[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4056":3,"related-4056":105},{"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":78,"slug":81,"view_count":82,"doi":83,"paper":84,"created_at":104},4056,"Adoption of Improved Pigeonpea (Cajanus cajan) Production Technologies in India-Status, Constraints and Opportunities: A Review","https:\u002F\u002Fdoi.org\u002F10.18805\u002Fijare.a-6600","Pigeonpea (Cajanus cajan L.) is a major pulse crop of India, contributing significantly to protein security and soil fertility in rainfed dryland systems. Despite the development of several improved production technologies, their adoption among smallholder farmers remains partial and uneven. A comprehensive literature search was conducted using Scopus, Web of Science, Google Scholar and Science Direct. Studies published between 2000 and 2024 and focusing on pigeonpea production technologies and technology adoption were considered. After screening for relevance, peer-reviewed articles, reports from ICAR, ICRISAT and FAO and government publications were synthesized in this narrative review. India accounts for approximately 70 per cent of global pigeonpea area and production, yet national average productivity remains below 900 kg\u002Fha - well short of the attainable yield potential. Adoption of improved varieties and recommended agronomic practices is hampered by non-availability of quality seeds, high pest and disease pressure, price fluctuations, labour shortages, climatic risks and inadequate extension outreach. Socio-economic factors - including education, farm size, institutional access and economic incentives - significantly determine adoption behaviour. Site-level evidence indicates that adoption of improved varieties can reach roughly 90 per cent of cropped area where active seed-multiplication support is present, against a considerably lower and uneven baseline elsewhere, while national productivity grew at only about -1.7 per cent per annum over 2016-17 to 2021-22, underscoring a yield gap driven more by uneven technology diffusion than by area constraints. Emerging opportunities include hybrid and climate-resilient varieties, digital advisory platforms, Farmer producer organizations (FPOs) and climate-smart agriculture practices that can collectively narrow yield gaps and improve farm income.","木豆（Cajanus cajan L.）是印度主要的豆类作物，在雨养旱地系统中对蛋白质安全和土壤肥力具有重要贡献。尽管已开发出多项改良生产技术，但小农户的采用仍然不充分且不均衡。本研究通过Scopus、Web of Science、Google Scholar和Science Direct进行了全面的文献检索，纳入2000年至2024年间发表的聚焦木豆生产技术及技术采用的研究。经相关性筛选后，本叙述性综述综合了同行评审论文、ICAR、ICRISAT和FAO的报告以及政府出版物。印度约占全球木豆种植面积和产量的70%，但全国平均生产力仍低于900 kg\u002Fha，远未达到可实现的产量潜力。改良品种和推荐农艺措施的采用受到优质种子不可获得、病虫害压力大、价格波动、劳动力短缺、气候风险及推广服务不足等因素的制约。社会经济因素——包括教育程度、农场规模、制度可及性和经济激励——显著决定采用行为。站点层面的证据表明，在具备活跃种子扩繁支持的地区，改良品种的采用率可达种植面积的约90%，而其他地区的基线则显著更低且不均衡；同时，2016-17年至2021-22年间全国生产力年增长率仅为约-1.7%，凸显出产量差距更多由技术扩散不均衡而非面积约束所驱动。新兴机遇包括杂交品种和气候韧性品种、数字咨询平台、农民生产者组织（FPOs）以及气候智慧型农业实践，这些可共同缩小产量差距并提高农场收入。",null,"Indian Journal of Agricultural Research","2026-10-02T00:00:00Z","论文",10,false,77,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,20,17,14,8,1,"系统综述印度木豆改良技术采纳现状与制约因素，数据翔实、结论可靠，对豆类产业与农技推广有参考价值，但属域外研究、时效性一般。",[25],{"name":10,"url":6},[27,28,29,30,31],"种业振兴","气候智慧农业","技术采纳","木豆","数字农技推广",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"needs_review","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":42,"reason":77},[39,48,55,62,67,72],{"code":40,"score":41,"supported":42,"title":43,"abstract":44,"tags":47},"G2",6,true,[],[45,46],"小农户","smallholder",[],{"code":49,"score":41,"supported":42,"title":50,"abstract":51,"tags":54},"H2",[],[52,53],"土壤","soil",[],{"code":56,"score":57,"supported":42,"title":58,"abstract":59,"tags":61},"I1",3,[],[60],"smart agriculture",[],{"code":63,"score":22,"supported":14,"title":64,"abstract":65,"tags":66},"F1",[],[],[27],{"code":68,"score":22,"supported":14,"title":69,"abstract":70,"tags":71},"G1",[],[],[29],{"code":73,"score":22,"supported":14,"title":74,"abstract":75,"tags":76},"H7",[],[],[28],"多个产业证据相当，需要确认主归属",[79,80],"印度 