[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3474":3,"related-3474":55},{"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,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":54},3474,"Assessing The Impact of Flooding on Agricultural Livelihood in Rwanda: A Case Study of Musanze District","https:\u002F\u002Fdoi.org\u002F10.53819\u002F81018102t2609","Flooding is a major natural hazard affecting agricultural livelihoods in Musanze District, Rwanda, where agriculture provides food and income for most households. This study assessed the causes of flooding, agricultural production patterns, effects on livelihoods, and the relationship between flooding and livelihood difficulties. A descriptive and correlational research design using quantitative and qualitative approaches was employed. Data were collected from 399 respondents across seven sectors through questionnaires, interviews, observations, and documentary review. Findings showed that heavy rainfall on volcanic slopes was the leading cause of flooding (48.7%), followed by steep mountainous terrain (18.5%), poor agricultural practices and deforestation (15.1%), and high population density and settlement in flood-prone areas (8.2%). Most floods occurred during the March–May rainy season (58.1%). Irish potatoes dominated agricultural production and were the most affected crop, representing 75.7% of the total damaged area. Flooding caused significant livelihood challenges: 84.1% of households experienced food shortages, 78.9% lost agricultural income, and 62.5% incurred debt. Regression analysis indicated a very strong positive relationship between flooding and agricultural livelihood difficulties (R = 0.885, R² = 0.783, p = 0.046), with flooding explaining 78.3% of the variation in livelihood challenges. The study recommends stronger flood management infrastructure, improved early warning systems, climate-smart agriculture, and further research on long-term climate change impacts and mitigation effectiveness. Keywords: Agricultural livelihood, Climate change, Disaster risk, Flood impact, Flood vulnerability, Flooding, Rural livelihoods. Top of Form","洪水是影响卢旺达穆桑泽地区农业生计的主要自然灾害，当地农业为大多数家庭提供粮食和收入。本研究评估了洪水的成因、农业生产模式、对生计的影响，以及洪水与生计困难之间的关系。研究采用描述性和相关性研究设计，结合定量与定性方法。通过问卷、访谈、观察和文献查阅，从七个部门的399名受访者中收集数据。研究结果表明，火山坡上的强降雨是洪水的主要成因（48.7%），其次是陡峭的山地地形（18.5%）、不良农业实践和森林砍伐（15.1%），以及高人口密度和洪泛区定居（8.2%）。大多数洪水发生在3月至5月的雨季（58.1%）。爱尔兰马铃薯在农业生产中占主导地位，也是受影响最严重的作物，占总受损面积的75.7%。洪水造成了严重的生计挑战：84.1%的家庭经历粮食短缺，78.9%失去农业收入，62.5%陷入债务。回归分析表明，洪水与农业生计困难之间存在非常强的正相关关系（R = 0.885，R² = 0.783，p = 0.046），洪水解释了生计挑战中78.3%的变异。研究建议加强洪水管理基础设施、改善预警系统、推广气候智能型农业，并进一步研究长期气候变化影响及缓解措施的有效性。关键词：农业生计、气候变化、灾害风险、洪水影响、洪水脆弱性、洪水、农村生计。",null,"Journal of Agriculture","2026-09-23T00:00:00Z","论文",10,false,69,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,20,16,13,8,1,"基于399份问卷的实证研究，量化了洪水对卢旺达农业生计的影响，数据扎实但属区域性案例，国际参考价值有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"气候智慧农业","灾害预警","洪水灾害","农业生计","卢旺达农业",[33,34],"卢旺达 Musanze 洪水","洪水 农业生计 马铃薯","卢旺达Musanze洪水-3474",0,"10.53819\u002F81018102t2609",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":45,"card":46,"direction":52,"ingested_from":53},"W7214084377",[41,43],{"name":42,"orcid":9},"Pacifique