[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3461":3,"related-3461":85},{"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":26,"primary_topic":9,"secondary_topics":32,"classification":33,"search_phrases":57,"slug":60,"view_count":61,"doi":62,"paper":63,"created_at":84},3461,"How government environmental attention influences agricultural green total factor productivity: evidence from Chinese provincial data","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1858269","China’s agricultural development is increasingly constrained by resource and environmental factors, making the improvement of green total factor productivity in agriculture and the pursuit of high-quality development imperative. Government environmental attention serves as an important policy prerequisite for green agricultural development. Based on theoretical analysis, this paper empirically examines the impact mechanism and spatial spillover effect of government environmental attention on agricultural green total factor productivity (AGTFP) using Chinese provincial panel data from 2003 to 2022. The empirical results indicate that: (1) government environmental attention significantly improves AGTFP. (2) Government environmental attention promotes the improvement of AGTFP through two pathways—environmental regulation and agricultural green technology innovation. (3) Government environmental attention drives the enhancement of local AGTFP while exerting a negative spillover effect on AGTFP of neighboring provinces. The findings above clarify the relationship between government environmental attention and agricultural green efficiency, providing policy implications for promoting agricultural green, healthy, and sustainable development.","中国农业发展日益受到资源与环境因素的制约，提升农业绿色全要素生产率、实现高质量发展势在必行。政府环境关注是农业绿色发展的重要政策前提。本文在理论分析的基础上，利用2003—2022年中国省级面板数据，实证检验了政府环境关注对农业绿色全要素生产率（AGTFP）的影响机制与空间溢出效应。实证结果表明：（1）政府环境关注显著提升了AGTFP。（2）政府环境关注通过环境规制和农业绿色技术创新两条路径促进AGTFP提升。（3）政府环境关注在推动本地AGTFP提升的同时，对邻近省份AGTFP产生负向溢出效应。上述发现厘清了政府环境关注与农业绿色效率之间的关系，为促进农业绿色、健康、可持续发展提供了政策启示。",null,"Frontiers in Sustainable Food Systems","2026-09-24T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,21,17,13,9,1,"基于2003—2022年省级面板数据的实证研究，揭示政府环境关注通过环境规制与绿色技术创新提升农业绿色全要素生产率并存在负向空间溢出，结论与政策含义对农业绿色发展有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"农业绿色发展","空间溢出效应","环境规制","农业全要素生产率","农业绿色技术",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"unclassified","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":55,"reason":56},[39,45,50],{"code":40,"score":41,"supported":14,"title":42,"abstract":43,"tags":44},"H8",2,[],[],[27,31],{"code":46,"score":22,"supported":14,"title":47,"abstract":48,"tags":49},"H4",[],[],[27],{"code":51,"score":22,"supported":14,"title":52,"abstract":53,"tags":54},"I4",[],[],[28],true,"缺少足够的主题证据",[58,59],"政府环境关注 农业绿色全要素生产率","中国省级面板数据 农业绿色发展","政府环境关注农业绿色全要素生产率-3461",4,"10.3389\u002Ffsufs.2026.1858269",{"doi":62,"openalex_id":64,"authors":65,"venue":10,"cited_by_count":76,"oa_url":6,"card":77,"direction":81,"ingested_from":83},"W7214243204",[66,69,71,73],{"name":67,"orcid":68},"Mengna Li","https:\u002F\u002Forcid.org\u002F0009-0005-2898-6275",{"name":70,"orcid":9},"Xuan Gao",{"name":72,"orcid":9},"Xi Yang",{"name":74,"orcid":75},"Li