[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3884":3,"related-3884":77},{"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":30,"secondary_topics":36,"classification":37,"search_phrases":61,"slug":64,"view_count":65,"doi":66,"paper":67,"created_at":76},3884,"Sustainable Coffee Production: Biotechnology, Circular Bioeconomy, and Climate-Smart Agriculture","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11196777\u002Fv1","Sustainable Coffee Production: Biotechnology, Circular Bioeconomy, and Climate-Smart Agriculture。Research Square",null,"Research Square","2026-09-30T00:00:00Z","论文",10,false,61,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,14,12,9,8,1,"主题契合农业科技与可持续生产，但摘要信息量有限，属细分领域研究进展，未达重大突破层级。",[24],{"name":9,"url":6},[26,27,28,29],"气候智慧农业","咖啡产业","农业生物技术","循环生物经济",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"B3","tea-coffee","茶叶与咖啡","\u002Ftopic\u002Fhorticulture\u002Ftea-coffee","B",[],{"status":38,"locked":13,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":44},[43,49,56],{"code":31,"score":18,"supported":44,"title":45,"abstract":47,"tags":48},true,[46],"coffee",[46],[27],{"code":50,"score":51,"supported":44,"title":52,"abstract":54,"tags":55},"I1",11,[53],"smart agriculture",[53],[],{"code":57,"score":21,"supported":13,"title":58,"abstract":59,"tags":60},"H7",[],[],[26],[62,63],"可持续咖啡生产 生物技术","气候智慧农业 咖啡","可持续咖啡生产生物技术-3884",2,"10.21203\u002Frs.3.rs-11196777\u002Fv1",{"doi":66,"openalex_id":68,"authors":69,"venue":9,"cited_by_count":73,"oa_url":6,"card":8,"direction":74,"ingested_from":75},"W7214969071",[70],{"name":71,"orcid":72},"Mitiku Muanenda","https:\u002F\u002Forcid.org\u002F0000-0003-3022-9175",0,"智慧农业 \u002F 农业物联网","openalex","2026-10-01T23:30:09.668346Z",{"total":78,"page":21,"page_size":78,"items":79},6,[80,142,227,333,402,449],{"id":81,"title":82,"url":83,"summary":84,"summary_zh":85,"content":8,"source_name":86,"source_url":83,"published_at":87,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":88,"score_detail":89,"sources":92,"tags":94,"primary_topic":99,"secondary_topics":100,"classification":101,"search_phrases":121,"slug":124,"view_count":73,"doi":125,"paper":126,"created_at":141},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":16,"depth":90,"authority":19,"freshness":19,"relevant":21,"comment":91},15,"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。",[93],{"name":86,"url":83},[95,96,97,98,27],"数字农业","价值链","合作社","数字溯源",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":102},{"candidates":103,"agricultural_evidence":44},[104,109,116],{"code":31,"score":90,"supported":44,"title":105,"abstract":106,"tags":108},[46],[107,46],"咖啡",[27],{"code":110,"score":111,"supported":44,"title":112,"abstract":113,"tags":115},"G2",4,[],[114],"农民合作社",[97],{"code":50,"score":111,"supported":44,"title":117,"abstract":118,"tags":120},[],[119],"digital agriculture",[95],[122,123],"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":125,"openalex_id":127,"authors":128,"venue":86,"cited_by_count":73,"oa_url":83,"card":135,"direction":74,"ingested_from":75},"W7223041235",[129,131,133],{"name":130,"orcid":8},"Kedir Biftu",{"name":132,"orcid":8},"Kebede Hailu",{"name":134,"orcid":8},"Tadila Tadessa