[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3154":3,"related-3154":107},{"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":23,"tags":25,"primary_topic":30,"secondary_topics":36,"classification":42,"search_phrases":79,"slug":82,"view_count":69,"doi":83,"paper":84,"created_at":106},3154,"The Role of Agricultural Extension Services in Promoting Climate-Smart Agriculture Adoption among Smallholder Farmers in Mwingi West sub-county Kitui County, Kenya","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fajaees\u002F2026\u002Fv44i103022","Agricultural extension services provide smallholder farmers with knowledge, technical guidance, and advisory support that can facilitate the adoption of climate-smart agricultural (CSA) practices. This study examined the role of agricultural extension services in promoting CSA adoption among smallholder farmers in Mwingi West Sub-County, Kitui County, Kenya. A cross-sectional mixed-methods design was used. Quantitative data were collected from 200 randomly selected farmers through structured questionnaires, while qualitative evidence was obtained from 10 agricultural extension officers and 10 focus group discussions with farmer groups. Quantitative data were analysed using descriptive statistics and the chi-square test of independence. Significant associations were reported between CSA adoption and access to agricultural extension services, the source of extension information, type of extension support received, frequency of extension contact, perceived usefulness of extension services, CSA practices promoted through extension, and farmers’ perceived influence of extension services on adoption. Most respondents (82.0%) had access to extension services. Extension agents were the main information source (46.0%), and technical training was the most frequently reported support (38.0%). Conservation agriculture (30.0%), agroforestry (22.0%), and water harvesting (19.0%) were the leading practices promoted through extension activities. Nearly half of respondents (48.0%) reported that extension services had increased CSA adoption to a great extent. The findings indicate that accessible, practical, and regular extension support is closely associated with CSA adoption in the study area.","农业推广服务为小农户提供知识、技术指导和咨询服务，有助于促进气候智能型农业（CSA）实践的采纳。本研究考察了农业推广服务在促进肯尼亚基图伊县姆温吉西分区小农户采纳气候智能型农业实践中的作用。研究采用横断面混合方法设计。定量数据通过结构化问卷从200名随机抽取的农户中收集，定性证据则来自10名农业推广官员以及10次农户小组焦点小组讨论。定量数据采用描述性统计和卡方独立性检验进行分析。结果显示，气候智能型农业实践的采纳与以下因素存在显著关联：能否获得农业推广服务、推广信息来源、所获推广支持类型、推广接触频率、推广服务的感知有用性、通过推广所宣传的气候智能型农业实践，以及农户对推广服务在采纳过程中影响力的感知。大多数受访者（82.0%）能够获得推广服务。推广人员是主要的信息来源（46.0%），技术培训是最常报告的支持类型（38.0%）。通过推广活动宣传的主要实践包括保护性农业（30.0%）、农林业（22.0%）和雨水收集（19.0%）。近半数受访者（48.0%）表示推广服务在很大程度上提高了气候智能型农业实践的采纳率。研究结果表明，在研究区域内，可及、实用且定期的推广支持与气候智能型农业实践的采纳密切相关。",null,"Asian Journal of Agricultural Extension Economics & Sociology","2026-09-22T00:00:00Z","论文",10,false,65,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":22},8,20,15,12,1,"基于肯尼亚小农户的实证研究，数据翔实但地域性强，对国内三农信息化参考价值有限，可作国际经验收录。",[24],{"name":10,"url":6},[26,27,28,29],"肯尼亚","小农户","气候智慧农业","农业推广",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"G1","extension-transfer","农技推广与成果转化","\u002Ftopic\u002Frural-services\u002Fextension-transfer","G",[37],{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",{"status":43,"locked":14,"version":44,"method":45,"evidence":46},"classified","2026-10-22.2","rules",{"candidates":47,"agricultural_evidence":50},[48,56,61,67,74],{"code":31,"score":49,"supported":50,"title":51,"abstract":53,"tags":55},18,true,[52],"agricultural extension",[29,54,52],"技术培训",[29],{"code":38,"score":19,"supported":50,"title":57,"abstract":59,"tags":60},[58],"smallholder",[27,58],[27],{"code":62,"score":17,"supported":50,"title":63,"abstract":65,"tags":66},"I1",[64],"smart agriculture",[],[],{"code":68,"score":69,"supported":50,"title":70,"abstract":71,"tags":73},"H8",3,[],[72],"conservation agriculture",[],{"code":75,"score":21,"supported":14,"title":76,"abstract":77,"tags":78},"H7",[],[],[28],[80,81],"气候智慧农业 农业推广 小农户 肯尼亚","气候智慧农业 农业推广","气候智慧农业农业推广小农户肯尼亚-3154","10.9734\u002Fajaees\u002F2026\u002Fv44i103022",{"doi":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":97,"oa_url":6,"card":98,"direction":104,"ingested_from":105},"W7213979623",[87,89,91,93,95],{"name":88,"orcid":9},"Simon Mbala",{"name":90,"orcid":9},"David Kawioo Mwanzia",{"name":92,"orcid":9},"Thomas Ekamais Akuja",{"name":94,"orcid":9},"Felix Ngunzo Kioli",{"name":96,"orcid":9},"Harrison Musyoka Maithya",0,{"tldr":99,"method":100,"finding":101,"direction":102,"opportunity":103},"研究肯尼亚小农户中农业推广服务对气候智慧型农业采纳的促进作用。","混合方法，200份农户问卷、10名推广员访谈和10组焦点小组，卡方检验。","推广服务可及性、信息源、支持类型和接触频率与CSA采纳显著相关，82%农户有推广服务。","数字乡村与农业信息化","可探索数字推广渠道（如手机短信、APP）如何替代或补充传统推广员，提升小农户CSA采纳率。","智慧农业 \u002F 农业物联网","openalex","2026-09-22T23:30:10.323072Z",{"total":108,"page":21,"page_size":108,"items":109},6,[110,181,229,323,430,502],{"id":111,"title":112,"url":113,"summary":114,"summary_zh":115,"content":9,"source_name":116,"source_url":113,"published_at":117,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":118,"score_detail":119,"sources":124,"tags":126,"primary_topic":130,"secondary_topics":136,"classification":139,"search_phrases":158,"slug":161,"view_count":162,"doi":163,"paper":164,"created_at":180},1747,"Artificial Intelligence and Large Language Models in Agricultural Extension: Critical Synthesis of Adoption, Efficacy, and Equity in Smallholder Advisory Systems","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fair\u002F2026\u002Fv27i51723","Agricultural extension and advisory services are undergoing a rapid digital transformation driven by artificial intelligence (AI), machine learning, natural language processing, and, more recently, generative artificial intelligence and large language models (LLMs). These technologies have the potential to address persistent constraints in conventional agricultural extension, including limited adviser-to-farmer ratios, geographical isolation, inadequate localisation of information, and delays in the dissemination of climate, market, and agronomic information. LLM-based advisory systems are particularly significant because they can transform complex agricultural knowledge into conversational, multilingual, and potentially personalised guidance. However, their technical capability does not automatically translate into effective or equitable agricultural outcomes. This review synthesises emerging evidence on the adoption, efficacy, scalability, and equity implications of AI and LLM-based agricultural advisory systems, with particular emphasis on smallholder farmers in low- and middle-income countries. The literature indicates that AI-enabled advisory systems can improve access to timely information, facilitate question-answering, support crop and pest management, and extend the reach of human extension personnel. Emerging platforms such as Farmer.Chat demonstrate the feasibility of large-scale generative AI-enabled advisory delivery, while recent experiments with retrieval-augmented generation indicate promising pathways for improving factual grounding and contextual relevance. Nevertheless, evidence of direct impacts on farm productivity, profitability, resilience, and sustained behavioural change remains considerably weaker than evidence of technological feasibility and user engagement. Major limitations include hallucination, outdated or geographically inappropriate information, language and dialect constraints, weak interoperability with local agricultural databases, limited transparency, data governance concerns, and overreliance on automated recommendations. Equity is an equally important concern because digital access, literacy, gender, income, connectivity, and social norms influence who can benefit from AI-enabled services. The review argues that LLMs should therefore be positioned as augmentation technologies within pluralistic extension systems rather than as substitutes for human advisers. Future agricultural AI systems should combine retrieval from authoritative local knowledge bases, multimodal and multilingual interfaces, human oversight, participatory design, continuous evaluation, responsible data governance, and explicit equity metrics. The future value of AI in agricultural extension will ultimately depend not on model sophistication alone but on the quality of the socio-technical systems in which these technologies are embedded.","农业推广与咨询服务正在经历一场由人工智能（AI）、机器学习、自然语言处理以及近年来兴起的生成式人工智能和大语言模型（LLMs）驱动的快速数字化转型。这些技术有望解决传统农业推广中长期存在的制约因素，包括推广人员与农民比例有限、地理隔离、信息本地化不足，以及气候、市场和农艺信息传播的延迟。基于大语言模型的咨询系统尤为重要，因为它们能够将复杂的农业知识转化为对话式、多语言且可能实现个性化的指导。然而，其技术能力并不会自动转化为有效或公平的农业成果。本综述综合了关于基于AI和大语言模型的农业咨询系统在采用、有效性、可扩展性和公平性影响方面的新兴证据，特别关注低收入和中等收入国家的小农户。文献表明，AI赋能的咨询系统能够改善及时信息的获取，促进问答交互，支持作物与病虫害管理，并扩展人工推广人员的服务范围。诸如Farmer.Chat等新兴平台展示了大规模生成式AI赋能咨询服务的可行性，而近期关于检索增强生成的实验则表明，在改善事实依据和情境相关性方面存在有前景的路径。尽管如此，关于对农业生产率、盈利能力、韧性及持续性行为改变产生直接影响的证据，仍明显弱于关于技术可行性和用户参与度的证据。主要局限包括幻觉现象、信息过时或地理上不适用、语言和方言限制、与当地农业数据库的互操作性薄弱、透明度有限、数据治理问题，以及对自动化建议的过度依赖。公平性同样是一个重要关切，因为数字接入、素养、性别、收入、连通性和社会规范都会影响谁能够从AI赋能的服务中受益。本综述认为，大语言模型应被定位为多元推广体系中的增强技术，而非人类推广人员的替代品。未来的农业AI系统应将检索增强生成与结构化农业知识图谱、","Advances in Research","2026-09-04T00:00:00Z",82,{"impact":120,"substance":120,"depth":18,"authority":121,"freshness":122,"relevant":21,"comment":123},22,13,5,"系统综述AI与LLM在农技推广中的应用、效能与公平性，对智慧农业实践有重要参考价值。",[125],{"name":116,"url":113},[127,128,27,129],"农业人工智能","大语言模型","农技推广",{"code":131,"slug":132,"name":133,"path":134,"parent_code":135},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[137,138],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},{"status":43,"locked":14,"version":44,"method":45,"evidence":140},{"candidates":141,"agricultural_evidence":50},[142,150,154],{"code":131,"score":143,"supported":50,"title":144,"abstract":146,"tags":149},19,[145],"artificial intelligence",[147,148,145],"机器学习","machine learning",[127,128],{"code":31,"score":19,"supported":50,"title":151,"abstract":152,"tags":153},[52],[29,52],[129],{"code":38,"score":19,"supported":50,"title":155,"abstract":156,"tags":157},[58],[27,58],[27],[159,160],"农业人工智能 大语言模型 农技推广 小农户","农业人工智能 大语言模型","农业人工智能大语言模型农技推广小农户-1747",2,"10.9734\u002Fair\u002F2026\u002Fv27i51723",{"doi":163,"openalex_id":165,"authors":166,"venue":116,"cited_by_count":97,"oa_url":113,"card":174,"direction":102,"ingested_from":105},"W7208785535",[167,170,172],{"name":168,"orcid":169},"Swati Sucharita","https:\u002F\u002Forcid.org\u002F0000-0003-3409-3295",{"name":171,"orcid":9},"Pratima Sachan",{"name":173,"orcid":9},"T. Sravan Kumar",{"tldr":175,"method":176,"finding":177,"direction":178,"opportunity":179},"综述AI与LLM在农业推广中的应用，评估其采纳、效果与公平性，尤其关注小农户。","系统综述新兴证据，分析AI\u002FLLM咨询系统的采用、效能、可扩展性及公平性。","AI可提升信息获取，但生产力影响证据弱，存在幻觉、公平性等问题，应作为增强而非替代。","农业人工智能与决策模型","研究空白：LLM在农业推广中的实际生产力影响与公平性机制，以及如何结合本地数据与人类顾问实现增强。","2026-09-05T23:30:36.654266Z",{"id":182,"title":183,"url":184,"summary":185,"summary_zh":9,"content":186,"source_name":187,"source_url":9,"published_at":188,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":189,"score_detail":190,"sources":194,"tags":196,"primary_topic":199,"secondary_topics":200,"classification":202,"search_phrases":224,"slug":227,"view_count":162,"doi":9,"paper":9,"created_at":228},377,"中国小农户采用数字农业推广服务的驱动因素及福利效应——Double-Hurdle模型分析1475户果蔬种植户","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260807103355465.htm","基于中国三个省份1475名果蔬种植户的微观调查数据,采用Double-Hurdle模型区分初始采纳与持续采纳,并识别不同驱动因素。研究进一步应用逆概率加权回归调整(IPWRA)评估DAES采纳对人均家庭净收入的福利效应。结果显示,初始采纳率为60.14%,但持续采纳率仅为24%,揭示显著的'采纳-持续采纳'差距。资源禀赋、风险偏好与社会网络等行为机制,以及数字可及性与政府信任等制度供给均显著促进这两个阶段,极端天气感知持续制约采纳行为。福利分析表明,采纳DAES使年度人均家庭净收入增加约12.6%。