木豆 生产技术","ICRISAT 木豆 品种","印度木豆生产技术-4056",2,"10.18805\u002Fijare.a-6600",{"doi":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":95,"oa_url":6,"card":96,"direction":102,"ingested_from":103},"W7215702303",[87,89,91,93],{"name":88,"orcid":9},"Archana P.",{"name":90,"orcid":9},"Manjunath Nagabhushan",{"name":92,"orcid":9},"U. Bhojanna",{"name":94,"orcid":9},"B.A. Karpagam",0,{"tldr":97,"method":98,"finding":99,"direction":100,"opportunity":101},"综述印度木豆改良技术采用现状、制约因素与机遇，指出推广不均导致产量差距。","基于Scopus等数据库2000-2024年文献及ICAR、ICRISAT、FA","良种采用率在种子扩繁支持下可达90%，但全国单产不足900 kg\u002Fha且近年增长为负。","数字乡村与农业信息化","可研究数字咨询平台与FPO结合如何提升小农户木豆技术采用率并缩小产量差距。","智慧农业 \u002F 农业物联网","openalex","2026-10-03T23:30:09.709078Z",{"total":41,"page":22,"page_size":41,"items":106},[107,173,249,344,406,488],{"id":108,"title":109,"url":110,"summary":111,"summary_zh":9,"content":9,"source_name":112,"source_url":9,"published_at":113,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":114,"score_detail":115,"sources":120,"tags":122,"primary_topic":126,"secondary_topics":132,"classification":138,"search_phrases":159,"slug":162,"view_count":95,"doi":163,"paper":164,"created_at":172},5460,"数字农技推广对农户科学施肥技术采纳的影响及机制研究 (Research on the Impact and Mechanism of Digital Agricultural Technology Extension on Farmers' Adoption of Scientific Fertilization)","https:\u002F\u002Fdoi.org\u002F10.13872\u002Fj.1000-0275.2026.1666","基于2025年河南省707户种粮农户调查，有序Probit模型检验。每增加1种数字推广方式，不采纳概率降低9.4个百分点，采纳2类技术概率提高7.4个百分点，经工具变量与PSM支持。感知易用性中介占比更大。属网络首发。","农业现代化研究（网络首发）2026-10-20","2026-10-20T00:00:00Z",78,{"impact":116,"substance":117,"depth":19,"authority":118,"freshness":13,"relevant":22,"comment":119},16,22,13,"基于707户调查的实证研究，数据扎实、结论明确，对数字农技推广与绿色施肥有参考价值，但属细分领域论文，影响范围有限。",[121],{"name":112,"url":110},[123,29,124,31,125],"数字乡村","科学施肥","河南农户",{"code":127,"slug":128,"name":129,"path":130,"parent_code":131},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",[133],{"code":68,"slug":134,"name":135,"path":136,"parent_code":137},"extension-transfer","农技推广与成果转化","\u002Ftopic\u002Frural-services\u002Fextension-transfer","G",{"status":139,"locked":14,"version":35,"method":36,"evidence":140},"classified",{"candidates":141,"agricultural_evidence":42},[142,148,154],{"code":127,"score":19,"supported":42,"title":143,"abstract":146,"tags":147},[144,145],"施肥","fertilization",[],[124],{"code":68,"score":149,"supported":42,"title":150,"abstract":152,"tags":153},9,[151],"农技推广",[],[29],{"code":155,"score":22,"supported":14,"title":156,"abstract":157,"tags":158},"I6",[],[],[123],[160,161],"河南 种粮农户 数字农技推广","科学施肥 技术采纳 有序Probit","河南种粮农户数字农技推广-5460","10.13872\u002Fj.1000-0275.2026.1666",{"doi":163,"openalex_id":9,"authors":165,"venue":9,"cited_by_count":95,"oa_url":9,"card":166,"direction":100,"ingested_from":171},[],{"tldr":167,"method":168,"finding":169,"direction":100,"opportunity":170},"基于河南707户调查，检验数字农技推广对农户科学施肥技术采纳的影响。","2025年河南707户问卷，有序Probit模型，工具变量与PSM稳健性检验。","每增加一种数字推广方式，不采纳概率降9.4个百分点，采纳两类技术概率升7.4个百分点。","可延伸研究不同数字推广渠道组合的差异化效果，及感知易用性之外的中介机制。","agent","2026-10-21T00:10:08.151021Z",{"id":174,"title":175,"url":176,"summary":177,"summary_zh":178,"content":9,"source_name":179,"source_url":176,"published_at":180,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":181,"score_detail":182,"sources":184,"tags":186,"primary_topic":190,"secondary_topics":195,"classification":196,"search_phrases":222,"slug":225,"view_count":95,"doi":226,"paper":227,"created_at":248},4805,"How much climate-smart agriculture is enough? A dose-response analysis of technology adoption effects on farmer welfare in Ghana","https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pclm.0000886","Climate-smart agricultural technologies (CSAT) are promoted to enhance agricultural productivity and strengthen resilience to climate change. However, limited empirical evidence exists on the effects of adoption intensity, particularly when farmers adopt multiple technologies simultaneously. This study examines the