Qajela",{"tldr":136,"method":137,"finding":138,"direction":139,"opportunity":140},"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。","数字乡村与农业信息化","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":143,"title":144,"url":145,"summary":146,"summary_zh":147,"content":8,"source_name":148,"source_url":145,"published_at":149,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":150,"score_detail":151,"sources":156,"tags":158,"primary_topic":163,"secondary_topics":164,"classification":171,"search_phrases":196,"slug":199,"view_count":21,"doi":200,"paper":201,"created_at":226},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",77,{"impact":152,"substance":153,"depth":16,"authority":154,"freshness":20,"relevant":21,"comment":155},16,22,13,"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。",[157],{"name":148,"url":145},[159,27,160,161,162],"小农户","施肥管理","产量差","遮荫栽培",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[165],{"code":166,"slug":167,"name":168,"path":169,"parent_code":170},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",{"status":38,"locked":13,"version":39,"method":40,"evidence":172},{"candidates":173,"agricultural_evidence":44},[174,178,185,192],{"code":31,"score":90,"supported":44,"title":175,"abstract":176,"tags":177},[46],[107,46],[27],{"code":166,"score":19,"supported":44,"title":179,"abstract":180,"tags":184},[],[181,182,183],"肥料","养分管理","fertilizer",[],{"code":186,"score":187,"supported":44,"title":188,"abstract":189,"tags":191},"I3",3,[],[190],"估产",[],{"code":110,"score":21,"supported":13,"title":193,"abstract":194,"tags":195},[],[],[159],[197,198],"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":200,"openalex_id":202,"authors":203,"venue":148,"cited_by_count":73,"oa_url":219,"card":220,"direction":225,"ingested_from":75},"W7221151398",[204,207,210,213,216],{"name":205,"orcid":206},"Hue Tran","https:\u002F\u002Forcid.org\u002F0000-0003-0606-0525",{"name":208,"orcid":209},"Thuy Phan Thi","https:\u002F\u002Forcid.org\u002F0000-0001-5451-7185",{"name":211,"orcid":212},"Long Nhat Cao","https:\u002F\u002Forcid.org\u002F0000-0002-5345-7472",{"name":214,"orcid":215},"Jacob Schenthal","https:\u002F\u002Forcid.org\u002F0000-0002-1265-033X",{"name":217,"orcid":218},"Ketan Patel","https:\u002F\u002Forcid.org\u002F0009-0007-1813-2449","https:\u002F\u002Fcoffeescience.ufla.br\u002Findex.php\u002FCoffeescience\u002Farticle\u002Fdownload\u002F2515\u002F2608",{"tldr":221,"method":222,"finding":223,"direction":139,"opportunity":224},"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",{"id":228,"title":229,"url":230,"summary":231,"summary_zh":232,"content":8,"source_name":233,"source_url":230,"published_at":234,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":235,"score_detail":236,"sources":239,"tags":241,"primary_topic":246,"secondary_topics":247,"classification":260,"search_phrases":304,"slug":307,"view_count":73,"doi":308,"paper":309,"created_at":332},4570,"Agroecological practices, perceived benefits, and determinants of adoption in the Yayu Coffee Forest Biosphere Reserve, Southwest Ethiopia","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44274-026-01113-4","Agroecology offers a promising pathway for reconciling forest conservation with rural livelihoods in biodiversity-rich tropical landscapes, yet empirical evidence on the breadth, intensity, and determinants of adoption remains limited, particularly in UNESCO biosphere reserves. This study investigates agroecological practices, perceived contributions, and determinants