[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3563":3,"related-3563":74},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"primary_topic":8,"secondary_topics":31,"classification":32,"search_phrases":51,"slug":54,"view_count":55,"doi":56,"paper":57,"created_at":73},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",null,"Journal of Rural Studies","2026-09-25T00:00:00Z","论文",10,false,78,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},16,21,18,14,9,1,"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。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字农业","智慧农业","农业技术推广","农业无人机","农户支付意愿",[],{"status":33,"locked":13,"version":34,"method":35,"evidence":36},"unclassified","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":49,"reason":50},[38,44],{"code":39,"score":40,"supported":13,"title":41,"abstract":42,"tags":43},"I1",2,[],[],[26,27],{"code":45,"score":21,"supported":13,"title":46,"abstract":47,"tags":48},"G1",[],[],[28],true,"缺少足够的主题证据",[52,53],"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",3,"10.1016\u002Fj.jrurstud.2026.104423",{"doi":56,"openalex_id":58,"authors":59,"venue":9,"cited_by_count":70,"oa_url":6,"card":8,"direction":71,"ingested_from":72},"W7214363671",[60,62,65,68],{"name":61,"orcid":8},"Zhixian Lu",{"name":63,"orcid":64},"Huang Chen","https:\u002F\u002Forcid.org\u002F0000-0002-2284-8083",{"name":66,"orcid":67},"Yi-Xiang Wang","https:\u002F\u002Forcid.org\u002F0000-0001-5697-0717",{"name":69,"orcid":8},"Kaixing Huang",0,"数字乡村与农业信息化","openalex","2026-09-26T23:30:38.738490Z",{"total":75,"page":21,"page_size":75,"items":76},6,[77,140,196,266,348,392],{"id":78,"title":79,"url":80,"summary":81,"summary_zh":82,"content":8,"source_name":83,"source_url":80,"published_at":84,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":85,"score_detail":86,"sources":91,"tags":93,"primary_topic":96,"secondary_topics":101,"classification":102,"search_phrases":121,"slug":124,"view_count":55,"doi":125,"paper":126,"created_at":139},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":87,"substance":17,"depth":88,"authority":89,"freshness":20,"relevant":21,"comment":90},12,17,13,"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。",[92],{"name":83,"url":80},[26,27,28,94,95],"农户采纳","摩洛哥农业",{"code":39,"slug":97,"name":98,"path":99,"parent_code":100},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":103,"locked":13,"version":34,"method":35,"evidence":104},"classified",{"candidates":105,"agricultural_evidence":49},[106,112,116],{"code":39,"score":107,"supported":49,"title":108,"abstract":110,"tags":111},19,[109],"digital agriculture",[27,26,109],[26,27],{"code":45,"score":21,"supported":13,"title":113,"abstract":114,"tags":115},[],[],[28],{"code":117,"score":21,"supported":13,"title":118,"abstract":119,"tags":120},"G2",[],[],[94],[122,123],"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":125,"openalex_id":127,"authors":128,"venue":83,"cited_by_count":70,"oa_url":80,"card":133,"direction":138,"ingested_from":72},"W7213999238",[129,131],{"name":130,"orcid":8},"Adil Jouamaa Mohammed",{"name":132,"orcid":8},"I. Mubarak Abdulilah",{"tldr":134,"method":135,"finding":136,"direction":71,"opportunity":137},"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。","智慧农业 \u002F 