[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2651":3,"related-2651":92},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":67,"slug":70,"view_count":21,"doi":71,"paper":72,"created_at":91},2651,"Development and Web-Based Visualization of a Domain-Specific Semantic Model for Coffee Culture and Production Processes","https:\u002F\u002Fdoi.org\u002F10.34248\u002Fbsengineering.1991498","The global agricultural supply chain is a complex network with different data silos, complicated cultivation parameters and highly subjective sensory evaluation metrics. Formal knowledge representation is a must, if real semantic interoperability is to be achieved across this multidimensional domain. This work consists of the rigorous design, implementation and quantitative evaluation of the “Coffee Culture and Production Processes Ontology” and a custom client-side web-application named the “Coffee Ontology Explorer”. The semantic model, developed with standard ontology design principles and the Web Ontology Language (OWL), captures the entire coffee lifecycle from botanical taxonomy and harvesting methods to specific roasting profiles and subjective brewing evaluations. Meanwhile, the React.js based ontology explorer tackles the ongoing limitations of traditional, heavy-client ontology visualization tools by utilizing a browser-native document parsing application programming interface for high efficiency, serverless ontology parsing. The quantitative estimation of the developed semantic model gives a 0.297 relation richness indicator, which confirms a highly interconnected and structurally complex knowledge graph, and not a simple taxonomic flat. Moreover, the performance profiling of the web application shows less than one second for parsing and less than 200 milliseconds for rendering complex graphical data even for large ontological hierarchies. This technical framework is a highly scalable, multilingual semantic infrastructure that is uniquely suited for integration into larger industrial traceability systems and provides a fundamental template for computer scientists, agritech developers, and agricultural stakeholders who want to exploit semantic web technologies for precision agriculture.","全球农业供应链是一个复杂的网络，包含不同的数据孤岛、复杂的种植参数以及高度主观的感官评价指标。若要实现这一多维领域真正的语义互操作，形式化知识表示必不可少。本研究包括“咖啡文化与生产过程本体”（Coffee Culture and Production Processes Ontology）的严格设计、实现与定量评估，以及一个名为“咖啡本体浏览器”（Coffee Ontology Explorer）的定制客户端网页应用。该语义模型依据标准本体设计原则并使用Web本体语言（OWL）开发，涵盖从植物分类学和采收方法到特定烘焙曲线及主观冲泡评价的整个咖啡生命周期。与此同时，基于React.js的本体浏览器利用浏览器原生文档解析应用程序编程接口实现高效的无服务器本体解析，从而解决了传统重型客户端本体可视化工具的持续局限。对所开发语义模型的定量评估给出了0.297的关系丰富度指标，这证实了一个高度互联且结构复杂的知识图谱，而非简单的分类扁平结构。此外，该网页应用的性能分析表明，即使面对大型本体层级结构，解析时间也不到一秒，复杂图形数据的渲染时间不到200毫秒。该技术框架是一个高度可扩展的多语言语义基础设施，特别适合集成到更大的工业追溯系统中，并为希望利用语义网技术实现精准农业的计算机科学家、农业科技开发者和农业利益相关者提供了一个基础模板。",null,"Black Sea Journal of Engineering and Science","2026-09-14T00:00:00Z","论文",10,false,69,{"impact":17,"substance":18,"depth":19,"authority":17,"freshness":20,"relevant":21,"comment":22},12,20,17,8,1,"咖啡全生命周期本体与浏览器端可视化工具，方法新颖、性能数据扎实，为农业语义互操作与溯源提供可复用模板，但属细分作物领域，产业影响有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","本体建模","咖啡产业","农业知识图谱","语义互操作",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"B3","tea-coffee","茶叶与咖啡","\u002Ftopic\u002Fhorticulture\u002Ftea-coffee","B",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,52,60],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":51},15,true,[48],"coffee",[50,48],"咖啡",[28],{"code":53,"score":54,"supported":46,"title":55,"abstract":56,"tags":59},"I1",7,[],[57,58],"精准农业","precision agriculture",[26],{"code":61,"score":62,"supported":46,"title":63,"abstract":64,"tags":66},"J3",3,[],[65],"全球农业",[],[68,69],"农业知识图谱 语义互操作 咖啡产业 智慧农业","农业知识图谱 语义互操作","农业知识图谱语义互操作咖啡产业智慧农业-2651","10.34248\u002Fbsengineering.1991498",{"doi":71,"openalex_id":73,"authors":74,"venue":10,"cited_by_count":81,"oa_url":82,"card":83,"direction":89,"ingested_from":90},"W7213004624",[75,78],{"name":76,"orcid":77},"Ömer Doğan","https:\u002F\u002Forcid.org\u002F0000-0003-4815-8619",{"name":79,"orcid":80},"Alpay