[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3123":3,"related-3123":72},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":57,"slug":60,"view_count":51,"doi":8,"paper":61,"created_at":71},3123,"Turning Data into Sustainability: Agricultural Big Data Policy, Capital Composition, and Rural Eco-Environmental Sustainability in China（数据转化为可持续性：中国农业大数据政策、资本构成与农村生态环境可持续性）","https:\u002F\u002Fwww.mdpi.com\u002F2071-1050\u002F18\u002F18\u002F9478","湖南第一师范学院马克思主义学院 Zhumiao Wang 等联合吉林大学、韩国圆光大学在《Sustainability》18(18): 9478 发表论文（2026-09-16 发表）。农村环境退化是分散的、监测薄弱的、难以治理的，是可持续发展目标（SDGs）最持久的障碍之一。以 2010-2024 年中国 271 个城市面板数据为基础，以 2016 年农业农村大数据政策（ABDP）试点为\"准自然实验\"，采用交错双重差分（DID）设计估计政策对农村生态环境可持续性（RES）的效应。结果显示 ABDP 使 RES 提升 0.0015 个指数点（相当于样本均值 2.91%、分布 6.8 个百分位点）；效应规模取决于政策所面临的资本存量：随农业机械化（AM）上升而下降并在高机械化水平下变得不显著，随数字资本（DC）上升而上升；田间\"做什么\"的资本替代信息，向田间\"传递信息\"的资本补充信息。增益集中在生产—环境维度。",null,"MDPI Sustainability","2026-09-16T00:00:00Z","论文",10,false,84,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},22,23,18,13,8,1,"基于271城面板数据的交错DID实证，量化农业大数据政策对农村生态可持续性的效应及资本构成的调节作用，方法规范、结论有政策参考价值。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字乡村","农业大数据","农业政策","双重差分","农村生态环境",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":39,"locked":13,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":45},[44,49],{"code":32,"score":12,"supported":45,"title":46,"abstract":47,"tags":48},true,[27],[],[27,26],{"code":50,"score":51,"supported":45,"title":52,"abstract":53,"tags":56},"F5",6,[],[54,55],"农业机械","机械化",[],[58,59],"农业大数据政策 农村生态环境","Zhumiao Wang 农业大数据","农业大数据政策农村生态环境-3123",{"doi":8,"openalex_id":8,"authors":62,"venue":8,"cited_by_count":63,"oa_url":8,"card":64,"direction":68,"ingested_from":70},[],0,{"tldr":65,"method":66,"finding":67,"direction":68,"opportunity":69},"以2016年农业大数据政策试点为准自然实验，评估其对中国农村生态环境可持续性的影响。","2010-2024年271个城市面板数据，交错双重差分（DID）设计。","政策使农村生态可持续性提升约2.91%，效应随数字资本上升、随机械化上升而减弱。","数字乡村与农业信息化","可探究数字资本与机械资本的替代\u002F互补机制，及政策效应在非生产维度的异质性。","agent","2026-09-22T00:05:38.376954Z",{"total":51,"page":21,"page_size":51,"items":73},[74,148,217,270,309,366],{"id":75,"title":76,"url":77,"summary":78,"summary_zh":79,"content":8,"source_name":80,"source_url":77,"published_at":81,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":82,"score_detail":83,"sources":86,"tags":88,"primary_topic":92,"secondary_topics":93,"classification":94,"search_phrases":128,"slug":131,"view_count":63,"doi":132,"paper":133,"created_at":147},5469,"How institutional digitalization reshapes entrepreneurial activity in new agricultural business forms: quasi-natural experimental evidence from China's Digital Village Pilot Policy","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1946061","New agricultural business forms are a key driving