农业物联网","2026-09-23T23:30:11.088448Z",{"id":141,"title":142,"url":143,"summary":144,"summary_zh":8,"content":8,"source_name":145,"source_url":8,"published_at":146,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":147,"score_detail":148,"sources":151,"tags":153,"primary_topic":156,"secondary_topics":161,"classification":162,"search_phrases":182,"slug":185,"view_count":70,"doi":186,"paper":187,"created_at":195},5529,"数字农业技术采纳的驱动因素与障碍：基于复杂网络与演化博弈的分析","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1894648\u002Ffull","文章从演化博弈视角构建数字农业技术采纳的驱动与阻碍机制框架，系统梳理影响农户采纳数字农业技术的关键因素与障碍路径。研究强调通用大模型难以直接满足专业知识、结果依据与溯源能力要求，为政策设计提供了技术采纳侧的理论依据。","Frontiers in Sustainable Food Systems 2026-10-19","2026-10-19T00:00:00Z",67,{"impact":87,"substance":18,"depth":16,"authority":89,"freshness":149,"relevant":21,"comment":150},8,"从演化博弈视角分析农户采纳数字农业技术的驱动与障碍，方法有新意、结论有政策参考价值，但属理论性论文，影响范围限于细分领域。",[152],{"name":145,"url":143},[26,27,154,155],"技术采纳","农户行为",{"code":157,"slug":158,"name":159,"path":160,"parent_code":100},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[],{"status":103,"locked":13,"version":34,"method":35,"evidence":163},{"candidates":164,"agricultural_evidence":49},[165,169,174,178],{"code":39,"score":89,"supported":49,"title":166,"abstract":167,"tags":168},[26],[26],[26,27],{"code":157,"score":55,"supported":49,"title":170,"abstract":171,"tags":173},[],[172],"大模型",[],{"code":45,"score":21,"supported":13,"title":175,"abstract":176,"tags":177},[],[],[154],{"code":117,"score":21,"supported":13,"title":179,"abstract":180,"tags":181},[],[],[155],[183,184],"数字农业 技术采纳 演化博弈","农户行为 技术采纳 数字农业 智慧农业","数字农业技术采纳演化博弈-5529","10.3389\u002Ffsufs.2026.1894648\u002Ffull",{"doi":186,"openalex_id":8,"authors":188,"venue":8,"cited_by_count":70,"oa_url":8,"card":189,"direction":71,"ingested_from":194},[],{"tldr":190,"method":191,"finding":192,"direction":71,"opportunity":193},"构建演化博弈框架分析农户采纳数字农业技术的驱动因素与障碍路径。","演化博弈建模与复杂网络分析，梳理采纳影响因素。","通用大模型难以满足专业知识、结果依据与溯源要求，需政策引导。","可结合实证数据检验博弈模型，并探索面向溯源与专业知识的专用农业模型设计。","agent","2026-10-22T00:07:09.498742Z",{"id":197,"title":198,"url":199,"summary":200,"summary_zh":201,"content":8,"source_name":202,"source_url":199,"published_at":203,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":204,"score_detail":205,"sources":208,"tags":210,"primary_topic":214,"secondary_topics":220,"classification":221,"search_phrases":246,"slug":249,"view_count":70,"doi":250,"paper":251,"created_at":265},5477,"Smart Digital Coffee Value Chain Transformation: A Scientific Implementation Manual for Kata Muduga Multipurpose Farmers Cooperatives Union, Oromia, Ethiopia Authors: Kedir Nefo Biftu, Kebede Hail, and Tadila Tadessa Qajela","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23488198","Smart Digital Coffee Value Chain Transformation: A Scientific Implementation Manual for Kata Muduga Multipurpose Farmers Cooperatives Union, Oromia, EthiopiaAuthors: Kedir Nefo Biftu, Kebede Hail, and Tadila Tadessa Qajela Publication year: 2026 Publication type: Scientific technical manual and five-year strategic implementation guide DescriptionThis 30-page scientific implementation manual provides a practical, evidence-based framework for transforming the coffee value chain of Kata Muduga Multipurpose Farmers Cooperatives Union in Jimma Zone, Oromia, Ethiopia. The manual translates