[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3537":3,"related-3537":97},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":28,"primary_topic":9,"secondary_topics":34,"classification":35,"search_phrases":76,"slug":79,"view_count":80,"doi":81,"paper":82,"created_at":96},3537,"INTERNATIONAL EXPERIENCE IN DEVELOPING FAMILY ENTREPRENEURSHIP IN AGRICULTURE","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22950127","Family entrepreneurship in agriculture is an important component of rural economic development, food security, employment generation, and sustainable use of natural resources. Although family farms differ considerably in size, specialization, ownership structure, and level of commercialization, they remain a dominant organizational form of agricultural production in many countries. This article examines international approaches to the development of family entrepreneurship in agriculture and identifies policy instruments that have contributed to the economic sustainability of family farms. The study applies comparative analysis, institutional analysis, generalization, and synthesis of international policy practices. Particular attention is given to the experiences of the European Union, the United States, Japan, South Korea, and Brazil. The analysis demonstrates that effective support systems for family farmers generally combine preferential financing, income support, investment assistance, access to technology, agricultural extension services, producer cooperation, market integration, and measures aimed at attracting young people to agriculture. The European Union experience demonstrates the importance of combining direct income support with environmental requirements and targeted assistance for small and young farmers. The United States provides an example of credit-guarantee and targeted lending mechanisms for family and beginning farmers. Japan emphasizes direct payments, environmental sustainability, and preservation of rural communities, while South Korea increasingly integrates family farming with smart agriculture, digital technologies, and innovation. Brazil's experience demonstrates the importance of dedicated financial and institutional mechanisms for family farming. The study concludes that there is no universal model of family entrepreneurship support; however, international experience indicates that a multidimensional policy framework combining finance, knowledge, technology, cooperation, and market access is more sustainable than isolated financial assistance.","农业中的家庭创业是农村经济发展、粮食安全、就业创造和自然资源可持续利用的重要组成部分。尽管家庭农场在规模、专业化程度、所有权结构和商业化水平方面存在显著差异，但在许多国家，它们仍然是农业生产的主导组织形式。本文考察了国际上促进农业家庭创业发展的做法，并识别了有助于家庭农场经济可持续性的政策工具。研究采用比较分析、制度分析、归纳总结以及国际政策实践综合等方法。研究特别关注欧盟、美国、日本、韩国和巴西的经验。分析表明，有效的家庭农民支持体系通常将优惠融资、收入支持、投资援助、技术获取、农业推广服务、生产者合作、市场融入以及旨在吸引年轻人从事农业的措施结合起来。欧盟的经验表明，将直接收入支持与环境要求以及对小农和年轻农民的有针对性援助相结合十分重要。美国提供了面向家庭农场和起步农民的信贷担保及定向贷款机制范例。日本强调直接支付、环境可持续性和农村社区保护，而韩国则日益将家庭农业与智慧农业、数字技术和创新相结合。巴西的经验表明，专门针对家庭农业的金融和制度机制十分重要。