Abimana",{"name":44,"orcid":9},"Kant James KAMUHANDA","https:\u002F\u002Fstratfordjournalpublishers.org\u002Fjournals\u002Findex.php\u002Fjournal-of-agriculture\u002Farticle\u002Fdownload\u002F3003\u002F3686",{"tldr":47,"method":48,"finding":49,"direction":50,"opportunity":51},"评估卢旺达穆桑泽地区洪水对农业生计的影响及成因。","对399户问卷访谈，描述性与相关分析，回归建模。","洪水解释78.3%生计困难，84.1%家庭缺粮，马铃薯受损最重。","农业绿色发展与碳","可延伸研究气候智慧型农业与洪水预警系统在火山坡地的减灾效果。","智慧农业 \u002F 农业物联网","openalex","2026-09-25T23:30:11.238088Z",{"total":56,"page":22,"page_size":56,"items":57},6,[58,112,149,196,228,265],{"id":59,"title":60,"url":61,"summary":62,"summary_zh":63,"content":9,"source_name":64,"source_url":61,"published_at":65,"category":12,"cover_url":9,"hotness":66,"is_selected":14,"score":67,"score_detail":68,"sources":75,"tags":80,"search_phrases":85,"slug":88,"view_count":36,"doi":89,"paper":90,"created_at":111},3470,"AI-generated advice as a reinforcement layer in climate-smart agriculture","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landusepol.2026.108336","Climate-smart agricultural (CSA) practices are central to food-system decarbonisation, yet adoption often falls short of farmers’ stated intentions, weakening the impact of incentives and extension under capacity constraints. We test whether spatially targeted, AI-generated advice can narrow this intention-action gap in a randomised field experiment with 1529 row crop farmers in Iowa, Illinois and Indiana during the cover crop decision window. Farmers assigned to receive four AI-generated emails were 4.45 %age points more likely to plant cover crops than controls (z = 2.81, p = 0.005), despite high baseline intentions in both groups. Effects operated on the extensive margin: there was no detectable change in the share of land planted among adopters. Survey responses indicate high engagement and a shift from untested optimism to more calibrated trust after exposure. Supervised AI advice can provide a low-cost, scalable complement to existing extension, improving follow-through and modestly expanding uptake without displacing human expertise.","气候智慧型农业（CSA）实践是食品系统脱碳的核心，然而在能力受限的情况下，农户的实际采用往往低于其声称的意愿，削弱了激励措施和推广服务的效果。我们在爱荷华州、伊利诺伊州和印第安纳州开展了一项随机田间试验，覆盖1529名大田作物种植户，在覆盖作物决策窗口期测试了空间靶向的AI生成建议能否缩小这一意愿—行动差距。被分配接收四封AI生成电子邮件的农户种植覆盖作物的概率比对照组高4.45个百分点（z = 2.81，p = 0.005），尽管两组基线意愿均较高。效应体现在广延边际上：采用者中种植土地比例未检测到显著变化。调查回复表明参与度较高，且在接触建议后，农户从未经检验的乐观转向更为校准的信任。有监督的AI建议可作为现有推广服务的低成本、可扩展补充，改善后续落实并适度扩大采用，而不会取代人类专业知识。","Land Use Policy","2026-09-24T00:00:00Z",25,87,{"impact":69,"substance":70,"depth":71,"authority":72,"freshness":73,"relevant":22,"comment":74},22,23,19,14,9,"随机对照试验证实AI生成建议可低成本缩小农户意愿与行动差距，对智慧农业推广具参考价值。",[76,77],{"name":64,"url":61},{"name":78,"url":79},"Apollo","https:\u002F\u002Fdoi.org\u002F10.17863\u002Fcam.134741",[81,82,83,84,27],"智慧农业","农业人工智能","农业技术推广","覆盖作物",[86,87],"AI生成建议 覆盖作物","爱荷华 伊利诺伊 印第安纳 覆盖作物","AI生成建议覆盖作物-3470","10.1016\u002Fj.landusepol.2026.108336",{"doi":89,"openalex_id":91,"authors":92,"venue":64,"cited_by_count":36,"oa_url":61,"card":105,"direction":52,"ingested_from":53},"W7214223143",[93,96,98,100,103],{"name":94,"orcid":95},"Callum