Tan","https:\u002F\u002Forcid.org\u002F0000-0003-1155-8977",0,{"tldr":78,"method":79,"finding":80,"direction":81,"opportunity":82},"基于中国省级面板数据，实证检验政府环境关注对农业绿色全要素生产率的影响机制与空间溢出效应。","2003-2022年中国省级面板数据，中介效应与空间计量模型。","政府环境关注显著提升农业绿色全要素生产率，通过环境规制与绿色技术创新传导，但对邻省产生负向溢出。","农业绿色发展与碳","可探究负向溢出的成因与跨区域协同治理机制，并引入数字技术或环境分权等调节变量。","openalex","2026-09-25T23:30:07.059834Z",{"total":86,"page":22,"page_size":86,"items":87},6,[88,150,213,260,315,390],{"id":89,"title":90,"url":91,"summary":92,"summary_zh":93,"content":9,"source_name":10,"source_url":91,"published_at":94,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":95,"score_detail":96,"sources":99,"tags":101,"primary_topic":105,"secondary_topics":111,"classification":112,"search_phrases":129,"slug":132,"view_count":76,"doi":133,"paper":134,"created_at":149},4790,"Climate change, environmental regulations, and agricultural total factor productivity: implications for food production in emerging economies","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1925201","This study investigates the long-run impacts of climate change, environmental policy stringency (EPS), and agricultural total factor productivity (ATFP) on food production across selected emerging economies over the period 1990–2022. Second-generation econometric methods, robust to cross-sectional dependence and slope heterogeneity, are employed to ensure methodological rigor. Using the Cross-Sectionally Augmented Autoregressive Distributed Lag model alongside panel cointegration tests, the study establishes long-term relationships among the variables of interest. The results reveal that a 1% increase in average annual precipitation (APRE), ATFP, and EPS is associated with long-term increases in food production of 0.15, 0.93, and 0.04%, respectively. In contrast, a 1% rise in average annual temperature (ATP) is found to reduce food production by 0.98% in the long term. Moderation analysis further demonstrates that ATFP significantly moderates the relationship between both APRE and ATP and food production in both the long and short term. EPS, however, exerts a significant moderating effect exclusively on the ATP-food production nexus in the short term. The robustness of the baseline estimates is confirmed through alternative estimation strategies, including Fully Modified Ordinary Least Squares and Dynamic Ordinary Least Squares, as well as the incorporation of alternative control variables. Based on these findings, the study offers actionable policy recommendations for selected emerging economies, emphasizing the enhancement of ATFP and the implementation of stringent environmental regulatory frameworks as critical pathways to ensuring food security in the face of accelerating climate change.","本研究考察了1990—2022年间气候变化、环境政策严格度（EPS）和农业全要素生产率（ATFP）对部分新兴经济体粮食生产的长期影响。为确保方法论的严谨性，本研究采用了对截面依赖性和斜率异质性具有稳健性的第二代计量经济学方法。通过使用截面增强自回归分布滞后模型并结合面板协整检验，本研究确立了所关注变量之间的长期关系。结果表明，年均降水量（APRE）、ATFP和EPS每增加1%，粮食生产在长期内分别增加0.15%、0.93%和0.04%。相比之下，年均气温（ATP）每上升1%，粮食生产在长期内减少0.98%。调节效应分析进一步表明，ATFP在长期和短期内均显著调节APRE和ATP与粮食生产之间的关系。然而，EPS仅在短期内对ATP—粮食生产关系具有显著的调节效应。基准估计结果的稳健性通过替代估计策略得到验证，包括完全修正普通最小二乘法（FMOLS）和动态普通最小二乘法（DOLS），以及纳入替代控制变量。基于上述发现，本研究为部分新兴经济体提出了可操作的政策建议，强调提升ATFP和实施严格的环境监管框架是面对加速气候变化时确保粮食安全的关键路径。","2026-10-12T00:00:00Z",80,{"impact":17,"substance":97,"depth":17,"authority":20,"freshness":21,"relevant":22,"comment":98},22,"基于1990—2022年新兴经济体面板数据的实证研究，量化了气温、降水、环境规制与农业全要素生产率对粮食生产的长期影响，方法严谨、结论具体，对气候适应型农业政策有参考价值。",[100],{"name":10,"url":91},[102,103,29,30,104],"粮食安全","气候变化","新兴经济体",{"code":106,"slug":107,"name":108,"path":109,"parent_code":110},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":113,"locked":14,"version":35,"method":36,"evidence":114},"classified",{"candidates":115,"agricultural_evidence":55},[116,122],{"code":106,"score":117,"supported":55,"title":118,"abstract":120,"tags":121},15,[119],"climate