Doruk","https:\u002F\u002Forcid.org\u002F0000-0002-6190-288X",0,"https:\u002F\u002Fdergipark.org.tr\u002Fen\u002Fdownload\u002Farticle-file\u002F6208007",{"tldr":84,"method":85,"finding":86,"direction":87,"opportunity":88},"构建咖啡文化与生产过程的OWL本体，并开发浏览器端可视化工具。","用OWL本体建模咖啡全生命周期，React.js实现无服务器本体解析与可视化。","本体关系丰富度0.297，解析\u003C1秒、渲染\u003C200毫秒，可扩展至溯源系统。","数字乡村与农业信息化","可借鉴该语义本体框架，为其他农产品构建轻量级浏览器端知识图谱与溯源集成方案。","智慧农业 \u002F 农业物联网","openalex","2026-09-16T23:30:15.075138Z",{"total":93,"page":21,"page_size":93,"items":94},6,[95,140,229,287,345,392],{"id":96,"title":97,"url":98,"summary":99,"summary_zh":9,"content":9,"source_name":100,"source_url":9,"published_at":101,"category":102,"cover_url":9,"hotness":13,"is_selected":14,"score":103,"score_detail":104,"sources":111,"tags":113,"primary_topic":117,"secondary_topics":118,"classification":119,"search_phrases":135,"slug":138,"view_count":62,"doi":9,"paper":9,"created_at":139},2879,"中国咖啡的品质根基与创新驱动论坛在昆明举办:云南省农科院聚焦全产业链标准体系","https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20260918A07YT800","9月17日,2026中国热带作物产业大会分论坛在昆明举行,来自中国标准化研究院、云南省农业科学院等单位的80余名代表参会。论坛以标准筑基科技赋能为主线,中国农业大学副教授李想作AI助力种好咖啡报告,介绍AI农技大脑一田一策精准决策、AI撮合平台、田间移动服务站、智慧农场ERP等农事服务新模式,提出AI-农业服务人员-农民服务路径。","中国新闻网\u002F腾讯新闻","2026-09-18T00:00:00Z","报道",68,{"impact":105,"substance":106,"depth":107,"authority":108,"freshness":109,"relevant":21,"comment":110},18,16,14,11,9,"省级科研机构主导的咖啡全产业链标准与AI农技服务论坛，行业细分进展有实质信息，但影响层级限于产业与省级范围。",[112],{"name":100,"url":98},[26,114,28,115,116],"农业人工智能","热带作物","农业标准体系",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":120},{"candidates":121,"agricultural_evidence":46},[122,126,130],{"code":32,"score":17,"supported":46,"title":123,"abstract":124,"tags":125},[50],[50],[28],{"code":53,"score":21,"supported":14,"title":127,"abstract":128,"tags":129},[],[],[26],{"code":131,"score":21,"supported":14,"title":132,"abstract":133,"tags":134},"I2",[],[],[114],[136,137],"云南省农科院 咖啡 标准体系","AI农技大脑 咖啡","云南省农科院咖啡标准体系-2879","2026-09-19T00:06:04.718237Z",{"id":141,"title":142,"url":143,"summary":144,"summary_zh":145,"content":9,"source_name":146,"source_url":143,"published_at":147,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":148,"score_detail":149,"sources":151,"tags":153,"primary_topic":157,"secondary_topics":158,"classification":165,"search_phrases":207,"slug":210,"view_count":211,"doi":212,"paper":213,"created_at":228},2308,"Coffee phytobiome dynamics: integrating multitrophic interactions and plant physiology for climate-resilient production","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffmicb.2026.1951767","Coffee ( Coffea arabica L. and Coffea canephora Pierre ex A. Froehner) is a globally important perennial plantation crop that sustains the livelihoods of millions of smallholder farmers while making substantial contributions to agricultural economies worldwide global agricultural economies. Nevertheless, sustainable coffee production is increasingly constrained by climate change, declining soil fertility, emerging pests and diseases and the environmental costs associated with intensive use of synthetic agrochemicals. Recent advances in plant microbiome research have transformed the understanding of coffee from an individual organism to a holobiont, where the host plant and its associated microorganisms operate as an integrated biological system. The coffee phytobiome encompasses diverse microbial communities inhabiting the rhizosphere, rhizoplane, endosphere, phyllosphere, anthosphere, carposphere and spermosphere, together with complex multitrophic interactions involving shade trees, soil fauna, insects and the surrounding environment. These interactions collectively regulate nutrient acquisition, carbon assimilation, water-use efficiency, hormonal balance, stress tolerance, immune responses and overall plant productivity. This review critically examines current advances in multitrophic plant–microbe interactions that influence physiological adaptation in coffee, with particular emphasis on sustainable production under Indian agroecological conditions. It highlights the functional functions of plant growth-promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AMF), endophytic microorganisms and other beneficial microbes in enhancing root development, nutrient cycling, and resilience to biotic and abiotic stresses. Furthermore, the review evaluates recent progress in metagenomics, metatranscriptomics, metabolomics and microbiome engineering for harnessing indigenous microbial resources. Finally, it outlines future research priorities integrating plant physiology, microbial ecology, systems biology, and precision agriculture to develop climate-resilient, resource-efficient, and environmentally sustainable coffee production systems.","咖啡（Coffea arabica L. 