Alexander","https:\u002F\u002Forcid.org\u002F0009-0007-5275-4583",{"name":97,"orcid":9},"Aiora Zabala",{"name":99,"orcid":9},"Andreas Kontoleon",{"name":101,"orcid":102},"Shalamar Armstrong","https:\u002F\u002Forcid.org\u002F0000-0002-1326-9936",{"name":104,"orcid":9},"Anuoluwa Sangotayo",{"tldr":106,"method":107,"finding":108,"direction":109,"opportunity":110},"随机试验检验AI生成建议能否缩小农户覆盖作物种植的意图-行动差距。","1529户美国中西部农户随机对照试验，四次AI生成邮件干预。","AI建议使覆盖作物种植率提高4.45个百分点，效果体现在是否采纳而非种植面积。","农业人工智能与决策模型","可探索AI建议与人工推广协同、长期持续效果及不同作物区域的异质性影响。","2026-09-25T23:30:09.887867Z",{"id":113,"title":114,"url":115,"summary":116,"summary_zh":117,"content":9,"source_name":118,"source_url":115,"published_at":65,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":119,"score_detail":120,"sources":124,"tags":126,"search_phrases":131,"slug":134,"view_count":36,"doi":135,"paper":136,"created_at":148},3466,"Socio-Economic Impact of Climate-Smart Agricultural Techniques. A Case of Kotwidika Cooperative, Kayonza District","https:\u002F\u002Fdoi.org\u002F10.37284\u002Fajccrs.5.2.5857","Climate Smart Agriculture (CSA) is widely regarded as an important technique for tackling climate change concerns while maintaining socio-economic aspects. This study assesses the socio-economic impact of Climate Smart Agricultural Techniques in Kayonza District, a case of KOTWIDIKA Cooperative, a region vulnerable to climate variability and highly dependent on agriculture. The research focused on the chosen cooperative members through stratified random sampling from 845 farmers, with an additional interview conducted with 8 cooperative leaders and 7 additional key stakeholders. Data were collected using structured questionnaires, key informant interviews, focus group discussions and field observations. A mixed-methods approach incorporating both quantitative and qualitative data was used to assess the effectiveness of CSA techniques on agricultural productivity and the relationship between CSA practices and socio-economic development. The research evaluated the CSA adoption rates, income, food security, and community health. The Statistical Package for Social Sciences (SPSS) version 31.0 was used to perform Statistical analyses for quantitative data, including correlation and regression analyses to evaluate the relationships between variables, while qualitative data were examined through thematic analysis. The research found that the adoption of CSA techniques led to significant increases in income (15-22%), improved food security, and enhanced psychological well-being among members. The analysis revealed a strong statistical relationship between CSA adoption and improved livelihoods, supported by regression results (R = 0.991, R² = 0.982) and a correlation coefficient of 0.985, affirming the efficacy of these methods in promoting community resilience. The study concludes that CSA practices greatly enhance socio-economic conditions for KOTWIDIKA Cooperative members. It recommends strengthening agricultural extension services to further promote CSA adoption. Future research should explore barriers to CSA adoption and conduct long-term impact assessments to ensure sustainable agricultural development.","气候智慧型农业(CSA)被广泛视为在应对气候变化问题的同时维持社会经济的重要技术。