[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-249":3,"related-249":67},{"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,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":61,"slug":64,"view_count":65,"doi":8,"paper":8,"created_at":66},249,"上海\"十五五\"农业科技进步贡献率力争达82%左右——明确建设10万亩智慧农场、培育3-5家新型研发机构","https:\u002F\u002Ffinance.sina.com.cn\u002Ftjhz\u002F2026-08-07\u002Fdoc-inimmtwx3280026.shtml","经上海市政府批准,《上海市推进乡村全面振兴\"十五五\"规划》正式印发,提出\"1512\"目标体系:1个总目标(到2030年上海乡村全面振兴取得实质性新成效)+5个分目标(产业体系质效更优、优质空间覆盖更广、文明新风浸润更深、治理体系基础更牢、居民生活水平更高)+12项主要指标。\"十四五\"末上海农业科技进步贡献率已达81.7%,位居全国第一;《规划》提出到2030年农业科技进步贡献率达到82%左右,加快农业数智化转型,建立健全农业数据分级分类体系,推动市区两级共建共享\"农业一张图\",提升智慧农业产业数据归集运用水平,建设10万亩智慧农场;引导社会力量建设3-5家新型研发机构,新培育一批农业产业领域上市企业;强化企业创新主体地位,支持涉农科技型企业联动高端装备、人工智能等领域企业牵头开展以产业应用为导向的集成创新。",null,"“十五五”的上海乡村什么样？根据日前印发的《上海市推进乡村全面振兴“十五五”规划》（以下简称《规划》），上海将进一步凸显乡村地区的经济价值、生态价值、社会价值、文化价值，让乡村成为新质生产力的“孵化器”和“试验场”。\n\n农业如何在超大城市释放大能量？《规划》给出一个清晰的“1+5+12”目标体系——“1”是到2030年上海乡村全面振兴取得实质性新成效的总目标；“5”个分目标涵盖乡村产业体系质效更优、乡村优质空间覆盖更广、乡村文明新风浸润更深、乡村治理体系基础更牢、乡村居民生活水平更高；“12”项主要指标中，农业劳动生产率提升至7.3万元\u002F人左右，城乡居民人均可支配收入比值缩小至1.85左右，宜居宜业和美乡村覆盖率提升至60%。\n\n“这份《规划》关于产业振兴的笔墨更重、内涵更丰富，核心是让上海的乡村不仅有好风光、好生态，更要有新产业、新业态。”上海市政府副秘书长、市发展改革委主任刘健表示。\n\n《规划》的重点任务可概括为五个方面：一是在发展格局上强统筹，推动城乡更加融合，构建“一带、四区、多节点”的乡村全面振兴战略布局，“一带”即环都市圈城乡融合发展带，“四区”即崇明三岛、黄浦江上游、杭州湾北岸、沪北等重点功能区，“多节点”即结合“五个新城”、长三角生态绿色一体化发展示范区等重大战略区域打造乡村振兴核心节点；二是在产业发展上增动能，推动产业更兴旺；三是在乡村建设上提品质，推动村庄更和美，到2030年累计打造不少于50个宜居宜业和美乡村片区；四是在农民增收上拓渠道，推动生活更富裕；五是在体制机制上谋创新，推动资源向农村倾斜。\n\n值得注意的是，科技创新是推进上海乡村全面振兴的一大突破口。“十四五”末，上海农业科技进步贡献率达81.7%，位居全国第一。\n\n以金山区为例，当地正搭建科创平台，推动先正达集团全球植保中国创新中心、节水抗旱稻国际策源中心等高能级载体落地；深化与上海市农业科学院及高校合作，加快培育像“申K6”食用菌、“申王1号”肉鸽一样拥有自主知识产权的突破性品种，健全枫泾黑毛猪等特色种质资源保护利用体系。\n\n《规划》提出，到2030年，农业科技进步贡献率达到82%左右。上海将加快农业数智化转型，建立健全农业数据分级分类体系，推动市区两级共建共享“农业一张图”，提升智慧农业产业数据归集运用水平，建设10万亩智慧农场；引导社会力量建设3—5家新型研发机构，新增一批农业产业领域上市企业，培育一批生物育种、农业生物制造、现代设施农业等领域科技型企业；强化企业创新主体地位，支持涉农科技型企业联动高端装备、人工智能等领域企业，牵头开展以产业应用为导向的集成创新，打造和开放一批具有全国影响力的农业科技创新应用场景。（王春）","科技日报 2026-08-07","2026-08-07T00:00:00Z","政策",10,false,87,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":22},25,22,18,12,1,"上海十五五农业规划发布，明确智慧农场等量化目标，政策层级高、信息具体，时效性强。",[24],{"name":10,"url":6},[26,27,28,29,30],"十五五规划","智慧农场","上海","农业科技进步贡献率","农业数智化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I1","smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,51,56],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":50},4,true,[],[49],"智慧农业",[30],{"code":52,"score":21,"supported":14,"title":53,"abstract":54,"tags":55},"F6",[],[],[27],{"code":57,"score":21,"supported":14,"title":58,"abstract":59,"tags":60},"J1",[],[],[26],[62,63],"农业科技进步贡献率 农业数智化 十五五规划 智慧农场","农业科技进步贡献率 农业数智化","农业科技进步贡献率农业数智化十五五规划智慧农场-249",14,"2026-08-07T00:18:27.780379Z",{"total":68,"page":21,"page_size":68,"items":69},6,[70,129,184,241,298,340],{"id":71,"title":72,"url":73,"summary":74,"summary_zh":8,"content":8,"source_name":75,"source_url":73,"published_at":76,"category":77,"cover_url":8,"hotness":13,"is_selected":14,"score":78,"score_detail":79,"sources":82,"tags":84,"primary_topic":89,"secondary_topics":90,"classification":91,"search_phrases":105,"slug":108,"view_count":109,"doi":110,"paper":111,"created_at":128},5579,"A Composite Field-Evaluation Framework for Digital Agriculture Maps","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11283264\u002Fv1","A Composite Field-Evaluation Framework for Digital Agriculture Maps。