force for developing countries to overcome the constraints of traditional agriculture and achieve sustainability in food systems. However, it remains unclear whether institutional digitalization can effectively stimulate entrepreneurial vitality in new agricultural business forms. This study develops a theoretical framework of “opportunity creation–opportunity identification–opportunity transformation” and treats China's Digital Village Pilot Policy (DVPP), implemented in 2020, as a quasi-natural experiment. Based on panel data from 1,743 counties in China from 2014 to 2023, this study employs Double Machine Learning (DML) and Spatial Durbin Difference-in-Differences (SDM-DID) models, among other methods, to systematically identify the impact, transmission mechanisms, heterogeneous effects, and spatial spillover effects of institutional digitalization on Entrepreneurial Activity in New Agricultural Business Forms (EANA). The results reveal that: (1) DVPP significantly enhances EANA, and this finding remains robust after a series of tests, including placebo tests, Propensity Score Matching–Difference-in-Differences (PSM-DID), Synthetic Control Method–Difference-in-Differences (SCM-DID), and instrumental variable (IV) estimation; (2) agricultural technological innovation, digital infrastructure development, and digital financial development serve as mediating mechanisms; (3) the policy effects are more pronounced in counties with higher levels of digital access, better-developed transportation infrastructure, and higher levels of digital financial development, exhibiting a pattern of Central > Western > Eastern regions, and are significantly stronger in areas with advantages in characteristic agricultural products; (4) DVPP generates a significant negative spatial spillover effect on EANA in neighboring counties. This study expands theoretical understanding of the relationship between institutional digitalization and entrepreneurship in new agricultural business forms and provides empirical evidence for China and other developing countries to optimize digital rural development and foster new agricultural business forms.","农业新业态是发展中国家突破传统农业约束、实现食物系统可持续发展的关键驱动力。然而，制度数字化能否有效激发农业新业态的创业活力仍不明确。本研究构建了“机会创造—机会识别—机会转化”的理论框架，并将中国2020年实施的数字乡村试点政策（Digital Village Pilot Policy，DVPP）视为准自然实验。基于中国1743个县2014—2023年的面板数据，本研究采用双重机器学习（Double Machine Learning，DML）和空间杜宾双重差分（Spatial Durbin Difference-in-Differences，SDM-DID）等模型，系统识别制度数字化对农业新业态创业活动（Entrepreneurial Activity in New Agricultural Business Forms，EANA）的影响、传导机制、异质性效应和空间溢出效应。结果表明：（1）DVPP显著提升了EANA，且该结论在经过安慰剂检验、倾向得分匹配—双重差分（PSM-DID）、合成控制法—双重差分（SCM-DID）和工具变量（IV）估计等一系列检验后依然稳健；（2）农业技术创新、数字基础设施建设和数字金融发展发挥中介机制作用；（3）政策效应在数字接入水平较高、交通基础设施较完善和数字金融发展水平较高的县更为显著，呈现出中部>西部>东部的格局，且在特色农产品优势区显著更强；（4）DVPP对邻近县的EANA产生显著的负向空间溢出效应。