institutional assessment findings, scientific knowledge, digital-system requirements, and value-chain management principles into operational procedures suitable for cooperative organizations and other agricultural value-chain institutions. The manual draws on the Union's institutional questionnaire completed on 7 October 2026 and relevant scientific publications on international, African, and Ethiopian coffee production, processing, traceability, sustainability, and cooperative development. Its integrated methodological structure consists of 18 end-to-end coffee value-chain components, nine value-creation and conversion points, three institutional levels, and eight stages of the Big Win delivery methodology. The institutional baseline includes 28,164 members, 61,270 hectares of coffee-growing land, 49,287 productive hectares, an annual production of 315,337 quintals, 62 washing and collection facilities, 5,127 GPS-mapped farms, and reported direct-export experience. The manual evaluates these existing institutional capacities and identifies priority gaps in farmer-level digital identification, planting-material genealogy, production information, product traceability, processing utilization, quality testing, environmental compliance, market contracts, payment verification, and coordinated performance management. It establishes differentiated responsibilities for three institutional levels: Core value-chain actors: Farmers, primary cooperatives, cooperative unions, processors, exporters, and buyers responsible for biological production, collection, processing, commercial transactions, and payment. Supporting institutions: Research centers, agricultural extension services, financial institutions, quality laboratories, logistics providers, and digital technology organizations responsible for specialized technical and operational services. Policy and enabling institutions: The Oromia Cooperative Promotion Commission, agricultural and trade bureaus, regulatory organizations, and regional and national governments responsible for governance, standards, policy coordination, and enabling infrastructure. The manual specifies practical Business Requirements (BR), Functional Requirements (FR), data ownership, information exposing and consuming relationships, interoperable digital identification, transaction records, quality assurance, institutional accountability, and measurable performance indicators. Recent international and African experiences are incorporated to identify transferable best practices in cooperative modernization, agricultural digitalization, specialty-coffee differentiation, sustainable production, traceability, and circular value creation. The proposed five-year implementation roadmap applies the Big Win methodology through Direction, Mini-Lab, Open Day, Roadmap, KPI\u002FKRI Development, Implementation, Verification, and Annual Performance Reporting. Implementation priorities include reliable farmer and farm registration, verified production data, digital collection receipts, coffee-lot genealogy, quality-preserving processing, transparent market contracts, buyer acceptance, producer-payment reconciliation, and feedback-driven corrective actions. The principal contribution of this manual is a structured and adaptable