effects of CSAT adoption intensity on maize yield and household asset accumulation in Ghana using survey data from 2,151 maize farmers. A dose–response model with Heckman selection is applied to address potential selection bias and estimate the causal effects of varying adoption levels. The findings show that farmers’ education, access to credit, extension services, and perceived drought significantly influence both the likelihood and intensity of CSAT adoption. Results reveal a U-shaped relationship between CSAT adoption intensity and maize yield, where yields initially decline but increase as adoption intensity rises. On average, higher CSAT adoption is associated with a 21% increase in maize yield. Similarly, CSAT intensity shows a nonlinear positive relationship with household asset accumulation, with an average 19.5% increase in assets. The results also indicate heterogeneous effects across farmers. Overall, higher CSAT adoption improves agricultural productivity and long-term household welfare, highlighting the need to strengthen extension services, expand credit access, and raise climate risk awareness to promote sustainable agricultural development.","气候智能型农业技术(CSAT)被推广用于提高农业生产力和增强对气候变化的适应能力。然而，关于采用强度的效应，尤其是当农民同时采用多项技术时，实证证据仍然有限。本研究利用来自加纳2151户玉米种植户的调查数据，考察了气候智能型农业技术采用强度对玉米产量和家庭资产积累的影响。研究采用带Heckman选择的剂量—反应模型来处理潜在的选择偏差，并估计不同采用水平的因果效应。研究结果表明，农民的受教育程度、信贷可得性、推广服务以及感知到的干旱显著影响其采用气候智能型农业技术的可能性和强度。结果揭示了气候智能型农业技术采用强度与玉米产量之间呈U型关系，即产量最初下降，但随着采用强度的提高而增加。平均而言，较高的气候智能型农业技术采用与玉米产量提高21%相关。同样，气候智能型农业技术采用强度与家庭资产积累呈非线性正相关关系，资产平均增加19.5%。结果还表明，不同农民之间存在异质性效应。总体而言，较高的气候智能型农业技术采用提高了农业生产力和长期家庭福利，凸显了加强推广服务、扩大信贷获取渠道和提高气候风险意识的必要性，以促进农业可持续发展。","PLOS Climate","2026-10-12T00:00:00Z",79,{"impact":116,"substance":117,"depth":17,"authority":20,"freshness":149,"relevant":22,"comment":183},"基于2151户加纳玉米农户的剂量反应分析，揭示气候智慧农业技术采纳强度与产量、资产的U型及非线性关系，方法扎实、数据规模可观，对技术推广强度决策有参考价值。",[185],{"name":179,"url":176},[28,187,29,188,189],"加纳","玉米产量","农户福利",{"code":73,"slug":191,"name":192,"path":193,"parent_code":194},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":139,"locked":14,"version":35,"method":36,"evidence":197},{"candidates":198,"agricultural_evidence":42},[199,207,211,218],{"code":73,"score":13,"supported":42,"title":200,"abstract":201,"tags":206},[],[202,203,204,205],"气候变化","干旱","climate change","drought",[28],{"code":56,"score":21,"supported":42,"title":208,"abstract":209,"tags":210},[60],[],[],{"code":212,"score":41,"supported":42,"title":213,"abstract":214,"tags":217},"A3",[],[215,216],"玉米","maize",[],{"code":68,"score":22,"supported":14,"title":219,"abstract":220,"tags":221},[],[],[29],[223,224],"加纳 气候智慧农业 玉米","气候智慧农业 农户福利 技术采纳 玉米产量","加纳气候智慧农业玉米-4805","10.1371\u002Fjournal.pclm.0000886",{"doi":226,"openalex_id":228,"authors":229,"venue":179,"cited_by_count":95,"oa_url":176,"card":242,"direction":102,"ingested_from":103},"W7221536273",[230,233,236,239],{"name":231,"orcid":232},"Stephen Prah","https:\u002F\u002Forcid.org\u002F0000-0002-0482-087X",{"name":234,"orcid":235},"John N. Ng’ombe","https:\u002F\u002Forcid.org\u002F0000-0002-1410-1350",{"name":237,"orcid":238},"Bright Owusu Asante","https:\u002F\u002Forcid.org\u002F0000-0002-5415-6110",{"name":240,"orcid":241},"Jonathan Masasi","https:\u002F\u002Forcid.org\u002F0009-0007-8855-783X",{"tldr":243,"method":244,"finding":245,"direction":246,"opportunity":247},"基于加纳2151户玉米农户，分析气候智慧型技术采纳强度对产量与家庭资产的影响。","剂量反应模型结合Heckman选择，处理采纳强度与选择偏差。","采纳强度与产量呈U型关系，高强度采纳使产量增21%、资产增19.5%。","农业人工智能与决策模型","可探究不同技术组合的剂量阈值与异质性，为精准推广策略提供依据。","2026-10-13T23:30:09.001081Z",{"id":250,"title":251,"url":252,"summary":253,"summary_zh":254,"content":9,"source_name":255,"source_url":252,"published_at":256,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":257,"score_detail":258,"sources":262,"tags":264,"primary_topic":9,"secondary_topics":267,"classification":268,"search_phrases":323,"slug":326,"view_count":22,"doi":327,"paper":328,"created_at":343},4662,"ADOPTION OF CLIMATE-SMART AGRICULTURE AND ITS EFFECT ON FOOD CROP