研究得出结论，不存在普遍适用的家庭创业支持模式；然而，国际经验表明，将金融、知识、技术、合作和市场准入相结合的多维政策框架，比孤立的财政援助更具可持续性。",null,"Zenodo (CERN European Organization for Nuclear Research)","2026-09-25T00:00:00Z","论文",25,false,77,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,20,17,13,9,1,"系统比较欧盟、美国、日韩、巴西家庭农业支持政策，结论具参考价值，但属综述性研究、非一手数据突破。",[25,26],{"name":10,"url":6},{"name":10,"url":27},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22950126",[29,30,31,32,33],"智慧农业","家庭农场","农业政策","国际比较","农村金融",[],{"status":36,"locked":14,"version":37,"method":38,"evidence":39},"needs_review","2026-10-22.2","rules",{"candidates":40,"agricultural_evidence":44,"reason":75},[41,49,57,64,70],{"code":42,"score":43,"supported":44,"title":45,"abstract":46,"tags":48},"I1",7,true,[],[29,47],"smart agriculture",[29],{"code":50,"score":51,"supported":44,"title":52,"abstract":53,"tags":56},"A8",6,[],[54,55],"粮食安全","food security",[],{"code":58,"score":51,"supported":44,"title":59,"abstract":60,"tags":63},"G1",[],[61,62],"农业推广","agricultural extension",[],{"code":65,"score":66,"supported":44,"title":67,"abstract":68,"tags":69},"G2",4,[],[30],[30],{"code":71,"score":22,"supported":14,"title":72,"abstract":73,"tags":74},"G3",[],[],[33],"多个产业证据相当，需要确认主归属",[77,78],"家庭农业 国际经验 政策支持","欧盟 美国 日本 家庭农场","家庭农业国际经验政策支持-3537",3,"10.5281\u002Fzenodo.22950127",{"doi":81,"openalex_id":83,"authors":84,"venue":10,"cited_by_count":87,"oa_url":6,"card":88,"direction":94,"ingested_from":95},"W7214295649",[85],{"name":86,"orcid":9},"Saida Alimurod qizi Sharofova",0,{"tldr":89,"method":90,"finding":91,"direction":92,"opportunity":93},"比较欧盟、美国、日本、韩国、巴西支持农业家庭创业的政策工具，总结有效支持体系特征。","采用比较分析、制度分析与国际政策实践综合归纳方法。","有效支持需金融、知识、技术、合作与市场多维政策组合，无普适模式。","数字乡村与农业信息化","可研究数字技术如何嵌入家庭农场多维支持政策，尤其小农与青年农户的数字化服务机制。","智慧农业 \u002F 农业物联网","openalex","2026-09-26T23:30:09.717058Z",{"total":51,"page":22,"page_size":51,"items":98},[99,164,221,311,381,441],{"id":100,"title":101,"url":102,"summary":103,"summary_zh":9,"content":104,"source_name":105,"source_url":9,"published_at":106,"category":107,"cover_url":9,"hotness":108,"is_selected":14,"score":109,"score_detail":110,"sources":114,"tags":116,"primary_topic":9,"secondary_topics":120,"classification":121,"search_phrases":159,"slug":162,"view_count":87,"doi":9,"paper":9,"created_at":163},5252,"山东印发《关于大力发展智慧农业的实施意见》鲁政办字〔2026〕85号","http:\u002F\u002Fwww.daiyue.gov.cn\u002Fart\u002F2026\u002F10\u002F14\u002Fart_255813_10401578.html","山东省政府办公厅10月14日印发85号文,提出到2030年粮油作物水肥一体化应用面积达2000万亩、加力推进优势产业智慧转型、智慧赋能设施农业改造升级、智慧赋能畜牧业节本增效、智慧赋能渔业产业提档升级、培育农业人工智能产业生态等7项重点任务,打造全国智慧农业发展高地。","由农业农村部门牵头，加强与发展改革、财政、科技、工业和信息化、自然资源、畜牧兽医、大数据、气象等部门沟通配合，强化省、市、县三级协同联动，确保任务落到实处。统筹乡村振兴重大专项资金等各级相关领域财政资金推进智慧农业建设，重点支持关键技术攻关、数字农业发展县和应用场景建设。省级每年支持建设30个智慧农业应用场景。优化金融服务落实税收优惠政策，支持智慧农业科技企业和创新平台发展。推动高校、科研院所与智慧农业企业深化合作，培养精通信息技术与农业产业的复合型人才。持续推动高素质农民培育、基层农技推广队伍素质提升等项目，提升生产经营主体数字素养与技能。推进智慧农业领域从业人员职业技能培训与评价，吸引各类人才投身智慧农业发展。