政策启示:缩小数字素养差距、开发气候适应型DAES、加强制度信任与社会网络。","《NJAS: Impact in Agricultural and Life Sciences》：Drivers and welfare effects of adopting digital agricultural extension services among smallholder farmers in China\n\n_【字体： 大 中 小 】_ _时间：2026年08月07日_ _来源：NJAS: Impact in Agricultural and Life Sciences 1.6_\n\n**编辑推荐：**\n\n数字农业推广服务（DAES）旨在改善小农户的信息获取渠道，然而许多农户在初步尝试后停止使用的原因仍缺乏充分理解。基于中国三个省份1,475名果蔬种植户的微观调查数据，本研究采用Double-Hurdle模型区分了初始采纳与持续采纳，并识别了它们的不同驱动因素。\n\n数字农业推广服务（DAES）旨在改善小农户的信息获取渠道，然而许多农户在初步尝试后停止使用的原因仍缺乏充分理解。基于中国三个省份1,475名果蔬种植户的微观调查数据，本研究采用Double-Hurdle模型区分了初始采纳与持续采纳，并识别了它们的不同驱动因素。研究进一步应用逆概率加权回归调整（IPWRA）来评估DAES采纳对人均家庭净收入的福利效应。结果显示，初始采纳率为60.14%，但持续采纳率仅为24%，揭示了显著的“采纳-持续采纳”差距。资源禀赋、风险偏好与社会网络等行为机制，以及数字可及性与政府信任等制度供给均显著促进了这两个阶段，而感知的极端天气则持续制约采纳行为。福利分析表明，采纳DAES使年度人均家庭净收入增加约12.6%。通过将行为经济学与制度分析相结合，本研究阐明了农户从初始数字接入到持续使用的行为阶段性逻辑，并提出了数字素养支持、气候适应型服务以及制度信任重建的政策路径。主要政策启示包括：缩小数字素养差距以帮助农户从初始向持续采纳转变；开发在极端天气下保持有效的气候适应型DAES以克服持续使用的关键障碍；加强制度信任与社会网络以支持初始与持续采纳。\n\n**研究背景与意义**：农业推广服务是扩散农业技术、增强农村生计韧性及改善农户生产决策的重要制度安排。随着气候变化加剧和市场环境波动，小农户对及时、准确的农业信息需求不断累积，然而传统的线下推广模式在覆盖面、时效性和成本控制上存在明显局限，难以有效服务庞大的小农户群体。在此背景下，数字农业推广服务（DAES，依托移动互联网、数字服务平台等提供农业指导、市场信息和气象预警的服务）逐渐成为克服传统局限的有效工具。尽管中国农村互联网普及率显著提升，数字硬件约束得到缓解，但基础设施的改善并未带来DAES的常态化深度应用。许多农户在政策引导和邻里示范下进行初步接触后，仍停留在浅层试验阶段，难以将其纳入长期农业决策。现有的二元“采纳或不采纳”研究范式过度简化了农户使用DAES的内部过程，忽视了从初始接触到持续采纳的阶段异质性，且在福利效应评估中常面临样本自选择偏差。为解答农户从初始向持续采纳转型的驱动因素以及DAES常态化采纳能否有效提升农户收入的科学问题，研究人员开展了这项研究。该研究有助于厘清农户数字采纳的阶段性逻辑，为优化数字乡村建设中的服务供给、提升DAES包容性提供重要实证依据，论文发表在《NJAS: Impact in Agricultural and Life Sciences》。\n\n**关键技术方法**：研究人员主要利用2019年和2020年在山东、山西和陕西三省收集的1,475份果蔬种植户微观调查队列数据开展研究。在数据分析阶段，研究采用了Double-Hurdle模型将农户的采纳行为解构为初始采纳和持续采纳强度两个相互独立又关联的阶段，以克服传统Tobit模型在同质性假设上的缺陷；同时结合逆概率加权回归调整（IPWRA）构建反事实框架，以消除可观测协变量引起的自选择偏差并准确识别DAES对农户收入的净因果效应；此外，还运用了探索性因子分析（EFA）从浏览、下载、评价和分享四个维度构建了持续采纳指数，并采用Bootstrap法计算平均偏效应的标准误。\n\n**研究结果**：\n\n* **Double-Hurdle模型估计结果**：通过该模型分析发现，农户对DAES的采纳存在显著的阶段性差异。初始采纳率高达60.14%，但持续采纳率仅为24%，呈现出明显的“高接入、低粘性”特征。户主受教育程度对跨越初始采纳门槛具有显著正向作用，但对长期持续使用无显著影响；而耕地面积和人均家庭收入等资源禀赋在两个阶段均发挥显著正向促进作用。在行为机制方面，风险偏好和社会网络显著促进了初始与持续采纳；制度供给方面，数字网络设备获取便利性与对政府推广服务的满意度均显著正向影响两阶段决策。自然环境中，极端天气感知在两个阶段均产生显著负向影响，表明气候冲击并未激发信息避险需求，反而放大了农户对生产系统的整体不确定性感知。\n\n* **边际效应估计结果**：通过计算平均偏效应（APE）进一步量化了各因素的影响力。结果显示，数字网络设备获取便利性的平均边际效应最为突出（0.068），该变量每增加一个单位，初始采纳概率提升8.3%，持续采纳程度提升8.6%，是克服双重采纳障碍的关键基础设施。人均家庭收入和风险偏好的平均边际效应分别为0.032和0.038，对促进深度参与具有重要作用。户主性别、年龄、受教育程度、耕地面积、政府服务满意度及极端天气感知的整体平均边际效应未达统计显著水平，说明这些因素的影响存在阶段性局限。\n\n* **Heckman模型稳健性检验**：研究人员采用Heckman两阶段模型对基准结果进行检验。逆米尔斯比率（IMR）在1%水平上显著，证实了样本选择偏差的存在。在初始采纳方程中，核心变量的方向与显著性与Double-Hurdle模型高度一致，支持了核心结论的稳健性。在持续采纳方程中，因模型假设误差项联合正态分布，部分变量效应被选择修正项吸收，导致个别变量显著性发生变化，这恰好印证了Double-Hurdle模型在捕捉两阶段机制异质性上的适用性与必要性。\n\n* **DAES的福利效应**：通过IPWRA模型估计发现，DAES采纳对农户收入的平均处理效应（ATT）为0.126，在1%水平上显著。这表明在控制自选择偏差后，采纳DAES使农户年度人均家庭净收入增加约12.6%。通过平衡检验和多倾向得分匹配（PSM）方法的交叉验证，匹配后样本协变量偏差显著降低，不同匹配方法估计的增收效应稳定在34.7至38.9个百分点之间，证实了数字服务能实质性地改善农户家庭福利。\n\n**讨论与结论**：在讨论部分，研究人员指出，DAES的采纳并非简单的二元选择，而是从“初始采纳”向“持续采纳”演进的动态过滤过程，数字不平等已从传统的“接入鸿沟”转变为更深层的“使用鸿沟”。单一行为或制度视角无法解释这种阶段性差异，需将行为经济学与制度分析结合。行为机制上，农户受有限理性和损失厌恶影响，风险偏好通过降低心理不确定性促进持续采纳；制度维度上，熟人社会的网络扩散与政府公共机构的信任背书共同克服了农户的防御心理。极端天气感知的负向效应构成了“气候风险感知悖论”，表明若缺乏本地化的精准响应方案，外部冲击只会放大农户的失控感。研究最终得出以下结论：第一，DAES采纳表现出显著的阶段性“不连续性”，初始接入依靠行政动员，而持续采纳有赖于微观行为与宏观制度供给的匹配；第二，持续采纳取决于内部行为机制与外部制度供给的协同作用，极端天气感知持续抑制采纳，凸显了服务本地化适应的紧迫性；第三，DAES的收入红利并非数字接入的自动产物，而是源于生产实践中的持续嵌入。从初始接入到持续采纳的实质性转化，才是实现农业数字化转型包容性福利效应的核心前提。","NJAS: Impact in Agricultural and Life Sciences 2026-08-07","2026-08-07T00:00:00Z",79,{"impact":49,"substance":191,"depth":18,"authority":192,"freshness":69,"relevant":21,"comment":193},24,14,"基于1475户样本的实证研究，揭示数字农业推广服务采纳的阶段性差异及增收效应，方法严谨，结论具有政策参考价值，但发表于一周前，时效性稍弱。",[195],{"name":187,"url":184},[27,197,198],"数字农业推广服务","Double-Hurdle NJAS",{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},[201],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":43,"locked":14,"version":44,"method":45,"evidence":203},{"candidates":204,"agricultural_evidence":50},[205,210,214,219],{"code":38,"score":206,"supported":50,"title":207,"abstract":208,"tags":209},9,[27],[],[27],{"code":31,"score":17,"supported":50,"title":211,"abstract":212,"tags":213},[29],[],[],{"code":62,"score":17,"supported":50,"title":215,"abstract":217,"tags":218},[216],"数字农业",[],[],{"code":75,"score":69,"supported":50,"title":220,"abstract":221,"tags":223},[],[222],"气候适应",[],[225,226],"数字农业推广服务 小农户 Double-Hurdle NJAS","数字农业推广服务 小农户","数字农业推广服务小农户Double-HurdleNJAS-377","2026-08-10T23:54:46.300709Z",{"id":230,"title":231,"url":232,"summary":233,"summary_zh":234,"content":9,"source_name":235,"source_url":232,"published_at":236,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":237,"score_detail":238,"sources":240,"tags":242,"primary_topic":245,"secondary_topics":251,"classification":258,"search_phrases":301,"slug":304,"view_count":97,"doi":305,"paper":306,"created_at":322},5478,"Characterisation of Food Security Situation for Smallholder Farmers in Zvimba","https:\u002F\u002Fdoi.org\u002F10.71458\u002Frx0qpm30","This study provides a comprehensive analysis of the food security situation among smallholder farmers (SHFs) in Zvimba District, Zimbabwe. Smallholder agriculture is the bedrock of Zimbabwe's food system, yet it remains highly vulnerable to a complex array of shocks and stressors. Using a mixed-methods approach, this research investigates the prevalence, drivers and lived experiences of food insecurity within this community. A structured survey was administered to 412 randomly selected smallholder households across the district's wards. The quantitative data were supplemented by 12 Focus Group Discussions (FGDs) and 24 Key Informant Interviews (KIIs) with farmers, community leaders and agricultural extension officers to capture qualitative nuances. The study is grounded in the Food Security Theory (FST), which conceptualises food security through its four pillars: food availability, food