Research Square","Research Square","2026-10-21T00:00:00Z","论文",38,{"impact":80,"substance":68,"depth":80,"authority":68,"freshness":13,"relevant":21,"comment":81},8,"预印本提出数字农业地图的田间复合评估框架，方法有一定新意，但摘要信息极少、未经同行评审，公共影响有限，暂不宜进入每日精选。",[83],{"name":75,"url":73},[85,86,87,88],"数字农业","农业信息化","遥感","地图评估",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":92},{"candidates":93,"agricultural_evidence":46},[94,100],{"code":32,"score":95,"supported":46,"title":96,"abstract":98,"tags":99},13,[97],"digital agriculture",[97],[86,85],{"code":101,"score":21,"supported":14,"title":102,"abstract":103,"tags":104},"I3",[],[],[87],[106,107],"Research Square 数字农业","农业信息化 地图评估 数字农业 遥感","ResearchSquare数字农业-5579",0,"10.21203\u002Frs.3.rs-11283264\u002Fv1",{"doi":110,"openalex_id":112,"authors":113,"venue":75,"cited_by_count":109,"oa_url":73,"card":8,"direction":126,"ingested_from":127},"W7223099987",[114,117,120,123],{"name":115,"orcid":116},"Phillip Lanza","https:\u002F\u002Forcid.org\u002F0000-0002-5545-1744",{"name":118,"orcid":119},"David G. Rossiter","https:\u002F\u002Forcid.org\u002F0000-0003-4558-1286",{"name":121,"orcid":122},"Diana Stuart Sinton","https:\u002F\u002Forcid.org\u002F0000-0001-5828-9001",{"name":124,"orcid":125},"Louis Longchamps","https:\u002F\u002Forcid.org\u002F0000-0002-4761-6094","数字乡村与农业信息化","openalex","2026-10-22T11:20:47.463814Z",{"id":130,"title":131,"url":132,"summary":133,"summary_zh":134,"content":8,"source_name":135,"source_url":132,"published_at":76,"category":77,"cover_url":8,"hotness":13,"is_selected":14,"score":136,"score_detail":137,"sources":140,"tags":142,"primary_topic":147,"secondary_topics":148,"classification":149,"search_phrases":166,"slug":169,"view_count":109,"doi":170,"paper":171,"created_at":183},5578,"Unlocking digital agriculture through new quality productive forces: nonlinear thresholds and spatial spillovers in China","https:\u002F\u002Fdoi.org\u002F10.1057\u002Fs41599-026-09510-z","New quality productive forces (NQPF) critically enable agricultural digitisation. Using China as a case study, this paper employs panel data from 284 prefecture-level cities in China from 2011 to 2022. The results show that NQPF has a significant promoting effect on agricultural digital transformation and exhibits positive spatial spillover effects, driving not only local transformation but also the development of surrounding regions. Labour skills and innovation capacity play mediating roles in this process. Notably, the enabling effect of NQPF on agricultural digitisation displays significant regional heterogeneity. Threshold analysis indicates that its promoting effect follows a non-linear pattern, characterised by a double threshold effect. Therefore, the development of NQPF should be accelerated, with emphasis placed on regional coordination and talent cultivation, to promote the sustained and in-depth advancement of agricultural digital transformation in accordance with local conditions.","新质生产力（New Quality Productive Forces, NQPF）对农业数字化具有关键赋能作用。本文以中国为案例，采用2011—2022年中国284个地级市的面板数据。