[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3538":3,"related-3538":56},{"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,"search_phrases":31,"slug":34,"view_count":35,"doi":36,"paper":37,"created_at":55},3538,"Rethinking ecological balance: An assessment of farmers' ecological knowledge and agrochemical use in the Sissala East Municipality, Ghana","https:\u002F\u002Fdoi.org\u002F10.1080\u002F27658511.2026.2736409","Agriculture in Sub-Saharan Africa is central to livelihoods, but agrochemical use poses environmental risks. This study examined the links between farmers' ecological knowledge, agrochemical use and farm management practices through a mixed-methods design involving 382 household surveys, 17 key informant interviews and 5 focus group discussions. Quantitatively, data were analysed using chi-square tests, while qualitative data were thematically analysed. The findings revealed that farmers understood the ecological risks of fertilisers, herbicides, insecticides and fungicides, with management decisions significantly shaped by farmers education, extension service access and farming experience (p ≤ 0.05). Despite farmers awareness of sustainable farming practices such as agroforestry, climate-smart agriculture and manure application, adoption remained low. The study concludes that while farmers possess adequate ecological knowledge, a gap exists between awareness and practice. The study recommends empowering farmers with training, skills and decision-making support to enhance adoption of sustainable agroecological farming systems and reduce dependence on synthetic inputs.","撒哈拉以南非洲的农业是生计的核心，但农用化学品的使用带来了环境风险。本研究通过混合方法设计，结合382份农户调查、17次关键知情人访谈和5次焦点小组讨论，考察了农民生态知识、农用化学品使用与农场管理实践之间的联系。定量数据采用卡方检验分析，定性数据则进行主题分析。研究发现，农民了解化肥、除草剂、杀虫剂和杀菌剂的生态风险，其管理决策显著受农民教育程度、推广服务获取和务农经验的影响（p ≤ 0.05）。尽管农民对农林业、气候智能型农业和施用粪肥等可持续农业实践有所认识，但采用率仍然较低。研究认为，虽然农民具备足够的生态知识，但认知与实践之间存在差距。研究建议通过培训、技能培养和决策支持赋能农民，以促进可持续农业生态耕作系统的采用，并减少对合成投入品的依赖。",null,"Sustainable Environment","2026-09-25T00:00:00Z","论文",10,false,64,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,20,16,12,1,"基于加纳382户调查的混合方法研究，揭示农户生态认知与绿色实践之间的知行落差，对农业绿色转型与推广服务有参考价值，但属区域案例、影响层级有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"农业技术推广","撒哈拉以南非洲","农药减量","生态农业","农户认知",[32,33],"加纳 Sissala East 农户 农药使用","农户生态知识 农药投入","加纳SissalaEast农户农药使用-3538",0,"10.1080\u002F27658511.2026.2736409",{"doi":36,"openalex_id":38,"authors":39,"venue":10,"cited_by_count":35,"oa_url":6,"card":47,"direction":53,"ingested_from":54},"W7214316034",[40,43,45],{"name":41,"orcid":42},"Godwin Kumpong Naazie","https:\u002F\u002Forcid.org\u002F0000-0002-4498-3673",{"name":44,"orcid":9},"John Bosco B. Sumani",{"name":46,"orcid":9},"Suleman Mula",{"tldr":48,"method":49,"finding":50,"direction":51,"opportunity":52},"研究加纳农户生态知识与农药使用的关系，发现认知高但可持续实践采用率低。","混合方法：382户问卷、17个关键访谈、5组焦点讨论，卡方检验与主题分析。","农户了解农药生态风险，但教育、推广服务和经验影响管理决策，知行差距显著。","农业绿色发展与碳","可探索数字推广工具如何弥合生态认知与可持续实践之间的知行差距。","智慧农业 \u002F 农业物联网","openalex","2026-09-26T23:30:09.775806Z",{"total":57,"page":21,"page_size":57,"items":58},6,[59,83,122,159,206,241],{"id":60,"title":61,"url":62,"summary":63,"summary_zh":9,"content":9,"source_name":64,"source_url":9,"published_at":65,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":66,"score_detail":67,"sources":73,"tags":75,"search_phrases":77,"slug":80,"view_count":13,"doi":81,"paper":9,"created_at":82},36,"撒哈拉以南非洲农业创新扩散仍偏重横向推广：基于系统综述的研究议程","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1891557\u002Fabstract","按PRISMA范围综述方法，从2,070项研究中筛选2016—2026年间的54项实证研究。