（省委金融办、省发展改革委、省教育厅、省科技厅、省工业和信息化厅、省财政厅、省人力资源社会保障厅、省自然资源厅、省农业农村厅、省大数据局、省畜牧局、山东金融监管局、省税务局、省气象局按职责分工负责）","岱岳区人民政府(2026-10-14)","2026-10-14T00:00:00Z","政策",10,75,{"impact":111,"substance":112,"depth":19,"authority":21,"freshness":51,"relevant":22,"comment":113},22,21,"省级智慧农业实施意见，含资金、场景数量与多部门分工等实质条款，具备政策参考价值。",[115],{"name":105,"url":102},[117,29,118,119,31],"数字乡村","数字素养","应用场景",[],{"status":36,"locked":14,"version":37,"method":38,"evidence":122},{"candidates":123,"agricultural_evidence":44,"reason":75},[124,129,135,141,147,153],{"code":42,"score":125,"supported":44,"title":126,"abstract":127,"tags":128},12,[29],[29],[29],{"code":130,"score":80,"supported":44,"title":131,"abstract":132,"tags":134},"C",[],[133],"畜牧",[],{"code":136,"score":80,"supported":44,"title":137,"abstract":138,"tags":140},"D",[],[139],"渔业",[],{"code":142,"score":80,"supported":44,"title":143,"abstract":144,"tags":146},"F3",[],[145],"水肥一体化",[],{"code":148,"score":80,"supported":44,"title":149,"abstract":150,"tags":152},"I2",[],[151],"农业人工智能",[],{"code":154,"score":155,"supported":14,"title":156,"abstract":157,"tags":158},"I6",2,[],[],[117,118],[160,161],"山东 智慧农业 实施意见","智慧农业应用场景 山东","山东智慧农业实施意见-5252","2026-10-19T00:07:31.203786Z",{"id":165,"title":166,"url":167,"summary":168,"summary_zh":9,"content":9,"source_name":169,"source_url":9,"published_at":170,"category":12,"cover_url":9,"hotness":108,"is_selected":14,"score":171,"score_detail":172,"sources":174,"tags":176,"primary_topic":179,"secondary_topics":184,"classification":185,"search_phrases":207,"slug":210,"view_count":87,"doi":211,"paper":212,"created_at":220},4783,"Steering smart farming technology adoption toward a safe and just operating space","https:\u002F\u002Fbeta.iopscience.iop.org\u002Farticle\u002F10.1088\u002F2976-601X\u002Faeb127","Adenaeuer等学者首次将安全公正运营空间SJOS概念应用于智慧农业政策设计。文章提出智慧农业采纳率仍低于社会期望,需通过区域特定的政策激励引导最具社会环境价值的技术。文章给出四步实施框架:细分环境社会条件、评分现状、评估单项技术、综合排序。文章为政策制定者、研究者和产业相关方提供决策框架,面向全球应用。文中明确为预印本,未经过同行评审最终版。","IOP Publishing 2026-10-07","2026-10-07T00:00:00Z",71,{"impact":17,"substance":18,"depth":19,"authority":108,"freshness":51,"relevant":22,"comment":173},"首次将SJOS框架引入智慧农业政策设计，提出四步实施框架，具方法新颖性与政策参考价值，但为未经同行评审的预印本，权威性略打折。",[175],{"name":169,"url":167},[29,31,177,178],"可持续农业","技术采纳",{"code":42,"slug":180,"name":181,"path":182,"parent_code":183},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":186,"locked":14,"version":37,"method":38,"evidence":187},"classified",{"candidates":188,"agricultural_evidence":44},[189,193,198,202],{"code":42,"score":66,"supported":44,"title":190,"abstract":191,"tags":192},[],[29],[29],{"code":194,"score":80,"supported":44,"title":195,"abstract":196,"tags":197},"J1",[],[31],[],{"code":58,"score":22,"supported":14,"title":199,"abstract":200,"tags":201},[],[],[178],{"code":203,"score":22,"supported":14,"title":204,"abstract":205,"tags":206},"H8",[],[],[177],[208,209],"Adenaeuer 智慧农业 SJOS","安全公正运营空间 智慧农业","Adenaeuer智慧农业SJOS-4783","10.1088\u002F2976-601x\u002Faeb127",{"doi":211,"openalex_id":9,"authors":213,"venue":9,"cited_by_count":87,"oa_url":9,"card":214,"direction":92,"ingested_from":219},[],{"tldr":215,"method":216,"finding":217,"direction":92,"opportunity":218},"首次将安全公正运营空间概念用于智慧农业政策设计，提出引导技术采纳的四步框架。","概念移植与政策框架设计，基于区域环境社会条件评分与排序。","智慧农业采纳率低于社会期望，需区域特定政策激励引导高价值技术。","可实证检验四步框架在不同区域的适用性，并开发量化评估工具与决策支持系统。","agent","2026-10-13T00:08:38.364182Z",{"id":222,"title":223,"url":224,"summary":225,"summary_zh":226,"content":9,"source_name":227,"source_url":224,"published_at":228,"category":12,"cover_url":9,"hotness":108,"is_selected":14,"score":229,"score_detail":230,"sources":235,"tags":237,"primary_topic":241,"secondary_topics":246,"classification":247,"search_phrases":291,"slug":294,"view_count":22,"doi":295,"paper":296,"created_at":310},4745,"Digital