结果表明，新质生产力对农业数字化转型具有显著促进作用，并呈现正向空间溢出效应，不仅推动本地转型，也带动周边地区发展。劳动技能与创新能力在这一过程中发挥中介作用。值得注意的是，新质生产力对农业数字化的赋能效应表现出显著的区域异质性。门槛分析表明，其促进作用呈非线性特征，表现为双重门槛效应。因此，应加快新质生产力发展，注重区域协调与人才培养，因地制宜推动农业数字化转型持续深入推进。","Humanities and Social Sciences Communications",81,{"impact":19,"substance":18,"depth":19,"authority":65,"freshness":138,"relevant":21,"comment":139},9,"基于284个地级市面板数据的实证研究，揭示新质生产力对农业数字化的非线性门槛与空间溢出效应，方法规范、结论有政策参考价值，值得进入每日精选。",[141],{"name":135,"url":132},[85,143,144,145,146],"新质生产力","空间溢出","区域协调","农业数字化转型",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":150},{"candidates":151,"agricultural_evidence":46},[152,156,161],{"code":32,"score":13,"supported":46,"title":153,"abstract":154,"tags":155},[97],[],[146,85],{"code":157,"score":21,"supported":14,"title":158,"abstract":159,"tags":160},"I4",[],[],[144],{"code":162,"score":21,"supported":14,"title":163,"abstract":164,"tags":165},"J2",[],[],[143],[167,168],"新质生产力 农业数字化","地级市 面板数据","新质生产力农业数字化-5578","10.1057\u002Fs41599-026-09510-z",{"doi":170,"openalex_id":172,"authors":173,"venue":135,"cited_by_count":109,"oa_url":132,"card":178,"direction":126,"ingested_from":127},"W7221723385",[174,176],{"name":175,"orcid":8},"Qingqing Huang",{"name":177,"orcid":8},"Wenjing Guo",{"tldr":179,"method":180,"finding":181,"direction":126,"opportunity":182},"基于中国284个地级市面板数据，检验新质生产力对农业数字化的促进、空间溢出与门槛效应。","2011—2022年284个地级市面板数据，空间计量与门槛回归，中介效应检验。","新质生产力显著促进农业数字化并具正向空间溢出，存在双门槛非线性效应与区域异质性。","可深入探究新质生产力影响农业数字化的微观机制，以及不同区域门槛条件下的差异化政策路径。","2026-10-22T11:20:47.354744Z",{"id":185,"title":186,"url":187,"summary":188,"summary_zh":8,"content":8,"source_name":189,"source_url":187,"published_at":190,"category":77,"cover_url":8,"hotness":13,"is_selected":14,"score":191,"score_detail":192,"sources":196,"tags":198,"primary_topic":203,"secondary_topics":204,"classification":205,"search_phrases":220,"slug":223,"view_count":109,"doi":224,"paper":225,"created_at":240},5539,"Robust and transparent crop-row detection from RGB field imagery for vision-based agricultural guidance systems","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11119-026-10473-z","Robust and transparent crop-row detection from RGB field imagery for vision-based agricultural guidance systems。Precision Agriculture","Precision Agriculture","2026-10-22T00:00:00Z",79,{"impact":193,"substance":194,"depth":19,"authority":65,"freshness":13,"relevant":21,"comment":195},16,21,"核心期刊新论文，提出鲁棒且可解释的RGB作物行检测方法，对视觉导航农机具参考价值明确，但属细分技术进展，未达重大突破层级。",[197],{"name":189,"url":187},[49,199,200,201,202],"农业人工智能","精准农业","机器视觉","作物行检测",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":206},{"candidates":207,"agricultural_evidence":46},[208,214],{"code":32,"score":209,"supported":46,"title":210,"abstract":211,"tags":213},5,[],[212],"precision agriculture",[49,200],{"code":215,"score":216,"supported":14,"title":217,"abstract":218,"tags":219},"I2",2,[],[],[199,201],[221,222],"RGB 作物行检测","农业人工智能 作物行检测 智慧农业 机器视觉","RGB作物行检测-5539","10.1007\u002Fs11119-026-10473-z",{"doi":224,"openalex_id":226,"authors":227,"venue":189,"cited_by_count":109,"oa_url":8,"card":8,"direction":8,"ingested_from":127},"W7223117828",[228,231,234,237],{"name":229,"orcid":230},"Esther