本研究评估了卡永扎地区气候智慧型农业技术的社会经济影响，以KOTWIDIKA合作社为例，该地区易受气候变率影响且高度依赖农业。研究通过分层随机抽样从845名农民中选取该合作社成员作为研究对象，并对8名合作社领导者和7名其他关键利益相关者进行了访谈。数据通过结构化问卷、关键信息人访谈、焦点小组讨论和实地观察收集。采用混合方法，结合定量和定性数据，评估CSA技术对农业生产力的有效性以及CSA实践与社会经济发展之间的关系。研究评估了CSA采纳率、收入、粮食安全和社区健康。使用社会科学统计软件包(SPSS)31.0版对定量数据进行统计分析，包括相关分析和回归分析以评估变量之间的关系，定性数据则通过主题分析进行审查。研究发现，采用CSA技术使收入显著增加(15-22%)，粮食安全得到改善，成员的心理福祉得到提升。分析显示，CSA采纳与生计改善之间存在显著的统计关系，回归结果(R = 0.991, R² = 0.982)和相关系数0.985予以支持，证实了这些方法在促进社区韧性方面的有效性。研究得出结论，CSA实践极大地改善了KOTWIDIKA合作社成员的社会经济状况。建议加强农业推广服务以进一步促进CSA的采纳。未来研究应探索CSA采纳的障碍，并进行长期影响评估，以确保农业可持续发展。","African Journal of Climate Change and Resource Sustainability",62,{"impact":21,"substance":121,"depth":122,"authority":17,"freshness":73,"relevant":22,"comment":123},18,15,"非洲卢旺达合作社的气候智慧农业实证研究，方法规范、数据翔实，但属区域性案例，公共影响有限，可作为国际经验参考而非每日精选头条。",[125],{"name":118,"url":115},[127,128,27,129,130],"粮食安全","合作社","农户增收","卢旺达",[132,133],"KOTWIDIKA 合作社 气候智慧农业","Kayonza 气候智慧农业 农户收入","KOTWIDIKA合作社气候智慧农业-3466","10.37284\u002Fajccrs.5.2.5857",{"doi":135,"openalex_id":137,"authors":138,"venue":118,"cited_by_count":36,"oa_url":115,"card":143,"direction":52,"ingested_from":53},"W7214150705",[139,141],{"name":140,"orcid":9},"Jacques Ngendahimana",{"name":142,"orcid":9},"Christophe Mupenzi",{"tldr":144,"method":145,"finding":146,"direction":50,"opportunity":147},"评估卢旺达KOTWIDIKA合作社气候智慧型农业技术的社会经济影响。","混合方法，分层随机抽样845农户，问卷、访谈、焦点小组，SPSS回归与主题分析。","采用气候智慧型农业使收入增15-22%，粮食安全与心理健康改善，回归R²=0.982。","可研究小农户采用气候智慧型农业的障碍及长期可持续性影响评估。","2026-09-25T23:30:09.387601Z",{"id":150,"title":151,"url":152,"summary":153,"summary_zh":154,"content":9,"source_name":155,"source_url":152,"published_at":65,"category":12,"cover_url":9,"hotness":156,"is_selected":14,"score":157,"score_detail":158,"sources":161,"tags":168,"search_phrases":173,"slug":176,"view_count":36,"doi":177,"paper":178,"created_at":195},3465,"Framework for implementation of climate-smart agriculture for common bean (Phaseolus vulgaris L.) systems in Africa","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.33987127","Climate-smart agriculture (CSA) has become a key strategy to tackle climate change, food insecurity, and agricultural sustainability in Africa. Its application to common bean (Phaseolus vulgaris L.) systems remains under-conceptualized, and its approaches focus on immediate gains in yield and technology adoption, providing little consideration for biological and ecological processes that enable long-term resilience. In this review, the assumptions, evidence base, and methodological limitations of CSA in common bean production systems in Africa are critically discussed. An unstructured literature review was conducted from 2010 to 2025, and research focused on drought response, symbiotic nitrogen fixation, soil management, and climate-smart legume systems was synthesized. This review revealed that common bean is not just a target of CSA interventions but also a key ecological actor whose adaptation relies on physiological plasticity, plant–microbe