of adoption in the Yayu Coffee Forest Biosphere Reserve (YCFBR), Southwest Ethiopia. A cross-sectional concurrent mixed-methods design was employed, combining 293 randomly selected households, complemented by key informant interviews, focus group discussions, and field observations. Binary logistic regression identified determinants of adoption (extensive margin), while ordinal logistic regression examined adoption intensity using the Agroecological Adoption Index (AAI) (intensive margin). Number of Practices Adopted (NPA), Weighted Adoption Intensity (WAI), and Duration of Adoption (DUR) provided complementary insights into adoption breadth, intensity, and persistence. Qualitative data were analyzed thematically to contextualize quantitative findings. Results showed that 72% of households adopted at least one agroecological practice, including coffee agroforestry, homegarden agroforestry, soil and water conservation, climate-smart agriculture, intercropping, crop rotation, mixed tree planting, afforestation and reforestation, organic soil fertility management, and biological pest and disease management. Adoption intensity varied: 34.6% low, 41.2% moderate, and 24.2% high. Practices were perceived to improve soil fertility, biodiversity conservation, climate resilience, forest management, and livelihood diversification while reducing pressure on natural forests and strengthening ecological connectivity and adaptive capacity. Sex, education, farm size, extension services, training, credit access, and cooperative membership significantly determined adoption and intensity, whereas age, household size, farming experience, and distance to forest were non-significant. Agroecology provides a multifunctional, context-specific pathway for advancing sustainable forest management, biodiversity conservation, and livelihood resilience. Strengthening agroecology-oriented extension, gender-responsive training, access to finance, indigenous knowledge integration, and policy mainstreaming are essential for long-term environmental sustainability and community resilience in the YCFBR and comparable forest-dependent landscapes.","农业生态学为在生物多样性丰富的热带景观中协调森林保护与农村生计提供了一条有前景的路径，但关于其采用广度、强度及决定因素的实证证据仍然有限，尤其是在联合国教科文组织生物圈保护区中。本研究调查了埃塞俄比亚西南部亚尤咖啡森林生物圈保护区（YCFBR）的农业生态实践、感知贡献及采用决定因素。研究采用横断面同步混合方法设计，结合293户随机选取的家庭，并辅以关键知情人访谈、焦点小组讨论和实地观察。二元逻辑回归识别了采用的决定因素（外延边际），而有序逻辑回归则使用农业生态采用指数（AAI）考察了采用强度（内涵边际）。采用实践数量（NPA）、加权采用强度（WAI）和采用持续时间（DUR）为采用广度、强度和持续性提供了补充性见解。定性数据采用主题分析法，以对定量发现进行情境化解释。结果表明，72%的家庭至少采用了一项农业生态实践，包括咖啡农林复合、家庭园圃农林复合、水土保持、气候智能型农业、间作、轮作、混合植树、植树造林和再造林、有机土壤肥力管理以及生物病虫害管理。采用强度存在差异：低度34.6%、中度41.2%、高度24.2%。受访者认为这些实践改善了土壤肥力、生物多样性保护、气候韧性、森林管理和生计多样化，同时减轻了对天然森林的压力，并增强了生态连通性和适应能力。性别、教育程度、农场规模、推广服务、培训、信贷获取和合作社成员资格显著决定了采用及采用强度，而年龄、家庭规模、耕作经验和距森林距离则不显著。农业生态学为推进可持续森林管理、生物多样性保护和生计韧性提供了一条多功能、因地制宜的路径。加强面向农业生态学的推广、性别响应型培训、融资渠道、本土知识整合和政策主流化，对于YCFBR及类似依赖森林的地区实现长期环境可持续性和社区韧性至关重要。","Discover