PRODUCTION AND NUTRITION SECURITY: MICROECONOMIC-LEVEL EVIDENCE FROM FARMING HOUSEHOLDS IN SOUTHWEST NIGERIA","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23278557","ABSTRACT: The impacts of climate change on agricultural productivity and food nutrition security in Nigeria and especially for smallholder farming households is a major concern. This study investigates the adoption of Climate-Smart Agricultural (CSA) and their impact on food crop production and nutrition security in Southwest Nigeria. A multistage sampling technique was adopted and 180 farm households were randomly sampled from Ogun, Ekiti and Oyo states. Descriptive statistics and qualitative analysis were used to evaluate the CSA adoption pattern, food security status and barrier to CSA adoption. The findings indicated that there was high awareness about CSA practices (86.67%) with 74.44% of the respondents implementing at least one of the CSA technologies. Improved crop varieties (88.89%), irrigation\u002Fwater conservation (76.67%) and crop rotation (74.44%) were the most adopted practices. The outcomes of food and nutrition security were, however, highly vulnerable with 84.44% of the households expressing concern about food availability and 85.56% of households decreasing the size of their meals. Key factors identified as having an impact on adoption were access to finance (58.89%), extension support (52.78%) and access to inputs (43.89%). The poor extension services (83.89%) and high cost (77.78%) and lack of information (74.44%) were the major constraints. The results indicate that awareness of CSA is high, but that CSA adoption alone will not lead to better food and nutrition security unless accompanying efforts are made to tackle structural constraints. Policy recommendations include enhancing extension services, making credit more accessible, and encouraging farmer associations as a means of disseminating CSA. The study adds empirical evidence to support Nigeria's commitments to SDG 2 (Zero Hunger) and SDG 13 (Climate Action). Keywords: Climate change; Extremes; Food security; Southwest; Sustainable farming","摘要：气候变化对尼日利亚农业生产力和食品营养安全的影响，尤其是对小农农户的影响，是一个重大关切。本研究探讨了尼日利亚西南部气候智能型农业（Climate-Smart Agriculture, CSA）的采用情况及其对粮食作物生产和营养安全的影响。研究采用多阶段抽样技术，从奥贡州、埃基蒂州和奥约州随机抽取了180个农户。运用描述性统计和定性分析评估了CSA采用模式、粮食安全状况及CSA采用的障碍。研究结果表明，农户对CSA实践的认知度较高（86.67%），74.44%的受访者至少实施了一项CSA技术。改良作物品种（88.89%）、灌溉\u002F节水（76.67%）和轮作（74.44%）是采用最多的实践。然而，粮食和营养安全的结果高度脆弱，84.44%的农户对粮食可获得性表示担忧，85.56%的农户减少了餐食份量。影响采用的关键因素包括融资渠道（58.89%）、推广支持（52.78%）和农资获取（43.89%）。推广服务薄弱（83.89%）、成本高昂（77.78%）和信息缺乏（74.44%）是主要制约因素。结果表明，CSA认知度虽高，但仅靠采用CSA并不能带来更好的粮食和营养安全，除非同时采取措施解决结构性制约。政策建议包括加强推广服务、提高信贷可及性，以及鼓励农民协会作为传播CSA的途径。本研究为尼日利亚对可持续发展目标2（零饥饿）和可持续发展目标13（气候行动）的承诺提供了实证支持。关键词：气候变化；极端事件；粮食安全；西南部；可持续农业","Zenodo (CERN European Organization for Nuclear Research)","2026-10-10T00:00:00Z",72,{"impact":259,"substance":18,"depth":116,"authority":260,"freshness":149,"relevant":22,"comment":261},15,12,"基于180户农户微观调查的实证研究，数据扎实、结论明确，对气候智慧农业推广与粮食安全政策有参考价值，但属区域性研究，影响层级有限。",[263],{"name":255,"url":252},[265,45,28,29,266],"粮食安全","尼日利亚",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":269},{"candidates":270,"agricultural_evidence":42,"reason":77},[271,276,283,287,294,301,308,313,319],{"code":56,"score":272,"supported":42,"title":273,"abstract":274,"tags":275},11,[60],[60],[],{"code":277,"score":278,"supported":42,"title":279,"abstract":280,"tags":282},"A8",7,[],[265,281],"food security",[265],{"code":73,"score":278,"supported":42,"title":284,"abstract":285,"tags":286},[],[202,204],[28],{"code":288,"score":41,"supported":42,"title":289,"abstract":290,"tags":293},"A7",[],[291,292],"轮作","crop rotation",[],{"code":295,"score":41,"supported":42,"title":296,"abstract":297,"tags":300},"E2",[],[298,299],"食品营养","food nutrition",[],{"code":302,"score":41,"supported":42,"title":303,"abstract":304,"tags":307},"H3",[],[305,306],"灌溉","irrigation",[],{"code":40,"score":309,"supported":42,"title":310,"abstract":311,"tags":312},4,[],[46],[45],{"code":314,"score":57,"supported":42,"title":315,"abstract":316,"tags":318},"H8",[],[317],"可持续农业",[],{"code":68,"score":22,"supported":14,"title":320,"abstract":321,"tags":322},[],[],[29],[324,325],"尼日利亚 