change",[103,119],[103],{"code":123,"score":124,"supported":55,"title":125,"abstract":126,"tags":128},"A8",7,[],[102,127],"food security",[102],[130,131],"农业全要素生产率 气候变化 粮食生产","环境政策强度 新兴经济体 粮食安全","农业全要素生产率气候变化粮食生产-4790","10.3389\u002Ffsufs.2026.1925201",{"doi":133,"openalex_id":135,"authors":136,"venue":10,"cited_by_count":76,"oa_url":91,"card":144,"direction":81,"ingested_from":83},"W7221508368",[137,140,142],{"name":138,"orcid":139},"Awais Ahmed Brohi","https:\u002F\u002Forcid.org\u002F0009-0004-4290-9877",{"name":141,"orcid":9},"Waheed Ali",{"name":143,"orcid":9},"Yoshihisa Suzuki",{"tldr":145,"method":146,"finding":147,"direction":81,"opportunity":148},"研究气候变化、环境政策与农业全要素生产率对新兴经济体粮食生产的长期影响。","采用横截面增强自回归分布滞后模型与面板协整检验，基于1990–2022年新兴经济","气温每升1%使粮食产量降0.98%，而农业全要素生产率与环境政策严格度则显著促进粮食生产。","可探究环境政策严格度与农业全要素生产率的协同机制，以及在不同气候情景下的动态阈值效应。","2026-10-13T23:30:06.664953Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":9,"content":9,"source_name":155,"source_url":9,"published_at":9,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":156,"score_detail":157,"sources":160,"tags":162,"primary_topic":166,"secondary_topics":172,"classification":173,"search_phrases":199,"slug":202,"view_count":41,"doi":9,"paper":203,"created_at":212},4475,"数绿协同转型赋能乡村产业振兴的效应检验与机制研究","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F165473.html","侯建、麻洁云、张朝阳（河南农业大学）基于2013—2023年中国30个省份面板数据，构建数字化与绿色化耦合协同指标体系，并利用动态门槛回归模型、空间杜宾模型，从农村人力资本视角深入探究数绿协同转型对乡村产业振兴的影响机制；研究表明数绿协同转型显著推动了乡村产业振兴，东中部地区及非平原地区受益更为显著；存在农村人力资本门槛效应，呈现U型关系；具有正向空间溢出效应；研究得到国家社会科学基金青年项目（25CJY083）资助。","农业经济与管理 2026年第3期",74,{"impact":17,"substance":97,"depth":17,"authority":158,"freshness":41,"relevant":22,"comment":159},14,"基于30省份面板数据的实证研究，方法规范、结论有新意，但属学术论文且时效性偏弱，适合主题聚合而非每日精选。",[161],{"name":155,"url":153},[163,27,164,165,28],"数字乡村","乡村产业振兴","农村人力资本",{"code":167,"slug":168,"name":169,"path":170,"parent_code":171},"G4","rural-industry","乡村产业与县域经济","\u002Ftopic\u002Frural-services\u002Frural-industry","G",[],{"status":113,"locked":14,"version":35,"method":36,"evidence":174},{"candidates":175,"agricultural_evidence":55},[176,182,186,190,194],{"code":167,"score":177,"supported":55,"title":178,"abstract":180,"tags":181},12,[179],"乡村产业",[179],[164],{"code":46,"score":22,"supported":14,"title":183,"abstract":184,"tags":185},[],[],[27],{"code":40,"score":22,"supported":14,"title":187,"abstract":188,"tags":189},[],[],[27],{"code":51,"score":22,"supported":14,"title":191,"abstract":192,"tags":193},[],[],[28],{"code":195,"score":22,"supported":14,"title":196,"abstract":197,"tags":198},"I6",[],[],[163],[200,201],"河南农业大学 数绿协同 乡村产业振兴","30省份面板 数字化绿色化 耦合协同","河南农业大学数绿协同乡村产业振兴-4475",{"doi":9,"openalex_id":9,"authors":204,"venue":9,"cited_by_count":76,"oa_url":9,"card":205,"direction":209,"ingested_from":211},[],{"tldr":206,"method":207,"finding":208,"direction":209,"opportunity":210},"基于30省面板数据，检验数绿协同转型对乡村产业振兴的效应与机制。","构建数字化与绿色化耦合协同指标，用动态门槛回归与空间杜宾模型。","数绿协同显著促进乡村产业振兴，存在人力资本U型门槛与正向空间溢出。","数字乡村与农业信息化","可深入微观农户或县域层面，探究人力资本门槛的成因与跨区域溢出路径。","agent","2026-10-09T00:05:02.298238Z",{"id":214,"title":215,"url":216,"summary":217,"summary_zh":9,"content":9,"source_name":218,"source_url":9,"published_at":9,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":219,"score_detail":220,"sources":222,"tags":224,"primary_topic":9,"secondary_topics":227,"classification":228,"search_phrases":248,"slug":251,"view_count":41,"doi":9,"paper":252,"created_at":259},4403,"数字技术发展赋能农业绿色全要素生产率 — 基于机制异质性与区域适配的实证分析","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F173656.html","张建伟、孟婷洁基于 