Environment","2026-10-08T00:00:00Z",73,{"impact":18,"substance":153,"depth":237,"authority":154,"freshness":19,"relevant":21,"comment":238},17,"基于293户调查的实证研究，数据扎实、结论具体，对热带林区农业生态化与咖啡产业可持续发展有参考价值，但属区域性案例研究，公共影响层级有限。",[240],{"name":233,"url":230},[242,27,243,244,245],"可持续生计","生态农业","农林复合经营","生物多样性保护",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[248,254],{"code":249,"slug":250,"name":251,"path":252,"parent_code":253},"A7","forage-cropping","饲草与耕作制度","\u002Ftopic\u002Ffield-crops\u002Fforage-cropping","A",{"code":255,"slug":256,"name":257,"path":258,"parent_code":259},"H6","biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity","H",{"status":38,"locked":13,"version":39,"method":40,"evidence":261},{"candidates":262,"agricultural_evidence":44},[263,267,275,283,290,295,299],{"code":31,"score":90,"supported":44,"title":264,"abstract":265,"tags":266},[46],[107,46],[27],{"code":249,"score":19,"supported":44,"title":268,"abstract":269,"tags":274},[],[270,271,272,273],"轮作","间作","crop rotation","intercropping",[],{"code":255,"score":19,"supported":44,"title":276,"abstract":277,"tags":282},[],[278,279,280,256,281],"生物多样性","农业生态","水土保持","agroecology",[],{"code":284,"score":78,"supported":44,"title":285,"abstract":286,"tags":289},"H2",[],[287,288],"土壤","soil",[],{"code":57,"score":187,"supported":44,"title":291,"abstract":292,"tags":294},[],[293],"climate resilience",[],{"code":50,"score":187,"supported":44,"title":296,"abstract":297,"tags":298},[],[53],[],{"code":300,"score":21,"supported":13,"title":301,"abstract":302,"tags":303},"H8",[],[],[243],[305,306],"埃塞俄比亚 亚尤咖啡林 生物圈保护区","农林复合经营 采纳影响因素","埃塞俄比亚亚尤咖啡林生物圈保护区-4570","10.1007\u002Fs44274-026-01113-4",{"doi":308,"openalex_id":310,"authors":311,"venue":233,"cited_by_count":73,"oa_url":325,"card":326,"direction":74,"ingested_from":75},"W7221057925",[312,315,318,321,323],{"name":313,"orcid":314},"Alemayehu Abera","https:\u002F\u002Forcid.org\u002F0000-0002-6225-9304",{"name":316,"orcid":317},"Samuel Taye","https:\u002F\u002Forcid.org\u002F0000-0001-9662-3939",{"name":319,"orcid":320},"Adanech Asfaw","https:\u002F\u002Forcid.org\u002F0009-0007-2586-0559",{"name":322,"orcid":8},"Chaluma Kicha",{"name":324,"orcid":8},"Endashew Mogessie","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44274-026-01113-4.pdf",{"tldr":327,"method":328,"finding":329,"direction":330,"opportunity":331},"研究埃塞俄比亚亚尤咖啡森林生物圈保护区农户采用农业生态实践的程度、感知效益及影响因素。","混合方法：293户问卷+访谈+焦点小组，二元与有序logistic回归分析采用广","72%农户至少采用一项实践，采用强度分低中高；性别、教育、推广、信贷等显著影响采用。","农业绿色发展与碳","可延伸研究农业生态实践采用对森林保护与生计韧性的长期因果效应及数字化推广干预。","2026-10-10T23:30:11.538537Z",{"id":334,"title":335,"url":336,"summary":337,"summary_zh":338,"content":8,"source_name":339,"source_url":336,"published_at":234,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":340,"score_detail":341,"sources":344,"tags":346,"primary_topic":351,"secondary_topics":352,"classification":353,"search_phrases":376,"slug":379,"view_count":73,"doi":380,"paper":381,"created_at":401},4507,"Nearly ninety percent of Indonesian coffee area is classified as deforestation-free under the European Union Deforestation Regulation (EUDR)","https:\u002F\u002Fdoi.org\u002F10.1088\u002F1748-9326\u002Faeb1e2","Abstract Indonesia is the third-largest coffee producer globally and exports a substantial share of its production to European Union (EU) countries. Recent implementation of the EU Deforestation Regulation (EUDR), which requires deforestation-free supply chains, highlights the need for spatially-explicit coffee mapping to support the assessment of coffee-associated deforestation. In this study, we utilized multitemporal and multi-sensor remote sensing to produce annual maps of coffee distribution from 2016 to 2024. We analyzed the spatial patterns of annual coffee distribution during this period, and evaluated the potential implications of EUDR for coffee production in