气候智慧农业 小农户","西南尼日利亚 粮食安全 技术采纳","尼日利亚气候智慧农业小农户-4662","10.5281\u002Fzenodo.23278557",{"doi":327,"openalex_id":329,"authors":330,"venue":255,"cited_by_count":95,"oa_url":252,"card":337,"direction":102,"ingested_from":103},"W7221360914",[331,333,335],{"name":332,"orcid":9},"Sulaimon, O.I., Sulaimon, O.I.",{"name":334,"orcid":9},"A. A. Awolola",{"name":336,"orcid":9},"Olabimisi, A. D. , Olabimisi, A. D.",{"tldr":338,"method":339,"finding":340,"direction":341,"opportunity":342},"研究尼日利亚西南部农户采用气候智慧型农业及其对粮食生产和营养安全的影响。","多阶段抽样调查180户农户，用描述性统计和定性分析评估采用模式与障碍。","CSA认知度高但营养安全仍脆弱，结构性约束（推广、资金、信息）限制其效果。","农业绿色发展与碳","可研究数字推广与信贷服务如何协同破解CSA采用的结构性障碍，提升营养安全。","2026-10-11T23:30:08.023132Z",{"id":345,"title":346,"url":347,"summary":348,"summary_zh":349,"content":9,"source_name":350,"source_url":347,"published_at":351,"category":12,"cover_url":9,"hotness":352,"is_selected":14,"score":353,"score_detail":354,"sources":356,"tags":360,"primary_topic":362,"secondary_topics":365,"classification":366,"search_phrases":390,"slug":393,"view_count":57,"doi":394,"paper":395,"created_at":405},3610,"Awareness, Adoption Intensity and Institutional Determinants of Climate-Smart Agricultural Practices among Crop Farmers in Ebonyi State, Nigeria","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22973610","Background: Ebonyi State's predominantly rain-fed crop production exposes farmers to rainfall variability and flooding, yet empirical evidence on climate-smart agriculture (CSA) within the State remains limited. Objective: This study assessed farmers' awareness of CSA practices, identified practices adopted, determined adoption intensity, examined associated socioeconomic and institutional factors, and identified major constraints to adoption. Method: A cross-sectional survey of 302 crop farmers across the Abakaliki, Onueke and Afikpo Agricultural Development Programme zones was conducted using a structured questionnaire; data were analysed with descriptive statistics and multinomial logistic regression. Results: Overall awareness was moderate (M = 2.19, SD = 0.91). Adoption was highest for irrigation (91.2%), organic manure (87.9%) and early planting (83.8%), and lowest for agroforestry (36.8%); 74.5% of farmers recorded high adoption intensity. Extent of use was highest for early planting (M = 3.20, SD = 0.77) and lowest for agroforestry (M = 1.84, SD = 0.95). High input cost (M = 2.67), lack of awareness (M = 2.66) and poor credit access (M = 2.59) were the leading constraints. The multinomial model was significant, χ²(28) = 101.15, p \u003C .001, Nagelkerke R² = .372; credit access was positively associated with high adoption intensity (OR = 9.56, p \u003C .001), while association membership was negatively associated (OR = 0.42, p = .035). Conclusion: Current approaches appear more successful at encouraging simpler, low-cost practices than at facilitating systemic integration of technically demanding ones, underscoring the need to address financial and informational constraints. Unique Contribution: The study contributes empirical evidence to SDG 2 (Zero Hunger) and SDG 13 (Climate Action), informs state-level adaptation planning and extension targeting, and integrates the Diffusion of Innovations with the Theory of Planned Behaviour in explaining adoption intensity in sub-Saharan Africa. Key Recommendation: Extension agencies should establish demonstration plots within existing farmer groups that bundle widely adopted practices with underutilised ones such as agroforestry, while policymakers link microfinance schemes to registered farmers' associations to reduce input costs and expand credit access.","背景：埃邦伊州以雨养作物生产为主，使农民面临降雨变率和洪涝风险，但该州范围内关于气候智慧型农业（CSA）的实证证据仍然有限。目的：本研究评估了农民对CSA措施的认知，识别了所采用的措施，确定了采用强度，考察了相关的社会经济和制度因素，并识别了采用的主要制约因素。