本研究拓展了关于制度数字化与农业新业态创业之间关系的理论认识，为中国及其他发展中国家优化数字乡村发展、培育农业新业态提供了经验证据。","Frontiers in Sustainable Food Systems","2026-10-20T00:00:00Z",85,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":84,"relevant":21,"comment":85},9,"基于1743个县面板数据的准自然实验，方法扎实、结论有政策参考价值，值得进入每日精选。",[87],{"name":80,"url":77},[89,26,90,28,91],"数字农业","县域经济","农村创业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":95},{"candidates":96,"agricultural_evidence":45},[97,103,110,117,123],{"code":32,"score":98,"supported":45,"title":99,"abstract":101,"tags":102},15,[100],"digital 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Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":142,"method":143,"finding":144,"direction":68,"opportunity":145},"用双重机器学习与空间DID评估数字乡村试点政策对新农业业态创业活力的影响。","基于1743县2014-2023面板数据，用DML与SDM-DID做准自然实验。","试点政策显著提升新农业业态创业，经技术创新、数字基建与数字金融中介，并对邻县有负向溢出。","可探究政策负向空间溢出的形成机制及跨县协同激励设计，避免创业资源虹吸。","openalex","2026-10-21T23:30:07.205317Z",{"id":149,"title":150,"url":151,"summary":152,"summary_zh":8,"content":8,"source_name":153,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":154,"score_detail":155,"sources":160,"tags":162,"primary_topic":166,"secondary_topics":167,"classification":168,"search_phrases":205,"slug":208,"view_count":21,"doi":8,"paper":209,"created_at":216},5134,"数字乡村建设的相关问题及对策建议 涉农要素供给、农业经济新业态与数字素养","http:\u002F\u002Fwww.fbxslw.com\u002Fjjlw\u002F29025.html","针对当前涉农要素供给受限的问题,文章提出:一是发挥各级政府部门在涉农要素供给中的主导作用,形成以涉农企业、数字企业为核心的产学研协同创新机制;二是积极引导农业院校、科研机构与农业企业、农户开展技术合作;三是充分发挥大数据的要素属性,完善体现当地农业农情的大数据技术平台,充分利用遥感、云计算、地理信息等新型技术;四是加大农业物联网建设力度,以农业智能设备研发及应用为基础,加强农业大数据模型与算法的结合力度。在农业经济新业态方面,文章提出继续完善农村电商、社交平台为核心的农产品数字流通渠道,推进三次产业的数字化融合力度,提升农业生产过程与生态环境保护的相容力度。最后强调提升农业生产经营主体的数字素养,通过各类数字村务、政务或教育平台向新型职业农民提供数字培训服务。","钧创学术论文网 数字乡村建设研究 2026 年 10 月",47,{"impact":156,"substance":157,"depth":158,"authority":112,"freshness":119,"relevant":21,"comment":159},16,14,12,"选题切合数字乡村与农业信息化方向，但属学术论文网转载的综述性对策文章，无新数据与独家结论，信源权威性和时效性均弱，不宜进入每日精选。",[161],{"name":153,"url":151},[163,26,164,165,27],"农村电商","数字素养","农业物联网",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":169},{"candidates":170,"agricultural_evidence":45},[171,175,181,187,193,199],{"code":32,"score":157,"supported":45,"title":172,"abstract":173,"tags":174},[26],[27],[27,26,164],{"code":176,"score":177,"supported":45,"title":178,"abstract":179,"tags":180},"E5",4,[],[163],[163],{"code":182,"score":177,"supported":45,"title":183,"abstract":184,"tags":186},"I5",[],[185],"物联网",[165],{"code":188,"score":112,"supported":45,"title":189,"abstract":190,"tags":192},"G1",[],[191],"产学研",[],{"code":194,"score":112,"supported":45,"title":195,"abstract":196,"tags":198},"I3",[],[197],"遥感",[],{"code":200,"score":112,"supported":45,"title":201,"abstract":202,"tags":204},"I4",[],[203],"地理信息",[],[206,207],"数字乡村建设 