Gascó","https:\u002F\u002Forcid.org\u002F0000-0003-1798-4483",{"name":232,"orcid":233},"Clara I. López-González","https:\u002F\u002Forcid.org\u002F0000-0002-2755-1692",{"name":235,"orcid":236},"Eva Besada-Portas","https:\u002F\u002Forcid.org\u002F0000-0001-6129-4653",{"name":238,"orcid":239},"Gonzalo Pájares","https:\u002F\u002Forcid.org\u002F0000-0003-0915-6282","2026-10-22T11:20:09.678587Z",{"id":242,"title":243,"url":244,"summary":245,"summary_zh":246,"content":8,"source_name":247,"source_url":244,"published_at":248,"category":77,"cover_url":8,"hotness":17,"is_selected":14,"score":249,"score_detail":250,"sources":253,"tags":257,"primary_topic":262,"secondary_topics":263,"classification":264,"search_phrases":281,"slug":284,"view_count":109,"doi":285,"paper":286,"created_at":297},5397,"The Relationship Between Nutrient Concentration and Measurable Optical Characteristics of Banana Leaves: A Quantitative Image-Based Study","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23469780","Relationship between Nutrient Concentration and Measurable Optical Characteristics of Banana Leaves: A Quantitative Image-Based Study explores the relationship between nutrient concentrations and the optical characteristics of banana leaves using quantitative image analysis. The study focuses on measurable leaf features, including colour intensity, RGB values, and other image-derived parameters, to identify patterns associated with plant nutrient status. Digital images of banana leaves can provide valuable information about variations in leaf appearance that may reflect differences in nutrient availability. By analysing these characteristics alongside nutrient concentration measurements, the study aims to establish quantitative relationships that can support plant nutrient assessment. This approach may contribute to the development of cost-effective, non-destructive, and image-based techniques for monitoring banana plant health. The findings can be useful for precision agriculture, crop management, and future research on digital image processing for agricultural applications.","香蕉叶片养分浓度与可测量光学特征之间的关系：一项基于定量图像的研究探讨了利用定量图像分析研究香蕉叶片养分浓度与光学特征之间的关系。该研究聚焦于可测量的叶片特征，包括颜色强度、RGB值及其他图像衍生参数，以识别与植物养分状况相关的模式。香蕉叶片的数字图像可提供关于叶片外观变化的有价值信息，这些变化可能反映养分有效性的差异。通过将这些特征与养分浓度测量结果一并分析，该研究旨在建立可支持植物养分评估的定量关系。该方法可能有助于开发低成本、非破坏性且基于图像的香蕉植株健康监测技术。研究结果可用于精准农业、作物管理以及未来农业应用数字图像处理的研究。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-19T00:00:00Z",66,{"impact":20,"substance":19,"depth":251,"authority":20,"freshness":138,"relevant":21,"comment":252},15,"该研究基于图像定量分析香蕉叶片营养状况，方法新颖且面向无损监测，对精准农业有参考价值，但属单作物探索性研究，影响范围有限。",[254,255],{"name":247,"url":244},{"name":247,"url":256},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23470020",[49,258,259,260,261],"图像分析","香蕉","无损监测","作物营养",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":265},{"candidates":266,"agricultural_evidence":46},[267,272,277],{"code":32,"score":268,"supported":46,"title":269,"abstract":270,"tags":271},7,[],[200,212],[49],{"code":273,"score":21,"supported":14,"title":274,"abstract":275,"tags":276},"B2",[],[],[259],{"code":215,"score":21,"supported":14,"title":278,"abstract":279,"tags":280},[],[],[258],[282,283],"香蕉叶片 营养浓度 图像分析","香蕉 无损监测 