结果显示86%研究集中在2016—2021年发布；地理分布以肯尼亚（28%）、埃塞俄比亚（12%）和多国SSA研究（16%）为主；方法偏量化，随机对照试验占47%、比较调查26%、面板数据16%；65%研究聚焦农资与增产技术，仅9%关注价值链或市场导向创新；70%研究将扩展框架为'横向扩散'。促进因素以信息\u002F推广\u002F社会网络（60%）和金融可及性（30%）为主，主要障碍为资金约束（23%）、可及性（21%）和知识缺口（16%）；仅不足15%研究显式考虑系统维度，提示需从扩散中心论转向系统导向整合方法。","Frontiers in Sustainable Food Systems · 2026-07-22 接收","2026-07-22T00:00:00Z",73,{"impact":68,"substance":69,"depth":68,"authority":70,"freshness":71,"relevant":21,"comment":72},18,22,13,2,"系统综述方法规范，数据详实，对非洲农业推广模式有深刻洞察，但时效性差且地域远离中国，影响有限。",[74],{"name":64,"url":62},[26,76,27],"系统综述",[78,79],"撒哈拉以南非洲 农业技术推广 系统综述","撒哈拉以南非洲 农业技术推广","撒哈拉以南非洲农业技术推广系统综述-36","10.3389\u002Ffsufs.2026.1891557\u002Fabstract","2026-07-28T03:05:27.127667Z",{"id":84,"title":85,"url":86,"summary":87,"summary_zh":9,"content":9,"source_name":88,"source_url":86,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":89,"score_detail":90,"sources":95,"tags":97,"search_phrases":102,"slug":105,"view_count":35,"doi":106,"paper":107,"created_at":121},3563,"Can information increase farmers’ willingness to pay for digital agricultural technologies? A survey experiment on agricultural drones in rural China","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jrurstud.2026.104423","Can information increase farmers’ willingness to pay for digital agricultural technologies? A survey experiment on agricultural drones in rural China。Journal of Rural Studies","Journal of Rural Studies",78,{"impact":19,"substance":91,"depth":68,"authority":92,"freshness":93,"relevant":21,"comment":94},21,14,9,"基于中国农村调查实验，实证信息干预对农户数字农业技术支付意愿的影响，方法规范、结论有政策参考价值，值得进入每日精选。",[96],{"name":88,"url":86},[98,99,26,100,101],"数字农业","智慧农业","农业无人机","农户支付意愿",[103,104],"农业无人机 农户 支付意愿","信息干预 调查实验","农业无人机农户支付意愿-3563","10.1016\u002Fj.jrurstud.2026.104423",{"doi":106,"openalex_id":108,"authors":109,"venue":88,"cited_by_count":35,"oa_url":9,"card":9,"direction":120,"ingested_from":54},"W7214363671",[110,112,115,118],{"name":111,"orcid":9},"Zhixian Lu",{"name":113,"orcid":114},"Huang Chen","https:\u002F\u002Forcid.org\u002F0000-0002-2284-8083",{"name":116,"orcid":117},"Yi-Xiang Wang","https:\u002F\u002Forcid.org\u002F0000-0001-5697-0717",{"name":119,"orcid":9},"Kaixing Huang","数字乡村与农业信息化","2026-09-26T23:30:38.738490Z",{"id":123,"title":124,"url":125,"summary":126,"summary_zh":127,"content":9,"source_name":128,"source_url":125,"published_at":129,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":130,"score_detail":131,"sources":133,"tags":135,"search_phrases":139,"slug":142,"view_count":35,"doi":143,"paper":144,"created_at":158},3512,"AI-Driven Agricultural Advisory and Diagnostic Systems for Smallholder Farming: Technical Architectures, Evidence and Deployment Priorities for North-East India","https:\u002F\u002Fdoi.org\u002F10.9734\u002Farja\u002F2026\u002Fv19i4919","Artificial intelligence (AI) is being introduced into agricultural advisory services through machine learning, computer vision, conversational large language models, retrieval-augmented generation and multimodal interfaces. For smallholder farming, the