2011-2023 年中国 31 个省份面板数据,采用熵值法和 SBM-GML 模型测度数字技术发展与农业绿色全要素生产率,运用双向固定效应模型检验发现数字技术发展具有显著促进作用且存在双重异质性;空间上回报率呈地理位置为主导的分化,效率上呈边际效应递减;机制上要素数字化呈现「转化—产出」结构性失衡,东部强于转化弱于产出,中西部相反。","西藏大学经济与管理学院《华东经济管理》2026 年第 06 期",73,{"impact":17,"substance":97,"depth":17,"authority":20,"freshness":41,"relevant":22,"comment":221},"基于31省面板数据的实证研究，方法规范、结论有区域适配价值，但属学术论文且时效性弱，适合主题聚合而非每日精选。",[223],{"name":218,"url":216},[163,225,27,226,30],"数字技术","区域差异",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":229},{"candidates":230,"agricultural_evidence":55,"reason":56},[231,235,239,244],{"code":46,"score":22,"supported":14,"title":232,"abstract":233,"tags":234},[],[],[27],{"code":40,"score":22,"supported":14,"title":236,"abstract":237,"tags":238},[],[],[27],{"code":240,"score":22,"supported":14,"title":241,"abstract":242,"tags":243},"I1",[],[],[225],{"code":195,"score":22,"supported":14,"title":245,"abstract":246,"tags":247},[],[],[163],[249,250],"数字技术 农业绿色全要素生产率","SBM-GML 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数字化绿色化 协同发展","农村居民收入 空间溢出效应","农业农村数字化绿色化协同发展-4153","10.11841\u002Fj.issn.1007-4333.2026.10.06",{"doi":306,"openalex_id":9,"authors":308,"venue":9,"cited_by_count":76,"oa_url":9,"card":309,"direction":209,"ingested_from":211},[],{"tldr":310,"method":311,"finding":312,"direction":209,"opportunity":313},"测度中国农业农村数字化绿色化协同水平并检验其时空格局与增收效应。","熵值法、耦合协调度模型、Kernel密度、空间Markov链与空间计量模型。","全国及各省数绿协同水平缓慢上升，仍处基本协同阶段，且对农村居民收入有影响与空间溢出。","可深入探究数绿协同增收效应的区域异质性与微观农户传导机制，识别关键短板维度。","2026-10-04T00:09:09.731896Z",{"id":316,"title":317,"url":318,"summary":319,"summary_zh":320,"content":9,"source_name":321,"source_url":318,"published_at":322,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":323,"score_detail":324,"sources":327,"tags":329,"primary_topic":333,"secondary_topics":337,"classification":338,"search_phrases":371,"slug":374,"view_count":375,"doi":376,"paper":377,"created_at":389},3365,"The Impact of Agricultural Digitization on Green Total Factor Productivity in Agriculture: Evidence from 30 Provinces in China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18199758","Amid tighter resource and environmental limits in China, the integration of digitization and greening gives new momentum to sustainable agriculture; however, its methods and structural conditions remain unclear. This study utilizes provincial panel data from 2011–2023 and the super-efficiency SBM-GML model to estimate agricultural green total factor productivity (AGTFP). It empirically examines the green empowerment effect of agricultural digitization, its transmission pathways, and structural boundaries. Unlike existing studies that rely on input-oriented or rural-level digitalization measures and qualitative regional groupings, this study constructs an agriculture-specific index, identifies agricultural socialized services (ASS) as an organizational channel, examines the moderating role of environmental regulation, and uses a continuous threshold variable to identify the structural breakpoint at which digitization’s green effect changes. The findings indicate that digitization considerably enhances AGTFP, and this association remains stable across a range of robustness checks. Mechanism analysis indicates that ASS partially mediates this effect, while environmental regulation intensity positively moderates the relationship. Heterogeneity and threshold analyses show that the empowering effect is only significant in the eastern region, but not in the central and western regions; it is significant in the main grain-producing areas. Moreover, a