[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-617":3,"related-617":64},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":58,"slug":61,"view_count":62,"doi":8,"paper":8,"created_at":63},617,"湖南农科院联合华中农业大学创制新型 Ogura CMS 恢复系 R206 发表于《JIPB》","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260812081808487.htm","华中农业大学油菜研究团队联合湖南省农业科学院、崖州湾国家实验室在 JIPB 在线发表题为'A mechanized hybrid seed production technology for rapeseed based on a novel Ogura CMS restorer line'的研究论文。研究团队通过远缘杂交与连续六代回交,创制出携带最小萝卜染色体片段的新型 Ogura CMS 恢复系 R206,有效减少了不良性状的连锁累赘,与已知恢复系相比携带萝卜来源导入片段最短。",null,"【JIPB】油菜团队联合湖南省农业科学院创制新型油菜Ogura CMS恢复系\n\n_【字体： 大 中 小 】_ _时间：2026年08月12日_ _来源：华中农业大学植物科学技术学院_\n\n**编辑推荐：**\n\n南湖新闻网讯（通讯员 李宝）近日，我校油菜研究团队联合湖南省农业科学院、崖州湾国家实验室，在JIPB在线发表题为“A mechanized hybrid seed production technology for rapeseed based on a novel Ogura CMS restorer line”的研究论文\n\n南湖新闻网讯（通讯员 李宝）近日，我校油菜研究团队联合湖南省农业科学院、崖州湾国家实验室，在JIPB在线发表题为“A mechanized hybrid seed production technology for rapeseed based on a novel Ogura CMS restorer line”的研究论文。研究团队通过远缘杂交与连续六代回交，创制出携带最小萝卜染色体片段的新型Ogura CMS恢复系R206。\n\n油菜是我国重要的油料作物，杂种优势利用是提高其产量和综合性状的重要途径。Ogura细胞质雄性不育（CMS）系统以其不育性表现稳定，被视为最可靠的杂交制种系统之一。然而，该系统的广泛应用长期受制于两大瓶颈：一是恢复基因（Rfo）来源于萝卜，在导入油菜基因组时伴随“连锁累赘”，导致结实率下降、种子硫苷含量上升及恢复基因传递效率偏低；二是传统杂交制种依赖父母本分行种植和人工去杂，劳动力成本高、效率低，难以适应机械化规模化生产需求。\n\n研究团队创制的新型Ogura CMS恢复系R206，与已知恢复系（如R2000、CLR650）相比，携带的萝卜来源导入片段最短，有效减少了不良性状的连锁累赘。R206主要农艺性状及种子硫苷含量均与轮回亲本无显著差异，且其恢复基因在分离群体中未发生显著的偏分离，增强了恢复基因传递的稳定性，从而有效解决了Ogura CMS恢复系存在的“品质下降”与“偏分离”等问题。\n\n为进一步解析其遗传基础，研究团队结合PacBio HiFi测序、Hi-C技术及BSA-seq分析，完成了R206的高质量基因组组装，并将恢复基因精确定位至A10染色体末端一个3.37 Mb的导入片段。基因注释表明，该区段不包含萝卜来源的MYB28基因(该基因导致种子硫苷升高)，从基因层面解释了R206优质性状的原因。\n\n![Image 1](http:\u002F\u002Febtshare.ebiotrade.com\u002Faipdf\u002F202608120454056a7b8bed1cde7.png)\n\nR206恢复源的创制和基于种子颜色的机械化杂交种制种技术（课题组供图）\n\n依托R206稳定高效的育性恢复能力，研究团队创新性地以种皮颜色为标记，结合高通量光学色选机，建立了一套高效的油菜杂交种机械化制种技术体系。将黄籽恢复系与黑籽不育系按1:3比例混合播种，成熟后机械混收，再通过色选机实现杂交种子与自交种子的高效分离。经过多轮分选优化，杂交种纯度可从72%提升至94%以上，种子损失率控制在5%以下。该技术突破了传统油菜杂交制种的人工依赖瓶颈，为油菜混播混收机械化杂交制种提供了可行方案。\n\n目前，恢复系R206已与国内十余家油菜育种单位签订了合作协议，快速应用于油菜新品种选育与杂交种生产，多个品种已进入推广阶段，有望助推我国油菜杂交品种选育和杂交种生产的提质增效与油菜产业升级。该研究成果不仅为油菜杂交制种提供了具有自主知识产权的核心种质资源，也为我国油菜种业自主创新和产业升级提供了重要支撑。\n\n华中农业大学、崖州湾国家实验室郭亮教授、华中农业大学涂金星教授、湖南省农业科学院作物研究所、岳麓山实验室王同华研究员为论文共同通讯作者，华中农业大学李宝博士（现湖南省农业科学院作物研究所副研究员）和吴增祥博士（现广东省农业科学院蔬菜研究所助理研究员）为共同第一作者。湖南省农业科学院作物研究所\u002F岳麓山实验室李莓研究员给予了重要指导，崖州湾国家实验室唐珊博士、娄洪祥博士、刘云豪博士及博士研究生陈敏建参与了部分研究工作。