implementation model for converting agricultural production potential into traceable products, conserved quality, added commercial value, accepted market transactions, and realized producer benefits. The manual is designed for practical application by farmers, cooperatives, cooperative unions, researchers, government organizations, development partners, technology developers, exporters, and investors in Ethiopia, Africa, and other coffee-producing regions. It serves as an operational companion to the scientific case study and provides guidance for institutional capacity development, digital-system implementation, monitoring, evaluation, and replication of verified best practices. The five-year roadmap and performance targets represent proposed interventions requiring stakeholder approval, practical implementation, and independent validation. KeywordsSmart Digital Coffee Value Chain; Kata Muduga; Scientific Implementation Manual; Coffee Cooperatives; Jimma; Oromia; Ethiopia; Digital Agriculture; Value Creation; Value Conservation; Value Addition; Biological Efficiency; Economic Efficiency; Business Requirements; Functional Requirements; Institutional Dependency; Big Win Methodology; CAPA; Coffee Sustainability.","智能数字咖啡价值链转型：埃塞俄比亚奥罗米亚州Kata Muduga多用途农民合作社联盟科学实施手册\n\n作者：Kedir Nefo Biftu、Kebede Hail 和 Tadila Tadessa Qajela\n出版年份：2026年\n出版类型：科学技术手册与五年战略实施指南\n\n描述\n\n这本30页的科学实施手册为埃塞俄比亚奥罗米亚州吉马地区的Kata Muduga多用途农民合作社联盟的咖啡价值链转型提供了一个实用的、基于证据的框架。该手册将机构评估结果、科学知识、数字系统要求和价值链管理原则转化为适用于合作社组织及其他农业价值链机构的操作程序。该手册依据该联盟于2026年10月7日完成的机构问卷，以及有关国际、非洲和埃塞俄比亚咖啡生产、加工、可追溯性、可持续性和合作社发展的相关科学出版物。其综合方法结构由18个端到端咖啡价值链组成部分、九个价值创造与转化点、三个机构层级以及“大赢”（Big Win）交付方法的八个阶段组成。机构基线包括28，164名成员、61，270公顷咖啡种植土地、49，287公顷生产性土地、年产量315，337公担、62个水洗和收集设施、5，127个经GPS测绘的农场，以及已报告的直接出口经验。该手册评估了这些现有机构能力，并识别出农民层面数字身份识别、种植材料谱系、生产信息、产品可追溯性、加工利用率、质量检测、环境合规、市场合同、付款验证和协调绩效管理等方面的优先差距。该手册为三个机构层级确立了差异化责任：核心价值链参与者：负责生物生产、收集、加工、商业交易和付款的农民、初级合作社、合作社联盟、加工商、出口商和买家。支持性机构：负责专业技术和运营服务的研究中心、农业推广服务机构、金融机构、质量实验室、物流服务提供商和数字技术组织。政策与赋能机构：奥罗","Zenodo (CERN European Organization for Nuclear Research)","2026-10-20T00:00:00Z",79,{"impact":18,"substance":206,"depth":18,"authority":87,"freshness":20,"relevant":21,"comment":207},22,"该手册面向埃塞俄比亚咖啡合作社，提供数字化价值链实施框架，数据详实、方法结构清晰，对农业信息化有参考价值，但属区域性案例，影响范围有限。",[209],{"name":202,"url":199},[26,27,211,212,213],"咖啡产业链","农业合作社","产品溯源",{"code":215,"slug":216,"name":217,"path":218,"parent_code":219},"B3","tea-coffee","茶叶与咖啡","\u002Ftopic\u002Fhorticulture\u002Ftea-coffee","B",[],{"status":103,"locked":13,"version":34,"method":35,"evidence":222},{"candidates":223,"agricultural_evidence":49},[224,230,236,241],{"code":215,"score":19,"supported":49,"title":225,"abstract":227,"tags":229},[226],"coffee",[228,226],"咖啡",[],{"code":45,"score":75,"supported":49,"title":231,"abstract":232,"tags":235},[],[233,234],"农业推广","agricultural extension",[],{"code":39,"score":237,"supported":49,"title":238,"abstract":239,"tags":240},5,[],[109],[26,27],{"code":117,"score":55,"supported":49,"title":242,"abstract":243,"tags":245},[],[244],"农民合作社",[],[247,248],"Kata Muduga 咖啡 合作社","埃塞俄比亚 咖啡 数字价值链","KataMuduga咖啡合作社-5477","10.5281\u002Fzenodo.23488198",{"doi":250,"openalex_id":252,"authors":253,"venue":202,"cited_by_count":70,"oa_url":199,"card":260,"direction":138,"ingested_from":72},"W7223028195",[254,256,258],{"name":255,"orcid":8},"Kedir