涉农要素供给","农业经济新业态 数字素养","数字乡村建设涉农要素供给-5134",{"doi":8,"openalex_id":8,"authors":210,"venue":8,"cited_by_count":63,"oa_url":8,"card":211,"direction":68,"ingested_from":70},[],{"tldr":212,"method":213,"finding":214,"direction":68,"opportunity":215},"分析数字乡村建设中涉农要素供给、农业新业态与数字素养问题并提出对策。","政策分析与对策建议，涉及大数据、遥感、物联网、电商平台等。","需政府主导、产学研协同，完善大数据平台与物联网，提升农民数字素养。","可实证检验数字素养培训对农户采纳数字技术及新业态参与的影响机制。","2026-10-17T00:13:45.192454Z",{"id":218,"title":219,"url":220,"summary":221,"summary_zh":8,"content":8,"source_name":222,"source_url":8,"published_at":223,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":224,"score_detail":225,"sources":227,"tags":229,"primary_topic":233,"secondary_topics":234,"classification":235,"search_phrases":257,"slug":260,"view_count":177,"doi":261,"paper":262,"created_at":269},4198,"促进农业技术创新的数字力量——基于数字乡村建设视角","https:\u002F\u002Fnyxdhyj.isa.ac.cn\u002Farticle\u002Fdoi\u002F10.13872\u002Fj.1000-0275.2025.1035","黄建碧、马春艳、李睿琪、熊航（华中农业大学经济管理学院\u002F数字农业研究院）。发表于《农业现代化研究》2026年第47卷第2期325-338页。从数字乡村建设视角系统分析其对农业技术创新的促进作用，基于数字乡村试点数据构建多维评价指标体系，结合双重差分模型与机制检验考察数字乡村建设对农业技术创新的影响路径与作用机理。研究发现数字乡村建设通过促进农业科技创新要素集聚、提升农业科技创新效率、推动农业科技创新成果转化等机制显著促进农业技术创新。得到国家自然科学基金项目(72173050)、教育部哲学社会科学研究重大专项(2024JZDZ060)资助。","农业现代化研究2026, 47(2)","2026-09-01T00:00:00Z",75,{"impact":18,"substance":16,"depth":18,"authority":157,"freshness":112,"relevant":21,"comment":226},"核心期刊论文，方法规范、结论明确，但发表已逾一月，时效性偏弱，适合主题聚合而非每日精选。",[228],{"name":222,"url":220},[26,29,230,231,232],"农业技术创新","华中农业大学","国家自然科学基金",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":236},{"candidates":237,"agricultural_evidence":45},[238,242,247,251],{"code":32,"score":158,"supported":45,"title":239,"abstract":240,"tags":241},[26],[26],[26],{"code":188,"score":112,"supported":45,"title":243,"abstract":244,"tags":246},[],[245],"成果转化",[],{"code":124,"score":112,"supported":45,"title":248,"abstract":249,"tags":250},[],[89],[],{"code":252,"score":112,"supported":45,"title":253,"abstract":254,"tags":256},"J2",[],[255],"农业现代化",[],[258,259],"华中农业大学 数字乡村 农业技术创新","数字乡村试点 双重差分 农业技术创新","华中农业大学数字乡村农业技术创新-4198","10.13872\u002Fj.1000-0275.2025.1035",{"doi":261,"openalex_id":8,"authors":263,"venue":8,"cited_by_count":63,"oa_url":8,"card":264,"direction":68,"ingested_from":70},[],{"tldr":265,"method":266,"finding":267,"direction":68,"opportunity":268},"基于数字乡村试点数据，实证检验数字乡村建设对农业技术创新的促进作用及机制。","数字乡村试点数据、多维评价指标体系、双重差分模型与机制检验。","数字乡村建设通过要素集聚、效率提升和成果转化显著促进农业技术创新。","可探究数字乡村建设对不同区域、不同农业技术类型创新影响的异质性及空间溢出效应。","2026-10-05T00:04:56.164123Z",{"id":271,"title":272,"url":273,"summary":274,"summary_zh":8,"content":8,"source_name":275,"source_url":8,"published_at":276,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":277,"score_detail":278,"sources":281,"tags":283,"primary_topic":287,"secondary_topics":288,"classification":289,"search_phrases":297,"slug":300,"view_count":293,"doi":8,"paper":301,"created_at":308},3435,"《算力基础设施建设何以提升农业新业态创业活跃度》——基于278个地级市面板数据的多期DID","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F175707.html","基于2012—2023年中国278个地级市面板数据，以国家超级计算中心建设为准自然实验，运用多期双重差分模型实证检验算力基础设施建设对农业新业态创业活跃度的影响。