[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3297":3,"related-3297":79},{"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":22,"tags":24,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":74,"slug":77,"view_count":59,"doi":8,"paper":8,"created_at":78},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。",null,"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","报道",10,false,70,{"impact":17,"substance":17,"depth":18,"authority":18,"freshness":19,"relevant":20,"comment":21},18,14,6,1,"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。",[23],{"name":10,"url":6},[25,26,27,28,29,30],"智慧农业","农业遥感","成果转化","油菜","天空地一体化","大数据平台",{"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},[44,50,57,64,69],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},12,true,[28],[28],[28],{"code":51,"score":52,"supported":46,"title":53,"abstract":54,"tags":56},"G1",4,[],[55],"农技推广",[27],{"code":58,"score":59,"supported":46,"title":60,"abstract":61,"tags":63},"F4",3,[],[62],"植保",[],{"code":65,"score":20,"supported":14,"title":66,"abstract":67,"tags":68},"I1",[],[],[25],{"code":70,"score":20,"supported":14,"title":71,"abstract":72,"tags":73},"I3",[],[],[26],[75,76],"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",{"total":19,"page":20,"page_size":19,"items":80},[81,151,216,295,360,416],{"id":82,"title":83,"url":84,"summary":85,"summary_zh":86,"content":8,"source_name":87,"source_url":84,"published_at":88,"category":89,"cover_url":8,"hotness":13,"is_selected":14,"score":90,"score_detail":91,"sources":96,"tags":98,"primary_topic":102,"secondary_topics":103,"classification":104,"search_phrases":122,"slug":125,"view_count":126,"doi":127,"paper":128,"created_at":150},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 Agriculture","2026-10-01T00:00:00Z","论文",72,{"impact":45,"substance":92,"depth":93,"authority":18,"freshness":94,"relevant":20,"comment":95},20,17,9,"核心期刊论文，SPH-FEM耦合方法研究油菜秸秆磨料气体射流切割机理，方法有新意但属细分领域基础研究，产业影响有限。",[97],{"name":87,"url":84},[25,28,99,100,101],"数值模拟","农业机械","秸秆处理",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":105},{"candidates":106,"agricultural_evidence":46},[107,113,118],{"code":32,"score":108,"supported":46,"title":109,"abstract":111,"tags":112},15,[110],"rapeseed",[28,110],[28],{"code":114,"score":20,"supported":14,"title":115,"abstract":116,"tags":117},"F5",[],[],[100],{"code":65,"score":20,"supported":14,"title":119,"abstract":120,"tags":121},[],[],[25],[123,124],"油菜秸秆 磨料气体射流 切割","SPH-FEM 耦合 秸秆切割","油菜秸秆磨料气体射流切割-3983",0,"10.1016\u002Fj.compag.2026.112469",{"doi":127,"openalex_id":129,"authors":130,"venue":87,"cited_by_count":126,"oa_url":8,"card":143,"direction":147,"ingested_from":149},"W7215128671",[131,134,136,138,140],{"name":132,"orcid":133},"Mun-Sung Han","https:\u002F\u002Forcid.org\u002F0009-0000-4043-6982",{"name":135,"orcid":8},"Xiaokang Qin",{"name":137,"orcid":8},"Kai Yu",{"name":139,"orcid":8},"Yun Chen",{"name":141,"orcid":142},"Kaixiong Hu","https:\u002F\u002Forcid.org\u002F0000-0001-9904-6137",{"tldr":144,"method":145,"finding":146,"direction":147,"opportunity":148},"采用SPH-FEM耦合方法数值与实验研究磨料气体射流切割油菜茎秆的机理。","SPH-FEM耦合数值模拟结合切割实验，分析磨料气体射流切割过程。","揭示了磨料气体射流切割油菜茎秆的力学机制与切割参数影响规律。","农业人工智能与决策模型","可将SPH-FEM耦合仿真拓展至其他作物茎秆切割，并融合机器视觉实现切割参数智能优化。","openalex","2026-10-02T23:30:03.593073Z",{"id":152,"title":153,"url":154,"summary":155,"summary_zh":156,"content":8,"source_name":87,"source_url":154,"published_at":88,"category":89,"cover_url":8,"hotness":13,"is_selected":14,"score":90,"score_detail":157,"sources":159,"tags":161,"primary_topic":165,"secondary_topics":166,"classification":167,"search_phrases":184,"slug":187,"view_count":175,"doi":188,"paper":189,"created_at":215},3977,"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","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":45,"substance":92,"depth":93,"authority":18,"freshness":94,"relevant":20,"comment":158},"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。",[160],{"name":87,"url":154},[25,162,163,28,164],"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":168},{"candidates":169,"agricultural_evidence":46},[170,174,179],{"code":32,"score":108,"supported":46,"title":171,"abstract":172,"tags":173},[110],[28,110],[28],{"code":65,"score":175,"supported":14,"title":176,"abstract":177,"tags":178},2,[],[],[25,163],{"code":180,"score":20,"supported":14,"title":181,"abstract":182,"tags":183},"F6",[],[],[162],[185,186],"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":188,"openalex_id":190,"authors":191,"venue":87,"cited_by_count":126,"oa_url":8,"card":209,"direction":213,"ingested_from":149},"W7215105622",[192,195,197,199,202,204,206],{"name":193,"orcid":194},"Hua Yuan","https:\u002F\u002Forcid.org\u002F0000-0001-7594-8718",{"name":196,"orcid":8},"Qingxi Liao",{"name":198,"orcid":8},"Zhengyu Liu",{"name":200,"orcid":201},"Zhe Liu","https:\u002F\u002Forcid.org\u002F0000-0003-2653-0408",{"name":203,"orcid":8},"Lin Li",{"name":205,"orcid":8},"Yitao Liao",{"name":207,"orcid":208},"Wenli Xiao","https:\u002F\u002Forcid.org\u002F0000-0002-8443-8987",{"tldr":210,"method":211,"finding":212,"direction":213,"opportunity":214},"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":217,"title":218,"url":219,"summary":220,"summary_zh":221,"content":8,"source_name":222,"source_url":219,"published_at":223,"category":89,"cover_url":8,"hotness":13,"is_selected":14,"score":224,"score_detail":225,"sources":228,"tags":230,"primary_topic":234,"secondary_topics":235,"classification":236,"search_phrases":261,"slug":264,"view_count":52,"doi":265,"paper":266,"created_at":294},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":108,"substance":226,"depth":17,"authority":18,"freshness":94,"relevant":20,"comment":227},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。",[229],{"name":222,"url":219},[25,28,231,232,233],"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":237},{"candidates":238,"agricultural_evidence":46},[239,246,250,256],{"code":65,"score":17,"supported":46,"title":240,"abstract":242,"tags":245},[241],"digital twin",[163,243,244],"数字孪生","precision agriculture",[25],{"code":32,"score":108,"supported":46,"title":247,"abstract":248,"tags":249},[110],[28,110],[28],{"code":251,"score":59,"supported":46,"title":252,"abstract":253,"tags":255},"B1",[],[254],"甘蓝",[],{"code":257,"score":20,"supported":14,"title":258,"abstract":259,"tags":260},"I2",[],[],[232],[262,263],"油菜 植物数字孪生 表型","GreenLab 生长模型 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