central question is not whether these technologies can produce technically plausible outputs, but whether they can provide locally correct, actionable and safe recommendations under heterogeneous agronomic, linguistic and connectivity conditions. This critical narrative review integrates evidence on digital extension, AI-enabled agricultural advice, image-based diagnosis and responsible digital agriculture, with particular reference to North-East India. Literature published from 1 January 2010 to 17 July 2026 was considered, with emphasis on peer-reviewed field evaluations, technical validation studies, reviews and regionally relevant research. Evidence from digital extension provides the strongest causal baseline: mobile and personalised advisory services frequently improve information recall, agronomic knowledge and adoption of recommended practices, yet effects on yield, profit and welfare are inconsistent. Recent generative-AI studies show that large language models can produce useful agricultural responses, but site-specific rates, timing and local practice remain recurrent failure points. Retrieval grounding and expert feedback improve local relevance, although multi-season farm-level effectiveness evidence remains scarce. Image-based plant-disease systems achieve high accuracy in curated datasets, but performance can deteriorate sharply under field domain shift, class novelty and variable image quality. North-East Indian studies of mobile advisory systems in Meghalaya, Nagaland and Tripura demonstrate a valuable institutional foundation based on interactive voice response, local expert networks and user-centred service design; they do not, however, establish the effectiveness of autonomous AI. The most defensible deployment model is therefore an offline-tolerant, multilingual, multimodal and human-supervised architecture that grounds recommendations in curated regional knowledge, represents uncertainty, preserves provenance and escalates high-risk or out-of-distribution cases. Future research should prioritise prospective district- and season-spanning evaluations that connect model quality to farmer decisions, agronomic outcomes, equity, safety and cost-effectiveness.","人工智能（AI）正通过机器学习、计算机视觉、对话式大语言模型、检索增强生成和多模态界面被引入农业咨询服务。对于小农户而言，核心问题不在于这些技术能否产生技术上看似合理的输出，而在于它们能否在异质的农艺、语言和网络连接条件下提供本地正确、可操作且安全的建议。本批判性叙事综述整合了数字推广、AI赋能的农业建议、基于图像的诊断和负责任数字农业方面的证据，并特别关注印度东北部。本文考察了2010年1月1日至2026年7月17日期间发表的文献，重点关注同行评议的田间评估、技术验证研究、综述及区域相关研究。来自数字推广的证据提供了最强的因果基线：移动化和个性化咨询服务经常改善信息记忆、农艺知识和对推荐措施的采纳，但对产量、利润和福利的影响并不一致。近期生成式AI研究表明，大语言模型能够产生有用的农业回答，但针对具体地点的用量、时机和本地实践仍是反复出现的失败点。检索 grounding 和专家反馈可提高本地相关性，但多季农场层面的有效性证据仍然稀缺。基于图像的植物病害系统在精选数据集上达到高准确率，但在田间域偏移、类别新颖性和图像质量多变的情况下，性能可能急剧下降。印度东北部在梅加拉亚邦、那加兰邦和特里普拉邦开展的移动咨询系统研究展示了基于交互式语音应答、本地专家网络和以用户为中心的服务设计的宝贵制度基础；然而，这些研究并未确立自主AI的有效性。因此，最可辩护的部署模式是一种容忍离线、多语言、多模态且有人工监督的架构，该架构将建议建立在精选的区域知识之上，表征不确定性，保留来源信息，并对高风险或分布外案例进行升级处理。