interactions, and symbiotic nitrogen fixation. There is also evidence that the resilience benefits of CSA practices tend to be site-specific and are rarely assessed in the context of multiple climate stressors. Thus, this study suggests an ‘adaptive legume-centered’ climate-smart agriculture (ALC-CSA) framework that incorporates plant plasticity, Interaction-centered management, and conditional symbiosis, offering a biologically informed and analytical approach to understand and enhance the climate resilience of common bean systems in Africa.","气候智慧型农业(CSA)已成为非洲应对气候变化、粮食不安全和农业可持续性的关键策略。其在普通菜豆(Phaseolus vulgaris L.)体系中的应用仍缺乏概念化，且其方法侧重于产量和技术采纳的即时收益，很少考虑支撑长期韧性的生物和生态过程。本文对非洲普通菜豆生产体系中CSA的假设、证据基础和方法学局限进行了批判性讨论。本文开展了2010年至2025年的非结构化文献综述，并综合了聚焦于干旱响应、共生固氮、土壤管理和气候智慧型豆类体系的研究。本综述揭示，普通菜豆不仅是CSA干预的目标，也是关键的生态行动者，其适应性依赖于生理可塑性、植物—微生物互作和共生固氮。也有证据表明，CSA实践的韧性效益往往具有地点特异性，且很少在多重气候胁迫背景下进行评估。因此，本研究提出一个“以适应性豆类为中心”的气候智慧型农业(ALC-CSA)框架，该框架纳入植物可塑性、以互作为中心的管理和条件性共生，为理解和增强非洲普通菜豆体系的气候韧性提供了一种具有生物学依据的分析性方法。","Figshare",40,70,{"impact":17,"substance":18,"depth":159,"authority":17,"freshness":73,"relevant":22,"comment":160},17,"该综述提出以豆科作物为中心的适应性气候智慧农业框架，学术增量明确，但属非洲区域基础研究，对国内三农信息化实践的直接参考价值有限。",[162,163,165],{"name":155,"url":152},{"name":155,"url":164},"https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.33987127.v1",{"name":166,"url":167},"Journal of Plant Interactions","https:\u002F\u002Fdoi.org\u002F10.1080\u002F17429145.2026.2706488",[169,170,171,27,172],"豆科作物","非洲农业","生物固氮","普通菜豆",[174,175],"Phaseolus vulgaris 非洲 菜豆","气候智慧农业 普通菜豆 生物固氮 豆科作物","Phaseolusvulgaris非洲菜豆-3465","10.6084\u002Fm9.figshare.33987127",{"doi":177,"openalex_id":179,"authors":180,"venue":155,"cited_by_count":36,"oa_url":152,"card":190,"direction":52,"ingested_from":53},"W7214146746",[181,183,186,188],{"name":182,"orcid":9},"Victor Adebanjo",{"name":184,"orcid":185},"Olaniyi Oyatomi","https:\u002F\u002Forcid.org\u002F0000-0003-3094-374X",{"name":187,"orcid":9},"Michael Abberton",{"name":189,"orcid":9},"Olubukola Oluranti Babalola",{"tldr":191,"method":192,"finding":193,"direction":50,"opportunity":194},"综述非洲普通菜豆气候智慧型农业，提出以豆科为中心的适应性框架。","非结构化文献综述（2010-2025），综合干旱响应、共生固氮与土壤管理研究。","菜豆是生态参与者，其韧性依赖生理可塑性与共生固氮，现有CSA忽视生物生态过程。","可实证检验ALC-CSA框架，量化多气候胁迫下菜豆-微生物互作与共生固氮的韧性贡献。","2026-09-25T23:30:09.321815Z",{"id":197,"title":198,"url":199,"summary":200,"summary_zh":9,"content":9,"source_name":201,"source_url":9,"published_at":202,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":203,"score_detail":204,"sources":207,"tags":209,"search_phrases":214,"slug":217,"view_count":36,"doi":9,"paper":218,"created_at":227},3442,"《多因子监测实现小麦晚霜冻害大范围动态预警》——中国农科院资源区划所农业遥感团队","https:\u002F\u002Fpaper.sciencenet.cn\u002Fhtmlpaper\u002F2026\u002F9\u002F202692094936755155648.shtm","中国农科院农业资源与农业区划研究所农业遥感团队针对黄淮海平原冬小麦3至4月拔节至抽穗期频发的晚霜冻害，提出了多因子综合霜冻监测指数。该指数综合高精度气象预报和冬小麦生长进程信息，兼顾低温强度、持续时间及不同生育期敏感性，并利用遥感土壤水分数据构建非线性调节系数精准刻画湿润土壤对低温的缓冲效应。