研究发现：相对于非试点地区，国家超级计算中心建设显著推动了试点地区农业新业态创业活跃度的提升，且长期效应呈持续递增态势；通过促进农业大数据应用、提高农业劳动生产率、缓解农业资源错配以及推动农业科技创新等路径提升创业活跃度。","《广东财经大学学报》2026年第2期","2026-09-20T00:00:00Z",87,{"impact":16,"substance":17,"depth":279,"authority":157,"freshness":84,"relevant":21,"comment":280},19,"基于278个地级市面板数据的多期DID实证研究，方法规范、数据规模大，结论对农业数字化转型政策有参考价值，值得进入每日精选。",[282],{"name":275,"url":273},[26,27,284,285,286],"算力基础设施","农业新业态","创业活跃度",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":290},{"candidates":291,"agricultural_evidence":45},[292],{"code":32,"score":293,"supported":45,"title":294,"abstract":295,"tags":296},5,[],[27],[27,26],[298,299],"国家超级计算中心 农业新业态","算力基础设施 农业创业活跃度","国家超级计算中心农业新业态-3435",{"doi":8,"openalex_id":8,"authors":302,"venue":8,"cited_by_count":63,"oa_url":8,"card":303,"direction":68,"ingested_from":70},[],{"tldr":304,"method":305,"finding":306,"direction":68,"opportunity":307},"以国家超算中心为准自然实验，用多期DID检验算力基础设施对农业新业态创业活跃度的影响。","2012—2023年278个地级市面板数据，多期双重差分模型。","超算中心显著提升试点地区农业新业态创业活跃度，长期效应持续递增。","可探究算力设施对不同类型农业新业态的异质性影响，及与数据要素市场的协同机制。","2026-09-25T00:09:33.715628Z",{"id":310,"title":311,"url":312,"summary":313,"summary_zh":8,"content":314,"source_name":315,"source_url":8,"published_at":316,"category":317,"cover_url":8,"hotness":12,"is_selected":13,"score":318,"score_detail":319,"sources":321,"tags":323,"primary_topic":327,"secondary_topics":328,"classification":329,"search_phrases":361,"slug":364,"view_count":293,"doi":8,"paper":8,"created_at":365},3224,"刘永红：人工智能应用时不我待，以数智科技引领四川农业农村现代化——四川农科院将建设农业大数据中心破解农业AI数据难题","https:\u002F\u002Fcbgc.scol.com.cn\u002Fnews\u002F7979522","9-19 川观新闻报道：四川省农业科学院党委书记、院长刘永红在2026天府国际种业展暨第六届\"藏粮于技\"院士专家大讲堂上接受专访。\"人工智能在农业科技创新中有两大核心落地载体和应用方向。首要载体是智能农机，能够把数字化、智能化技术真正用到田间地头。另一大核心方向是生产方式与生产技术的智能化升级，相较于通用大模型，贴合具体作物、具体产业、具体生产环节的细分小模型更适配农业生产实际。\"刘永红坦言，农业AI发展滞后于工业，核心痛点是数据分散、采集困难，省农科院已明确系统性推进路径：搭建省级农业大数据中心；以AI变革农业科研范式；设立\"青年科学家工作室\"配套专项资金扶持科研。","[![Image 1](https:\u002F\u002Fcbgccdn.thecover.cn\u002F@\u002Fimages\u002F20250922\u002F1758523866060089130.png)](https:\u002F\u002Fcbgc.scol.com.cn\u002Fmediachannel_MQ==Q)[![Image 2](https:\u002F\u002Fcbgccdn.thecover.cn\u002F@\u002Fimages\u002F20251016\u002F1760585508939077059.png)](https:\u002F\u002Fcbgc.scol.com.cn\u002Fmediachannel_NzE2z)[![Image 3](https:\u002F\u002Fcbgccdn.thecover.cn\u002F@\u002Fimages\u002F20250917\u002F1758098174766036254.png)](https:\u002F\u002Fcbgc.scol.com.cn\u002Fmediachannel_NzEwz)[![Image 