未来研究应优先开展前瞻性的跨区县和跨季节评估，将模型质量与农户决策、农艺结果、公平性、安全性和成本效益联系起来。","Asian Research Journal of Agriculture","2026-09-24T00:00:00Z",80,{"impact":68,"substance":69,"depth":68,"authority":70,"freshness":93,"relevant":21,"comment":132},"系统综述AI农业咨询与诊断系统在印度东北小农场景的技术架构与落地证据，指出人机协同、离线多语言与检索增强是可行路径，对智慧农业落地有参考价值。",[134],{"name":128,"url":125},[136,99,137,26,138],"数字乡村","农业人工智能","小农户",[140,141],"印度东北部 农业AI 小农户","农业智能诊断 多语言 离线","印度东北部农业AI小农户-3512","10.9734\u002Farja\u002F2026\u002Fv19i4919",{"doi":143,"openalex_id":145,"authors":146,"venue":128,"cited_by_count":35,"oa_url":125,"card":152,"direction":120,"ingested_from":54},"W7214205238",[147,149],{"name":148,"orcid":9},"Pravangkar Boruah",{"name":150,"orcid":151},"Rubul Kumar Bania","https:\u002F\u002Forcid.org\u002F0000-0001-6294-0231",{"tldr":153,"method":154,"finding":155,"direction":156,"opportunity":157},"综述AI农业咨询与诊断系统，聚焦印度东北小农，提出人监督多模态部署架构。","批判性叙述综述，整合2010-2026年数字推广、生成式AI与图像诊断证据。","AI输出技术可行但本地化、安全与田间效果证据不足，需人监督与检索增强。","农业人工智能与决策模型","可开展跨区跨季前瞻评估，连接模型质量与农户决策、产量、公平及成本效益。","2026-09-25T23:30:39.745514Z",{"id":160,"title":161,"url":162,"summary":163,"summary_zh":164,"content":9,"source_name":165,"source_url":162,"published_at":129,"category":12,"cover_url":9,"hotness":166,"is_selected":14,"score":167,"score_detail":168,"sources":172,"tags":177,"search_phrases":180,"slug":183,"view_count":35,"doi":184,"paper":185,"created_at":205},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",25,87,{"impact":69,"substance":169,"depth":170,"authority":92,"freshness":93,"relevant":21,"comment":171},23,19,"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。",[173,174],{"name":165,"url":162},{"name":175,"url":176},"Apollo","https:\u002F\u002Fdoi.org\u002F10.17863\u002Fcam.134741",[99,137,26,178,179],"覆盖作物","气候智慧农业",[181,182],"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":184,"openalex_id":186,"authors":187,"venue":165,"cited_by_count":35,"oa_url":162,"card":200,"direction":53,"ingested_from":54},"W7214223143",[188,191,193,195,198],{"name":189,"orcid":190},"Callum Alexander","https:\u002F\u002Forcid.org\u002F0009-0007-5275-4583",{"name":192,"orcid":9},"Aiora Zabala",{"name":194,"orcid":9},"Andreas Kontoleon",{"name":196,"orcid":197},"Shalamar Armstrong","https:\u002F\u002Forcid.org\u002F0000-0002-1326-9936",{"name":199,"orcid":9},"Anuoluwa Sangotayo",{"tldr":201,"method":202,"finding":203,"direction":156,"opportunity":204},"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。","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":207,"title":208,"url":209,"summary":210,"summary_zh":211,"content":9,"source_name":212,"source_url":209,"published_at":213,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":214,"score_detail":215,"sources":218,"tags":220,"search_phrases":223,"slug":226,"view_count":35,"doi":227,"paper":228,"created_at":240},3273,"Determinants of the Use and Extent of Digital Agriculture Among Moroccan Farmers","https:\u002F\u002Fdoi.org\u002F10.22004\u002Fag.econ.412776","Digital agriculture, driven by advancements in financial engineering, holds significant potential to enhance productivity and sustainability in agricultural production. However, the adoption and extent of these technologies fundamentally depend on farmers’ willingness to accept and use them. While recent studies have identified key factors influencing the adoption of digital agriculture, to the best of our knowledge, no academic study has specifically examined the determinants of both the use and the extent of adoption, particularly within the Moroccan context. This study investigates both the adoption and intensity of digital agriculture among a sample of 250 Moroccan farmers, utilizing a paper-based survey and two