，粮食安全根基持续夯实，农业质量效益和竞争力不断提高”的目标。其实质，是生产力三要素的同步跃升，劳动对象从良田良种扩展到数据资源，劳动资料从机械装备升级为智能装备和模型算法，劳动者从传统农机手拓展到新型专业人才。“藏粮于地”稳的是根基，“藏粮于技”强的是手段，粮食产能不仅沉淀在耕地和良种里，也生成于以数据集成与智能作业为代表的农业新质生产力之中。\n\n目前，把产能真正蓄积到数据和智能作业之中，还要经历一段爬坡过坎的过程，应清晰地看到，这场生产方式变革还处在“起步期”。因此，未来需要给农业新质生产力发展加点“催化剂”，推动其由示范应用走向大面积普及。\n\n应加快关键核心技术攻关，使其成为农业新质生产力的“发动机”。以国家重大科技任务为牵引，设立智慧农业科技创新专项，聚焦高精度低成本传感器、农业专用芯片、作物生长模型与核心算法、智能决策系统、重型智能农机装备等领域，实行“揭榜挂帅”机制，推动产学研深度联动，明确企业创新主体地位，引导创新资源向农业科技领军企业集聚。同步夯实数据要素基础，加快构建“天空地”一体化农情灾情监测网络，健全数据标准和管理体系，面向育种、栽培、植保、农机作业等场景建设高质量数据集，形成“场景牵引数据、数据驱动模型、模型赋能应用、应用创造价值”的良性循环，并探索建立数据权益确认和收益分享机制，促进数据安全有序流通。\n\n应发展农业社会化服务，使其成为智能技术进村入田的“摆渡船”。通过发挥专业化服务组织和农机社会化服务中心的作用，通过托管、代耕代种等方式，将智能农机、植保无人机和智能决策服务导入小农户生产，使农户不必购置装备也能用上智能技术。通过鼓励服务主体提供贯穿全生产周期的农事指导、灾害预警等信息服务，把技术优势转化为农户的经营收益。通过加快智慧农场等应用场景示范推广，以技术到位率覆盖率和增产增效实绩检验成效，推动智能技术由点上示范向面上应用拓展。\n\n应完善配套制度体系，使其成为推动农业新质生产力发展的“稳压器”。通过建立适应智能农机、算法模型、数据产品等新型成果的分类评价机制，让科研力量向大田需求集聚。通过推动农机购置与应用补贴向智能装备和智能作业服务延伸，引导政策资源向智能化方向倾斜。通过加快前沿产品的登记资料要求、命名规则和评价标准制定，同步完善农业数据安全管理，使新技术新产品有标可依、有规可循。通过推进基层农技推广体系改革与建设，培育大田无人农机操作员、现代设施农业技术员等专业技术人才，为智能技术落地提供人才支撑。\n\n从“藏粮于地”到“藏粮于技”，体现了种植业科技战略在新一轮科技革命和产业变革中的深化拓展。“十五五”时期是基本实现农业农村现代化的关键时期，面向未来，当数据跃升为产能提升的核心要素，算法沉淀为生产决策的智能引擎，智能装备演化为田间作业的新型农具，农业新质生产力便会从战略蓝图照进田野现实。我们期待中国人的饭碗端得更稳、成色更足。\n\n**（作者：王洋，系东北农业大学经济管理学院副院长、教授）**","光明日报","2026-09-22T23:00:00Z",true,93,{"impact":51,"substance":52,"depth":53,"authority":18,"freshness":20,"relevant":21,"comment":54},28,24,18,"央媒权威解读种植业“十五五”规划，首次将农业新质生产力单列部署，政策条款与数据详实，值得进入每日精选。",[56],{"name":46,"url":43},[27,28,29,58,59,60],"农业新质生产力","藏粮于技","种植业规划",[62,63],"农业新质生产力 智慧种植","农业新质生产力 农业人工智能 种植业规划 智慧农业","农业新质生产力智慧种植-3210","2026-09-23T00:04:27.059734Z",{"id":67,"title":68,"url":69,"summary":70,"summary_zh":71,"content":8,"source_name":72,"source_url":69,"published_at":11,"category":73,"cover_url":8,"hotness":13,"is_selected":14,"score":74,"score_detail":75,"sources":79,"tags":81,"search_phrases":84,"slug":87,"view_count":35,"doi":88,"paper":89,"created_at":102},3194,"Optimization and Analysis of Agricultural Robot Drive Systems","https:\u002F\u002Fdoi.org\u002F10.54254\u002F2753-8818\u002F2026.37178","This study takes the agricultural robot drive system as the research object and carries out optimization research from two dimensions: mechanical structure and intelligent control. At the mechanical level, redundant degrees of freedom are eliminated through topological analysis of mechanism freedom, a 'short-chain direct-drive' transmission scheme is introduced to