和 Coffea canephora Pierre ex A. Froehner）是全球重要的多年生种植作物，维系着数百万小农户的生计，同时为全球农业经济作出重大贡献。然而，可持续咖啡生产日益受到气候变化、土壤肥力下降、新发病虫害以及集约化使用合成农用化学品所带来的环境成本的制约。近年来植物微生物组研究的进展已将人们对咖啡的认知从单一生物体转变为全息生物（holobiont），即宿主植物与其相关微生物作为一个整合的生物系统协同运作。咖啡植物微生物组（phytobiome）涵盖栖息于根际、根表、内生圈、叶际、花际、果际和种际的多样化微生物群落，以及涉及遮荫树、土壤动物、昆虫和周围环境的复杂多营养级相互作用。这些相互作用共同调控养分获取、碳同化、水分利用效率、激素平衡、胁迫耐受性、免疫应答和整体植物生产力。本文综述批判性地审视了影响咖啡生理适应的多营养级植物–微生物相互作用的最新进展，特别关注印度农业生态条件下的可持续生产。文章重点阐述了植物促生根际细菌（PGPR）和丛枝菌根真菌（AMF）、内生微生物及其他有益微生物在促进根系发育、养分循环以及增强生物和非生物胁迫韧性方面的功能。此外，本文评估了宏基因组学、宏转录组学、代谢组学和微生物组工程在利用本土微生物资源方面的最新进展。最后，文章展望了未来研究重点，即整合植物生理学、微生物生态学、系统生物学和精准农业，以开发气候韧性、资源高效和环境可持续的咖啡生产系统。","Frontiers in Microbiology","2026-09-10T00:00:00Z",77,{"impact":105,"substance":18,"depth":19,"authority":107,"freshness":20,"relevant":21,"comment":150},"系统综述咖啡植物微生物组与多营养级互作，为气候韧性生产提供微生物组工程与组学新思路，专业性强但属细分作物领域，产业影响中等。",[152],{"name":146,"url":143},[26,154,155,28,156],"气候韧性","土壤健康","植物微生物组",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[159],{"code":160,"slug":161,"name":162,"path":163,"parent_code":164},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"status":39,"locked":14,"version":40,"method":41,"evidence":166},{"candidates":167,"agricultural_evidence":46},[168,172,179,186,190,197,203],{"code":32,"score":45,"supported":46,"title":169,"abstract":170,"tags":171},[48],[50,48],[28],{"code":160,"score":13,"supported":46,"title":173,"abstract":174,"tags":178},[],[175,176,161,177],"土壤","根际","rhizosphere",[155],{"code":180,"score":54,"supported":46,"title":181,"abstract":182,"tags":185},"H7",[],[183,184],"气候变化","climate change",[154],{"code":53,"score":54,"supported":46,"title":187,"abstract":188,"tags":189},[],[57,58],[26],{"code":191,"score":93,"supported":46,"title":192,"abstract":193,"tags":196},"G2",[],[194,195],"小农户","smallholder",[],{"code":198,"score":62,"supported":46,"title":199,"abstract":200,"tags":202},"H6",[],[201],"农业生态",[],{"code":61,"score":62,"supported":46,"title":204,"abstract":205,"tags":206},[],[65],[],[208,209],"植物微生物组 咖啡产业 土壤健康 智慧农业","植物微生物组 咖啡产业","植物微生物组咖啡产业土壤健康智慧农业-2308",2,"10.3389\u002Ffmicb.2026.1951767",{"doi":212,"openalex_id":214,"authors":215,"venue":146,"cited_by_count":81,"oa_url":221,"card":222,"direction":89,"ingested_from":90},"W7212145113",[216,219],{"name":217,"orcid":218},"Somashekhargouda Patil","https:\u002F\u002Forcid.org\u002F0000-0002-0362-0745",{"name":220,"orcid":9},"C. S. Rudragouda","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fmicrobiology\u002Farticles\u002F10.3389\u002Ffmicb.2026.1951767\u002Fpdf",{"tldr":223,"method":224,"finding":225,"direction":226,"opportunity":227},"综述咖啡植物微生物组与多营养级互作，提出整合植物生理与微生物组提升气候韧性生产。","综述微生物组学、多组学与微生物组工程，聚焦印度咖啡农生态。","咖啡作为全生物体，其根际、内生等微生物组通过多营养级互作调控养分、抗逆与生产力。","农业绿色发展与碳","可探索咖啡全生物体多组学数据整合与微生物组工程，构建气候韧性精准调控模型。","2026-09-13T23:30:11.231069Z",{"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":247,"secondary_topics":248,"classification":249,"search_phrases":267,"slug":270,"view_count":81,"doi":271,"paper":272,"created_at":286},5479,"Comparative Scientific Evaluation of Five Coffee Cooperative Organizations in Oromia, Ethiopia: Digital Traceability, Value Conversion, Institutional Dependencies and Five-Year Transformation Strategies","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23504407","Comparative Scientific Evaluation of Five Coffee Cooperative Organizations in Oromia, Ethiopia: Digital Traceability, Value Conversion, Institutional Dependencies and Five-Year Transformation Strategies Authors: Kedir Nefo Biftu, Kebede Hail, and Tadila Tadessa QajelaPublication year: 2026Publication type: Comparative scientific research article \u002F Preprint Description This scientific article presents a comparative evaluation of five coffee cooperative organizations in Oromia, Ethiopia: Chercher Oda Bultum Farmers Cooperative