验证表明该指数对县级小麦产量具有显著指示作用，突破了气象站点的空间局限，可为农业主产区风险精细化管控和科学减灾提供技术支撑。","《欧洲农学杂志（European Journal of Agronomy）》","2026-09-20T00:00:00Z",82,{"impact":69,"substance":70,"depth":121,"authority":72,"freshness":205,"relevant":22,"comment":206},5,"国家级科研团队在核心期刊提出多因子霜冻监测指数，方法新颖、验证扎实，对黄淮海主产区减灾有实用价值，值得入选。",[208],{"name":201,"url":199},[210,211,212,28,213],"农业气象","遥感监测","冬小麦","晚霜冻害",[215,216],"中国农科院 冬小麦 晚霜冻害","黄淮海 小麦 遥感监测","中国农科院冬小麦晚霜冻害-3442",{"doi":9,"openalex_id":9,"authors":219,"venue":9,"cited_by_count":36,"oa_url":9,"card":220,"direction":224,"ingested_from":226},[],{"tldr":221,"method":222,"finding":223,"direction":224,"opportunity":225},"提出多因子综合霜冻监测指数，实现黄淮海冬小麦晚霜冻害大范围动态预警。","融合高精度气象预报、小麦生长进程与遥感土壤水分，构建非线性调节系数。","该指数对县级小麦产量有显著指示作用，突破气象站点空间局限。","农业遥感与作物表型","可结合多源遥感与机器学习，构建不同作物、区域的霜冻风险动态预警与保险定损模型。","agent","2026-09-25T00:09:34.300809Z",{"id":229,"title":230,"url":231,"summary":232,"summary_zh":233,"content":9,"source_name":234,"source_url":231,"published_at":11,"category":12,"cover_url":9,"hotness":66,"is_selected":14,"score":235,"score_detail":236,"sources":238,"tags":242,"search_phrases":247,"slug":250,"view_count":36,"doi":251,"paper":252,"created_at":264},3352,"Agricultural Productivity under Climate Change and the Dynamics of Rural Economic Resilience: Adaptation Pathways from Farms to Households and Territories","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22925809","This paper examines the relationship between climate change, agricultural productivity, and rural economic resilience by integrating evidence on climatic pressures, farm-level adaptation, and broader rural transformation. Climate change affects agricultural production through rising temperatures, heat stress, rainfall variability, drought, water scarcity, soil degradation, pests, and other interacting environmental pressures. These effects are transmitted beyond crop yields through farm income, employment, food security, agricultural value chains, and the economic stability of rural territories. The paper shows that agricultural resilience depends on farmers’ capacity to adopt complementary adaptation strategies, including crop diversification, improved soil management, climate-smart agriculture, water-management technologies, climate information, agricultural insurance, and other risk-management mechanisms. At the household level, livelihood diversification, migration, entrepreneurship, access to productive assets, and institutional support can reduce dependence on climate-sensitive agricultural activities. At the territorial level, resilient agricultural value chains, market access, infrastructure, local product valorization, and non-farm employment contribute to absorbing and adapting to climatic disturbances. The analysis therefore approaches resilience as a multidimensional process connecting agricultural productivity, household adaptive capacity, food security, and rural economic transformation. The findings suggest that effective climate adaptation requires coordinated interventions combining productive, financial, institutional, social, and territorial mechanisms rather than isolated technological responses","本文通过整合气候压力、农场层面适应以及更广泛的农村转型等方面的证据，考察了气候变化、农业生产率与农村经济韧性之间的关系。气候变化通过气温上升、热应激、降雨变率、干旱、水资源短缺、土壤退化、病虫害及其他相互作用的环境压力影响农业生产。这些影响超越作物产量，经由农场收入、就业、粮食安全、农业价值链以及农村地域的经济稳定等渠道传导。本文表明，农业韧性取决于农民采取互补性适应策略的能力，包括作物多样化、改善土壤管理、气候智慧型农业、水资源管理技术、气候信息、农业保险及其他风险管理机制。