reduce mechanical losses, and finite element topology optimization is combined to achieve lightweight design of key components. At the control level, artificial intelligence is introduced to establish a perception system based on convolutional neural networks (CNN) and multi-source information fusion, enabling accurate recognition and prediction of complex terrain. A Back Propagation (BP) neural network Proportion Integration Differentiation (PID) control strategy based on the Dung beetle Optimization (DBO)algorithm is proposed, which effectively addresses the shortcomings of traditional algorithms, such as slow convergence and large overshoot. Meanwhile, model predictive control and an improved soft actor-critic reinforcement learning algorithm are integrated to achieve online adaptive regulation of drive parameters and global optimal control to a considerable extent. The optimized drive system effectively improves the working performance and environmental adaptability of agricultural robots in complex terrain and provides new theoretical and technical ideas for the development of intelligent agricultural machinery.","本研究以农业机器人驱动系统为研究对象，从机械结构与智能控制两个维度开展优化研究。在机械层面，通过机构自由度拓扑分析去除冗余自由度，引入“短链直驱”传动方案以降低机械损耗，并结合有限元拓扑优化实现关键零部件的轻量化设计。在控制层面，引入人工智能，建立基于卷积神经网络（CNN）与多源信息融合的感知系统，实现对复杂地形的准确识别与预测；提出基于蜣螂优化（DBO）算法的BP神经网络PID控制策略，有效改善传统算法收敛慢、超调大等不足；同时融合模型预测控制与改进的柔性演员-评论家强化学习算法，实现驱动参数的在线自适应调节及较大程度上的全局最优控制。优化后的驱动系统有效提升了农业机器人在复杂地形下的作业性能与环境适应性，为智能农业机械的发展提供了新的理论与技术思路。","Theoretical and Natural Science","论文",69,{"impact":19,"substance":76,"depth":77,"authority":13,"freshness":13,"relevant":21,"comment":78},20,17,"论文提出短链直驱与DBO-BP-PID等控制优化方案，方法新颖但偏理论，产业影响有限。",[80],{"name":72,"url":69},[27,28,82,29,83],"农业机器人","驱动系统",[85,86],"农业机器人 驱动系统 优化","DBO BP神经网络 PID控制","农业机器人驱动系统优化-3194","10.54254\u002F2753-8818\u002F2026.37178",{"doi":88,"openalex_id":90,"authors":91,"venue":72,"cited_by_count":35,"oa_url":69,"card":95,"direction":99,"ingested_from":101},"W7213976318",[92],{"name":93,"orcid":94},"Ziyuan Ma","https:\u002F\u002Forcid.org\u002F0000-0002-7931-3258",{"tldr":96,"method":97,"finding":98,"direction":99,"opportunity":100},"从机械结构与智能控制两方面优化农业机器人驱动系统，提升复杂地形适应性与作业性能。","机构自由度拓扑分析、有限元拓扑优化、CNN多源融合感知、DBO-BP-PID与强","优化驱动系统有效提升农业机器人在复杂地形下的作业性能与环境适应性。","农业人工智能与决策模型","可探索轻量化驱动与在线强化学习控制在真实农田多机协同中的泛化性与能耗权衡。","openalex","2026-09-22T23:30:39.723894Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":108,"content":8,"source_name":109,"source_url":106,"published_at":11,"category":73,"cover_url":8,"hotness":13,"is_selected":14,"score":110,"score_detail":111,"sources":113,"tags":115,"search_phrases":118,"slug":121,"view_count":35,"doi":122,"paper":123,"created_at":148},3128,"Spatiotemporal