Biftu",{"name":257,"orcid":8},"Kebede Hailu",{"name":259,"orcid":8},"Tadila Tadessa Qajela",{"tldr":261,"method":262,"finding":263,"direction":71,"opportunity":264},"为埃塞俄比亚咖啡合作社联盟制定数字化价值链转型的科学实施手册。","基于机构问卷与文献，构建18个价值链环节、三级机构与八阶段交付方法。","识别出农户数字身份、溯源、质检与支付核验等优先数字化缺口。","可研究小农户合作社场景下低成本溯源与数字身份落地的效果评估。","2026-10-21T23:30:08.879737Z",{"id":267,"title":268,"url":269,"summary":270,"summary_zh":271,"content":8,"source_name":202,"source_url":269,"published_at":203,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":272,"score_detail":273,"sources":276,"tags":278,"primary_topic":282,"secondary_topics":288,"classification":289,"search_phrases":330,"slug":333,"view_count":70,"doi":334,"paper":335,"created_at":347},5476,"Digital Transformation of Haryana Agriculture: Strengthening Climate Resilience and Advancing the Sustainable Development Goals","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23491288","Climate change has surfaced as one of the most pivotal challenges confronting the agricultural sector, especially in agrarian regions vulnerable to resource degradation, water scarcity, and climate uncertainties. Haryana, a leading agricultural state in India, has faced significant environmental pressures in recent years, including declining groundwater levels, erratic rainfall patterns, rising temperatures, and soil degradation, necessitating the adoption of climate-resilient agricultural strategies. Against this backdrop, Information and Communication Technology has gained considerable importance as a transformative mechanism for strengthening agricultural sustainability, adaptive capacity, and informed decision-making among farmers. ICT-enabled interventions such as mobile-based advisory services, precision farming technologies, digital marketplaces, weather forecasting systems, remote sensing, and various e-governance platforms have increasingly contributed to improving agricultural efficiency and resilience. The present study aims to evaluate the role of ICT-enabled agricultural practices in Haryana and their contribution to climate resilience and to achieve the Sustainable Development Goals. This study applies a descriptive and analytical approach, drawing on secondary data and narrative review methodology. The study utilizes secondary data from government reports, policy documents, research articles, institutional publications, and international development reports on digital agriculture, climate change, and sustainable development, published between 2016 and 2026. The findings indicate that ICT-based agricultural innovations have substantially enhanced access to climate information, improved resource-use efficiency, increased market connectivity, and enabled adaptive agricultural management practices. Furthermore, ICT interventions have significant potential to support SDG 2: Zero Hunger, SDG 9: Industry, Innovation and Infrastructure, and SDG 13: Climate Action. However, challenges such as digital illiteracy, infrastructural disparities, limited technological accessibility among smallholders, and inadequate institutional support continue to hinder widespread adoption. The study emphasizes the need for inclusive digital policies, strengthened rural ICT infrastructure, farmer-centric skill development, and integrated climate-smart agricultural frameworks to facilitate sustainable, resilient agricultural development in Haryana.","气候变化已成为农业部门面临的最关键挑战之一，在易受资源退化、水资源短缺和气候不确定性影响的农业区域尤为如此。