Indonesia. Our maps of coffee agroecosystems demonstrate an overall classification accuracy exceeding 80%, and are broadly consistent with independent coffee datasets (i.e., national statistics and coffee probability maps from the Forest Data Partnership). We detected a net increase of ~15% in coffee area over the eight-year period, although the patterns of change vary across provinces. Based on these maps, we estimate that 87.9% of the coffee area in 2024 meets the EUDR deforestation-free criterion, and only a relatively small proportion of agroecosystems are classified as non-deforestation-free. These findings highlight opportunities for spatially targeted EUDR implementation, where deforestation-free coffee agroecosystems can be supported towards meeting broader EUDR requirements, while areas associated with forest conversion can be supported towards other pathways, such as sustainable agricultural practices, restoration, and forest conservation.","摘要：印度尼西亚是全球第三大咖啡生产国，并将相当大比例的产量出口至欧盟（EU）国家。近期实施的《欧盟零毁林条例》（EUDR）要求供应链不涉及毁林，这凸显了开展空间显式咖啡制图以支持咖啡相关毁林评估的必要性。本研究利用多时相和多传感器遥感技术，制作了2016年至2024年咖啡分布的年度地图。我们分析了这一时期咖啡年度分布的空间格局，并评估了EUDR对印度尼西亚咖啡生产的潜在影响。我们的咖啡农业生态系统地图总体分类精度超过80%，并与独立咖啡数据集（即国家统计数据以及森林数据伙伴关系提供的咖啡概率图）大体一致。我们检测到八年间咖啡面积净增加约15%，但各省变化格局有所不同。基于这些地图，我们估计2024年87.9%的咖啡面积符合EUDR无毁林标准，仅有相对较小比例的农业生态系统被归类为非无毁林。这些发现凸显了在空间上有针对性地实施EUDR的机会，即可以支持无毁林咖啡农业生态系统满足EUDR更广泛的要求，同时可以支持与森林转化相关的区域转向其他路径，如可持续农业实践、恢复和森林保护。","Environmental Research Letters",86,{"impact":153,"substance":342,"depth":16,"authority":17,"freshness":19,"relevant":21,"comment":343},23,"基于多时相多源遥感生成印尼咖啡分布图，量化EUDR合规比例，方法扎实、结论对咖啡出口与可持续供应链有直接参考价值。",[345],{"name":339,"url":336},[347,27,348,349,350],"遥感监测","供应链溯源","EUDR","毁林零容忍",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":354},{"candidates":355,"agricultural_evidence":44},[356,360,367,371],{"code":31,"score":90,"supported":44,"title":357,"abstract":358,"tags":359},[46],[107,46],[27],{"code":186,"score":361,"supported":44,"title":362,"abstract":363,"tags":366},7,[],[364,365],"遥感","remote sensing",[347],{"code":255,"score":187,"supported":44,"title":368,"abstract":369,"tags":370},[],[279],[],{"code":300,"score":187,"supported":44,"title":372,"abstract":373,"tags":375},[],[374],"可持续农业",[],[377,378],"印尼 咖啡 遥感制图","EUDR 咖啡 毁林","印尼咖啡遥感制图-4507","10.1088\u002F1748-9326\u002Faeb1e2",{"doi":380,"openalex_id":382,"authors":383,"venue":339,"cited_by_count":73,"oa_url":336,"card":396,"direction":225,"ingested_from":75},"W7221019615",[384,387,389,391,393],{"name":385,"orcid":386},"Tin Widyani Satriawan","https:\u002F\u002Forcid.org\u002F0000-0003-4580-9973",{"name":388,"orcid":8},"Xiangzhong (Remi) Luo",{"name":390,"orcid":8},"Shafira Nur Ramdhania",{"name":392,"orcid":8},"Agustín Escobar-López",{"name":394,"orcid":395},"Anggun Tridawati","https:\u002F\u002Forcid.org\u002F0000-0002-0070-883X",{"tldr":397,"method":398,"finding":399,"direction":225,"opportunity":400},"利用多时相多源遥感绘制印尼2016-2024年咖啡分布图，评估EUDR合规性。","多时相多传感器遥感分类，结合国家统计与森林数据伙伴关系概率图验证。","印尼咖啡面积净增约15%，2024年87.9%咖啡区符合EUDR无毁林标准。","可延伸研究：针对非合规小区域，结合高分辨率遥感与供应链追溯，设计精准干预与可持续转型路径。","2026-10-09T23:30:26.065388Z",{"id":403,"title":404,"url":405,"summary":406,"summary_zh":8,"content":407,"source_name":408,"source_url":8,"published_at":409,"category":410,"cover_url":8,"hotness":12,"is_selected":13,"score":411,"score_detail":412,"sources":415,"tags":417,"primary_topic":423,"secondary_topics":424,"classification":425,"search_phrases":444,"slug":447,"view_count":21,"doi":8,"paper":8,"created_at":448},3232,"2026年中国热带作物产业大会在昆明举办——云南农科院发布咖啡重大科技成果 云南咖啡种植面积占全国98%以上","https:\u002F\u002Fwww.jingjiribao.cn\u002Fstatic\u002Fdetail.jsp?id=684363","9-17 经济日报报道：2026年中国热带作物产业大会9-17在云南昆明举行。