access, food utilisation and food stability. Findings reveal a precarious food security situation. Quantitatively, 78.4% of households were found to be food insecure, with an average Hunger Months Index of 4.7 months per year. The study identifies a significant disconnect between maize production, the national staple and household consumption, with over 65% of households failing to produce enough maize to meet their annual requirements. Qualitative data illuminated the multi-faceted drivers of this insecurity. Key points to note include climate change whereby erratic rainfall and prolonged mid-season dry spells were consistently reported as the primary production challenges, limited access to farming inputs whereby high costs and unreliable supplies of certified seeds, fertilizers and agro[1]chemicals constrain productivity. Morelso, socio-economic factors such as poverty, lack of viable alternative livelihoods and limited access to formal credit perpetuate a cycle of vulnerability. In addition, institutional weaknesses, for example, challenges with agricultural extension services and market inefficiencies, exacerbate the situation. The study concludes that food insecurity in Zvimba is not merely a problem of food production, but is deeply rooted in structural issues affecting food access, food utilisation, as well as food stability. Recommendations are proposed for a multi-sectoral approach, including promoting Climate-Smart Agriculture (CSA) and drought-resistant crops, strengthening input support systems and rural finance, diversifying livelihood strategies and enhancing the capacity of extension services. This research contributes to a deeper understanding of the localised dynamics of food security and provides evidence-based guidance for policymakers, development practitioners and the farmers of Zvimba themselves.","本研究对津巴布韦兹维姆巴区小农户（smallholder farmers, SHFs）的粮食安全状况进行了全面分析。小农农业是津巴布韦粮食体系的基石，但仍极易受到一系列复杂冲击和压力的影响。本研究采用混合方法，考察了该社区粮食不安全的普遍程度、驱动因素及生活体验。研究对该区各选区随机抽取的412户小农户进行了结构化问卷调查。定量数据辅以12次焦点小组讨论（FGDs）和24次关键知情人访谈（KIIs），访谈对象包括农民、社区领袖和农业推广人员，以捕捉定性层面的细微差异。本研究以粮食安全理论（Food Security Theory, FST）为基础，该理论通过四大支柱界定粮食安全：粮食可供性、粮食获取、粮食利用和粮食稳定性。研究结果揭示了严峻的粮食安全形势。定量数据显示，78.4%的家庭存在粮食不安全，年均饥饿月份指数为4.7个月。研究发现，玉米产量——该国主粮——与家庭消费之间存在显著脱节，超过65%的家庭生产的玉米不足以满足其年度需求。定性数据揭示了这一不安全状况的多重驱动因素。值得注意的要点包括：气候变化，即降雨不稳定和持续的中期干旱被一致报告为主要生产挑战；农业投入品获取受限，即认证种子、化肥和农用化学品成本高昂且供应不可靠，制约了生产力。此外，贫困、缺乏可行的替代生计以及正规信贷获取受限等社会经济因素使脆弱性循环持续存在。此外，制度薄弱环节，例如农业推广服务面临的挑战和市场效率低下，加剧了这一状况。研究得出结论，兹维姆巴的粮食不安全不仅仅是粮食生产问题，而是深深植根于影响粮食获取、粮食利用以及粮食稳定性的结构性问题。研究提出了采取多部门方法的建议，包括推广气候智能型农业（Climate-Smart Agriculture, CSA）和抗旱作物、加强投入品支持体系和农村金融、多样化生计策略以及增强","Ngenani The Zimbabwe Ezekiel Guti Journal of Community Engagement and Societal Transformations","2026-10-20T00:00:00Z",55,{"impact":17,"substance":49,"depth":19,"authority":108,"freshness":17,"relevant":21,"comment":239},"基于412户调查与混合方法的扎实实证研究，但属津巴布韦地方性案例，公共影响与信源权威度有限，可作参考而非每日精选。",[241],{"name":235,"url":232},[243,27,28,29,244],"粮食安全","津巴布韦",{"code":246,"slug":247,"name":248,"path":249,"parent_code":250},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[252,253],{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},{"code":75,"slug":254,"name":255,"path":256,"parent_code":257},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":43,"locked":14,"version":44,"method":45,"evidence":259},{"candidates":260,"agricultural_evidence":50},[261,266,270,278,283,290,297],{"code":246,"score":19,"supported":50,"title":262,"abstract":264,"tags":265},[263],"food security",[243,263],[243],{"code":38,"score":19,"supported":50,"title":267,"abstract":268,"tags":269},[58],[27,58],[27],{"code":75,"score":13,"supported":50,"title":271,"abstract":272,"tags":277},[],[273,274,275,276],"气候变化","干旱","climate change","drought",[28],{"code":31,"score":279,"supported":50,"title":280,"abstract":281,"tags":282},7,[],[29,52],[29],{"code":284,"score":108,"supported":50,"title":285,"abstract":286,"tags":289},"A3",[],[287,288],"玉米","maize",[],{"code":291,"score":108,"supported":50,"title":292,"abstract":293,"tags":296},"G3",[],[294,295],"农村金融","rural finance",[],{"code":62,"score":69,"supported":50,"title":298,"abstract":299,"tags":300},[],[64],[],[302,303],"Zvimba 小农户 粮食安全","津巴布韦 小农 玉米","Zvimba小农户粮食安全-5478","10.71458\u002Frx0qpm30",{"doi":305,"openalex_id":307,"authors":308,"venue":235,"cited_by_count":97,"oa_url":9,"card":317,"direction":104,"ingested_from":105},"W7223029383",[309,312,315],{"name":310,"orcid":311},"Casper Myambo","https:\u002F\u002Forcid.org\u002F0009-0007-8625-7526",{"name":313,"orcid":314},"Chipo Plaxedes Mubaya","https:\u002F\u002Forcid.org\u002F0000-0002-4123-0238",{"name":316,"orcid":9},"Patience Mutopo",{"tldr":318,"method":319,"finding":320,"direction":102,"opportunity":321},"调查津巴布韦Zvimba小农户粮食安全状况，分析其普遍性、成因与实际体验。","混合方法：412户问卷、12场焦点小组、24个关键人物访谈，基于粮食安全四支柱理","78.4%家庭粮食不安全，年均饥饿月4.7个月，主因是气候、投入、社会经济与制度等结构性问题。","可探索用移动端问卷与遥感产量监测构建小农户粮食安全动态预警与精准干预系统。","2026-10-21T23:30:08.937079Z",{"id":324,"title":325,"url":326,"summary":327,"summary_zh":328,"content":9,"source_name":329,"source_url":326,"published_at":330,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":331,"score_detail":332,"sources":335,"tags":337,"primary_topic":339,"secondary_topics":340,"classification":343,"search_phrases":411,"slug":414,"view_count":97,"doi":415,"paper":416,"created_at":429},5185,"When the rains are too much: El Niño, Smallholder Farmers and Food Security in Western Kenya","https:\u002F\u002Fdoi.org\u002F10.18697\u002Fajfand.155.ed182","When the rains are too much: El Niño, Smallholder Farmers and Food Security in Western Kenya For generations, farmers in Western Kenya have watched the skies carefully. The arrival, duration, and distribution of rainfall have traditionally provided important signals about when to prepare land, plant, weed, and