4](https:\u002F\u002Fcbgccdn.thecover.cn\u002F@\u002Fimages\u002F20250917\u002F1758098174830074273.png)](https:\u002F\u002Fcbgc.scol.com.cn\u002Fmediachannel_NzA5z)[![Image 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20](https:\u002F\u002Fwapcdn.chuanbaoguancha.cn\u002Fcdn\u002Fcbgc\u002Fstatic\u002Fimg\u002Fai_reporter_avatar.png)\n全文播报\n\n该页面为预览地址，请勿公开转发。\n\n当前，人工智能正深刻重塑现代农业发展模式，成为农业科技创新的重要风口。针对人工智能在四川农业领域的应用价值、落地路径、现存短板以及省农科院相关布局成效，9月19日，四川省农业科学院党委书记、院长刘永红接受记者采访时表示，人工智能在农业领域的推广应用“等不起，也不能等”，必须加快推进，推动四川农业科研从“支撑产业”向“引领产业”转型升级。\n\n在刘永红看来，人工智能在农业科技创新中有两大核心落地载体和应用方向。首要载体是智能农机。“智能农机是人工智能算法、技术体系落地田间最好、最直接的承载平台，能够把数字化、智能化技术真正用到田间地头，是农业AI落地的基础支撑。”刘永红说。\n\n另一大核心方向是生产方式与生产技术的智能化升级。刘永红介绍，当前社会普遍关注通用大模型，但农业科研和一线应用更依赖“大模型+行业小模型”协同发力。相较于通用大模型，贴合具体作物、具体产业、具体生产环节的细分小模型，更适配农业生产实际。通过长期田间数据积累、生长过程建模、场景仿真模拟，能够智能研判田间情况，自动生成科学管理方案。\n\n据介绍，依托省级相关工作部署，省农科院已组建专家团队，在全省多个重点县域开展数字种业AI赋能试点工作。聚焦种业园区管理、灾害应急处置、田间技术配套、产量品质预判等关键环节，运用AI技术实现智能感知、快速反馈、精准施策，以数字赋能推动种业生产管理提质增效。\n\n在谈及四川农业人工智能发展的突出短板时，刘永红直指核心问题在于农业数据体系薄弱。他坦言，工业领域的人工智能应用成熟度远超农业，关键差距在数据。目前，四川农业数据呈现分散化、片段化特征，散落于各科研单位、市场主体、生产环节之间，缺乏统一汇交、整合与共享机制。同时，田间数据传感采集设备不足、采集方式传统、现代化布局滞后，导致农业可用数据量少、质量不高，无法有效支撑AI模型训练和智能决策，制约了农业人工智能落地见效。\n\n针对现存短板，省农科院已明确系统性推进路径，从数据基础、科研范式、科研基地三个维度全面发力。首先是搭建省级农业大数据中心，整合归集省农科院及全省农业科研系统的各类监测数据、试验数据、成果数据，实现数据统一管理、集中分析、高效利用，为农业人工智能研发应用筑牢基础底座。\n\n其次，是以AI变革农业科研范式。刘永红表示，传统农业科研高度依赖资深专家的经验积累，存在局限性。依托大数据中心，可整合以往科研成果、同行研究数据、各类试验数据，让科研人员能够精准摸清行业研究现状，快速找准创新发力点，实现从“经验科研”向“数字科研”转型。为适配新型科研模式，省农科院专门启动青年科学家工作室建设，专项赋能35岁以下青年科研团队，给予专项资金和平台支持，激活青年科创力量。\n\n最后，是推进科研基地现代化、智能化升级。刘永红认为，农业科研现代化必须走在农业生产现代化前面，不能出现“产业在升级、科研靠人工”的滞后局面。要全面升级科研基地设施设备，提升科研基地栽种、管护等环节的机械化、智能化水平，以现代化、智能化科研平台，保障农业科技创新先行一步。\n\n“农业现代化，关键是农业科技现代化。”刘永红表示，作为全省规模最大的省级农业科研单位，省农科院的定位不能止步于“支撑”农业农村现代化，更要主动引领农业农村现代化。下一步，该院将持续攻坚农业人工智能关键技术，补齐数据短板、迭代科研模式、升级科创平台，以数智化科技创新，持续赋能四川农业高质量发展和乡村全面振兴。\n\n记者 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农业大数据中心","刘永红 农业人工智能","四川农科院农业大数据中心-3224","2026-09-23T00:04:29.881810Z",{"id":367,"title":368,"url":369,"summary":370,"summary_zh":8,"content":371,"source_name":372,"source_url":8,"published_at":373,"category":317,"cover_url":8,"hotness":12,"is_selected":13,"score":374,"score_detail":375,"sources":377,"tags":379,"primary_topic":382,"secondary_topics":383,"classification":384,"search_phrases":395,"slug":398,"view_count":119,"doi":8,"paper":8,"created_at":399},2080,"山东定陶区\"一体三链多场景\"数字农业发展体系成型 入选省级数字乡村试点","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7683000671758598671","山东菏泽定陶区作为省级数字农业发展先行县、省级数字乡村试点地区,创新构建\"一体三链多场景\"数字农业发展体系,以农业大数据一张图为核心载体,搭建多维度智慧运维网络,将数字化智能化手段贯穿农业生产、管理、溯源全流程。同步推行的能评、水保\"无干预智能审批\"服务模式将项目审批时限由2个工作日压缩至分钟级,审批效率提升98%以上,打造可复制可推广的政务数字化改革\"定陶样本\"。","数字赋能启新程，数实融合促发展。