本次大会聚焦咖啡这一热带作物，以\"咖位中国·链动全球\"为主题。云南省农业科学院发布咖啡重大科技成果，包括咖啡园\"乔—灌—草\"立体复合种植技术、咖啡化肥农药减施增效技术、咖啡鲜果无水加工技术、咖啡定向发酵关键技术等，覆盖种植、植保与加工环节。云南省市场监管局宣布成立云南省咖啡技术标准化委员会并揭牌。\"十四五\"期间，云南咖啡豆精品率从8%跃升至41.7%，精深加工率从20%提升到85%。2025年云南咖啡种植面积达151.88万亩、产量达17.07万吨，均占全国98%以上，咖啡全产业链产值达995亿元。","2026年中国热带作物产业大会9月17日在云南昆明举行。本次大会聚焦咖啡这一热带作物，以“咖位中国·链动全球”为主题，200余名专家学者、企业家、业界代表等围绕咖啡提质、品牌建设与国际合作展开研讨，推动我国咖啡向标准化、精品化、品牌化方向发展。\n\n![Image 1](https:\u002F\u002Fstatic.jingjiribao.cn\u002F2026\u002F9\u002F20\u002F20260920103055_7096.JPEG)\n\n开幕式上，云南省市场监管局宣布成立云南省咖啡技术标准化委员会并揭牌。云南省农业科学院发布咖啡重大科技成果，包括咖啡园“乔—灌—草”立体复合种植技术、咖啡化肥农药减施增效技术、咖啡鲜果无水加工技术、咖啡定向发酵关键技术等，覆盖种植、植保与加工环节。云南日报报业集团发布《中式咖啡文化传播影响力报告》。\n\n据介绍，云南热区面积约8.1万平方公里，是全国热区资源富集省份之一。近年来，云南立足多样立体的气候资源禀赋，大力发展热作产业，咖啡成为最具辨识度、最有竞争力的热作产业之一。“十四五”期间，云南咖啡豆精品率从8%跃升至41.7%，精深加工率从20%提升到85%。2025年，云南咖啡种植面积达151.88万亩、产量达17.07万吨，均占全国98%以上，咖啡全产业链产值达995亿元。\n\n本次大会设“变局与新机——全球咖啡格局重塑中的中国路径与中非、GMS（大湄公河次区域）机遇”“标准筑基·科技赋能——中国咖啡的品质根基与创新驱动”“从产地到品牌——云南咖啡的精品化跃迁”“世界咖啡·中国表达——中国咖啡文化国际传播”4个平行分论坛。\n\n本次大会由农业农村部南亚热带作物中心、云南省农业农村厅、昆明市人民政府共同主办，大会期间，云南还举办咖啡加工工职业技能大赛、花咖之夜、2026云南咖啡展、滇池国际咖啡文化嘉年华·“秋韵啡扬”、滇池国际咖啡文化嘉年华·翠湖咖啡主题市集等活动，让参会嘉宾、游客与本地消费者体验云南丰富多彩的咖啡文化。","经济日报","2026-09-17T00:00:00Z","报道",87,{"impact":413,"substance":342,"depth":237,"authority":17,"freshness":78,"relevant":21,"comment":414},27,"全国性热带作物产业大会落地昆明，云南农科院发布覆盖种植到加工的重大科技成果，并给出精品率、精深加工率与全产业链产值等关键数据，产业级信息增量充足，值得进入每日精选。",[416],{"name":408,"url":405},[418,419,27,420,421,422],"品牌建设","标准化","精深加工","热带作物","农业科技成果",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":426},{"candidates":427,"agricultural_evidence":44},[428,432,439],{"code":31,"score":18,"supported":44,"title":429,"abstract":430,"tags":431},[107],[107],[27],{"code":433,"score":78,"supported":44,"title":434,"abstract":435,"tags":438},"F4",[],[436,437],"农药","植保",[],{"code":440,"score":21,"supported":13,"title":441,"abstract":442,"tags":443},"E5",[],[],[418],[445,446],"云南农科院 咖啡 科技成果","云南咖啡 种植面积 全产业链产值","云南农科院咖啡科技成果-3232","2026-09-23T00:04:30.734823Z",{"id":450,"title":451,"url":452,"summary":453,"summary_zh":8,"content":8,"source_name":454,"source_url":8,"published_at":455,"category":410,"cover_url":8,"hotness":12,"is_selected":13,"score":456,"score_detail":457,"sources":459,"tags":461,"primary_topic":465,"secondary_topics":466,"classification":467,"search_phrases":483,"slug":486,"view_count":111,"doi":8,"paper":8,"created_at":487},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",68,{"impact":16,"substance":152,"depth":17,"authority":51,"freshness":19,"relevant":21,"comment":458},"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。",[460],{"name":454,"url":452},[462,463,27,421,464],"智慧农业","农业人工智能","农业标准体系",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":468},{"candidates":469,"agricultural_evidence":44},[470,474,478],{"code":31,"score":18,"supported":44,"title":471,"abstract":472,"tags":473},[107],[107],[27],{"code":50,"score":21,"supported":13,"title":475,"abstract":476,"tags":477},[],[],[462],{"code":479,"score":21,"supported":13,"title":480,"abstract":481,"tags":482},"I2",[],[],[463],[484,485],"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"]