Union, Homa Multipurpose Farmers Cooperative, Kata Muduga Multipurpose Farmers Cooperative Union, Torban Anfillo Multipurpose Farmers Cooperative Union, and Sadetan Chora Farmers Cooperative Union. The research investigates variability in biological production, institutional organization, processing efficiency, digital traceability, product quality, market participation and financial value realization. The study uses institutional questionnaires, cooperative administrative records and previously developed case assessments, supported by recent international, African and Ethiopian scientific literature. Its integrated analytical framework comprises 18 end-to-end value-chain components, nine value-creation and conversion gates, three institutional levels and the eight-stage Big Win methodology. The comparative results demonstrate significant differences in organizational scale, coffee-growing ecology, farmer registration, geospatial mapping, production measurement, processing infrastructure, quality assurance, certification, export-market participation, financial settlement and digital readiness. The findings also identify common weaknesses in upstream traceability, data consistency, coffee-lot genealogy, processing mass balance, producer-level quality differentiation and verifiable links between commercial transactions and farmer payments. The scientific discussion examines how biological productivity, environmental sustainability, quality conservation, processing efficiency, value addition, buyer acceptance, and realized commercial value depend on reliable institutional coordination and information exchange. The analysis draws on recent research concerning digitalization and sustainability (Hidalgo et al., 2023), Ethiopian coffee traceability and buyer trust (Mbakop et al., 2023), digital traceability capabilities (Tadesse et al., 2024), geographical-origin compliance (Urugo et al., 2025), Ethiopian coffee-quality differentiation (Worku, Astatkie, and Boeckx, 2023), and sustainability performance in southwestern Oromia (Botola, Werke, and Birbirsa, 2026). International institutional frameworks from the International Coffee Organization, UNIDO, FAO, GS1, and ISO inform the proposed approaches to value-chain resilience, circular resource management, digital interoperability, and product traceability. The article proposes an integrated Smart Digital Coffee Value Chain architecture linking market intelligence, genetic resources, nursery development, producer and plot identity, extension services, production, harvesting, aggregation, processing, quality assurance, storage, certification, market contracts, buyer acceptance, financial settlement and feedback. A five-year scientific transformation proposal identifies differentiated improvement priorities for each organization, together with harmonized Business Requirements (BR), Functional Requirements (FR), institutional data dependencies, Key Performance Indicators (KPIs), Key Risk Indicators (KRIs) and corrective and preventive actions. The principal scientific contribution is a comparative framework demonstrating how cooperative organizations with different ecological, institutional, and commercial characteristics can implement a common, interoperable digital value-chain system while following locally appropriate transformation pathways. The study contributes to scientific understanding of cooperative value-chain performance, digital agriculture, institutional coordination, biological and economic efficiency, environmental sustainability and commercial value realization. The findings are based principally on documentary and organizational evidence. Reported performance indicators are distinguished from calculated measures and proposed interventions. Differences in reporting periods, measurement units and data completeness limit direct statistical comparability, while the proposed five-year improvements require implementation and independent evaluation. Keywords Smart Digital Coffee Value Chain; Comparative Scientific Evaluation; Oromia; Ethiopia; Coffee Cooperative Unions; Chercher Oda Bultum; Homa Cooperative; Kata Muduga; Torban Anfillo; Sadetan Chora; Digital Traceability; Value Creation; Value Conservation; Value Addition; Biological Efficiency; Economic Efficiency; Institutional Dependency; Big Win Methodology; Sustainable Coffee Production.","埃塞俄比亚奥罗米亚地区五家咖啡合作社组织的比较科学评估：数字可追溯性、价值转化、制度依赖与五年转型战略\n\n作者：Kedir Nefo Biftu、Kebede Hail、Tadila Tadessa Qajela\n\n出版年份：2026年\n\n出版类型：比较科学研究论文\u002F预印本\n\n描述\n\n本科学论文对埃塞俄比亚奥罗米亚地区五家咖啡合作社组织进行了比较评估：Chercher Oda Bultum农民合作社联盟、Homa多用途农民合作社、Kata Muduga多用途农民合作社联盟、Torban Anfillo多用途农民合作社联盟和Sadetan Chora农民合作社联盟。