Agricultural Transformation under Climate Risk: A Policy and Financing Perspective within the National Economy Model","https:\u002F\u002Fdoi.org\u002F10.24925\u002Fturjaf.v14i10.3038-3043.9028","Today, the global food system is undergoing a multidimensional transformation driven by climate change, population growth and rising food demand. Irregular precipitation regimes, increasing water scarcity and ecosystem degradation are making agricultural production increasingly unpredictable and fragile. In addition to these ecological pressures, shrinking arable land, the ageing agricultural labour force and rising input costs further challenge the sustainability of conventional farming systems. The growing frequency of extreme weather events demonstrates the vulnerability of existing production models and highlights the need for structural transformation in agriculture. Digital agriculture offers a potential solution through a technology-oriented paradigm shift. Technologies such as the Internet of Things (IoT), artificial intelligence (AI)-based decision support systems, remote sensing and precision agriculture enable site-specific resource management, reducing environmental impact while improving productivity. However, the adoption of these technologies is constrained by high investment costs and financial uncertainty, particularly for small and medium-scale producers. Therefore, integrating digital technologies into agricultural production depends on reducing financial and operational risks through effective public policy instruments. This conceptual analysis state-led strategic support mechanisms for digital agricultural transformation within the framework of the National Economy Model (NEM). The model’s production-oriented and cost-protection principles provide a stabilisation framework that may facilitate technological adoption. The study argues that public support mechanisms function not only as financial assistance but also as strategic policy instruments that enhance agricultural resilience and production continuity under climate-related risks.","当今，全球粮食体系正在气候变化、人口增长和粮食需求上升的驱动下经历多维转型。不规则的降水模式、日益加剧的水资源短缺和生态系统退化，使农业生产日益难以预测且脆弱。除这些生态压力外，耕地面积缩减、农业劳动力老龄化和投入成本上升，进一步挑战了传统农业系统的可持续性。极端天气事件日益频繁，表明现有生产模式的脆弱性，并凸显了农业结构性转型的必要性。数字农业通过技术导向的范式转变提供了潜在解决方案。物联网（IoT）、基于人工智能（AI）的决策支持系统、遥感和精准农业等技术，能够实现因地制宜的资源管理，在提高生产力的同时减少环境影响。然而，这些技术的采用受到高投资成本和财务不确定性的制约，对中小规模生产者尤为如此。因此，将数字技术融入农业生产，取决于通过有效的公共政策工具降低财务和运营风险。本概念性分析阐述了在国民经济模式（NEM）框架下，国家主导的战略支持机制对数字农业转型的作用。该模式以生产为导向和成本保护的原则提供了稳定化框架，可能促进技术采用。