在农户层面，生计多样化、迁移、创业、生产性资产获取以及制度支持能够降低对气候敏感型农业活动的依赖。在地域层面，具有韧性的农业价值链、市场准入、基础设施、本地产品增值以及非农就业有助于吸收和适应气候扰动。因此，本分析将韧性视为一个多维过程，连接农业生产率、农户适应能力、粮食安全与农村经济转型。研究结果表明，有效的气候适应需要将生产性、金融性、制度性、社会性和地域性机制相结合的协调干预，而非孤立的技术应对措施。","Zenodo (CERN European Organization for Nuclear Research)",77,{"impact":121,"substance":18,"depth":159,"authority":20,"freshness":73,"relevant":22,"comment":237},"系统梳理气候变化下农业生产力与农村经济韧性的多层次适应路径，结论具政策参考价值，但属综述性论文，非突破性成果。",[239,240],{"name":234,"url":231},{"name":234,"url":241},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22925808",[243,244,245,246,27],"乡村振兴","农业韧性","农业保险","气候变化",[248,249],"气候智慧农业 适应路径","农业韧性 农村经济","气候智慧农业适应路径-3352","10.5281\u002Fzenodo.22925809",{"doi":251,"openalex_id":253,"authors":254,"venue":234,"cited_by_count":36,"oa_url":231,"card":259,"direction":52,"ingested_from":53},"W7214087966",[255,257],{"name":256,"orcid":9},"Naledi Ncube",{"name":258,"orcid":9},"Rudo Marashe",{"tldr":260,"method":261,"finding":262,"direction":50,"opportunity":263},"综述气候变化下农业生产力与农村经济韧性的多维适应路径。","整合气候压力、农场适应与农村转型的文献证据分析。","有效适应需生产、金融、制度、社会与区域机制协同而非单一技术。","可量化农户—区域多层级适应组合的协同效应与韧性阈值。","2026-09-24T23:30:10.179607Z",{"id":266,"title":267,"url":268,"summary":269,"summary_zh":270,"content":9,"source_name":271,"source_url":268,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":272,"score_detail":273,"sources":275,"tags":277,"search_phrases":282,"slug":285,"view_count":36,"doi":286,"paper":287,"created_at":338},3351,"Integrated Land, Soil and Crop Information Systems in Ethiopia, Kenya, and Rwanda: Institutional Readiness and Implications for Climate-Smart Agriculture","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101776","Integrated land–soil–crop information systems are increasingly important for supporting climate-smart agricultural planning and implementation, yet their development in Eastern Africa is constrained by fragmented mandates, weak technical capacity, and limited data interoperability. This study assesses how institutional readiness, user demand, and technical and human-capacity conditions shape the integration of such systems into national Agricultural Knowledge and Innovation Systems (AKIS). A mixed-methods, multi-country assessment was conducted in Ethiopia, Kenya, and Rwanda (2022–2024), drawing on 145 semi-structured key-informant interviews, stakeholder mapping, national workshops, and a regional synthesis consultation. The analysis addressed three objectives: (i) diagnose institutional readiness and user demand; (ii) assess technical, infrastructural, and human-capacity requirements; and (iii) identify governance and design principles for embedding integrated information systems within AKIS and Climate-Smart Agriculture (CSA) strategies. The results show consistently high demand for spatially explicit soil and crop data but persistent fragmentation of mandates, uneven coordination, and substantial subnational capacity gaps. Despite these constraints, emerging digital-agriculture strategies, open-data policies, and regional soil-health initiatives provide potential entry points for integration. The study offers a comparative evidence base and design