精准农业","香蕉叶片营养浓度图像分析-5397","10.5281\u002Fzenodo.23469780",{"doi":285,"openalex_id":287,"authors":288,"venue":247,"cited_by_count":109,"oa_url":244,"card":291,"direction":126,"ingested_from":127},"W7222941290",[289],{"name":290,"orcid":8},"Anantjit Publication",{"tldr":292,"method":293,"finding":294,"direction":295,"opportunity":296},"用定量图像分析探究香蕉叶片养分浓度与可测光学特征的关系。","采集香蕉叶片数字图像，提取颜色强度、RGB值等参数，与养分浓度做定量关联分析。","叶片图像光学特征与养分浓度存在可量化的关联，可支撑无损养分评估。","农业遥感与作物表型","可扩展到多品种、多生育期与田间光照校正，并构建图像-养分反演模型与便携诊断工具。","2026-10-20T23:30:22.619634Z",{"id":299,"title":300,"url":301,"summary":302,"summary_zh":8,"content":8,"source_name":303,"source_url":301,"published_at":248,"category":77,"cover_url":8,"hotness":17,"is_selected":14,"score":304,"score_detail":305,"sources":307,"tags":311,"primary_topic":313,"secondary_topics":314,"classification":315,"search_phrases":322,"slug":325,"view_count":109,"doi":326,"paper":327,"created_at":339},5396,"Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.","https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.22601.71520","Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.。OpenAlex","OpenAlex",37,{"impact":80,"substance":68,"depth":80,"authority":68,"freshness":138,"relevant":21,"comment":306},"中非数字农业系统综述，主题相关但摘要信息极少，仅题录级元数据，增量与权威性有限，不建议进入每日精选。",[308,309],{"name":303,"url":301},{"name":303,"url":310},"https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.16146.41922",[85,49,86,312],"中非",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":316},{"candidates":317,"agricultural_evidence":46},[318],{"code":32,"score":65,"supported":46,"title":319,"abstract":320,"tags":321},[97],[97],[86,85,49],[323,324],"中非 数字农业","农业信息化 数字农业 智慧农业 中非","中非数字农业-5396","10.13140\u002Frg.2.2.22601.71520",{"doi":326,"openalex_id":328,"authors":329,"venue":8,"cited_by_count":109,"oa_url":301,"card":8,"direction":126,"ingested_from":127},"W7222930115",[330,332,334,337],{"name":331,"orcid":8},"Anani Ogou",{"name":333,"orcid":8},"Henry Chotangui",{"name":335,"orcid":336},"Honoré Beyegue-Djonko","https:\u002F\u002Forcid.org\u002F0009-0004-6447-5889",{"name":338,"orcid":8},"Christopher Mubeteneh Tankou","2026-10-20T23:30:22.542913Z",{"id":341,"title":342,"url":343,"summary":344,"summary_zh":345,"content":8,"source_name":346,"source_url":343,"published_at":248,"category":77,"cover_url":8,"hotness":17,"is_selected":14,"score":347,"score_detail":348,"sources":350,"tags":355,"primary_topic":361,"secondary_topics":362,"classification":363,"search_phrases":382,"slug":385,"view_count":109,"doi":386,"paper":387,"created_at":403},5383,"The transition towards CSA as a relational model: shaping relational processes between farmers and governments, agri-food corporations and the financial sector","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.34701594","Climate-smart agriculture (CSA) can enhance the mitigation and adaptation capacity of the sector. Yet progress towards CSA remains slow. Durable and scalable transformation requires more than technological adoption or changes in farmers’ capabilities; it depends on the relationships through which actors coordinate resources, interests, and institutional conditions. However, these interdependencies remain fragmented across the literature. This