方法：采用结构化问卷，对阿巴卡利基、奥努埃克和阿菲克波农业发展计划区的302名作物种植农民进行了横断面调查；数据采用描述性统计和多项逻辑回归进行分析。结果：总体认知处于中等水平（M = 2.19，SD = 0.91）。采用率最高的是灌溉（91.2%）、有机肥（87.9%）和早播（83.8%），最低的是农林业（36.8%）；74.5%的农民表现出高采用强度。使用程度最高的是早播（M = 3.20，SD = 0.77），最低的是农林业（M = 1.84，SD = 0.95）。高投入成本（M = 2.67）、缺乏认知（M = 2.66）和信贷获取困难（M = 2.59）是主要制约因素。多项逻辑模型显著，χ²(28) = 101.15，p \u003C .001，Nagelkerke R² = .372；信贷获取与高采用强度呈正相关（OR = 9.56，p \u003C .001），而协会成员身份呈负相关（OR = 0.42，p = .035）。结论：当前方法在鼓励较简单、低成本措施方面似乎比促进技术要求较高措施的系统性整合更为成功，凸显了解决金融和信息制约的必要性。独特贡献：本研究为可持续发展目标2（零饥饿）和可持续发展目标13（气候行动）提供了实证证据，为州级适应规划和推广定位提供参考，并将创新扩散理论与计划行为理论相结合，解释了撒哈拉以南非洲的采用强度。关键建议：推广机构应在现有农民群体中建立示范田，将广泛采用的措施与农林业等利用不足的措施捆绑推广；同时政策制定者应将小额信贷计划与注册农民协会对接，以降低投入成本并扩大信贷获取。","International Journal of Sub-Saharan African Research","2026-09-26T00:00:00Z",25,65,{"impact":21,"substance":18,"depth":116,"authority":260,"freshness":149,"relevant":22,"comment":355},"基于302户农户调查的实证研究，数据扎实、结论具体，对撒哈拉以南非洲气候智慧农业推广有参考价值，但地域性强、国内相关性有限。",[357,358],{"name":350,"url":347},{"name":350,"url":359},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22973609",[45,28,361,29,266],"农业推广",{"code":302,"slug":306,"name":363,"path":364,"parent_code":194},"水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",[],{"status":139,"locked":14,"version":35,"method":36,"evidence":367},{"candidates":368,"agricultural_evidence":42},[369,373,378,382,386],{"code":302,"score":41,"supported":42,"title":370,"abstract":371,"tags":372},[],[305,306],[],{"code":73,"score":309,"supported":42,"title":374,"abstract":375,"tags":377},[],[376],"洪涝",[28],{"code":56,"score":57,"supported":42,"title":379,"abstract":380,"tags":381},[],[60],[],{"code":68,"score":82,"supported":14,"title":383,"abstract":384,"tags":385},[],[],[361,29],{"code":40,"score":22,"supported":14,"title":387,"abstract":388,"tags":389},[],[],[45],[391,392],"气候智慧农业 农业推广 尼日利亚 技术采纳","气候智慧农业 农业推广","气候智慧农业农业推广尼日利亚技术采纳-3610","10.5281\u002Fzenodo.22973610",{"doi":394,"openalex_id":396,"authors":397,"venue":350,"cited_by_count":95,"oa_url":347,"card":400,"direction":102,"ingested_from":103},"W7214438042",[398],{"name":399,"orcid":9},"Ogodo, Monday Ogodo, Ugbo, Ejike Andrew, Elechi Joseph Ogbonnaya & Chidozie-Omi Mercy Kaosisochukwu",{"tldr":401,"method":402,"finding":403,"direction":100,"opportunity":404},"调查尼日利亚埃邦伊州农户对气候智慧农业的认知、采纳强度及制度影响因素。","302份问卷横断面调查，描述统计与多项逻辑回归分析。","灌溉、有机肥采纳率高，农林业最低；信贷可及性显著提升高采纳强度。","可探索将信贷与农户组织数字化联动，提升高成本气候智慧技术的系统集成采纳。","2026-09-27T23:30:13.956601Z",{"id":407,"title":408,"url":409,"summary":410,"summary_zh":411,"content":9,"source_name":412,"source_url":409,"published_at":413,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":414,"score_detail":415,"sources":417,"tags":419,"primary_topic":422,"secondary_topics":426,"classification":428,"search_phrases":466,"slug":469,"view_count":57,"doi":470,"paper":471,"created_at":487},3148,"Factors influencing the adoption of climate-smart agriculture practices among smallholder farmers in Melani and Msobomvu villages, Eastern Cape Province","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1869050","Climate-Smart Agriculture (CSA) is widely recognised as an effective approach for improving agricultural productivity, strengthening resilience to climate change, and enhancing food security among small-scale farmers. However, the adoption of CSA practices remains uneven in many rural communities, including Melani and Msobomvu villages in the Raymond Mhlaba Local Municipality, Eastern Cape Province, South Africa. This study investigated farmers’ awareness and understanding of climate-smart agriculture practices, identified the barriers limiting CSA adoption, and examined the socio-economic and institutional factors influencing adoption decisions. A descriptive research design within a quantitative research approach was employed. Data were collected from 158 randomly selected small-scale farmers using a structured questionnaire and analysed using descriptive statistics, including frequencies, percentages, means, and standard deviations. One-Way Analysis of Variance (ANOVA) was