tentative structural breakpoint is identified when the grain-sown area proportion reaches 0.486. Since this threshold is statistically significant only at the 10% level, it should be regarded as preliminary evidence. Accordingly, we recommend regionally differentiated digital agriculture strategies, strengthening the socialized agricultural service system, and enhancing synergy between environmental regulation and digital empowerment to effectively advance the green transformation of China’s agriculture.","在中国资源与环境约束趋紧的背景下，数字化与绿色化的融合为可持续农业注入了新动力；然而，其实现路径与结构性条件仍不明确。本研究利用2011—2023年省级面板数据和超效率SBM-GML模型测算农业绿色全要素生产率（AGTFP），实证检验了农业数字化的绿色赋能效应、传导路径及结构边界。与现有研究依赖投入导向或农村层面数字化指标以及定性区域分组不同，本研究构建了农业专属指数，识别出农业社会化服务（ASS）作为组织化渠道，考察了环境规制的调节作用，并使用连续门槛变量识别数字化绿色效应发生变化的结构性断点。研究发现，数字化显著提升了AGTFP，且该关联在一系列稳健性检验中保持稳定。机制分析表明，ASS在其中发挥部分中介作用，而环境规制强度正向调节该关系。异质性与门槛分析显示，赋能效应仅在东部地区显著，在中西部地区不显著；在粮食主产区显著。此外，当粮食播种面积占比达到0.486时，识别出一个初步的结构性断点。由于该门槛仅在10%水平上统计显著，应将其视为初步证据。据此，我们建议采取区域差异化的数字农业策略，强化农业社会化服务体系，并增强环境规制与数字赋能之间的协同效应，以有效推进中国农业绿色转型。","Sustainability","2026-09-23T00:00:00Z",85,{"impact":97,"substance":325,"depth":17,"authority":158,"freshness":268,"relevant":22,"comment":326},23,"基于30省面板数据的实证研究，方法规范、结论有政策参考价值，但属学术论文且时效性一般，适合主题聚合而非每日精选头条。",[328],{"name":321,"url":318},[27,330,331,332,29],"农业数字化","粮食主产区","农业社会化服务",{"code":40,"slug":334,"name":335,"path":336,"parent_code":110},"sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture",[],{"status":113,"locked":14,"version":35,"method":36,"evidence":339},{"candidates":340,"agricultural_evidence":55},[341,347,353,359,363,367],{"code":40,"score":124,"supported":55,"title":342,"abstract":343,"tags":346},[],[344,345],"可持续农业","sustainable agriculture",[27],{"code":240,"score":124,"supported":55,"title":348,"abstract":349,"tags":352},[],[350,351],"数字农业","digital agriculture",[330],{"code":354,"score":61,"supported":55,"title":355,"abstract":356,"tags":358},"G2",[],[357],"社会化服务",[332],{"code":123,"score":22,"supported":14,"title":360,"abstract":361,"tags":362},[],[],[331],{"code":46,"score":22,"supported":14,"title":364,"abstract":365,"tags":366},[],[],[27],{"code":279,"score":22,"supported":14,"title":368,"abstract":369,"tags":370},[],[],[330],[372,373],"农业数字化 绿色全要素生产率","农业社会化服务 环境规制","农业数字化绿色全要素生产率-3365",3,"10.3390\u002Fsu18199758",{"doi":376,"openalex_id":378,"authors":379,"venue":321,"cited_by_count":76,"oa_url":318,"card":384,"direction":209,"ingested_from":83},"W7214071788",[380,382],{"name":381,"orcid":9},"Zhaojuan Meng",{"name":383,"orcid":9},"Guixiang Lin",{"tldr":385,"method":386,"finding":387,"direction":81,"opportunity":388},"基于2011–2023年省级面板数据，检验农业数字化对农业绿色全要素生产率的赋能效应、机制与结构边界","超效率SBM-GML测算AGTFP，构建农业专属数字化指数，中介、调节与连续门槛","数字化显著提升AGTFP，农业社会化服务部分中介，环境规制正向调节，效应仅东部和主产区显著。","可深入探究中西部数字化绿色效应缺失的组织与市场条件，并验证粮食播种面积占比0.486的结构断点。","2026-09-24T23:30:25.917176Z",{"id":391,"title":392,"url":393,"summary":394,"summary_zh":395,"content":9,"source_name":10,"source_url":393,"published_at":322,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":396,"score_detail":397,"sources":399,"tags":401,"primary_topic":405,"secondary_topics":406,"classification":407,"search_phrases":436,"slug":439,"view_count":61,"doi":440,"paper":441,"created_at":465},3342,"Impact of agricultural greening on food production resilience-empirical evidence from China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1938875","The Food Production System is generally confronted with external uncertain shocks and rigid constraints from ecological factors. How to strengthen the system’s adaptability and