harvest. But these signals are becoming increasingly difficult to read. Climate change is altering rainfall patterns, while increasingly frequent extreme weather events are making farming more uncertain. The current outlook for the October–December 2026 season brings this challenge sharply into focus. The IGAD Climate Prediction and Applications Centre (ICPAC) forecasts a wetter-than-normal season across much of the Greater Horn of Africa. The Lake Victoria Basin, which includes large parts of Western Kenya, is among the areas with a high likelihood of receiving more than 400 mm of seasonal rainfall. ICPAC reports that El Niño has developed and is expected to strengthen, while a positive Indian Ocean Dipole is also expected—climate conditions that are commonly associated with enhanced rainfall in the region, and is likely to run into February of 2027. But what does this mean for the smallholder farmer? The first point is that more rainfall does not necessarily mean more food. For a farmer whose livelihood depends almost entirely on rain-fed agriculture, abundant rainfall can be a blessing. It can replenish streams and water sources, improve soil moisture, restore pasture and create favourable conditions for crop production. If well distributed, the rains could contribute to improved harvests and household food supplies. The problem arises when rainfall is too intense, too concentrated or poorly distributed. A farmer may receive a great deal of rain in a few days and then experience a dry spell. Another farmer a few kilometres away may receive considerably less. Heavy downpours can cause flooding, waterlogging and soil erosion. Seeds may be washed away soon after planting. Young crops can be submerged or damaged. Valuable topsoil and nutrients can be carried away, reducing the productivity of land in subsequent seasons. This is particularly important in Western Kenya, where many households depend on small parcels of land for both food and income. A failed or damaged crop is not simply an agricultural loss. It can mean less food in the household, less money for school fees and health care, and fewer resources to purchase nutritious foods. The food-security paradox We must, therefore, look beyond agricultural production to food and nutrition security. A household may produce enough maize yet still have a poor diet if vegetables, legumes, fruits, milk, eggs or other foods are unavailable or unaffordable. Climate shocks can reduce this diversity. When crops are damaged, families may depend more heavily on whatever staple food remains available. This is why climate resilience must also be nutrition-sensitive. Western Kenya has a rich agricultural tradition and considerable potential for diversified food production. Farmers grow cereals, legumes, vegetables and root crops and keep livestock and poultry. Such diversity is not merely an agricultural advantage; it is a nutritional resource. It can provide different foods, spread risk and generate income at different times of the year. Climate adaptation should, therefore, not encourage farmers simply to produce more of one crop. It should help them build diverse and resilient farming systems. Women carry a large part of the burden The impact of erratic and excessive rainfall also has a gender dimension. Women in smallholder households are often deeply involved in food production, processing, preparation and household nutrition. When harvests fail, or food prices rise, women frequently have to find ways of stretching limited household resources to feed the family. When roads become impassable or markets are disrupted, women may have greater difficulty accessing food and agricultural inputs. When water sources are contaminated or damaged, household responsibilities can become even more demanding. Climate adaptation must therefore deliberately include women—not simply as beneficiaries, but as decision-makers, innovators, farmers and leaders. Young people must also be part of the solution There is another group that deserves greater attention: young people. Western Kenya cannot build climate-resilient agriculture while treating agriculture as an occupation of the past. Young people need to see opportunities in modern farming, agro-processing, food safety, climate information services, irrigation, digital agriculture and agricultural entrepreneurship. The increasing unpredictability of climate may actually provide an opportunity to make agriculture more innovative. Young people can help introduce new technologies, improve access to climate information, develop value-added products and create businesses around food production and processing. From forecasting to action The availability of a climate forecast is useful only if it reaches the people who need it in time. Farmers need information that answers practical questions: When should I plant? Which crops or varieties are appropriate? How can I protect my soil? What should I do if rainfall becomes excessive? How can I protect harvested food? Where can I obtain reliable seed and other inputs? Seasonal forecasts should, therefore, be translated into local, practical agricultural advice. ICPAC itself emphasizes that seasonal forecasts should be used together with weekly and monthly forecasts and national meteorological information. This requires stronger links between meteorological services, agricultural extension officers, researchers, county governments, farmer organizations and communities. We should also strengthen simple but important measures: water harvesting, drainage, terracing and soil conservation; planting crops and varieties suited to local conditions; maintaining vegetation cover; diversifying crops and livestock; improving storage facilities; and protecting food from moisture