近年来，定陶区紧抓数字强省、数字强市建设机遇，深耕数字政务改革与智慧农业发展两大重点领域，以数字化、智能化变革破解发展痛点、激活发展动能，持续释放数字改革红利，推动政务服务提质增效、乡村产业迭代升级，为区域经济社会高质量发展注入强劲数字活力。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Fd8f11c1cff3d4cc5890467c944da0e92~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789689971&x-signature=m7FIiLyjBKSAM%2FaIjaOjU28gDR4%3D)\n\n聚焦政务服务提质增效，定陶区靶向破解工程建设项目审批流程繁琐、环节较多、耗时较长等行业痛点，创新推行能评、水保“无干预智能审批”服务模式。通过全面重构审批流程、深化跨部门数据共享、优化系统智能核验功能，构建起以信用承诺为基础、系统自动校验为支撑、全程网办、无感办理为特色的智能化审批体系，彻底改变传统人工审批模式。依托全新审批机制，相关项目审批时限由原先2个工作日压缩至分钟级，审批效率提升98%以上，实现了极简申报、智能秒批、全程无感的政务服务新突破。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002Ffb6a738632ab4dac90349fe0f70da7d0~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789689971&x-signature=hD%2BXgUjN6wUyt%2BXQ4exmKX0ISG8%3D)\n\n在提速增效的同时，定陶区坚持放管结合、提质固本，同步搭建“承诺—审批—监管”全链条闭环管理机制。审批办结后，系统自动推送审批数据至各行业监管部门，实现信息实时共享、业务联动衔接，全面强化事中事后精准监管、全流程监管，有效杜绝“重审批、轻监管”问题。该新模式自2025年10月落地实施以来，已高效保障8个重点项目顺利落地，企业满意度达100%，打造出可复制、可推广的政务数字化改革“定陶样本”，为全市数字政府建设积累了宝贵经验。\n\n定陶区行政审批服务局副局长马洪彬表示，下一步，将持续拓展智能审批应用场景，丰富涉企高频服务事项，持续擦亮“无感审批、有感服务”政务服务品牌，全方位优化全域营商环境，让企业和群众尽享数字化改革红利，为数字强市建设贡献审批服务力量。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F5c8cb91e21b14c5f82ba8e526e91064f~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789689971&x-signature=X8%2BKQYvVy84A9NXk9XucD%2FrlgTw%3D)\n\n政务数字化改革迭代升级的同时，定陶区智慧农业建设蹄疾步稳、成效凸显。作为省级数字农业发展先行县、省级数字乡村试点地区，定陶区立足本地特色农业资源优势，创新构建“一体三链多场景”数字农业发展体系，以农业大数据一张图为核心载体，配套搭建多维 度智慧运维网络，将数字化、智能化手段贯穿农业生产、管理、溯源全流程，有效破解传统农业粗放式经营、精细化程度不足等短板，全力推动传统农业向数字化、智能化、标准化转型升级。\n\n![Image 4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002Fa74a4cb090b148978f011ce87f9d907f~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789689971&x-signature=7bg%2BQ2tuJ4f44VI9pB%2FL15bzggc%3D)\n\n“我们把智能管控体系融入农业全产业链条，不断丰富数字农业应用场景，以数字技术赋能农业提质、增效、降本，为乡村全面振兴注入源源不断的数字动能。”定陶区农业农村局产业信息科科长邱爱兰说道。\n\n如今，定陶区数字农业建设成果丰硕、成效斐然。全区已建成智慧农业应用基地4万余亩，物联网监测技术应用面积达3万余亩，数字化智能精准施肥覆盖5000余亩，累计培育14个省级智慧农业应用基地。一组组亮眼数据，直观展现了定陶区深耕农业数字化转型的扎实成效，生动勾勒出数字赋能乡村产业振兴的崭新图景。\n\n定陶区大数据中心主任王善栋表示，下一步，将依托数字强省宣传月契机，持续深耕数智化应用场景建设，全力打通数据共享壁垒，深化数字经济与实体经济深度融合，以常态化、长效化数字化转型成效，持续赋能区域高质量发展。\n\n（记者：赵化林）","菏泽广电","2026-09-08T00:00:00Z",57,{"impact":156,"substance":98,"depth":158,"authority":51,"freshness":20,"relevant":21,"comment":376},"省级数字乡村试点落地报道，含智慧农业基地规模与智能审批提速等实质数据，但主体为地方政务与农业数字化成效宣传，全国性增量有限。",[378],{"name":372,"url":369},[26,324,380,27,381],"山东","智能审批",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":13,"version":40,"method":41,"evidence":385},{"candidates":386,"agricultural_evidence":45},[387,391],{"code":32,"score":156,"supported":45,"title":388,"abstract":389,"tags":390},[26],[26,27],[27,26],{"code":124,"score":158,"supported":45,"title":392,"abstract":393,"tags":394},[89],[89],[324],[396,397],"农业大数据 数字乡村 智慧农业 智能审批","农业大数据 数字乡村","农业大数据数字乡村智慧农业智能审批-2080","2026-09-11T00:04:18.569724Z"]