econometric approaches: a multinomial logit model and the Heckman model. The findings reveal that farmer age has a negative and significant impact on digital agriculture adoption. At the same time, crop type and risk aversion emerge as significant positive determinants of both the adoption and the extent of smart farming use. Specifically, technology adoption is mainly influenced by age, crop type, and risk aversion, whereas the extent of use is primarily driven by risk aversion and the type of crops cultivated. These results highlight the importance of implementing targeted policies and training programs to promote broader and more intensive use of digital agriculture technologies. Additionally, these findings open up avenues for further research aimed at better understanding the underlying factors that shape Moroccan farmers' behavior toward digital agriculture adoption.","由金融工程进步所驱动的数字农业，在提升农业生产率与可持续性方面具有巨大潜力。然而，这些技术的采用及其程度从根本上取决于农民接受和使用它们的意愿。尽管近期研究已识别出影响数字农业采用的关键因素，但据我们所知，尚无学术研究专门考察使用与采用程度的决定因素，尤其是在摩洛哥背景下。本研究基于250名摩洛哥农民的样本，采用纸质问卷调查和两种计量经济学方法——多项Logit模型与Heckman模型——考察了数字农业的采用情况及使用强度。研究发现，农民年龄对数字农业采用具有显著负向影响。与此同时，作物类型与风险规避对智慧农业的采用及使用程度均呈现显著正向决定作用。具体而言，技术采用主要受年龄、作物类型和风险规避影响，而使用程度则主要由风险规避和所种植作物类型驱动。这些结果凸显了实施有针对性的政策与培训项目以促进数字农业技术更广泛、更深入应用的重要性。此外，这些发现为后续研究开辟了方向，有助于更深入理解塑造摩洛哥农民数字农业采用行为的潜在因素。","AgEcon Search (University of Minnesota, USA)","2026-09-21T00:00:00Z",72,{"impact":20,"substance":91,"depth":216,"authority":70,"freshness":93,"relevant":21,"comment":217},17,"基于250户摩洛哥农户调查，用多项Logit与Heckman模型揭示年龄、作物类型与风险规避对数字农业采纳及使用强度的差异化影响，方法规范、结论有新意，对发展中国家数字农业推广有借鉴价值。",[219],{"name":212,"url":209},[98,99,26,221,222],"农户采纳","摩洛哥农业",[224,225],"摩洛哥 农户 数字农业","Heckman 模型 智慧农业 采纳","摩洛哥农户数字农业-3273","10.22004\u002Fag.econ.412776",{"doi":227,"openalex_id":229,"authors":230,"venue":212,"cited_by_count":35,"oa_url":209,"card":235,"direction":53,"ingested_from":54},"W7213999238",[231,233],{"name":232,"orcid":9},"Adil Jouamaa Mohammed",{"name":234,"orcid":9},"I. Mubarak Abdulilah",{"tldr":236,"method":237,"finding":238,"direction":120,"opportunity":239},"研究摩洛哥250位农民采用数字农业及其使用程度的决定因素。","纸质问卷，多项Logit模型与Heckman模型。","年龄负向影响采用，作物类型和风险规避正向影响采用与使用程度。","可针对不同作物和风险偏好农民设计差异化推广策略，并开展跨区域比较研究。","2026-09-23T23:30:11.088448Z",{"id":242,"title":243,"url":244,"summary":245,"summary_zh":246,"content":9,"source_name":247,"source_url":244,"published_at":248,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":249,"score_detail":250,"sources":252,"tags":254,"search_phrases":258,"slug":261,"view_count":35,"doi":262,"paper":263,"created_at":282},3269,"Heterogeneous allocation of organic fertilizer under spatial constraints: evidence from Northern Ghana","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1938147","Organic fertilizer use is a key component of sustainable soil fertility management in smallholder systems though its adoption remains limited across sub-Saharan Africa. Although previous studies have primarily focused on household-level adoption, less attention has been paid as to how farmers allocate organic inputs across heterogeneous plots under resource constraints. This study addresses this research gap by examining the plot-level determinants of organic fertilizer use in a heterogeneous smallholder system in Northern Ghana. Using household survey data covering