\n\n论文链接：[http:\u002F\u002Fdoi.org\u002F10.1111\u002Fjipb.70358](http:\u002F\u002Fdoi.org\u002F10.1111\u002Fjipb.70358)\n\n相关新闻\n\n![Image 2](https:\u002F\u002Fnews.ebiotrade.com\u002FQR_ebiotrade.jpg)生物通微信公众号\n\n![Image 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4](https:\u002F\u002Fwww.ebiotrade.com\u002Fimages\u002Fservice_com.gif)\n\n粤ICP备09063491号","生物通 2026-08-12 转自南湖新闻网","2026-08-12T00:00:00Z","报道",10,false,86,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},25,24,18,13,6,1,"油菜杂交制种技术重大突破，具产业级影响，信息详实，来源权威，时效稍逊。",[25],{"name":10,"url":6},[27,28,29,30],"湖南省农科院","油菜","Ogura CMS","JIPB",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"A4","soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds","A",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,51],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":50},7,true,[],[28,49],"rapeseed",[28],{"code":52,"score":53,"supported":46,"title":54,"abstract":55,"tags":57},"B1",3,[],[56],"萝卜",[],[59,60],"湖南省农科院 油菜 Ogura CMS JIPB","湖南省农科院 油菜","湖南省农科院油菜OguraCMSJIPB-617",5,"2026-08-16T23:55:40.855759Z",{"total":21,"page":22,"page_size":21,"items":65},[66,118,188,253,332,385],{"id":67,"title":68,"url":69,"summary":70,"summary_zh":8,"content":71,"source_name":72,"source_url":8,"published_at":73,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":74,"score_detail":75,"sources":80,"tags":82,"primary_topic":87,"secondary_topics":88,"classification":89,"search_phrases":112,"slug":115,"view_count":116,"doi":8,"paper":8,"created_at":117},5513,"江苏农科院经作所油菜新品种宁杂1588机播示范 含油量50.3%","https:\u002F\u002Fnewiic.jaas.ac.cn\u002Fxwdt\u002Fzxdt\u002Fart\u002F2026\u002Fart_bb5747ccb14b45378bb3304124f7295d.html","亚夫科技服务项目油菜新品种高产栽培技术示范推广机播现场会在镇江世业洲召开，现场演示三种精量条播机，可将播深精准控制在1.5至2厘米，一次性完成开沟、施肥、精量播种、覆土、镇压。大面积示范品种宁杂1588于2026年8月获得登记，含油量50.3%，抗病抗倒伏且适宜机播机收。","为推进2026年度亚夫科技服务项目《油菜新品种高产栽培技术示范推广》实施，培育高水平农技人才，10月20日，亚夫科技服务项目“油菜新品种高产栽培技术示范推广”机播现场暨培训会在镇江世业洲召开。会议邀请南京农业大学和扬州大学专家作专题授课，我院成果转化处魏国平科长到会指导。镇江市农技推广站负责人、基层农技人员、种植大户、及项目团队成员参会，油菜产业专家齐聚田间，看机具演示、学栽培技术，共探油菜品种农机农艺融合，产业提质增效新路径。\n\n机播现场演示了三种油菜精量条播机。精量播种机可将油菜种子精准控制在‌1.5~2cm‌的适宜播深范围内，彻底解决传统人工撒播深浅不一、出苗不齐的痛点，保障田间油菜出苗整齐、长势均衡；并能一次性完成开沟、施肥、精量播种、覆土、镇压等多项复式作业。此次现场机播大面积示范的品种为我院最新育成的油菜品种宁杂1588，该品种2026年8月获得登记，含油量50.3%，具有抗病、抗倒伏优点，适宜机播、机收。","江苏省农业科学院经济作物研究所 2026-10-20","2026-10-20T00:00:00Z",66,{"impact":76,"substance":19,"depth":77,"authority":77,"freshness":78,"relevant":22,"comment":79},16,12,8,"省级科研机构发布的新品种机播示范，含油量50.3%等具体数据有信息增量，但属区域性技术推广活动，影响力有限。",[81],{"name":72,"url":69},[83,84,28,85,86],"种业振兴","农机农艺融合","精量播种","宁杂1588",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":90},{"candidates":91,"agricultural_evidence":46},[92,96,102,107],{"code":32,"score":77,"supported":46,"title":93,"abstract":94,"tags":95},[28],[28],[28],{"code":97,"score":53,"supported":46,"title":98,"abstract":99,"tags":101},"F3",[],[100],"施肥",[],{"code":103,"score":22,"supported":14,"title":104,"abstract":105,"tags":106},"F1",[],[],[83],{"code":108,"score":22,"supported":14,"title":109,"abstract":110,"tags":111},"F5",[],[],[84],[113,114],"江苏省农科院 