synchronization-based seed position estimation for multi-row precision planting","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112396","Spatiotemporal synchronization-based seed position estimation for multi-row precision planting。Computers and Electronics in Agriculture","基于时空同步的多行精量播种种子位置估计。《农业计算机与电子》","Computers and Electronics in Agriculture",80,{"impact":53,"substance":76,"depth":53,"authority":18,"freshness":13,"relevant":21,"comment":112},"核心期刊论文，提出基于时空同步的多行精量播种种子位置估计方法，对智能播种机具研发有参考价值，但属细分技术进展，公共影响有限。",[114],{"name":109,"url":106},[27,28,29,116,117],"玉米","精准播种",[119,120],"多行精准播种 种子位置估计","时空同步 播种监测","多行精准播种种子位置估计-3128","10.1016\u002Fj.compag.2026.112396",{"doi":122,"openalex_id":124,"authors":125,"venue":109,"cited_by_count":35,"oa_url":8,"card":142,"direction":146,"ingested_from":101},"W7213976849",[126,129,131,134,136,138,140],{"name":127,"orcid":128},"Lin Jia","https:\u002F\u002Forcid.org\u002F0009-0002-2422-7974",{"name":130,"orcid":8},"Qingjie Wang",{"name":132,"orcid":133},"Hongwen Li","https:\u002F\u002Forcid.org\u002F0000-0002-5536-2346",{"name":135,"orcid":8},"Chao Wang",{"name":137,"orcid":8},"Jin He",{"name":139,"orcid":8},"Caiyun Lu",{"name":141,"orcid":8},"Xinyue Zhang",{"tldr":143,"method":144,"finding":145,"direction":146,"opportunity":147},"提出基于时空同步的多行精量播种种子位置估计方法。","利用播种机多行作业的时空同步信号估计种子落点位置。","该方法能实现多行精量播种的种子位置估计，提升播种质量监测精度。","智慧农业 \u002F 农业物联网","可结合机器视觉与GNSS实时校正，发展播种质量在线评估与变量播种闭环控制。","2026-09-22T23:30:01.680027Z",{"id":150,"title":151,"url":152,"summary":153,"summary_zh":154,"content":8,"source_name":109,"source_url":152,"published_at":11,"category":73,"cover_url":8,"hotness":13,"is_selected":14,"score":155,"score_detail":156,"sources":158,"tags":160,"search_phrases":163,"slug":166,"view_count":35,"doi":167,"paper":168,"created_at":191},3127,"Robust slip-ratio regulation for agricultural tractors with transformer-enhanced speed estimation","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112436","Robust slip-ratio regulation for agricultural tractors with transformer-enhanced speed estimation。Computers and Electronics in Agriculture","农业拖拉机滑转率的鲁棒调节：基于变压器增强的速度估计。