研究认为，公共支持机制不仅发挥财政援助功能，同时也是增强农业韧性和气候相关风险下生产连续性的战略性政策工具。","Turkish Journal of Agriculture - Food Science and Technology","2026-10-11T00:00:00Z",61,{"impact":125,"substance":231,"depth":232,"authority":125,"freshness":233,"relevant":22,"comment":234},15,14,8,"概念性论文，从政策与融资视角讨论气候风险下数字农业转型，有一定理论参考价值但缺乏实证数据，属细分领域学术探讨。",[236],{"name":227,"url":224},[238,29,31,239,240],"数字农业","农业金融","气候风险",{"code":242,"slug":243,"name":244,"path":245,"parent_code":183},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",[],{"status":186,"locked":14,"version":37,"method":38,"evidence":248},{"candidates":249,"agricultural_evidence":44},[250,258,265,272,278,285],{"code":42,"score":251,"supported":44,"title":252,"abstract":253,"tags":257},11,[],[254,238,255,256],"精准农业","precision agriculture","digital agriculture",[238,29],{"code":242,"score":21,"supported":44,"title":259,"abstract":260,"tags":264},[],[261,262,263],"物联网","internet of things","IoT",[],{"code":266,"score":43,"supported":44,"title":267,"abstract":268,"tags":271},"H7",[],[269,270],"气候变化","climate change",[240],{"code":148,"score":51,"supported":44,"title":273,"abstract":274,"tags":277},[],[275,276],"artificial intelligence","decision support",[],{"code":279,"score":51,"supported":44,"title":280,"abstract":281,"tags":284},"I3",[],[282,283],"遥感","remote sensing",[],{"code":286,"score":80,"supported":44,"title":287,"abstract":288,"tags":290},"H3",[],[289],"水资源",[],[292,293],"数字农业 转型 气候风险","农业政策 农业金融 数字农业 智慧农业","数字农业转型气候风险-4745","10.24925\u002Fturjaf.v14i10.3038-3043.9028",{"doi":295,"openalex_id":297,"authors":298,"venue":227,"cited_by_count":87,"oa_url":224,"card":305,"direction":94,"ingested_from":95},"W7221460591",[299,302],{"name":300,"orcid":301},"Mehmet Metin Özgüven","https:\u002F\u002Forcid.org\u002F0000-0002-6421-4804",{"name":303,"orcid":304},"Saliha Kilavuz","https:\u002F\u002Forcid.org\u002F0009-0006-6830-0730",{"tldr":306,"method":307,"finding":308,"direction":92,"opportunity":309},"基于国民经济模型，从政策与融资视角分析气候风险下数字农业转型的公共支持机制。","概念分析，结合NEM框架与物联网、AI、遥感等数字农业技术。","公共支持不仅是资金援助，更是提升农业气候韧性与生产连续性的战略政策工具。","可实证检验NEM政策工具对中小农户数字技术采纳与融资约束的缓解效果。","2026-10-12T23:30:12.745005Z",{"id":312,"title":313,"url":314,"summary":315,"summary_zh":316,"content":9,"source_name":317,"source_url":314,"published_at":318,"category":12,"cover_url":9,"hotness":108,"is_selected":14,"score":319,"score_detail":320,"sources":322,"tags":324,"primary_topic":327,"secondary_topics":332,"classification":333,"search_phrases":358,"slug":361,"view_count":155,"doi":362,"paper":363,"created_at":380},4481,"Climate policy uncertainty and agricultural digital-intelligent transformation in China: evidence from provincial panel data","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1909691","Introduction Climate policy uncertainty can affect long-term investment decisions in agriculture, yet its influence on agricultural digital-intelligent transformation remains insufficiently understood. This study examines how lagged climate policy uncertainty affects agricultural digital-intelligent transformation and whether rural finance and agricultural service policies can moderate this relationship. Methods Using panel data from 31 Chinese provinces from 2013 to 2022, we construct an agricultural digital-intelligent transformation index. A two-way fixed effects model, instrumental variable estimation, heterogeneity analysis, and moderation tests are adopted for empirical analysis. Results The results show that climate