宁杂1588 油菜","油菜精量播种 机播示范","江苏省农科院宁杂1588油菜-5513",0,"2026-10-22T00:07:03.872776Z",{"id":119,"title":120,"url":121,"summary":122,"summary_zh":123,"content":8,"source_name":124,"source_url":121,"published_at":125,"category":126,"cover_url":8,"hotness":13,"is_selected":14,"score":127,"score_detail":128,"sources":134,"tags":136,"primary_topic":141,"secondary_topics":142,"classification":143,"search_phrases":160,"slug":163,"view_count":116,"doi":164,"paper":165,"created_at":187},3983,"Numerical and experimental investigation on the cutting mechanism of rapeseed stalk using abrasive gas jet based on SPH-FEM coupling","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112469","Numerical and experimental investigation on the cutting mechanism of rapeseed stalk using abrasive gas jet based on SPH-FEM coupling。Computers and Electronics in Agriculture","基于SPH-FEM耦合的磨料气体射流油菜茎秆切割机理数值与实验研究。《计算机与电子农业》","Computers and Electronics in 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seedlings","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112468","Development and evaluation of a chain-groove lateral seedling feeding device based on modular stepping misalignment for multi-row transplanting of rapeseed bare-root seedlings。Computers and Electronics in Agriculture","基于模块化步进错位的链槽式侧向投苗装置开发与评估：面向油菜裸根苗多行移栽。Computers and Electronics in Agriculture",{"impact":77,"substance":129,"depth":130,"authority":131,"freshness":132,"relevant":22,"comment":195},"核心期刊论文，提出链槽式模块化错位送苗装置，对多行油菜裸苗移栽机械化有实质方法创新，但属细分领域技术进展，公共影响有限。",[197],{"name":124,"url":191},[137,199,200,28,201],"农业机器人","精准农业","移栽机械",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":205},{"candidates":206,"agricultural_evidence":46},[207,211,216],{"code":32,"score":147,"supported":46,"title":208,"abstract":209,"tags":210},[49],[28,49],[28],{"code":156,"score":212,"supported":14,"title":213,"abstract":214,"tags":215},2,[],[],[137,200],{"code":217,"score":22,"supported":14,"title":218,"abstract":219,"tags":220},"F6",[],[],[199],[222,223],"油菜裸苗移栽 链槽式送苗装置","Computers and Electronics in Agriculture 移栽","油菜裸苗移栽链槽式送苗装置-3977","10.1016\u002Fj.compag.2026.112468",{"doi":225,"openalex_id":227,"authors":228,"venue":124,"cited_by_count":116,"oa_url":8,"card":246,"direction":250,"ingested_from":186},"W7215105622",[229,232,234,236,239,241,243],{"name":230,"orcid":231},"Hua Yuan","https:\u002F\u002Forcid.org\u002F0000-0001-7594-8718",{"name":233,"orcid":8},"Qingxi Liao",{"name":235,"orcid":8},"Zhengyu Liu",{"name":237,"orcid":238},"Zhe Liu","https:\u002F\u002Forcid.org\u002F0000-0003-2653-0408",{"name":240,"orcid":8},"Lin Li",{"name":242,"orcid":8},"Yitao