article aims to address this gap by presenting a relational framework for this transformation by focusing on the most impactful relational processes through an integrative review. We identified three relational mechanisms shaping CSA transitions: resource-mobilising, interest-aligning, and institutional-shaping. Across these mechanisms, transformative capacity depends less on the actors involved or the resources exchanged than on how the underlying relationship is configured. Drawing on Emerson’s power-dependence framework and building on Pahl-Wostl’s conceptualisation of governance modes, the proposed framework shows how relational mechanisms and their specific configuration can reproduce hierarchical arrangements or contribute to more networked forms of governance. This study contributes to the body of research on agri-food sustainability transitions and governance by shifting attention from individual adoption and actor roles to the relational configurations through which CSA transitions are enabled or constrained. Moreover, it provides practitioners with insights into mechanisms enhancing CSA adoption.","气候智慧型农业（climate-smart agriculture, CSA）能够增强该领域的减缓与适应能力。然而，迈向气候智慧型农业的进展仍然缓慢。持久且可扩展的转型不仅需要技术采纳或农民能力的变化，还依赖于行动者用以协调资源、利益与制度条件的关系。然而，这些相互依存关系在现有文献中仍呈碎片化状态。本文旨在通过整合性综述聚焦最具影响力的关系过程，提出一个用于该转型的关系框架，以弥补这一空白。我们识别出塑造气候智慧型农业转型的三种关系机制：资源动员、利益协调与制度塑造。在这些机制中，转型能力与其说取决于所涉及的行动者或所交换的资源，不如说取决于底层关系的配置方式。借鉴Emerson的权力—依赖框架，并以Pahl-Wostl关于治理模式的概念化为基础，所提出的框架展示了关系机制及其特定配置如何能够再生产等级化安排，或促进更具网络化形式的治理。本研究通过将关注点从个体采纳和行动者角色转向使气候智慧型农业转型得以实现或受到制约的关系配置，为农业食品可持续转型与治理研究作出了贡献。此外，本研究为实践者提供了关于促进气候智慧型农业采纳机制的洞见。","Figshare",60,{"impact":20,"substance":19,"depth":193,"authority":68,"freshness":80,"relevant":21,"comment":349},"该文以整合性综述提出气候智慧农业转型的关系性框架，学术增量明确，但属理论探讨、来源为预印本平台，公共影响有限，不宜进入每日精选。",[351,352],{"name":346,"url":343},{"name":353,"url":354},"International Journal of Agricultural Sustainability","https:\u002F\u002Fdoi.org\u002F10.1080\u002F14735903.2026.2742575",[356,357,358,359,360],"气候智慧农业","农业可持续","农业转型","农业治理","农户关系",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":364},{"candidates":365,"agricultural_evidence":46},[366,372,377],{"code":32,"score":367,"supported":46,"title":368,"abstract":369,"tags":371},3,[],[370],"smart agriculture",[],{"code":373,"score":21,"supported":14,"title":374,"abstract":375,"tags":376},"H7",[],[],[356],{"code":378,"score":21,"supported":14,"title":379,"abstract":380,"tags":381},"H8",[],[],[357],[383,384],"气候智慧农业 农业可持续 农业治理 农业转型","气候智慧农业 农业可持续","气候智慧农业农业可持续农业治理农业转型-5383","10.6084\u002Fm9.figshare.34701594",{"doi":386,"openalex_id":388,"authors":389,"venue":346,"cited_by_count":109,"oa_url":343,"card":396,"direction":402,"ingested_from":127},"W7222983506",[390,392,394],{"name":391,"orcid":8},"Eduardo Garcia-Igualada",{"name":393,"orcid":8},"Amparo Merino de Diego",{"name":395,"orcid":8},"Victor Luis de Nicolás",{"tldr":397,"method":398,"finding":399,"direction":400,"opportunity":401},"通过整合综述提出关系框架，解释农民与政府、企业、金融部门的关系配置如何影响气候智慧型农业转型。","整合综述，基于Emerson权力依赖框架与Pahl-Wostl治理模式概念化三类","转型能力更取决于关系配置方式而非参与主体或交换资源，关系机制可复制等级安排或推动网络化治理。","农业绿色发展与碳","可将关系配置框架操作化为可测指标，结合中国小农户与政府、企业、金融互动数据检验其对CSA采纳的因果影响。","智慧农业 \u002F 农业物联网","2026-10-20T23:30:08.809392Z"]