policy uncertainty significantly inhibits agricultural digital-intelligent transformation, and this negative effect remains evident after addressing potential endogeneity. Heterogeneity analysis indicates that the inhibitory effect is significant only in regions with moderately developed digital finance and in major grain-consuming areas. Further analysis shows that loans to agriculture, forestry, animal husbandry and fishery industries and the pilot policy for full-process socialized agricultural services positively moderate this relationship and weaken the adverse effect of climate policy uncertainty. Discussion These findings contribute to the literature on climate policy uncertainty and sustainable agricultural transformation by linking policy expectations, agriculture-related loans, and digital-smart agriculture development. The results suggest that stabilizing climate policy expectations, improving rural credit support, and strengthening agricultural service systems are important for promoting climate-resilient and regionally differentiated digital transformation in agriculture.","引言 气候政策不确定性会影响农业的长期投资决策，但其对农业数字化智能化转型的影响尚缺乏充分认识。本研究考察滞后气候政策不确定性如何影响农业数字化智能化转型，以及农村金融和农业服务政策能否调节这一关系。方法 基于2013—2022年中国31个省份的面板数据，构建农业数字化智能化转型指数，采用双向固定效应模型、工具变量估计、异质性分析和调节效应检验进行实证分析。结果 结果表明，气候政策不确定性显著抑制农业数字化智能化转型，且在处理潜在内生性后这一负向效应依然明显。异质性分析表明，该抑制效应仅在数字金融中等发达地区及粮食主销区显著。进一步分析显示，农、林、牧、渔业贷款和农业生产全程社会化服务试点政策对这一关系具有正向调节作用，削弱了气候政策不确定性的不利影响。讨论 这些发现通过将政策预期、涉农贷款与数字智慧农业发展联系起来，为气候政策不确定性与农业可持续转型的文献作出了贡献。结果表明，稳定气候政策预期、完善农村信贷支持、健全农业服务体系，对于促进农业气候韧性型和区域差异化的数字化转型具有重要意义。","Frontiers in Sustainable Food Systems","2026-10-08T00:00:00Z",81,{"impact":17,"substance":111,"depth":17,"authority":232,"freshness":21,"relevant":22,"comment":321},"基于31省十年面板数据的实证研究，揭示气候政策不确定性对农业数字化智能化转型的抑制效应及农村金融、农业社会化服务的调节作用，方法规范、结论有政策参考价值，值得进入每日精选。",[323],{"name":317,"url":314},[117,29,33,325,326],"农业社会化服务","气候政策",{"code":71,"slug":328,"name":329,"path":330,"parent_code":331},"rural-finance","农村金融与保险","\u002Ftopic\u002Frural-services\u002Frural-finance","G",[],{"status":186,"locked":14,"version":37,"method":38,"evidence":334},{"candidates":335,"agricultural_evidence":44},[336,341,345,350,354],{"code":71,"score":43,"supported":44,"title":337,"abstract":338,"tags":340},[],[33,339],"rural finance",[33],{"code":42,"score":43,"supported":44,"title":342,"abstract":343,"tags":344},[],[29,47],[29],{"code":65,"score":66,"supported":44,"title":346,"abstract":347,"tags":349},[],[348],"社会化服务",[325],{"code":136,"score":80,"supported":44,"title":351,"abstract":352,"tags":353},[],[139],[],{"code":154,"score":22,"supported":14,"title":355,"abstract":356,"tags":357},[],[],[117],[359,360],"气候政策不确定性 农业数字化 省级面板","农业数字化智能化转型 农村金融","气候政策不确定性农业数字化省级面板-4481","10.3389\u002Ffsufs.2026.1909691",{"doi":362,"openalex_id":364,"authors":365,"venue":317,"cited_by_count":87,"oa_url":314,"card":375,"direction":94,"ingested_from":95},"W7221013071",[366,369,371,373],{"name":367,"orcid":368},"Wenwen Wang","https:\u002F\u002Forcid.org\u002F0000-0003-1547-5714",{"name":370,"orcid":9},"Yuanyi Yang",{"name":372,"orcid":9},"Yanru Yu",{"name":374,"orcid":9},"Yanwei