该研究考察了生物生产、制度组织、加工效率、数字可追溯性、产品质量、市场参与和财务价值实现方面的变异性。研究采用机构问卷、合作社行政记录和先前开发的案例评估，并以近期国际、非洲和埃塞俄比亚科学文献为支撑。其综合分析框架由18个端到端价值链组成部分、九个价值创造与转化关口、三个制度层面和八阶段“大赢”方法组成。比较结果揭示了在组织规模、咖啡种植生态、农民登记、地理空间测绘、生产计量、加工基础设施、质量保证、认证、出口市场参与、财务结算和数字准备度方面存在显著差异。研究结果还识别了上游可追溯性、数据一致性、咖啡批次谱系、加工物料平衡、生产者层面质量分级以及商业交易与农民付款之间可验证联系方面的共同弱点。科学讨论审视了生物生产力、环境可持续性、质量保持、加工效率、价值增值、买方接受度和已实现商业价值如何依赖于可靠的制度协调和信息交换。分析借鉴了近期关于数字化与可持续性（Hidalgo等，2023）、埃塞俄比亚咖啡可追溯性与买方信任（Mbakop等，2023）、数字可追溯能力（Tadesse等，2024）、地理原产地合规（Urugo等，2025）、埃塞俄比亚咖啡质量分级（Worku","Zenodo (CERN European Organization for Nuclear Research)","2026-10-20T00:00:00Z",59,{"impact":20,"substance":105,"depth":45,"authority":109,"freshness":109,"relevant":21,"comment":239},"该研究以埃塞俄比亚咖啡合作社为对象，提出数字价值链框架，方法有一定新意，但属区域性案例研究，对国内三农信息化仅有间接参考价值。",[241],{"name":235,"url":232},[243,244,245,246,28],"数字农业","价值链","合作社","数字溯源",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":250},{"candidates":251,"agricultural_evidence":46},[252,256,262],{"code":32,"score":45,"supported":46,"title":253,"abstract":254,"tags":255},[48],[50,48],[28],{"code":191,"score":257,"supported":46,"title":258,"abstract":259,"tags":261},4,[],[260],"农民合作社",[245],{"code":53,"score":257,"supported":46,"title":263,"abstract":264,"tags":266},[],[265],"digital agriculture",[243],[268,269],"埃塞俄比亚 咖啡合作社 数字溯源","咖啡产业 数字农业 数字溯源 价值链","埃塞俄比亚咖啡合作社数字溯源-5479","10.5281\u002Fzenodo.23504407",{"doi":271,"openalex_id":273,"authors":274,"venue":235,"cited_by_count":81,"oa_url":232,"card":281,"direction":89,"ingested_from":90},"W7223041235",[275,277,279],{"name":276,"orcid":9},"Kedir Biftu",{"name":278,"orcid":9},"Kebede Hailu",{"name":280,"orcid":9},"Tadila Tadessa Qajela",{"tldr":282,"method":283,"finding":284,"direction":87,"opportunity":285},"比较埃塞俄比亚奥罗米亚五个咖啡合作社的数字化追溯与价值转化差异。","机构问卷、合作社行政记录与案例评估，构建18环节价值链分析框架。","各社在组织规模、数字追溯与支付可验证性差异显著，上游追溯普遍薄弱。","可研究小农户合作社低成本数字追溯与批次谱系方案，打通交易与农户付款的可验证链路。","2026-10-21T23:30:09.167175Z",{"id":288,"title":289,"url":290,"summary":291,"summary_zh":292,"content":9,"source_name":235,"source_url":290,"published_at":236,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":293,"score_detail":294,"sources":297,"tags":299,"primary_topic":303,"secondary_topics":304,"classification":305,"search_phrases":328,"slug":331,"view_count":81,"doi":332,"paper":333,"created_at":344},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",79,{"impact":105,"substance":295,"depth":105,"authority":17,"freshness":109,"relevant":21,"comment":296},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。",[298],{"name":235,"url":290},[243,26,300,301,302],"咖啡产业链","农业合作社","产品溯源",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":306},{"candidates":307,"agricultural_evidence":46},[308,312,319,324],{"code":32,"score":107,"supported":46,"title":309,"abstract":310,"tags":311},[48],[50,48],[],{"code":313,"score":93,"supported":46,"title":314,"abstract":315,"tags":318},"G1",[],[316,317],"农业推广","agricultural extension",[],{"code":53,"score":320,"supported":46,"title":321,"abstract":322,"tags":323},5,[],[265],[243,26],{"code":191,"score":62,"supported":46,"title":325,"abstract":326,"tags":327},[],[260],[],[329,330],"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":332,"openalex_id":334,"authors":335,"venue":235,"cited_by_count":81,"oa_url":290,"card":339,"direction":89,"ingested_from":90},"W7223028195",[336,337,338],{"name":276,"orcid":9},{"name":278,"orcid":9},{"name":280,"orcid":9},{"tldr":340,"method":341,"finding":342,"direction":87,"opportunity":343},"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":346,"title":347,"url":348,"summary":349,"summary_zh":350,"content":9,"source_name":235,"source_url":348,"published_at":351,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":352,"sources":354,"tags":356,"primary_topic":358,"secondary_topics":359,"classification":360,"search_phrases":375,"slug":378,"view_count":81,"doi":379,"paper":380,"created_at":391},5377,"Title: Smart Digital Guji Cooperative Coffee Value Chain Transformation: Scientific Evaluation, Value Conversion, Digital Traceability and Five-Year Strategic Implementation Framework in Oromia, Ethiopia","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23481514","Title: Smart Digital Guji Cooperative Coffee Value Chain Transformation: Scientific Evaluation, Value Conversion, Digital Traceability, and Five-Year Strategic Implementation Framework in Oromia, Ethiopia Author: Kedir Nefo Biftu, Kebede Hailu, Tadila Tadessa Qajela DescriptionThis scientific paper presents an evidence-based evaluation and five-year strategic transformation framework for Homa Multipurpose Farmers Cooperative in Abaya Woreda, West Guji Zone, Oromia, Ethiopia. The study investigates how smallholder coffee production, cooperative aggregation, processing, quality assurance, international marketing, and financial transactions can be integrated into a smart digital coffee value chain that improves traceability, value conservation, economic efficiency, and producer benefits. The research integrates a structured cooperative questionnaire, a farmer-level administrative registry containing 2,000 records, and a comprehensive Business and Functional Requirements Specification (BFRS). The analytical framework comprises 18 end-to-end coffee value-chain components, nine points of value creation (conservation, addition, and conversion), three institutional levels (core value-chain actors, supporting institutions, and the policy environment), and the eight-stage Big Win delivery methodology. The assessment documents 2,000 cooperative members, including 449 women and 204 youth, managing approximately 1,585.2 hectares of coffee production. The cooperative reports annual red-cherry production of 4,968.696 tonnes, while its farmer registry records 4,832.929 tonnes. Reported processing volume is 2,388.254 tonnes of red cherry, equivalent to approximately 477.651 tonnes of green coffee under an indicative 5:1 conversion assumption. Direct green-coffee exports total 264.240 tonnes, with a reported export value of US$2,069,127.329 and an implied export unit value of approximately US$7.83\u002Fkg. The results identify important organizational strengths, including nursery operations, mapped smallholder farms, two washing stations, specialty coffee production, export-market participation, and reported certification activities. However, the analysis reveals weaknesses in planting-material genealogy, reliable source identification, digital transaction continuity, coffee-lot traceability, quality-linked producer payments, data validation, and institutional interoperability. Six farmer-coordinate records require further verification, while discrepancies between questionnaire and registry production figures indicate the need for improved administrative data governance. The scientific discussion compares these findings with recent international, African, and Ethiopian publications on coffee sustainability, digital traceability, geographical differentiation, processing quality, cooperative governance, and market competitiveness. Particular emphasis is placed on the relationship between biological productivity, product quality preservation, processing recovery, buyer acceptance, and realized economic value. The paper proposes an integrated Smart Digital Coffee Value Chain architecture linking market intelligence, research and genetics, nursery systems, farmer and plot identification, agricultural services, production, harvesting, collection, processing, storage, certification, buyer contracts, export acceptance, financial settlement, and performance feedback. It further translates the evaluation into prioritized Business Requirements (BR), Functional Requirements (FR), institutional data-supply and consumption responsibilities, interoperable information flows, corrective and preventive actions (CAPA), and measurable Key Performance and Key Risk Indicators (KPI\u002FKRI). A five-year implementation proposal establishes a phased pathway from