Liao",{"name":244,"orcid":245},"Wenli Xiao","https:\u002F\u002Forcid.org\u002F0000-0002-8443-8987",{"tldr":247,"method":248,"finding":249,"direction":250,"opportunity":251},"研发并评估链槽式侧向供苗装置，实现油菜裸根苗多行移栽的模块化步进错位供苗。","设计链槽侧向供苗机构，采用模块化步进错位方案，并进行样机试验评估。","该装置能实现多行裸根苗有序错位供苗，提升移栽效率与供苗质量。","智慧农业 \u002F 农业物联网","可结合视觉检测与伺服控制，研究供苗状态实时监测与自适应错位调节，提升多行移栽智能化水平。","2026-10-02T23:30:02.682513Z",{"id":254,"title":255,"url":256,"summary":257,"summary_zh":258,"content":8,"source_name":259,"source_url":256,"published_at":260,"category":126,"cover_url":8,"hotness":13,"is_selected":14,"score":261,"score_detail":262,"sources":265,"tags":267,"primary_topic":271,"secondary_topics":272,"classification":273,"search_phrases":297,"slug":300,"view_count":301,"doi":302,"paper":303,"created_at":331},3786,"A cost-effective approach of building plant digital twin combining plant phenotyping and growth models: A case study on rapeseed plants","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eja.2026.128341","High-throughput phenotyping platforms enable dense temporal monitoring of plant growth, yet field-based image collection remains labor-intensive with sparse sampling intervals, leading to missing information on intermediate developmental stages. Functional–structural plant models (FSPMs) offer dynamic growth simulation but often lack realistic 3D architecture derived from actual plants. This study proposes a lightweight framework that bridges sparse phenotyping time points by integrating 3D reconstruction with the GreenLab plant growth model, enabling the construction of plant digital twins for rapeseed ( Brassica napus L.). Multi-angle smartphone images of four rapeseed cultivars at two key growth stages were used to reconstruct 3D plant architecture via 3D Gaussian Splatting (3DGS). Leaves were segmented from the point cloud to calculate area. GreenLab source and sink parameters were estimated from organ-level fresh weights (leaves, internodes, and roots) measured at two growth stages. The goodness–of–fit was high, with weighted sum of squares (WSS) between 5.63 and 9.33 and Pearson correlation coefficients ( r ) ranging from 0.93 to 0.95 across the four cultivars. The calibrated model reproduced leaf areas consistent with 3D reconstructed static structures. Reconstructed organ geometries were used for visualization and functional analysis of light interception. The integrated model thus recovered the complete dynamic development and growth trajectory between sparse sampling points. Temporal hold-out validation showed reasonable agreement between reconstructed leaf area and length–width–derived reference estimates, with a single-leaf mean absolute percentage error (MAPE) of 18.42%. Light interception analysis revealed cultivar-specific differences in canopy light use efficiency attributable to contrasting morphological architectures. Simulated and reconstructed canopy light interception showed strong agreement ( r = 0.98 ). This framework provides a cost-effective approach to reconstructing plant growth dynamics and evaluating light capture characteristics from minimal field data. It offers practical utility for breeders in cultivar evaluation and for optimizing environmental control strategies in precision agriculture.","高通量表型平台能够实现对植物生长的高密度时间监测，但田间图像采集仍然劳动密集且采样间隔稀疏，导致中间发育阶段的信息缺失。功能–结构植物模型（FSPMs）能够进行动态生长模拟，但通常缺乏源自实际植物的真实三维结构。本研究提出了一种轻量级框架，通过整合三维重建与GreenLab植物生长模型来桥接稀疏表型时间点，从而为甘蓝型油菜（Brassica napus L.）构建植物数字孪生。利用四个油菜品种在两个关键生长阶段的多角度智能手机图像，通过三维高斯泼溅（3DGS）重建植物三维结构。从点云中分割叶片以计算叶面积。基于两个生长阶段测定的器官水平鲜重（叶片、节间和根系）估计GreenLab源和库参数。拟合优度较高，四个品种的加权平方和（WSS）在5.63至9.33之间，皮尔逊相关系数（r）在0.93至0.95之间。校准后的模型再现的叶面积与三维重建的静态结构一致。重建的器官几何结构用于可视化和光截获功能分析。该集成模型由此恢复了稀疏采样点之间完整的动态发育和生长轨迹。时间留出验证表明，重建叶面积与基于长宽推导的参考估计之间具有合理的一致性，单叶平均绝对百分比误差（MAPE）为18.42%。光截获分析揭示了由于形态结构差异导致的品种特异性冠层光利用效率差异。模拟与重建的冠层光截获表现出高度一致性（r = 0.98）。该框架提供了一种经济有效的方法，可从最少的田间数据重建植物生长动态并评估光捕获特征。它为育种者进行品种评估以及优化精准农业中的环境调控策略提供了实用价值。","European Journal of Agronomy","2026-09-28T00:00:00Z",78,{"impact":147,"substance":263,"depth":19,"authority":131,"freshness":132,"relevant":22,"comment":264},22,"该研究提出结合3D高斯泼溅与GreenLab模型的低成本植物数字孪生框架，在油菜上验证可靠，对智慧育种与精准农业有实用价值，值得精选。",[266],{"name":259,"url":256},[137,28,268,269,270],"表型组学","作物生长模型","植物数字孪生",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":274},{"candidates":275,"agricultural_evidence":46},[276,283,287,292],{"code":156,"score":19,"supported":46,"title":277,"abstract":279,"tags":282},[278],"digital twin",[200,280,281],"数字孪生","precision agriculture",[137],{"code":32,"score":147,"supported":46,"title":284,"abstract":285,"tags":286},[49],[28,49],[28],{"code":52,"score":53,"supported":46,"title":288,"abstract":289,"tags":291},[],[290],"甘蓝",[],{"code":293,"score":22,"supported":14,"title":294,"abstract":295,"tags":296},"I2",[],[],[269],[298,299],"油菜 植物数字孪生 表型","GreenLab 生长模型 油菜","油菜植物数字孪生表型-3786",4,"10.1016\u002Fj.eja.2026.128341",{"doi":302,"openalex_id":304,"authors":305,"venue":259,"cited_by_count":116,"oa_url":256,"card":325,"direction":329,"ingested_from":186},"W7214617633",[306,309,312,314,316,318,320,322],{"name":307,"orcid":308},"Xiujuan Wang","https:\u002F\u002Forcid.org\u002F0000-0001-8327-1735",{"name":310,"orcid":311},"Bowen Zheng","https:\u002F\u002Forcid.org\u002F0009-0008-1141-7158",{"name":313,"orcid":8},"Zhiqing Liu",{"name":315,"orcid":8},"Cuiping Bu",{"name":317,"orcid":8},"Jing Hua",{"name":319,"orcid":8},"Haoyu