and contamination. Prepare before the rain comes The greatest lesson from the current El Niño outlook is perhaps that preparedness must begin before the first heavy rains arrive. Governments and development partners should not wait for floods, damaged roads, destroyed crops or food shortages before responding. Early warning should lead to early action. Farmers should be supported to prepare their farms, protect livestock, secure seed and inputs, strengthen food storage and identify alternative routes to markets. This is particularly important because the same season can produce both opportunities and losses. ICPAC notes that enhanced rainfall can support agricultural production and replenish water resources, but can simultaneously increase the risk of flooding, flash floods and landslides in vulnerable areas. A changing climate requires a different agricultural mindset Perhaps the most important change we need is in the way we think about farming. For too long, agricultural planning has often assumed that rainfall will behave according to a familiar calendar. That assumption is becoming increasingly unsafe. Farmers now have to manage not only too little rain, but also too much rain, rain at the wrong time and rain in the wrong place. The challenge is, therefore, not simply to produce more food. It is to build food systems that can continue providing adequate, diverse, safe and nutritious food under increasingly uncertain climatic conditions. Western Kenya's smallholder farmers should not be left alone to carry this burden. They need science that responds to their realities, extension services that reach them, climate information they can understand and use, financial services that help them manage risk, markets that function during difficult seasons, and policies that recognize the central role of smallholder agriculture in national food and nutrition security, and partners who are willing to appreciate and make use of indigenous knowledge. El Niño should, therefore, be viewed neither simply as a disaster nor automatically as a blessing. It is a climate event whose consequences will depend greatly on our preparedness. The question before us is not merely, “Will the rains come?” They probably will. The more important question is: Will our farmers, food systems and institutions be ready when they do? That is where climate resilience—and ultimately food and nutrition security—will be tested. Prof. Ruth Khasaya Oniang'o Founder and Editor-in-Chief, AJFAND ORCiD: https:\u002F\u002Forcid.org\u002F0009-0005-8344-9093","当雨水过多时：厄尔尼诺现象、小农户与肯尼亚西部的粮食安全\n\n世代以来，肯尼亚西部的农民一直密切关注着天空。降雨的到来、持续时间和分布，传统上为何时整地、播种、除草和收获提供了重要信号。但这些信号正变得越来越难以解读。气候变化正在改变降雨模式，而日益频繁的极端天气事件使农业变得更加不确定。当前对2026年10月至12月季节的展望使这一挑战凸显出来。政府间发展组织气候预测与应用中心（ICPAC）预测，大非洲之角大部分地区将迎来高于正常水平的湿润季节。维多利亚湖流域——包括肯尼亚西部的大部分地区——属于极有可能获得超过400毫米季节性降雨的区域之一。ICPAC报告称，厄尔尼诺现象已经形成并预计将增强，同时预计还将出现正印度洋偶极子——这些气候条件通常与该地区降雨增强相关，并可能持续到2027年2月。但这对小农户意味着什么？首先，更多降雨并不必然意味着更多粮食。对于生计几乎完全依赖雨养农业的农民来说，充沛的降雨可能是福。它可以补充溪流和水源、改善土壤湿度、恢复牧场，并为作物生产创造有利条件。如果分布良好，降雨可能有助于改善收成和家庭粮食供应。问题出现在降雨过于猛烈、过于集中或分布不均的时候。一个农民可能在几天内获得大量降雨，随后又经历一段干旱期。几公里外的另一个农民可能获得的降雨少得多。暴雨可能引发洪水、渍涝和土壤侵蚀。种子可能在播种后不久被冲走。幼苗可能被淹没或受损。宝贵的表土和养分可能被带走，降低土地在后续季节的生产力。这在肯尼亚西部尤为重要，因为许多家庭依赖小块土地获取食物和收入。作物歉收或受损不仅仅是农业损失。它可能意味着家庭食物减少、用于学费和医疗的钱减少，以及购买营养食品的资源减少。粮食安全……","African Journal of Food Agriculture Nutrition and Development","2026-10-16T00:00:00Z",75,{"impact":49,"substance":18,"depth":333,"authority":121,"freshness":17,"relevant":21,"comment":334},16,"核心期刊评论文章，结合El Niño预测讨论小农户气候适应与粮食营养安全，有实质分析与行动建议，但属区域案例、非信息化技术突破。",[336],{"name":329,"url":326},[26,243,27,28,338],"气候预警",{"code":246,"slug":247,"name":248,"path":249,"parent_code":250},[341,342],{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},{"code":75,"slug":254,"name":255,"path":256,"parent_code":257},{"status":43,"locked":14,"version":44,"method":45,"evidence":344},{"candidates":345,"agricultural_evidence":50},[346,350,354,360,367,371,377,383,389,395,401,405],{"code":246,"score":19,"supported":50,"title":347,"abstract":348,"tags":349},[263],[243,263],[243],{"code":38,"score":19,"supported":50,"title":351,"abstract":352,"tags":353},[58],[27,58],[27],{"code":75,"score":13,"supported":50,"title":355,"abstract":356,"tags":359},[],[273,274,275,357,358],"climate resilience","waterlogging",[28],{"code":361,"score":108,"supported":50,"title":362,"abstract":363,"tags":366},"H2",[],[364,365],"土壤","soil",[],{"code":284,"score":69,"supported":50,"title":368,"abstract":369,"tags":370},[],[288],[],{"code":372,"score":69,"supported":50,"title":373,"abstract":374,"tags":376},"B4",[],[375],"月季",[],{"code":378,"score":69,"supported":50,"title":379,"abstract":380,"tags":382},"C",[],[381],"livestock",[],{"code":384,"score":69,"supported":50,"title":385,"abstract":386,"tags":388},"C3",[],[387],"poultry",[],{"code":390,"score":69,"supported":50,"title":391,"abstract":392,"tags":394},"E4",[],[393],"food safety",[],{"code":396,"score":69,"supported":50,"title":397,"abstract":398,"tags":400},"F4",[],[399],"除草",[],{"code":31,"score":69,"supported":50,"title":402,"abstract":403,"tags":404},[],[52],[],{"code":406,"score":69,"supported":50,"title":407,"abstract":408,"tags":410},"H3",[],[409],"irrigation",[],[412,413],"El Niño 小农户 粮食安全","ICPAC 季节预报 肯尼亚","ElNiño小农户粮食安全-5185","10.18697\u002Fajfand.155.ed182",{"doi":415,"openalex_id":417,"authors":418,"venue":329,"cited_by_count":97,"oa_url":422,"card":423,"direction":102,"ingested_from":105},"W7222630373",[419],{"name":420,"orcid":421},"Ruth Khasaya