the 2023 and 2024 cropping seasons, the analysis explicitly distinguishes among three decision stages: plot-level organic fertilizer use, intra-farm allocation, and application intensity. Econometric models were used to evaluate the associations of plot accessibility, crop choice, soil characteristics, and regional conditions. The results indicated that the allocation of organic inputs was associated with plot characteristics and varied across plots. Maize plots were more likely to receive organic fertilizer, whereas plots perceived as fertile were less likely to do so. Longer travel time from the homestead to the plot was negatively associated with plot-level organic fertilizer use and with within-household allocation, indicating that less accessible plots were less likely to receive organic fertilizer, whereas the association with application intensity differed by input type. Importantly, allocation patterns differed by input type; that is, poultry manure was concentrated in nearby plots, whereas compost was applied more widely across space. These findings suggest that organic fertilizer use reflects a context-specific allocation strategy associated with spatial constraints and input characteristics. As such, this study provides a more nuanced understanding of smallholder decision-making by going beyond a mere binary focus on adoption. Instead of assuming uniform application, policy and extension efforts should emphasize targeted site-specific interventions that may enhance fertilizer effectiveness and promote sustainable soil fertility management.","有机肥使用是小农系统中可持续土壤肥力管理的关键组成部分，但在撒哈拉以南非洲地区，其采用率仍然有限。尽管以往研究主要关注农户层面的采用情况，但对资源约束下农户如何在异质性地块之间分配有机投入品的关注较少。本研究通过考察加纳北部异质性小农系统中农户层面有机肥使用的影响因素，填补了这一研究空白。利用涵盖2023年和2024年种植季的农户调查数据，分析明确区分了三个决策阶段：地块层面的有机肥使用、农场内分配以及施用强度。研究采用计量经济模型评估地块可达性、作物选择、土壤特征和区域条件之间的关联。结果表明，有机投入品的分配与地块特征相关，且在不同地块之间存在差异。玉米地块更有可能获得有机肥，而被认为肥沃的地块则较不可能获得有机肥。从宅基地到地块的通行时间越长，与地块层面有机肥使用和农户内部分配均呈负相关，表明可达性较差的地块较不可能获得有机肥，而施用强度与通行时间的关联则因投入品类型而异。重要的是，分配模式因投入品类型而不同，即家禽粪便集中在附近地块，而堆肥则在空间上施用更为广泛。这些发现表明，有机肥使用反映了一种与空间约束和投入品特征相关的、情境特定的分配策略。因此，本研究超越了对采用与否的简单二元关注，提供了对小农决策更为细致的理解。政策和推广工作不应假设均匀施用，而应强调有针对性的、因地制宜的干预措施，以提高肥料有效性并促进可持续土壤肥力管理。","Frontiers in Sustainable Food Systems","2026-09-22T00:00:00Z",68,{"impact":17,"substance":91,"depth":216,"authority":70,"freshness":93,"relevant":21,"comment":251},"基于加纳北部两年农户调查的论文，揭示有机肥在异质地块间的配置策略，方法扎实但属区域性研究，公共影响有限。",[253],{"name":247,"url":244},[255,27,138,256,257],"精准施肥","有机肥","土壤肥力",[259,260],"小农户 有机肥 地块配置","撒哈拉以南非洲 土壤肥力 精准施肥 小农户","小农户有机肥地块配置-3269","10.3389\u002Ffsufs.2026.1938147",{"doi":262,"openalex_id":264,"authors":265,"venue":247,"cited_by_count":35,"oa_url":244,"card":277,"direction":120,"ingested_from":54},"W7214037932",[266,269,271,274],{"name":267,"orcid":268},"Yoshie Yageta","https:\u002F\u002Forcid.org\u002F0000-0001-8756-149X",{"name":270,"orcid":9},"Guenwoo Lee",{"name":272,"orcid":273},"Joseph Agebase Awuni","https:\u002F\u002Forcid.org\u002F0000-0003-0940-9462",{"name":275,"orcid":276},"Satoshi Nakamura","https:\u002F\u002Forcid.org\u002F0000-0002-0952-5618",{"tldr":278,"method":279,"finding":280,"direction":120,"opportunity":281},"研究加纳北部小农户在空间约束下有机肥的地块级分配决策。","2023-2024农户调查数据，计量模型分析地块可达性、作物与土壤特征。","地块越远越少施有机肥，禽粪集中于近地，堆肥分布更广。","可结合地块空间数据与遥感，构建小农户有机肥精准配置决策支持模型。","2026-09-23T23:30:07.582998Z"]