Wang",{"name":321,"orcid":8},"Qirun Huo",{"name":323,"orcid":324},"Mengzhen Kang","https:\u002F\u002Forcid.org\u002F0000-0002-5016-1772",{"tldr":326,"method":327,"finding":328,"direction":329,"opportunity":330},"结合手机3D重建与GreenLab生长模型，低成本构建油菜植株数字孪生。","多角度手机图像3D高斯泼溅重建，GreenLab源库参数标定与光截获分析。","模型拟合优度高（r=0.93-0.95），可恢复稀疏采样间生长动态并评估光截获。","农业遥感与作物表型","可探索将轻量级数字孪生框架扩展至更多作物及田间高通量场景，降低表型监测成本。","2026-09-29T23:30:23.763490Z",{"id":333,"title":334,"url":335,"summary":336,"summary_zh":8,"content":337,"source_name":338,"source_url":8,"published_at":339,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":340,"score_detail":341,"sources":343,"tags":345,"primary_topic":350,"secondary_topics":351,"classification":352,"search_phrases":380,"slug":383,"view_count":53,"doi":8,"paper":8,"created_at":384},3297,"山区油菜智能化监测成果在十堰国家农业科技园区落地推广——天空地一体化监测技术与山区油菜大数据平台","https:\u002F\u002Fwww.iarrp.cn\u002Fysdt\u002Fkydt\u002Fd6e5d598bf9f4f998f7f08d7c811699c.htm","近日，由中国农业科学院农业资源与农业区划研究所牵头实施的国家重点研发计划课题山区油菜产业智能化关键技术和机械装备研究示范成果应用推广会在十堰国家农业科技园区召开。项目首席科学家梅德圣研究员及行业专家，十堰市农技中心及下属各县农技中心、长阳县等秦巴山区县基层农技推广部门、区域内油菜种植大户代表参会。课题组精准锚定秦巴山区油菜生产实际需求，构建天空地一体化监测技术与山区油菜大数据平台，能够对区域气候环境、油菜长势、菌核病发生态势开展动态监测与智能研判；研发适配山地小地块、不规则地块的油菜播种、田间管护、无人植保等专用系统装备。","近日，由中国农业科学院农业资源与农业区划研究所牵头实施的国家重点研发计划课题“山区油菜产业智能化关键技术和机械装备研究示范”成果应用推广会在十堰国家农业科技园区顺利召开。本次会议聚焦山区油菜产业智能化转型痛点难点，集中交付项目核心科技成果，开展大数据平台实操培训，搭建成果落地、技术普及、产业赋能的产学研交流平台，助力秦巴山区油菜产业摆脱传统生产模式，全面迈向数字化、智能化、高效化高质量发展新阶段。项目首席科学家梅德圣研究员等行业专家，十堰市农技中心及下属各县农技中心、长阳县等秦巴山市区县基层农技推广部门，区域内油菜种植大户用户代表参会参训。\n\n我国秦巴等山区油菜种植体量较大，是保障区域油料供给、带动农民增收、助推乡村产业振兴的特色优势产业。但受山地、坡地为主的特殊地形制约，区域内耕地零散、地块不规则，长期存在机械化作业难、生产管理粗放、长势监测滞后、病虫害防控被动、生产数据缺失等突出问题，生产成本偏高、产量稳定性不足，严重制约山区油菜产业提质增效与绿色可持续发展。课题组精准锚定秦巴山区油菜生产实际需求，依托高水平产学研协同攻关体系，针对性开展智能技术改良、专用装备适配、数字体系构建与本地化示范推广，形成一套适配山地生产场景的成熟技术成果与应用模式。\n\n会上，课题组详细介绍了课题研发成果、技术创新亮点与本地化示范成效，顺利完成系列核心成果集中交付。中国农业科学院农业资源与农业区划研究所宋茜研究员表示，课题创新构建天空地一体化监测技术与山区油菜大数据平台，能够对区域气候环境、油菜长势、菌核病发生态势开展动态监测与智能研判，可为田间科学施肥、绿色防控、适时收获、精准植保提供精准数据支撑，改变山区油菜传统凭经验、粗放式的生产管理模式。同时，课题研发适配山地小地块、不规则地块的油菜播种、田间管护、无人植保等专用系统装备，有效破解山地农机作业难度大、精度低、损耗高的产业难题，全面提升山区油菜机械化、标准化作业水平。\n\n为切实打通科技成果落地“最后一公里”，会议同步开展山区油菜大数据平台专项实操培训。项目技术专家围绕平台功能架构、操作流程、数据填报、智能分析、后台运维等核心内容开展系统讲解，结合秦巴山区油菜生产真实场景进行实操演示，现场解答基层农技人员、种植大户在平台使用、技术落地、田间实操中的各类问题。培训内容贴合一线生产需求、实操性极强，有效提升了基层技术人员数字化应用能力，为成果规模化落地推广夯实人才基础。\n\n据了解，课题以十堰柳陂镇示范基地为核心辐射支点，持续拓展示范应用版图，辐射带动五峰、安阳、大柳等多个乡镇开展规模化示范种植，常态化开展技术培训、智能设备实操演示、田间观摩交流、入户指导等配套服务，不断优化完善技术应用模式，成功探索形成一套适配秦巴山区、可复制、可推广的智慧油菜绿色高效生产模式。通过智能化技术与装备的落地应用，有效实现油菜稳产提质、生产降本增效，显著提升山区油菜产业标准化、智能化、现代化发展水平。\n\n与会代表一致认为，该课题成果针对性解决了山区油菜生产的系列瓶颈问题，构建了适配山地特征的智慧油菜生产体系，为山区油料产业高质量发展提供了优秀示范样板。