used to determine the significance of selected socio-economic and institutional factors influencing CSA adoption. The findings revealed that respondents generally possessed a good awareness and understanding of climate-smart agriculture practices, although awareness differed across technologies. Rainwater harvesting (80%), crop diversification (71%), conservation agriculture (68%), and soil conservation (68%) recorded the highest levels of awareness, whereas awareness was comparatively lower for drought-tolerant crop varieties (57%), climate information services (55%), and improved livestock management (49%). The study further identified farmer resistance to change, inadequate financial resources, and limited extension materials as the major barriers limiting CSA adoption. One-Way ANOVA indicated that financial constraints, market access, knowledge of climate-smart agriculture technologies, and extension support were statistically significant factors influencing adoption decisions ( p \u003C 0.05).","气候智慧型农业（Climate-Smart Agriculture, CSA）被广泛认为是提高农业生产率、增强气候变化适应能力以及改善小农户粮食安全的有效途径。然而，在许多农村社区，包括南非东开普省雷蒙德·姆拉巴地方自治市内的梅拉尼和姆索博姆武两个村庄，气候智慧型农业实践的采用仍然不均衡。本研究调查了农民对气候智慧型农业实践的认识和理解，识别了限制气候智慧型农业采用的障碍，并考察了影响采用决策的社会经济与制度因素。研究采用定量研究路径下的描述性研究设计，通过结构化问卷从158名随机选取的小农户中收集数据，并运用描述性统计方法（包括频数、百分比、均值和标准差）进行分析。采用单因素方差分析（One-Way ANOVA）确定所选社会经济与制度因素对气候智慧型农业采用影响的显著性。研究结果表明，受访者总体上对气候智慧型农业实践具有较好的认识和理解，但不同技术之间的认知水平存在差异。雨水收集（80%）、作物多样化（71%）、保护性农业（68%）和土壤保持（68%）的认知度最高，而耐旱作物品种（57%）、气候信息服务（55%）和改良牲畜管理（49%）的认知度相对较低。研究进一步识别出农民对变革的抵触、资金资源不足以及推广材料有限是限制气候智慧型农业采用的主要障碍。单因素方差分析表明，资金约束、市场准入、气候智慧型农业技术知识和推广支持是影响采用决策的统计显著因素（p \u003C 0.05）。","Frontiers in Sustainable Food Systems","2026-09-21T00:00:00Z",63,{"impact":21,"substance":17,"depth":259,"authority":118,"freshness":149,"relevant":22,"comment":416},"以南非东开普省两个村庄158户小农为样本，量化了气候智慧农业采纳的显著影响因素，方法规范、数据具体，但属区域案例研究，公共影响层级有限。",[418],{"name":412,"url":409},[45,28,29,420,421],"南非农业","推广服务",{"code":40,"slug":423,"name":424,"path":425,"parent_code":137},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",[427],{"code":73,"slug":191,"name":192,"path":193,"parent_code":194},{"status":139,"locked":14,"version":35,"method":36,"evidence":429},{"candidates":430,"agricultural_evidence":42},[431,435,439,443,447,451,457,462],{"code":40,"score":260,"supported":42,"title":432,"abstract":433,"tags":434},[46],[45],[45],{"code":56,"score":272,"supported":42,"title":436,"abstract":437,"tags":438},[60],[60],[],{"code":73,"score":13,"supported":42,"title":440,"abstract":441,"tags":442},[],[202,204,205],[28],{"code":277,"score":41,"supported":42,"title":444,"abstract":445,"tags":446},[],[265,281],[],{"code":49,"score":41,"supported":42,"title":448,"abstract":449,"tags":450},[],[52,53],[],{"code":452,"score":57,"supported":42,"title":453,"abstract":454,"tags":456},"C",[],[455],"livestock",[],{"code":314,"score":57,"supported":42,"title":458,"abstract":459,"tags":461},[],[460],"conservation agriculture",[],{"code":68,"score":22,"supported":14,"title":463,"abstract":464,"tags":465},[],[],[29],[467,468],"Eastern Cape 小农户 气候智慧农业","Raymond Mhlaba 农业技术采纳","EasternCape小农户气候智慧农业-3148","10.3389\u002Ffsufs.2026.1869050",{"doi":470,"openalex_id":472,"authors":473,"venue":412,"cited_by_count":95,"oa_url":409,"card":482,"direction":102,"ingested_from":103},"W7213921129",[474,476,479],{"name":475,"orcid":9},"Sibonise Lufume",{"name":477,"orcid":478},"L. Gwala","https:\u002F\u002Forcid.org\u002F0000-0002-0186-050X",{"name":480,"orcid":481},"Leocadia Zhou","https:\u002F\u002Forcid.org\u002F0000-0002-0344-4710",{"tldr":483,"method":484,"finding":485,"direction":100,"opportunity":486},"研究南非东开普省小农户对气候智慧型农业的认知、障碍及影响因素。","对158户小农问卷调查，用描述统计与单因素方差分析。","农户认知较高但采用不均，资金、市场、知识与推广支持显著影响采用。","可探索气候信息服务与推广数字化如何降低小农采用气候智慧型农业的障碍。","2026-09-22T23:30:08.462412Z",{"id":489,"title":490,"url":491,"summary":492,"summary_zh":493,"content":9,"source_name":494,"source_url":491,"published_at":495,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":496,"score_detail":497,"sources":499,"tags":501,"primary_topic":504,"secondary_topics":509,"classification":510,"search_phrases":547,"slug":550,"view_count":22,"doi":551,"paper":552,"created_at":574},2772,"Analysis