哈里亚纳邦是印度领先的农业邦，近年来面临显著的环境压力，包括地下水位下降、降雨模式不稳定、气温上升和土壤退化，因而亟需采取气候韧性农业策略。在此背景下，信息与通信技术（ICT）作为增强农业可持续性、适应能力以及农民知情决策的变革性机制，其重要性日益凸显。基于ICT的干预措施，如移动端咨询服务、精准农业技术、数字市场、天气预报系统、遥感以及各类电子治理平台，已日益为提升农业效率和韧性作出贡献。本研究旨在评估哈里亚纳邦基于ICT的农业实践所发挥的作用及其对气候韧性和实现可持续发展目标的贡献。本研究采用描述性与分析性方法，依托二手数据和叙述性综述方法。研究使用的二手数据来源于2016年至2026年间发布的政府报告、政策文件、研究论文、机构出版物以及关于数字农业、气候变化和可持续发展的国际发展报告。研究结果表明，基于ICT的农业创新大幅提升了气候信息的获取能力，改善了资源利用效率，增强了市场连通性，并促成了适应性农业管理实践。此外，ICT干预措施在支持可持续发展目标2：零饥饿、目标9：产业、创新和基础设施以及目标13：气候行动方面具有显著潜力。然而，数字文盲、基础设施差距、小农户技术可及性有限以及机构支持不足等挑战仍阻碍其广泛采用。研究强调，需要制定包容性数字政策、加强农村ICT基础设施、开展以农民为中心的技能培养以及构建综合气候智慧型农业框架，以促进哈里亚纳邦可持续且具有韧性的农业发展。",70,{"impact":16,"substance":18,"depth":274,"authority":87,"freshness":20,"relevant":21,"comment":275},15,"基于二手数据的综述性研究，系统梳理印度哈里亚纳邦ICT农业与气候韧性、SDGs的关系，结论可靠但方法新颖性一般，对国内智慧农业与气候适应有参考价值。",[277],{"name":202,"url":269},[26,27,279,280,281],"可持续发展","气候韧性","农业ICT",{"code":283,"slug":284,"name":285,"path":286,"parent_code":287},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":103,"locked":13,"version":34,"method":35,"evidence":290},{"candidates":291,"agricultural_evidence":49},[292,299,305,312,319,324],{"code":283,"score":18,"supported":49,"title":293,"abstract":295,"tags":298},[294],"climate resilience",[296,297,294],"气候变化","climate change",[280],{"code":39,"score":300,"supported":49,"title":301,"abstract":302,"tags":304},11,[],[303,26,109],"精准农业",[26,27],{"code":306,"score":75,"supported":49,"title":307,"abstract":308,"tags":311},"H2",[],[309,310],"土壤","soil",[],{"code":313,"score":75,"supported":49,"title":314,"abstract":315,"tags":318},"I3",[],[316,317],"遥感","remote sensing",[],{"code":117,"score":55,"supported":49,"title":320,"abstract":321,"tags":323},[],[322],"小农户",[],{"code":325,"score":55,"supported":49,"title":326,"abstract":327,"tags":329},"H3",[],[328],"水资源",[],[331,332],"Haryana 数字化转型","ICT 气候韧性","Haryana数字化转型-5476","10.5281\u002Fzenodo.23491288",{"doi":334,"openalex_id":336,"authors":337,"venue":202,"cited_by_count":70,"oa_url":269,"card":342,"direction":138,"ingested_from":72},"W7223011965",[338,340],{"name":339,"orcid":8},"Himani Rathi",{"name":341,"orcid":8},"Pardeep Kumar Duhan",{"tldr":343,"method":344,"finding":345,"direction":71,"opportunity":346},"评估印度哈里亚纳邦ICT农业实践对气候韧性与可持续发展目标的贡献。","描述性与分析性方法，基于2016-2026年政府报告等二手数据与叙事综述。","ICT显著提升气候信息获取、资源效率与市场连接，助力SDG 2\u002F9\u002F13，但数字素养与基础设施不足制","可研究小农户数字素养与ICT采纳门槛的实证机制，及包容性数字政策在气候智慧农业中的落地路径。","2026-10-21T23:30:08.814085Z",{"id":349,"title":350,"url":351,"summary":352,"summary_zh":8,"content":8,"source_name":353,"source_url":351,"published_at":146,"category":11,"cover_url":8,"hotness":354,"is_selected":13,"score":355,"score_detail":356,"sources":358,"tags":362,"primary_topic":365,"secondary_topics":366,"classification":367,"search_phrases":374,"slug":377,"view_count":70,"doi":378,"paper":379,"created_at":391},5396,"Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.","https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.22601.71520","Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.。