Oniang'o","https:\u002F\u002Forcid.org\u002F0009-0005-8344-9093","https:\u002F\u002Fajfand.net\u002FVolume26\u002FNo8\u002FEditorialVol26No8.pdf",{"tldr":424,"method":425,"finding":426,"direction":427,"opportunity":428},"分析厄尔尼诺导致肯尼亚西部降雨过量对小农粮食安全的影响","基于ICPAC季节气候预测与厄尔尼诺、印度洋偶极子分析","降雨过多且分布不均会引发洪涝、土壤侵蚀，反而威胁小农粮食安全","农业绿色发展与碳","可结合遥感与农户调查，量化极端降雨时空分布对小农产量与粮食安全的非线性影响","2026-10-17T23:30:36.130973Z",{"id":431,"title":432,"url":433,"summary":434,"summary_zh":435,"content":9,"source_name":436,"source_url":433,"published_at":437,"category":12,"cover_url":9,"hotness":438,"is_selected":14,"score":15,"score_detail":439,"sources":441,"tags":445,"primary_topic":448,"secondary_topics":449,"classification":450,"search_phrases":476,"slug":479,"view_count":21,"doi":480,"paper":481,"created_at":501},2930,"SMALLHOLDER FARMERS' PERCEPTIONS AND USE OF CLIMATE-SMART AGRICULTURAL PRACTICES IN SOUTHWESTERN NIGERIA","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22832942","Climate-smart agriculture (CSA) is increasingly promoted as a means of strengthening the resilience of smallholder farming systems to climate variability. Yet awareness of CSA does not necessarily translate into actual implementation, particularly where farmers face financial, technical and institutional constraints. This study examined the roles of climate experience, agricultural information and socioeconomic characteristics in CSA adoption among smallholder farmers in southwestern Nigeria. Primary data were obtained through a structured cross-sectional survey of 190 farmers in Akinyele Local Government Area of Oyo State. Descriptive statistics were used to characterise respondents and examine CSA awareness, agricultural information, experience of weather variability, willingness to adopt, reported adoption and perceived constraints. Because the adoption outcome was highly imbalanced, Firth-penalised logistic regression was used to identify factors independently associated with actual CSA adoption. The results show that 98.4% of respondents were aware of CSA and 96.3% reported experiencing changes in weather conditions. Although 96.3% expressed willingness to adopt CSA, 88.4% reported actual use, indicating an intention–implementation gap. Water-conservation technologies received the highest proportion of “very important” responses (83.7%), followed by organic manure (80.5%), drought-resistant crops (80.0%) and crop rotation (79.5%). Government extension officers were the principal reported source of agricultural information (55.3%). Implementation cost was the leading constraint (54.7%), followed by uncertainty about effectiveness (25.8%) and difficulty learning new techniques (19.5%). In the Firth model, experience of changing weather conditions was the only statistically significant predictor of adoption (OR = 10.401, 95% CI: 3.118–34.694, p \u003C 0.001). Gender, education, farm size and extension information were not statistically significant. The findings indicate that CSA adoption in the study area is not adequately explained by awareness alone. Farmers’ direct experience of climatic variability appears to be an important stimulus for adaptation, while financial and technical constraints can restrict implementation. Climate adaptation policies should therefore move beyond general awareness creation towards practical extension, affordable inputs, locally relevant climate information and resource-supported implementation.","气候智慧型农业（climate-smart agriculture, CSA）日益被视为增强小农户耕作系统对气候变异性适应能力的手段。然而，对气候智慧型农业的认知并不必然转化为实际实施，尤其是在农户面临资金、技术和制度约束的情况下。本研究考察了气候经验、农业信息和社会经济特征在尼日利亚西南部小农户采用气候智慧型农业中的作用。原始数据通过结构化横断面调查获得，调查对象为奥约州阿基涅莱地方政府辖区的190名农户。采用描述性统计对受访者特征进行刻画，并考察气候智慧型农业认知、农业信息、天气变异性经历、采用意愿、报告采用情况及感知约束。由于采用结果高度不平衡，研究采用Firth惩罚逻辑回归识别与实际采用气候智慧型农业独立相关的因素。结果表明，98.4%的受访者知晓气候智慧型农业，96.3%报告经历了天气状况变化。尽管96.3%表示愿意采用气候智慧型农业，但88.4%报告实际使用，表明存在意愿—实施差距。节水技术获得“非常重要”评价的比例最高（83.7%），其次为有机肥（80.5%）、抗旱作物（80.0%）和轮作（79.5%）。政府推广人员是报告的主要农业信息来源（55.3%）。实施成本是首要约束（54.7%），其次是对有效性的不确定（25.8%）和学习新技术的困难（19.5%）。在Firth模型中，经历天气状况变化是采用行为的唯一具有统计学意义的预测因素（OR = 10.401，95% CI：3.118–34.694，p \u003C 0.001）。性别、教育程度、农场规模和推广信息在统计上不显著。研究结果表明，仅凭认知不足以充分解释研究区域的气候智慧型农业采用情况。农户对气候变异性的直接经历似乎是适应行为的重要刺激因素，而资金和技术约束可能限制实施。因此，气候适应政策应从一般性认知宣传转向实践推广、可负担投入、地方相关气候信息和资源支持下的实施。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-18T00:00:00Z",25,{"impact":17,"substance":18,"depth":333,"authority":20,"freshness":206,"relevant":21,"comment":440},"基于190户调查的实证研究，揭示气候智慧农业意愿与实施落差，对农业信息化推广有参考价值，但属区域性研究、影响层级有限。",[442,443],{"name":436,"url":433},{"name":436,"url":444},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22832941",[27,28,29,446,447],"尼日利亚","农业信息",{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},[],{"status":43,"locked":14,"version":44,"method":45,"evidence":451},{"candidates":452,"agricultural_evidence":50},[453,457,461,468,472],{"code":38,"score":19,"supported":50,"title":454,"abstract":455,"tags":456},[58],[27,58],[27],{"code":75,"score":279,"supported":50,"title":458,"abstract":459,"tags":460},[],[222,276],[28],{"code":462,"score":108,"supported":50,"title":463,"abstract":464,"tags":467},"A7",[],[465,466],"轮作","crop rotation",[],{"code":62,"score":69,"supported":50,"title":469,"abstract":470,"tags":471},[],[64],[],{"code":31,"score":21,"supported":14,"title":473,"abstract":474,"tags":475},[],[],[29],[477,478],"尼日利亚 小农户 气候智慧农业","Oyo State 农业推广","尼日利亚小农户气候智慧农业-2930","10.5281\u002Fzenodo.22832942",{"doi":480,"openalex_id":482,"authors":483,"venue":436,"cited_by_count":97,"oa_url":433,"card":496,"direction":104,"ingested_from":105},"W7213578578",[484,486,488,490,492,494],{"name":485,"orcid":9},"Folasade J. Odekunle",{"name":487,"orcid":9},"Adedotun A. Adetunji",{"name":489,"orcid":9},"Idris O. JINADU",{"name":491,"orcid":9},"Adedayo S. Adediran",{"name":493,"orcid":9},"Gabriel O. Adebayo",{"name":495,"orcid":9},"Akeem