of Climate‑Smart Agriculture (CSA) Adoption Level on Tidal Land and Its Effect on Household Food Security","https:\u002F\u002Fdoi.org\u002F10.22004\u002Fag.econ.410358","Climate change is a universal challenge for all those natural resource-based sectors, including agriculture. The farming community should adapt to climate change effects through Climate Smart Agriculture (CSA) approaches to resolve the same. The objectives of the study are to analyze the level of technology adoption of CSA practices that have been implemented by rice farmers on tidal land, to analyze the level of household food security of rice farmers on tidal land, and to analyze the effect of the level of technology adoption of CSA practices towards household food security in Telang Jaya Village, Muara Telang District, Banyuasin Regency. Sixty farmers are used for the respondents number. A study method with a survey approach of visiting the research site directly is employed here. The outcomes of this study indicate an increased awareness of climate change among farmers; one way is by adopting CSA, which can optimize farm productivity and increase farmer income, thus positively impacting food security. The adoption rate of CSA technology, i.e., tractors, water pumps, drainage, direct seeding planting, and combined harvesters, positively influences food security.","气候变化是所有以自然资源为基础的部门（包括农业）面临的普遍挑战。农业社区应通过气候智能型农业（CSA）方法来适应气候变化的影响，以解决这一问题。本研究的目标是分析潮汐地稻农已实施的气候智能型农业实践的技术采纳水平，分析潮汐地稻农的家庭粮食安全水平，并分析气候智能型农业实践的技术采纳水平对Banyuasin县Muara Telang区Telang Jaya村家庭粮食安全的影响。研究选取60名农民作为受访者。本研究采用直接前往研究地点进行调查的研究方法。研究结果表明，农民对气候变化的意识有所提高；其中一种方式就是采纳气候智能型农业，这可以优化农业生产率并增加农民收入，从而对粮食安全产生积极影响。气候智能型农业技术的采纳率，即拖拉机、水泵、排水、直播种植和联合收割机，对粮食安全产生正向影响。","AgEcon Search (University of Minnesota, USA)","2026-09-16T00:00:00Z",60,{"impact":21,"substance":116,"depth":20,"authority":118,"freshness":149,"relevant":22,"comment":498},"基于60户农户调研的CSA技术采纳与粮食安全实证研究，结论明确但样本小、地域性强，属细分领域学术进展，可作为主题页聚合素材。",[500],{"name":494,"url":491},[265,28,29,502,503],"水稻种植","盐沼地",{"code":277,"slug":505,"name":506,"path":507,"parent_code":508},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":139,"locked":14,"version":35,"method":36,"evidence":511},{"candidates":512,"agricultural_evidence":42},[513,517,521,525,531,537,543],{"code":277,"score":259,"supported":42,"title":514,"abstract":515,"tags":516},[281],[265,281],[265],{"code":56,"score":272,"supported":42,"title":518,"abstract":519,"tags":520},[60],[60],[],{"code":73,"score":278,"supported":42,"title":522,"abstract":523,"tags":524},[],[202,204],[28],{"code":526,"score":309,"supported":42,"title":527,"abstract":528,"tags":530},"A1",[],[529],"rice",[502],{"code":532,"score":57,"supported":42,"title":533,"abstract":534,"tags":536},"F5",[],[535],"收割机",[],{"code":538,"score":57,"supported":42,"title":539,"abstract":540,"tags":542},"I7",[],[541],"研究方法",[],{"code":68,"score":22,"supported":14,"title":544,"abstract":545,"tags":546},[],[],[29],[548,549],"气候智慧农业 技术采纳 水稻种植 粮食安全","气候智慧农业 技术采纳","气候智慧农业技术采纳水稻种植粮食安全-2772","10.22004\u002Fag.econ.410358",{"doi":551,"openalex_id":553,"authors":554,"venue":494,"cited_by_count":95,"oa_url":491,"card":569,"direction":102,"ingested_from":103},"W7213409702",[555,557,559,561,563,565,567],{"name":556,"orcid":9},"Yamin M.",{"name":558,"orcid":9},"Wahyu Swasdiningrum Putri Trisna",{"name":560,"orcid":9},"Dwi Saputri Salsabilah",{"name":562,"orcid":9},"Firdha Tafarini Meitry",{"name":564,"orcid":9},"Ayu Sulastri Merna",{"name":566,"orcid":9},"Damayanthy Dini",{"name":568,"orcid":9},"Ramadani Andelia Siti",{"tldr":570,"method":571,"finding":572,"direction":341,"opportunity":573},"分析潮汐地稻农采用气候智慧型农业技术的程度及其对家庭粮食安全的影响。","对60户稻农进行实地问卷调查，分析CSA技术采用水平与粮食安全的关系。","采用拖拉机、水泵、排水、直播和联合收割机等CSA技术能正向影响家庭粮食安全。","可探究不同CSA技术组合对粮食安全的差异化贡献，并引入遥感或物联网监测采用动态。","2026-09-17T23:30:13.841443Z"]