principles—covering governance, interoperability standards, co-production processes, and capacity strengthening—needed to transition from project-driven fragmentation toward interoperable and sustainable information systems. These findings provide diagnostic and design-oriented insights for national and regional efforts to strengthen agricultural information systems that support CSA implementation in Eastern Africa.","综合的土地—土壤—作物信息系统在支持气候智慧型农业规划与实施方面日益重要，但其在东非的发展受到职责分散、技术能力薄弱和数据互操作性有限的制约。本研究评估了制度准备度、用户需求以及技术和人力能力条件如何影响此类系统融入国家农业知识与创新系统（AKIS）。研究于2022—2024年在埃塞俄比亚、肯尼亚和卢旺达开展了混合方法、多国评估，基于145次半结构化关键知情人访谈、利益相关方映射、国家研讨会以及一次区域综合磋商。分析围绕三个目标展开：（i）诊断制度准备度和用户需求；（ii）评估技术、基础设施和人力能力需求；（iii）确定将综合信息系统嵌入AKIS和气候智慧型农业（CSA）战略的治理与设计原则。结果表明，对空间显式土壤和作物数据的需求持续较高，但职责分散、协调不均衡以及地方层面能力差距显著等问题长期存在。尽管存在这些制约，新兴的数字农业战略、开放数据政策和区域土壤健康倡议为整合提供了潜在切入点。本研究提供了比较性证据基础和设计原则——涵盖治理、互操作性标准、共同生产过程和能力建设——这些是从项目驱动的碎片化转向可互操作且可持续的信息系统所必需的。这些发现为国家和区域层面加强支持东非CSA实施的农业信息系统提供了诊断性和设计导向的见解。","Land",81,{"impact":121,"substance":69,"depth":121,"authority":72,"freshness":73,"relevant":22,"comment":274},"基于三国145位关键知情人访谈的混合方法研究，为东非农业信息系统整合与气候智慧农业提供治理与设计原则，方法扎实、结论可靠，具区域政策参考价值。",[276],{"name":271,"url":268},[278,81,279,27,280,281],"数字农业","土壤健康","农业数据","数据互操作",[283,284],"埃塞俄比亚 肯尼亚 卢旺达 农业信息系统","气候智慧农业 土壤作物数据","埃塞俄比亚肯尼亚卢旺达农业信息系统-3351","10.3390\u002Fland15101776",{"doi":286,"openalex_id":288,"authors":289,"venue":271,"cited_by_count":36,"oa_url":268,"card":332,"direction":52,"ingested_from":53},"W7214079859",[290,293,296,298,300,303,306,309,311,314,317,320,323,326,329],{"name":291,"orcid":292},"John Walker Recha","https:\u002F\u002Forcid.org\u002F0000-0002-1146-7197",{"name":294,"orcid":295},"A. Kooiman","https:\u002F\u002Forcid.org\u002F0000-0001-8208-6781",{"name":297,"orcid":9},"Thaïsa van der Woude",{"name":299,"orcid":9},"Hanneke Heesmans",{"name":301,"orcid":302},"Ermias Aynekulu","https:\u002F\u002Forcid.org\u002F0000-0002-1955-6995",{"name":304,"orcid":305},"Angela Nduta Gitau","https:\u002F\u002Forcid.org\u002F0000-0002-8963-2375",{"name":307,"orcid":308},"Pascal Debons","https:\u002F\u002Forcid.org\u002F0000-0001-6314-9935",{"name":310,"orcid":9},"Frank van Weert",{"name":312,"orcid":313},"Michael Okoti","https:\u002F\u002Forcid.org\u002F0000-0002-9550-8258",{"name":315,"orcid":316},"Elizabeth A. Okwuosa","https:\u002F\u002Forcid.org\u002F0000-0001-5941-7423",{"name":318,"orcid":319},"Kennedy Were","https:\u002F\u002Forcid.org\u002F0000-0002-8012-6812",{"name":321,"orcid":322},"Girma Mamo Diga","https:\u002F\u002Forcid.org\u002F0000-0002-2593-3187",{"name":324,"orcid":325},"Dejene Abera","https:\u002F\u002Forcid.org\u002F0000-0003-3692-8620",{"name":327,"orcid":328},"Pierre Celestin Ndayisaba","https:\u002F\u002Forcid.org\u002F0000-0002-8400-9146",{"name":330,"orcid":331},"Jules Rutebuka","https:\u002F\u002Forcid.org\u002F0000-0002-5236-3503",{"tldr":333,"method":334,"finding":335,"direction":336,"opportunity":337},"评估埃塞俄比亚、肯尼亚和卢旺达三国土地-土壤-作物综合信息系统的机构准备度与整合路径。","2022-2024年三国混合方法评估，含145个关键知情人访谈、利益相关方映射与","三国对空间化土壤作物数据需求高，但机构职责碎片化、协调不均、地方能力缺口大。","数字乡村与农业信息化","可研究开放数据政策与区域土壤健康倡议如何作为切入点，推动跨部门互操作标准与联合生产能力建设。","2026-09-24T23:30:10.120978Z"]