《计算机与电子农业》",74,{"impact":19,"substance":76,"depth":53,"authority":18,"freshness":13,"relevant":21,"comment":157},"核心期刊最新论文，将Transformer用于拖拉机速度估计与滑转率鲁棒控制，方法新颖但属细分技术进展，产业影响有限。",[159],{"name":109,"url":152},[27,28,29,161,162],"拖拉机","滑转率控制",[164,165],"农业拖拉机 滑转率 控制","Transformer 车速估计 拖拉机","农业拖拉机滑转率控制-3127","10.1016\u002Fj.compag.2026.112436",{"doi":167,"openalex_id":169,"authors":170,"venue":109,"cited_by_count":35,"oa_url":8,"card":186,"direction":99,"ingested_from":101},"W7213970956",[171,173,175,178,180,183],{"name":172,"orcid":8},"Xianghai Yan",{"name":174,"orcid":8},"Zijian Tong",{"name":176,"orcid":177},"Hang Wang","https:\u002F\u002Forcid.org\u002F0000-0003-0881-0553",{"name":179,"orcid":8},"Liyou Xu",{"name":181,"orcid":182},"Yiwei Wu","https:\u002F\u002Forcid.org\u002F0000-0003-0866-1228",{"name":184,"orcid":185},"Di Ao","https:\u002F\u002Forcid.org\u002F0000-0002-9455-7111",{"tldr":187,"method":188,"finding":189,"direction":99,"opportunity":190},"提出拖拉机滑转率鲁棒调节方法，用Transformer增强速度估计。","Transformer增强的速度估计与鲁棒滑转率控制。","Transformer提升速度估计精度，实现滑转率鲁棒调节。","可探索Transformer在农机复杂工况下多传感器融合与实时控制中的泛化能力。","2026-09-22T23:30:01.599253Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":8,"content":197,"source_name":198,"source_url":8,"published_at":199,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":200,"score_detail":201,"sources":204,"tags":206,"search_phrases":209,"slug":212,"view_count":35,"doi":8,"paper":8,"created_at":213},3039,"江苏沿江地区农科所参加华东地区农学会学术年会：以\"AI赋能农业新质生产力发展\"为主题","https:\u002F\u002Fyj.jaas.ac.cn\u002Fxww\u002Fxwzx\u002Fart\u002F2026\u002Fart_c0ccb7c5ca5547768d1e29ed9427f12a.html","2026年华东地区农学会学术年会9-17至19在江苏扬州召开，以\"AI赋能农业新质生产力发展\"为主题，汇聚华东六省一市农业科研院所、高等院校、农技推广部门及农业科技企业专家代表。江苏沿江地区农科所王顺祥所长、陆兵副所长带队，组织10余名科研人员参会交流。中国工程院院士张洪程作《水稻绿色丰产无人化栽培技术》报告；日本工程院院士邓明聪分享人工智能与非线性控制技术融合及其在农业工程领域的应用。年会同步开设四大平行专题论坛：智慧种植·丰产提质、智慧养殖·节本增效、智造农机·装备赋能、智驱加工·延链强链。","所内要闻|AI赋能聚力发展农业新质生产力——沿江农科所参加华东地区农学会学术年会\n\n作者：唐明霞 文章来源：沿江所 点击数： 发布时间：2026-09-20 16:09\n\n为学习农业领域前沿科技创新成果，加强跨区域科研交流合作，9月17日至19日，2026年华东地区农学会学术年会在江苏扬州中兴天成国际酒店召开。本次年会以“AI赋能农业新质生产力发展”为主题，汇聚华东六省一市农业科研院所、高等院校、农技推广部门及农业科技企业专家代表。江苏沿江地区农科所王顺祥所长、陆兵副所长带队，组织10余名科研人员赴扬州参会交流。\n\n会议由江苏省农学会、扬州大学承办。开幕式后，主旨报告环节大咖云集。中国工程院院士张洪程作《水稻绿色丰产无人化栽培技术》报告；日本工程院院士邓明聪分享人工智能与非线性控制技术融合及其在农业工程领域的应用；南京农业大学陆明洲教授围绕畜禽养殖智能化技术、装备与农业大模型展开交流；南京工业大学徐虹教授介绍基于AI赋能的新型生物刺激素绿色生物制造研究。专家们从智慧种植、智能养殖、生物制造等方面，展现AI技术赋能现代农业的最新进展。\n\n9月18日下午，年会同步开设四大平行专题论坛：智慧种植·丰产提质、智慧养殖·节本增效、智造农机·装备赋能、智驱加工·延链强链。