Zhang",{"tldr":376,"method":377,"finding":378,"direction":92,"opportunity":379},"研究气候政策不确定性如何抑制中国农业数字化智能化转型，并检验农村金融与服务政策的调节作用。","2013-2022年31省面板数据，构建农业数字化智能化转型指数，用双向固定效应","气候政策不确定性显著抑制农业数字化智能化转型，该效应仅在数字金融中等发达地区和粮食主销区显著。","可深入探究气候政策预期稳定机制与数字金融、农业社会化服务的协同路径，及区域差异化转型策略。","2026-10-09T23:30:06.185798Z",{"id":382,"title":383,"url":384,"summary":385,"summary_zh":386,"content":9,"source_name":387,"source_url":384,"published_at":388,"category":12,"cover_url":9,"hotness":108,"is_selected":14,"score":389,"score_detail":390,"sources":392,"tags":394,"primary_topic":397,"secondary_topics":402,"classification":403,"search_phrases":423,"slug":426,"view_count":155,"doi":427,"paper":428,"created_at":440},4342,"GREEN FINANCE AND CAPITAL CIRCULATION IN SMART AGRICULTURE: AI-DRIVEN INSIGHTS","https:\u002F\u002Fdoi.org\u002F10.24412\u002F2411-0450-2026-7-114-120","This scientific article examines the role of digitalization and smart agriculture in advancing green finance, AI-driven innovation, and inclusive rural investment. The main objective of the study is to assess how integrating digital technologies and AI systems into agricultural finance can enhance productivity and support sustainable community development. Drawing on the theoretical foundations of digital finance, green finance, and development policy, the research explores the relationship between traditional credit systems and innovative technological solutions to drive structural transformations in rural economies. The analysis shows that conventional agricultural finance mechanisms are often constrained by limited access to funds, high transaction costs, and insufficient risk management. Digital tools, including mobile banking, fintech platforms, and AI-based credit scoring, improve financial accessibility, optimize investment decisions, and increase transparency, while smart agricultural technologies enhance efficiency, productivity, and climate resilience. The study also discusses long-term trends in global agro-food trade and regional structural characteristics reflecting uneven import and export flows across regions. Overall, the research demonstrates that combining digitalization, AI, and targeted finance can significantly foster more sustainable and productive agricultural development, increasing both efficiency and financial inclusion while supporting long-term resilience in rural communities.","本文考察了数字化与智慧农业在推动绿色金融、人工智能驱动的创新以及包容性农村投资中的作用。研究的主要目标是评估将数字技术和人工智能系统融入农业金融，如何能够提升生产力并支持可持续的社区发展。基于数字金融、绿色金融和发展政策的理论基础，研究探讨了传统信贷体系与创新技术解决方案之间的关系，以推动农村经济的结构性转型。分析表明，传统农业金融机制往往受限于资金获取渠道有限、交易成本高以及风险管理不足。数字工具，包括移动银行、金融科技平台和基于人工智能的信用评分，改善了金融可及性，优化了投资决策，并提高了透明度，而智慧农业技术则提升了效率、生产力和气候韧性。研究还讨论了全球农食产品贸易的长期趋势以及反映各区域进出口流量不均衡的区域结构特征。