OpenAlex","OpenAlex",25,37,{"impact":149,"substance":75,"depth":149,"authority":75,"freshness":20,"relevant":21,"comment":357},"中非数字农业系统综述，主题相关但摘要信息极少，仅题录级元数据，增量与权威性有限，不建议进入每日精选。",[359,360],{"name":353,"url":351},{"name":353,"url":361},"https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.16146.41922",[26,27,363,364],"农业信息化","中非",{"code":39,"slug":97,"name":98,"path":99,"parent_code":100},[],{"status":103,"locked":13,"version":34,"method":35,"evidence":368},{"candidates":369,"agricultural_evidence":49},[370],{"code":39,"score":19,"supported":49,"title":371,"abstract":372,"tags":373},[109],[109],[363,26,27],[375,376],"中非 数字农业","农业信息化 数字农业 智慧农业 中非","中非数字农业-5396","10.13140\u002Frg.2.2.22601.71520",{"doi":378,"openalex_id":380,"authors":381,"venue":8,"cited_by_count":70,"oa_url":351,"card":8,"direction":71,"ingested_from":72},"W7222930115",[382,384,386,389],{"name":383,"orcid":8},"Anani Ogou",{"name":385,"orcid":8},"Henry Chotangui",{"name":387,"orcid":388},"Honoré Beyegue-Djonko","https:\u002F\u002Forcid.org\u002F0009-0004-6447-5889",{"name":390,"orcid":8},"Christopher Mubeteneh Tankou","2026-10-20T23:30:22.542913Z",{"id":393,"title":394,"url":395,"summary":396,"summary_zh":8,"content":8,"source_name":397,"source_url":8,"published_at":398,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":399,"score_detail":400,"sources":402,"tags":404,"primary_topic":408,"secondary_topics":413,"classification":415,"search_phrases":436,"slug":439,"view_count":21,"doi":8,"paper":440,"created_at":447},5304,"Front. Sustain. Food Syst.:数字农业技术推广与贵州辣椒种植户极端气候适应技术采纳","https:\u002F\u002Fscienmag.com\u002Fdigital-agricultural-extension-linked-to-climate-adaptation-among-chili-farmers-in-mountainous-china","Gao H, Han H (2026) 在Frontiers in Sustainable Food Systems发表论文,以贵州辣椒种植户为研究对象,发现数字农业技术推广(DATP)对极端气候适应技术采纳呈显著正相关,通过更广泛信息渠道、信息信任和应用能力发挥作用,益处与风险预期确认起调节作用;数字信息素养较高种植户DATP效应更强(系数0.326、0.408 vs. 低素养0.084、0.133),规模化种植户效应同样更强。","Frontiers in Sustainable Food Systems(2026,Article 1914305)","2026-10-13T00:00:00Z",74,{"impact":16,"substance":17,"depth":18,"authority":89,"freshness":75,"relevant":21,"comment":401},"基于贵州辣椒种植户实证数据，揭示数字农业推广对气候适应技术采纳的调节机制，结论具体且具政策参考价值，值得入选。",[403],{"name":397,"url":395},[26,27,405,406,407],"数字素养","气候适应","辣椒种植",{"code":409,"slug":410,"name":411,"path":412,"parent_code":219},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables",[414],{"code":283,"slug":284,"name":285,"path":286,"parent_code":287},{"status":103,"locked":13,"version":34,"method":35,"evidence":416},{"candidates":417,"agricultural_evidence":49},[418,422,426,431],{"code":39,"score":89,"supported":49,"title":419,"abstract":420,"tags":421},[26],[26],[26,27],{"code":283,"score":87,"supported":49,"title":423,"abstract":424,"tags":425},[406],[406],[406],{"code":409,"score":300,"supported":49,"title":427,"abstract":429,"tags":430},[428],"辣椒",[428],[],{"code":432,"score":21,"supported":13,"title":433,"abstract":434,"tags":435},"I6",[],[],[405],[437,438],"贵州 辣椒种植户 数字农业技术推广","极端气候适应 技术采纳 数字素养","贵州辣椒种植户数字农业技术推广-5304",{"doi":8,"openalex_id":8,"authors":441,"venue":8,"cited_by_count":70,"oa_url":8,"card":442,"direction":71,"ingested_from":194},[],{"tldr":443,"method":444,"finding":445,"direction":71,"opportunity":446},"研究数字农业技术推广对贵州辣椒种植户采纳极端气候适应技术的影响。","基于贵州辣椒种植户调查数据，采用回归分析检验中介与调节效应。","数字农业技术推广显著促进适应技术采纳，信息渠道、信任与应用能力起中介作用，数字素养和规模起调节作用。","可探究数字推广服务对不同作物、不同气候区农户适应行为的差异化机制与长期效果。","2026-10-19T00:07:48.767992Z"]