智慧种植专场聚焦AI大田生产管控、农业碳汇、水肥智能决策、数字化育种、大豆抗逆新品种选育等研究；智慧养殖专场研讨畜禽水产智能感知、稻虾生态种养智慧管控、畜禽行为智能识别与养殖环境调控技术；智造农机专场交流名优茶采摘机器人、设施蔬菜装备、智能育种加速器、丘陵山地农机装备研发实践；智驱加工专场围绕食品加工数字孪生、全溶性植物蛋白开发、果蔬及特色农产品精深加工技术开展研讨，覆盖农业生产全链条数字化转型。\n\n参会期间，我所科研人员结合自身研究方向，分赴各专题会场认真聆听报告，积极参与学术讨论，与华东地区同行专家深入交流，重点学习智慧农业装备、绿色高效栽培、农产品加工增值等领域创新成果，探讨科研项目协同合作路径。\n\n此次参会，有效拓宽了科研人员学术视野，进一步搭建起跨区域科研协作桥梁。下一步，江苏沿江地区农科所将充分吸收本次年会的新理念、新技术，立足南通沿江农业产业实际需求，持续推进农业科技创新，加快科技成果示范转化，为培育农业新质生产力、推动区域农业高质量发展贡献科研力量。\n\n[![Image 1: 1.jpeg](https:\u002F\u002Fyj.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F695893685\u002Fpicture\u002F20268\u002FS254e30553383497089ded7cfd802aec4-800.jpeg)](https:\u002F\u002Fyj.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F695893685\u002Fpicture\u002F20268\u002F254e30553383497089ded7cfd802aec4.jpeg)\n\n（图文：唐明霞；责任编辑：陈满峰；审核人：陈国清）","江苏省农业科学院沿江地区农业科学研究所","2026-09-20T10:00:00Z",58,{"impact":19,"substance":18,"depth":19,"authority":202,"freshness":20,"relevant":21,"comment":203},11,"区域性学术年会参会通稿，信息以会议议程与报告概览为主，无新增数据或独家结论，但AI赋能农业主题契合度高、时效新，可作为智慧农业主题页的聚合素材。",[205],{"name":198,"url":195},[27,28,207,29,208],"新质生产力","数字育种",[210,211],"华东地区农学会 学术年会","沿江农科所 扬州 AI赋能","华东地区农学会学术年会-3039","2026-09-21T00:04:34.285572Z",{"id":215,"title":216,"url":217,"summary":218,"summary_zh":8,"content":8,"source_name":219,"source_url":8,"published_at":220,"category":73,"cover_url":8,"hotness":13,"is_selected":14,"score":74,"score_detail":221,"sources":225,"tags":227,"search_phrases":230,"slug":233,"view_count":35,"doi":8,"paper":234,"created_at":242},3002,"改进生物神经网络的农业播种机全覆盖路径规划","https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F18\u002F1968","江苏大学魏军等提出一种考虑播种与非播种运动模式切换机制的改进生物神经网络（BNN）方法，基于周围环境条件将下一节点状态分类为播种、封闭或转移节点。在BNN景观引导下机器沿平行直线路径继续播种操作；检测到封闭节点时切换至非播种模式并使用深度优先搜索算法搜索潜在封闭区域；检测到转移节点时同样切换非播种模式搜索合理的新目标节点。仿真表明该方法实现播种操作的完全覆盖同时避免重复遍历已播种区域。","MDPI Agriculture 16(18):1968","2026-09-14T00:00:00Z",{"impact":19,"substance":222,"depth":77,"authority":223,"freshness":38,"relevant":21,"comment":224},21,13,"提出改进生物神经网络的全覆盖路径规划方法，方法新颖、结论可靠，但属细分领域学术进展，公共影响有限。",[226],{"name":219,"url":217},[27,28,29,228,229],"路径规划","播种机",[231,232],"江苏大学 播种机 全覆盖路径规划","生物神经网络 播种机 路径规划","江苏大学播种机全覆盖路径规划-3002",{"doi":8,"openalex_id":8,"authors":235,"venue":8,"cited_by_count":35,"oa_url":8,"card":236,"direction":99,"ingested_from":241},[],{"tldr":237,"method":238,"finding":239,"direction":99,"opportunity":240},"提出改进生物神经网络，实现农业播种机全覆盖路径规划并避免重复播种。","改进BNN结合节点分类与深度优先搜索，仿真验证。","方法实现播种完全覆盖，同时避免重复遍历已播种区域。","可结合真实农田地形与多机协同，验证动态环境下的路径规划鲁棒性。","agent","2026-09-20T00:03:08.288198Z"]