baseline reconciliation and digital identity verification to transaction-level traceability, quality conservation, commercial integration, producer-payment transparency, and evidence-based scaling. The principal scientific contribution is a practical and replicable framework for transforming fragmented smallholder coffee activities into an integrated, traceable, and economically accountable value chain. The study demonstrates how biological production, quality conservation, value addition, market conversion, and financial realization can be assessed through connected institutional responsibilities and verifiable digital records. The findings provide useful evidence and implementation guidance for coffee farmers, primary cooperatives, cooperative unions, the Oromia Cooperative Promotion Commission, regional and national government institutions, researchers, exporters, investors, and digital-system developers in Ethiopia and other coffee-producing regions. The reported organizational findings describe the available 2026 baseline, while proposed interventions, performance targets, and anticipated economic benefits require field implementation and independent verification. Publication classificationArticle type: Scientific case study, institutional performance assessment, and prospective five-year transformation proposal. Keywords: Smart Digital Coffee Value Chain; Guji Coffee; Homa Multipurpose Farmers Cooperative; Oromia; Ethiopia; Coffee Traceability; Biological Efficiency; Economic Efficiency; Value Conservation; Value Addition; Cooperative Development; Business Requirements; Functional Requirements; Big Win Methodology; Digital Agriculture; Coffee Sustainability.","标题：智能数字古吉合作社咖啡价值链转型：埃塞俄比亚奥罗米亚州科学评估、价值转化、数字追溯与五年战略实施框架\n\n作者：Kedir Nefo Biftu, Kebede Hailu, Tadila Tadessa Qajela\n\n描述：本科学论文针对埃塞俄比亚奥罗米亚州西古吉区阿巴亚沃雷达的霍马多用途农民合作社，提出了一项基于证据的评估与五年战略转型框架。研究探讨如何将小农咖啡生产、合作社聚合、加工、质量保证、国际营销和金融交易整合为智能数字咖啡价值链，以提升可追溯性、价值保存、经济效率和生产者收益。研究整合了结构化合作社问卷、包含2000条记录的农户级行政登记册以及全面的业务与功能需求规范（BFRS）。分析框架包括18个端到端咖啡价值链组成部分、九个价值创造点（保存、增加和转化）、三个制度层面（核心价值链参与者、支持机构和政策环境）以及八阶段“大赢”交付方法。评估记录了2000名合作社成员，其中包括449名妇女和204名青年，管理约1585.2公顷咖啡生产。合作社报告的年红果产量为4968.696吨，而其农户登记册记录为4832.929吨。报告的加工量为2388.254吨红果，在指示性5：1转化假设下约相当于477.651吨生咖啡。直接生咖啡出口总量为264.240吨，报告的出口价值为2，069，127.329美元，隐含出口单价约为7.83美元\u002F千克。结果识别出重要的组织优势，包括苗圃运营、已测绘的小农农场、两个水洗站、精品咖啡生产、出口市场参与以及报告的认证活动。然而，分析揭示了在种植材料谱系、可靠来源识别、数字交易连续性、咖啡批次可追溯性、与质量挂钩的生产者付款、数据验证和制度互操作性方面的弱点。六条农户坐标记录需要进一步核实，而问卷之间的差异","2026-10-19T00:00:00Z",{"impact":17,"substance":295,"depth":105,"authority":20,"freshness":109,"relevant":21,"comment":353},"基于2000条农户登记与18个价值链环节的实证评估，数据扎实、框架可复制，但属区域案例，公共影响有限。",[355],{"name":235,"url":348},[26,245,246,357,300],"埃塞俄比亚",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":361},{"candidates":362,"agricultural_evidence":46},[363,367,371],{"code":32,"score":107,"supported":46,"title":364,"abstract":365,"tags":366},[48],[50,48],[],{"code":191,"score":54,"supported":46,"title":368,"abstract":369,"tags":370},[],[260,195],[245],{"code":53,"score":257,"supported":46,"title":372,"abstract":373,"tags":374},[],[265],[26],[376,377],"Guji 咖啡 数字溯源","埃塞俄比亚 咖啡合作社 价值链","Guji咖啡数字溯源-5377","10.5281\u002Fzenodo.23481514",{"doi":379,"openalex_id":381,"authors":382,"venue":235,"cited_by_count":81,"oa_url":348,"card":386,"direction":89,"ingested_from":90},"W7222944563",[383,384,385],{"name":276,"orcid":9},{"name":278,"orcid":9},{"name":280,"orcid":9},{"tldr":387,"method":388,"finding":389,"direction":87,"opportunity":390},"为埃塞俄比亚Guji咖啡合作社设计智慧数字价值链转型与五年战略框架。","合作社问卷、2000条农户登记数据与BFRS需求规范，18环节价值链分析。","合作社具备出口能力，但缺乏批次追溯、数字交易连续性与质量挂钩支付。","可研究小农户咖啡区块链追溯与质量溢价支付机制，填补数据互操作空白。","2026-10-20T23:30:08.394987Z",{"id":393,"title":394,"url":395,"summary":396,"summary_zh":397,"content":9,"source_name":398,"source_url":395,"published_at":399,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":148,"score_detail":400,"sources":403,"tags":405,"primary_topic":409,"secondary_topics":410,"classification":417,"search_phrases":441,"slug":444,"view_count":81,"doi":445,"paper":446,"created_at":471},4685,"Farm management and yield gaps in Robusta (Coffea canephora) coffee production across the three largest Asian origins","https:\u002F\u002Fdoi.org\u002F10.25186\u002F.v21i.2515","Robusta