Adewole",{"tldr":497,"method":498,"finding":499,"direction":102,"opportunity":500},"研究尼日利亚小农户对气候智慧农业的认知、采用意愿与实际使用及其影响因素。","对奥约州190户农户问卷调查，采用Firth惩罚逻辑回归分析采用因素。","认知与意愿高但实际采用存在落差，天气变化经历是唯一显著预测因素。","可探索农业信息传播与气候经历如何协同促进小农户从意愿到实际采用。","2026-09-19T23:30:11.305594Z",{"id":503,"title":504,"url":505,"summary":506,"summary_zh":507,"content":9,"source_name":508,"source_url":505,"published_at":509,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":510,"score_detail":511,"sources":513,"tags":515,"primary_topic":518,"secondary_topics":519,"classification":521,"search_phrases":549,"slug":552,"view_count":21,"doi":553,"paper":554,"created_at":569},2142,"Analyzing the Socio-Economic and Institutional Determinants of Climate-Smart Agricultural Practices Adoption among Smallholder Green Gram Farmers in Masinga Sub-County, Kenya","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fjeai\u002F2026\u002Fv48i104499","Climate-smart agriculture (CSA) holds significant potential for enhancing productivity and climate resilience among smallholder farmers. In Masinga Sub-County, approximately 9,900 green gram farmers face erratic rainfall, droughts, and soil degradation, resulting in mean yields of only 460 kg\u002Fha against a potential of 1.5 tons\u002Fha. This study examined the socio-economic and institutional determinants, incentives, and constraints influencing CSA adoption. Anchored in the Theory of Planned Behavior and the Technology Acceptance Model, the study employed a descriptive cross-sectional design. Data were collected using semi-structured questionnaires administered to 390 green gram farmers selected through stratified random sampling across the five wards of Masinga Sub-County. Data were analysed using descriptive statistics in SPSS Version 29. Results showed that 54.0% of respondents had adopted at least two CSA practices, with drought-resistant seed varieties (43.2%) and minimum tillage (42.4%) being the most common. The binary logistic regression model demonstrated a good fit (McFadden Pseudo R² = 0.395; overall classification accuracy = 80.4%) and identified significant positive predictors: access to input subsidies (OR = 2.33, p \u003C 0.001), perceived government policy support (OR = 2.37, p = 0.002), annual household income (OR = 2.09, p = 0.006), and market linkages (OR = 1.74, p = 0.049). High input costs were the main significant barrier (OR = 0.42, p = 0.002). Thematic analysis confirmed infrastructure deficits, financial barriers, and awareness gaps as interconnected obstacles. The study findings provided valuable insights for the academic literature by addressing gaps in research on CSA adoption in semi-arid regions, particularly for drought-prone crops like green gram. Additionally, the study findings benefit policymakers by offering data-driven recommendations for designing and developing policies that enhance CSA adoption and sustainability in smallholder farming. Agricultural extension services and development organisations may use these findings to design targeted programmes that address key incentives and constraints. The study concluded that income level and access to input subsidies were the primary drivers of CSA adoption, while high input costs constituted the foremost structural barrier, with incentives and constraints each operating as integrated, mutually reinforcing systems rather than isolated factors.","气候智慧型农业（Climate-Smart Agriculture, CSA）在提升小农户生产力和气候韧性方面具有显著潜力。在马辛加分区，约9900名绿豆种植户面临降雨不规律、干旱和土壤退化等问题，平均产量仅为460公斤\u002F公顷，而潜在产量可达1.5吨\u002F公顷。本研究考察了影响气候智慧型农业采纳的社会经济与制度性决定因素、激励因素及制约因素。研究以计划行为理论和技术接受模型为理论基础，采用描述性横断面设计。数据通过半结构化问卷收集，调查对象为通过分层随机抽样在马辛加分区五个选区选取的390名绿豆种植户。数据使用SPSS第29版进行描述性统计分析。结果显示，54.0%的受访者至少采纳了两项气候智慧型农业措施，其中抗旱种子品种（43.2%）和少耕\u002F免耕（42.4%）最为常见。二元逻辑回归模型拟合良好（McFadden伪R²=0.395；总体分类准确率=80.4%），并识别出显著的正向预测因素：获得投入品补贴（OR=2.33，p\u003C0.001）、感知到的政府政策支持（OR=2.37，p=0.002）、家庭年收入（OR=2.09，p=0.006）以及市场联结（OR=1.74，p=0.049）。高投入成本是主要显著障碍（OR=0.42，p=0.002）。主题分析证实，基础设施不足、资金障碍和认知差距是相互关联的障碍。本研究发现通过填补半干旱地区气候智慧型农业采纳研究中的空白，特别是针对绿豆等易旱作物，为学术文献提供了有价值的见解。此外，本研究发现为政策制定者提供了基于数据的建议，有助于设计和制定促进小农农业中气候智慧型农业采纳与可持续性的政策。农业推广服务机构和发展组织可利用这些发现设计有针对性的项目，以解决关键激励因素和制约因素。研究结论认为，收入水平和获得投入品补贴是气候智慧型农业采纳的主要驱动因素，而高投入成本构成首要结构性障碍，激励因素与制约因素各自作为相互关联、相互强化的系统发挥作用，而非孤立因素。","Journal of Experimental Agriculture International","2026-09-10T00:00:00Z",69,{"impact":20,"substance":18,"depth":333,"authority":20,"freshness":206,"relevant":21,"comment":512},"基于390户小农调查的实证研究，量化了补贴、政策支持与收入对气候智慧农业采纳的影响，数据扎实但属区域性案例，公共影响有限。",[514],{"name":508,"url":505},[26,516,27,28,517],"绿豆","技术采纳",{"code":38,"slug":39,"name":40,"path":41,"parent_code":35},[520],{"code":75,"slug":254,"name":255,"path":256,"parent_code":257},{"status":43,"locked":14,"version":44,"method":45,"evidence":522},{"candidates":523,"agricultural_evidence":50},[524,528,532,536,540,544],{"code":38,"score":19,"supported":50,"title":525,"abstract":526,"tags":527},[58],[27,58],[27],{"code":75,"score":13,"supported":50,"title":529,"abstract":530,"tags":531},[],[274,357,276],[28],{"code":31,"score":279,"supported":50,"title":533,"abstract":534,"tags":535},[],[29,52],[517],{"code":361,"score":108,"supported":50,"title":537,"abstract":538,"tags":539},[],[364,365],[],{"code":62,"score":69,"supported":50,"title":541,"abstract":542,"tags":543},[],[64],[],{"code":545,"score":21,"supported":14,"title":546,"abstract":547,"tags":548},"A5",[],[],[516],[550,551],"气候智慧农业 技术采纳 小农户 肯尼亚","气候智慧农业 技术采纳","气候智慧农业技术采纳小农户肯尼亚-2142","10.9734\u002Fjeai\u002F2026\u002Fv48i104499",{"doi":553,"openalex_id":555,"authors":556,"venue":508,"cited_by_count":97,"oa_url":505,"card":564,"direction":104,"ingested_from":105},"W7212140110",[557,559,561],{"name":558,"orcid":9},"Anna Ndunge Mutinda",{"name":560,"orcid":9},"Martin Kagiki Njogu",{"name":562,"orcid":563},"Pauline Micheni Kananu","https:\u002F\u002Forcid.org\u002F0000-0003-1795-345X",{"tldr":565,"method":566,"finding":567,"direction":102,"opportunity":568},"研究肯尼亚Masinga小农户绿豆种植采纳气候智慧农业的社会经济与制度决定因素。","对390户分层随机抽样问卷，用SPSS做描述统计与二元逻辑回归。","收入、投入补贴、政策支持与市场联系促进采纳，高投入成本是主要障碍。","可探索将补贴、市场与推广服务数字化联动，构建小农户CSA采纳决策支持系统。","2026-09-11T23:30:10.306285Z"]