resilience through green transition pathways is a crucial research topic in the field of modern agricultural governance. With the provincial panel data from China, the entropy method is adopted in this paper to measure agricultural greening and food production resilience, and then the two-way fixed-effect model, the moderating-effect model, the threshold-effect model and spatial econometric models are applied for empirical testing. According to the results, the degree of agricultural greening has promoted food production resilience; at the same time, regions show heterogeneity across geographical regions and grain functional zones. Green finance and rural scientific and technological input will also be effective driving forces. There is a single threshold for economic development level; after exceeding it, the marginal promoting effect on resilience weakens, but remains significantly positive. Food production resilience also exhibits significant spatial dependence, and agricultural greening generates positive spillover effects on neighboring provinces under the adjacency-based spatial specification. This paper will provide new ideas for the theory of resilience enhancement and offer some references to help optimize the distribution of agricultural green factors and foster long-term stable grain production.","粮食生产系统普遍面临外部不确定冲击与生态因素的刚性约束。如何通过绿色转型路径增强系统的适应性与韧性，是现代农业农村治理领域的重要研究课题。本文基于中国省级面板数据，采用熵值法测度农业绿色化与粮食生产韧性，进而运用双向固定效应模型、调节效应模型、门槛效应模型及空间计量模型进行实证检验。结果表明，农业绿色化程度提升了粮食生产韧性；同时，不同地理区域与粮食功能区呈现出异质性。绿色金融与农村科技投入也是有效的驱动力量。经济发展水平存在单一门槛，跨越门槛后对韧性的边际促进效应减弱，但仍显著为正。粮食生产韧性还表现出显著的空间依赖性，在邻接空间设定下，农业绿色化对邻近省份产生正向溢出效应。本文将为韧性提升理论提供新思路，并为优化农业绿色要素配置、促进粮食长期稳定生产提供一定参考。",79,{"impact":17,"substance":97,"depth":17,"authority":20,"freshness":268,"relevant":22,"comment":398},"基于中国省级面板数据的实证研究，方法扎实、结论有政策参考价值，但属学术论文而非产业级事件，适合进入主题聚合而非头条精选。",[400],{"name":10,"url":393},[27,402,403,404,28],"粮食生产韧性","农业科技投入","绿色金融",{"code":51,"slug":276,"name":277,"path":278,"parent_code":279},[],{"status":113,"locked":14,"version":35,"method":36,"evidence":408},{"candidates":409,"agricultural_evidence":55},[410,414,418,423,427,431],{"code":51,"score":61,"supported":55,"title":411,"abstract":412,"tags":413},[],[288],[28],{"code":123,"score":22,"supported":14,"title":415,"abstract":416,"tags":417},[],[],[402],{"code":419,"score":22,"supported":14,"title":420,"abstract":421,"tags":422},"G3",[],[],[404],{"code":46,"score":22,"supported":14,"title":424,"abstract":425,"tags":426},[],[],[27],{"code":40,"score":22,"supported":14,"title":428,"abstract":429,"tags":430},[],[],[27],{"code":432,"score":22,"supported":14,"title":433,"abstract":434,"tags":435},"J2",[],[],[403],[437,438],"农业绿色化 粮食生产韧性","绿色金融 农村科技投入","农业绿色化粮食生产韧性-3342","10.3389\u002Ffsufs.2026.1938875",{"doi":440,"openalex_id":442,"authors":443,"venue":10,"cited_by_count":76,"oa_url":393,"card":460,"direction":81,"ingested_from":83},"W7214113879",[444,446,449,451,453,455,458],{"name":445,"orcid":9},"Huimin Shao",{"name":447,"orcid":448},"Wenjuan Zhang","https:\u002F\u002Forcid.org\u002F0000-0001-5062-1292",{"name":450,"orcid":9},"Qiong Peng",{"name":452,"orcid":9},"Haichuan Liu",{"name":454,"orcid":9},"Liangyan Lu",{"name":456,"orcid":457},"Mcxin Tee","https:\u002F\u002Forcid.org\u002F0000-0001-7990-8377",{"name":459,"orcid":9},"Qing Jin",{"tldr":461,"method":462,"finding":463,"direction":81,"opportunity":464},"基于中国省级面板数据，实证检验农业绿色化对粮食生产韧性的提升作用。","熵值法测度指标，双向固定效应、调节效应、门槛效应与空间计量模型。","农业绿色化显著提升粮食生产韧性，存在区域异质性、经济门槛及正向空间溢出。","可探究绿色金融与科技投入的协同机制，及跨区域溢出路径的微观落地。","2026-09-24T23:30:07.857044Z"]