总体而言，研究表明，将数字化、人工智能和有针对性的金融相结合，能够显著促进更可持续、更具生产力的农业发展，在提高效率和金融包容性的同时，支持农村社区的长期韧性。","cyberleninka.ru","2026-10-06T00:00:00Z",72,{"impact":17,"substance":18,"depth":19,"authority":233,"freshness":21,"relevant":22,"comment":391},"论文从数字金融与AI信贷视角切入智慧农业与绿色金融，结论具参考价值，但来源为俄语开放期刊，权威性一般，适合作为主题聚合素材而非头条精选。",[393],{"name":387,"url":384},[29,151,395,33,396],"数字普惠金融","绿色金融",{"code":266,"slug":398,"name":399,"path":400,"parent_code":401},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":186,"locked":14,"version":37,"method":38,"evidence":404},{"candidates":405,"agricultural_evidence":44},[406,410,414,419],{"code":42,"score":231,"supported":44,"title":407,"abstract":408,"tags":409},[47],[29,47],[29],{"code":71,"score":80,"supported":14,"title":411,"abstract":412,"tags":413},[],[],[33,395,396],{"code":266,"score":80,"supported":44,"title":415,"abstract":416,"tags":418},[],[417],"climate resilience",[],{"code":148,"score":22,"supported":14,"title":420,"abstract":421,"tags":422},[],[],[151],[424,425],"智慧农业 绿色金融","AI 农业信贷 数字金融","智慧农业绿色金融-4342","10.24412\u002F2411-0450-2026-7-114-120",{"doi":427,"openalex_id":429,"authors":430,"venue":387,"cited_by_count":87,"oa_url":384,"card":435,"direction":94,"ingested_from":95},"W7220700804",[431,433],{"name":432,"orcid":9},"A.V. Mardoyan",{"name":434,"orcid":9},"H.A. Sargsyan",{"tldr":436,"method":437,"finding":438,"direction":92,"opportunity":439},"研究数字化与智慧农业如何推动绿色金融、AI创新与农村包容性投资。","基于数字金融、绿色金融与发展政策理论，分析移动银行、金融科技与AI信用评分。","数字工具与AI可提升金融可及性、优化投资并增强农业气候韧性。","可实证检验AI信用评分对农户信贷可得性与绿色投资决策的因果影响。","2026-10-07T23:30:08.959053Z",{"id":442,"title":443,"url":444,"summary":445,"summary_zh":9,"content":9,"source_name":446,"source_url":9,"published_at":447,"category":12,"cover_url":9,"hotness":108,"is_selected":14,"score":448,"score_detail":449,"sources":451,"tags":453,"primary_topic":456,"secondary_topics":460,"classification":461,"search_phrases":476,"slug":479,"view_count":22,"doi":9,"paper":480,"created_at":487},3433,"《数字农业发展的信贷融资效应——来自江苏省家庭农场的证据》","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fzgncgc\u002Fmulu\u002F647040.html","周月书、葛云杰使用江苏省家庭农场实地问卷调查数据考察数字农业发展的信贷融资效应及其作用机制。研究发现：数字农业发展显著提升了家庭农场的信贷可得性与信贷融资规模；机制上通过缓解信息不对称程度、降低信贷交易成本和提升风险抵御能力促进家庭农场融资；异质性分析发现数字农业发展对于所在地农业技术发展环境较好、农技人员服务水平较高的家庭农场，以及家庭农场主资本禀赋较低、金融认知能力较低以及种植粮食作物的家庭农场具有更显著的融资增进作用。","《中国农村观察》\u002F南京农业大学","2026-09-20T00:00:00Z",78,{"impact":17,"substance":111,"depth":17,"authority":232,"freshness":51,"relevant":22,"comment":450},"基于江苏家庭农场实地调研的实证研究，机制与异质性分析扎实，对数字普惠金融与新型经营主体融资有参考价值。",[452],{"name":446,"url":444},[238,30,454,33,455],"江苏","信贷融资",{"code":65,"slug":457,"name":458,"path":459,"parent_code":331},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",[],{"status":186,"locked":14,"version":37,"method":38,"evidence":462},{"candidates":463,"agricultural_evidence":44},[464,468,472],{"code":65,"score":125,"supported":44,"title":465,"abstract":466,"tags":467},[30],[30],[30],{"code":42,"score":125,"supported":44,"title":469,"abstract":470,"tags":471},[238],[238],[238],{"code":71,"score":22,"supported":14,"title":473,"abstract":474,"tags":475},[],[],[33],[477,478],"江苏 家庭农场 数字农业 信贷","周月书 数字农业 融资","江苏家庭农场数字农业信贷-3433",{"doi":9,"openalex_id":9,"authors":481,"venue":9,"cited_by_count":87,"oa_url":9,"card":482,"direction":92,"ingested_from":219},[],{"tldr":483,"method":484,"finding":485,"direction":92,"opportunity":486},"基于江苏家庭农场调查，研究数字农业发展对信贷融资的影响及机制。","江苏省家庭农场实地问卷调查数据，实证分析信贷效应与机制。","数字农业显著提升信贷可得性与规模，通过缓解信息不对称、降成本、提风险抵御力实现。","可探究数字农业融资效应在不同区域和作物类型间的差异，及金融科技的中介作用。","2026-09-25T00:09:33.572434Z"]