coffee is a key livelihood crop in Asia, and its productivity differs largely across main regions. However, the factors underlying these differences remain limited. This study examines yield variation across Vietnam, Indonesia, and India, the three largest Robusta-producing countries in Asia. Using 13,525 farm-level surveys, the study applied descriptive statistics, correlation analysis, and regression-based threshold methods to assess the relationships between yield and key management practices. The results show that median yields reach 2,643 kg GBE ha⁻¹ in Vietnam, compared with 1,359 kg ha⁻¹ in India-Karnataka, 509 kg ha⁻¹ in India-Kerala, and 383 kg ha⁻¹ in Indonesia. Correlation analysis shows that inorganic fertilizer use is positively associated with yield across the three countries, with coefficients ranging from 0.326 to 0.408. Pruning practices are also associated with higher yields in several regions, whereas shade levels are negatively related to yield in Vietnam. These findings indicate that yield gaps in Asian Robusta systems arise from different constraints across countries. Input scarcity appears to constrain productivity in Indonesia, while inefficiencies in nutrient management and structural characteristics of production systems play a larger role in Vietnam and India. The results highlight the need for context-specific strategies to improve productivity and sustainability in Robusta coffee production. Key words: Yield differences; fertilizer efficiency; shade management; plantation rejuvenation; Robusta coffee.","罗布斯塔咖啡（Robusta coffee）是亚洲重要的生计作物，但其生产力在主产区之间差异显著。然而，造成这些差异的因素仍缺乏充分研究。本研究考察了亚洲三大罗布斯塔咖啡生产国——越南、印度尼西亚和印度之间的产量差异。研究利用13,525份农场层面调查数据，采用描述性统计、相关分析和基于回归的阈值方法，评估产量与关键管理措施之间的关系。结果表明，越南的产量中位数达到2,643 kg GBE ha⁻¹，而印度卡纳塔克邦为1,359 kg ha⁻¹，印度喀拉拉邦为509 kg ha⁻¹，印度尼西亚为383 kg ha⁻¹。相关分析显示，无机肥料施用与三国产量均呈正相关，系数范围为0.326至0.408。修剪措施在若干地区也与较高产量相关，而越南的遮阴水平与产量呈负相关。这些发现表明，亚洲罗布斯塔咖啡系统的产量差距源于各国不同的限制因素。投入品短缺似乎制约了印度尼西亚的生产力，而养分管理效率低下和生产系统的结构性特征在越南和印度发挥了更大作用。研究结果凸显了制定因地制宜策略以提高罗布斯塔咖啡生产力和可持续性的必要性。关键词：产量差异；肥料效率；遮阴管理；种植园更新；罗布斯塔咖啡。","Coffee Science","2026-10-09T00:00:00Z",{"impact":106,"substance":295,"depth":105,"authority":401,"freshness":20,"relevant":21,"comment":402},13,"基于13,525份农户调查揭示亚洲三大罗布斯塔产区的产量差与管理约束，数据规模大、结论有区域针对性，对咖啡产业信息化与精准施肥有参考价值。",[404],{"name":398,"url":395},[194,28,406,407,408],"施肥管理","产量差","遮荫栽培",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[411],{"code":412,"slug":413,"name":414,"path":415,"parent_code":416},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",{"status":39,"locked":14,"version":40,"method":41,"evidence":418},{"candidates":419,"agricultural_evidence":46},[420,424,431,437],{"code":32,"score":45,"supported":46,"title":421,"abstract":422,"tags":423},[48],[50,48],[28],{"code":412,"score":109,"supported":46,"title":425,"abstract":426,"tags":430},[],[427,428,429],"肥料","养分管理","fertilizer",[],{"code":432,"score":62,"supported":46,"title":433,"abstract":434,"tags":436},"I3",[],[435],"估产",[],{"code":191,"score":21,"supported":14,"title":438,"abstract":439,"tags":440},[],[],[194],[442,443],"越南 印尼 印度 罗布斯塔 咖啡","罗布斯塔 咖啡 产量差 施肥","越南印尼印度罗布斯塔咖啡-4685","10.25186\u002F.v21i.2515",{"doi":445,"openalex_id":447,"authors":448,"venue":398,"cited_by_count":81,"oa_url":464,"card":465,"direction":470,"ingested_from":90},"W7221151398",[449,452,455,458,461],{"name":450,"orcid":451},"Hue Tran","https:\u002F\u002Forcid.org\u002F0000-0003-0606-0525",{"name":453,"orcid":454},"Thuy Phan Thi","https:\u002F\u002Forcid.org\u002F0000-0001-5451-7185",{"name":456,"orcid":457},"Long Nhat Cao","https:\u002F\u002Forcid.org\u002F0000-0002-5345-7472",{"name":459,"orcid":460},"Jacob Schenthal","https:\u002F\u002Forcid.org\u002F0000-0002-1265-033X",{"name":462,"orcid":463},"Ketan Patel","https:\u002F\u002Forcid.org\u002F0009-0007-1813-2449","https:\u002F\u002Fcoffeescience.ufla.br\u002Findex.php\u002FCoffeescience\u002Farticle\u002Fdownload\u002F2515\u002F2608",{"tldr":466,"method":467,"finding":468,"direction":87,"opportunity":469},"基于13525份农户调查，分析越南、印尼、印度罗布斯塔咖啡产量差异及管理因素。","13,525份农户调查，描述统计、相关分析与回归阈值法。","无机肥与产量正相关；印尼受投入不足限制，越南和印度则受养分管理低效与结构因素制约。","可构建分区域咖啡产量差诊断与精准施肥决策模型，结合遥感与物联网实现管理处方推荐。","农业遥感与作物表型","2026-10-11T23:30:31.779147Z"]