下一步，课题各方将持续深化产学研协同合作，依托十堰国家农业科技园区平台优势，持续迭代优化大数据平台功能与智能装备性能，持续扩大示范推广覆盖面，常态化开展基层技术赋能服务，全力推动智慧油菜生产技术在秦巴武陵山区落地普及、提质增效，持续助力区域油料稳产保供、农业绿色发展、农民增收致富与乡村全面振兴。","中国农业科学院农业资源与农业区划研究所 2026年09月18日","2026-09-18T00:00:00Z",70,{"impact":19,"substance":19,"depth":131,"authority":131,"freshness":21,"relevant":22,"comment":342},"国家重点研发计划课题成果在十堰国家农业科技园区落地推广，天空地一体化监测与山区油菜大数据平台具备实质技术内容与示范价值，值得进入每日精选。",[344],{"name":338,"url":335},[137,346,347,28,348,349],"农业遥感","成果转化","天空地一体化","大数据平台",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":353},{"candidates":354,"agricultural_evidence":46},[355,359,365,371,375],{"code":32,"score":77,"supported":46,"title":356,"abstract":357,"tags":358},[28],[28],[28],{"code":360,"score":301,"supported":46,"title":361,"abstract":362,"tags":364},"G1",[],[363],"农技推广",[347],{"code":366,"score":53,"supported":46,"title":367,"abstract":368,"tags":370},"F4",[],[369],"植保",[],{"code":156,"score":22,"supported":14,"title":372,"abstract":373,"tags":374},[],[],[137],{"code":376,"score":22,"supported":14,"title":377,"abstract":378,"tags":379},"I3",[],[],[346],[381,382],"十堰 山区油菜 智能化监测","天空地一体化 油菜大数据平台","十堰山区油菜智能化监测-3297","2026-09-24T00:03:59.027363Z",{"id":386,"title":387,"url":388,"summary":389,"summary_zh":8,"content":8,"source_name":390,"source_url":8,"published_at":391,"category":126,"cover_url":8,"hotness":13,"is_selected":14,"score":261,"score_detail":392,"sources":395,"tags":397,"primary_topic":401,"secondary_topics":402,"classification":403,"search_phrases":430,"slug":433,"view_count":212,"doi":8,"paper":434,"created_at":442},3000,"Plant-GeoAT：几何感知3D植物点云器官身份解析用于器官级表型分析","https:\u002F\u002Fwww.mdpi.com\u002F2073-4395\u002F16\u002F18\u002F1809","四川农业大学吴俊杰等提出Plant-GeoAT几何感知解析网络，在RGB融合前编码局部相对-XYZ邻域并将空间邻域与特征空间关系耦合用于密集点预测。在自建油菜数据集、基于图像的大豆数据集、激光扫描Pheno4D玉米和番茄数据集上评估，5个随机种子下mIoU分别达92.26±0.28%、82.50±0.24%、99.74±0.05%、94.75±0.15%，玉米Stem IoU达99.57±0.09%。","MDPI Agronomy 16(18):1809","2026-09-15T00:00:00Z",{"impact":19,"substance":393,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":394},23,"方法新颖、多作物多数据集验证且精度数据扎实，属器官级表型分析细分领域的重要技术进展，值得进入每日精选。",[396],{"name":390,"url":388},[137,398,28,399,400],"农业人工智能","高通量表型","三维点云",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":404},{"candidates":405,"agricultural_evidence":46},[406,411,417,422,426],{"code":32,"score":45,"supported":46,"title":407,"abstract":408,"tags":410},[],[409,28],"大豆",[28],{"code":412,"score":53,"supported":46,"title":413,"abstract":414,"tags":416},"A3",[],[415],"玉米",[],{"code":52,"score":53,"supported":46,"title":418,"abstract":419,"tags":421},[],[420],"番茄",[],{"code":293,"score":212,"supported":14,"title":423,"abstract":424,"tags":425},[],[],[400,398],{"code":156,"score":22,"supported":14,"title":427,"abstract":428,"tags":429},[],[],[137],[431,432],"四川农业大学 植物点云 器官识别","Plant-GeoAT 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