[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-93":3,"related-93":74},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":8,"secondary_topics":30,"classification":31,"search_phrases":69,"slug":72,"view_count":19,"doi":8,"paper":8,"created_at":73},93,"山东数智农业：从凭经验看天到依数据管地 数据如何种好一块田","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7665864415985205775\u002F","山东省加快应用场景落地,赋能农业转型升级,通过聚焦粮食单产提升以及设施农业、畜牧业、海洋渔业、盐碱地综合利用,培育起智慧农业应用场景近1000个。山东打造'齐鲁农云'数字大脑,构建'一个数据总仓、一个鲁农码管理平台、六项基础能力和多个应用场景'总体架构,启动40个深化实数融合数字农业发展县建设。",null,"盛夏时节，济南市济阳区现代农业产业示范园的玻璃温室内，并不见人来人往的繁忙景象。传统农业生产中的“力气活”正被机器接过，过去凭经验作的判断，正转化为可以分析调用的数据。园区通过椰糠无土栽培、智能水肥一体化和熊蜂授粉等技术，实现节水节肥与全链条数字化管理。\n\n类似的变化，正在山东不同的农业场景中发生。\n\n山东是农业大省，也是粮食生产大省。当新一代信息技术进入田间地头，如何让亿万条数据真正服务一块田、一座棚、一头牛、一尾鱼？如何让数字化生产最终形成产业收益？\n\n答案，正在一片片田野、一座座园区和一条条产业链中逐渐显现。\n\n**技术“扎进”田间地头**\n\n在胶州市里岔镇“智农祓里”乡村振兴片区，田地也有了自己的“数字档案”。\n\n打开“千年祓都·预见上合”手机小程序，温度、湿度、风力、降雨量等数据实时跳动。农户点开自家地块，作物长势、种植天数、生长周期一目了然。\n\n“以前浇地得排队等水、铺管，现在一部手机就能搞定。”当地农户感受到的变化，来自田间一张看不见的智慧网络。\n\n在智慧灌溉示范区，68个智能电磁阀和84套智能设备分布在6个地块。高清摄像头观察作物长势，土壤墒情采集仪深入地下，实时监测土壤的温度、湿度和养分；傍晚，杀虫诱捕灯自动亮起，系统定时抓拍、识别虫类，分析病虫害发生规律。过去靠农户下地查看、凭经验判断的农情，转化为一组组实时更新的数据。\n\n“目前落地的1.0版，核心是数据采集。”项目负责人介绍，农户通过手机便可上传土壤、气象和农事信息，实现地块级精细管理。正在研发的2.0版，则将引入多光谱无人机和人工智能大模型，根据土壤、气候和作物长势，为种植户提供“种什么、怎么种、何时管”的建议。目前，这套体系已经覆盖里岔镇1.1万亩绿色增粮先行区，惠及13个行政村。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F734ab7dcd90444c8bdc6a8c20b756f49~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786060927&x-signature=kMW0g1NrgePTOx%2FnbkJg8Yd0boU%3D)\n数字技术进入田间，不只是增加几台设备，更是改变农户观察土地、安排农事的方式。\n\n过去，农民要靠多年积累的经验察墒情、看苗情。如今，埋在土里的传感器、飞在空中的无人机和运行在平台上的算法，把管理节点不断前移——农业生产由出了问题再处理，逐渐转向根据数据提前调节。\n\n数字技术的应用并不意味着传统农事经验失去了价值。恰恰相反，算法要想真正“读懂”庄稼，离不开农艺知识和长期生产经验。只不过，过去掌握在少数种植能手头脑中的经验，正在通过数据积累和模型分析，转化为更加稳定、可以复制的生产方案。\n\n数字化也在重新调整人与机器的分工。重复、繁重和标准化程度较高的劳动，更多交由机器完成；农业生产者则从单纯的体力投入中抽身，转向设备管理、农情判断和异常处置。\n\n**数据汇入“齐鲁农云”**\n\n农业生产中，土地、农机、气象、农资、经营主体和市场价格等数据，往往分散在不同地区、不同部门和不同系统中。数据彼此不连通，便难以形成完整的农业生产画像，支撑跨区域资源调度和风险研判。\n\n把散落在一线的数据汇集起来，成为山东推动数字农业继续向纵深发展的关键。\n\n一块田里的土壤墒情、一座温室里的环境参数、一处牧场里的养殖数据，如果只是停留在各自的平台和设备中，仍然是彼此分散的“信息孤岛”。2025年底，山东省农业农村综合性数字化管理服务平台“齐鲁农云”正式上线运行，汇聚全省涉农数据29.4亿条，初步形成“鲁农数据一张图”，并建设片区建设、粮食安全、特色产业、质量安全等16个应用场景。2026年夏收期间，山东依托相关数据能力，对农机作业进行远程监测和跨区域调配，使“人、机、田”衔接更加精准。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fb92f0387d360c19c55444dbcc8c7dbd9~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786060927&x-signature=1Q9ei0FWqJ%2BHAdIgY%2FbYIiond9E%3D)\n如果把散布在齐鲁田野的传感器比作神经末梢，那么“齐鲁农云”就是连接和处理信息的“中枢神经”。\n\n“三夏”、“三秋”时节，卫星遥感可以识别作物分布和成熟进度，北斗物联网设备则实时反馈农机位置和作业状态。哪片麦田已经成熟，周边有哪些收割机可以调度，管理人员能够在平台上直观掌握。\n\n平台构建起“一个数据总仓、一个‘鲁农码’管理平台、六项基础能力和多个应用场景”的总体架构。人工智能、卫星遥感、物联网、视联网和地理信息技术在这里交汇，原本分散的农业主体、农业资源和农业政策数据，被放到同一张数字地图上。\n\n山东已启动40个深化实数融合数字农业发展县建设，并研究起草《关于大力发展智慧农业的指导意见》。智慧农业正从单一技术应用，进入多领域协同创新阶段。\n\n**土特产插上“数据翅膀”**\n\n数字技术可以帮助农民把地种得更好、把畜禽养得更精细，但数字农业最终还要回答一个现实问题：生产出来的优质农产品，如何更顺畅地进入市场，转化为实实在在的产业收益？\n\n如果说“齐鲁农云”侧重汇聚生产、资源和管理数据，那么山东建设的齐鲁农超农副产品交易服务平台，连接的则是农业生产的另一端——交易、营销和消费。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fdc52b1e7a5347a4f0e0a2f94259b71f1~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786060927&x-signature=J1Y1zvcdl6HWFXOy1HNhbJkw85w%3D)\n高唐县赵庄的花生米品质出挑，却始终难以完成从地方特产到大众消费品的跨越。“酒香也怕巷子深”的窘境，一度让高唐县吉祥豆食品有限公司掌舵人袁春红一筹莫展。\n\n进驻齐鲁农超平台后，这一乡土名吃借助数字化快车直达北京、上海等一线城市，延伸至黑龙江、新疆等地，订单爆发式增长。目前，该平台已沉淀活跃用户超10万人，交易额超2.5亿元。\n\n从生产端到消费端，实数融合并不是让虚拟世界取代真实农业，而是用数据提高实体农业配置资源、抵御风险和连接市场的能力，从根本上改变农业生产方式、组织方式、资源配置方式和产销衔接方式。\n\n来源：大众新闻·大众日报","新黄河 2026-07-24","2026-07-23T23:09:00Z","报道",10,false,67,{"impact":17,"substance":18,"depth":19,"authority":13,"freshness":20,"relevant":21,"comment":22},20,18,16,3,1,"省级智慧农业综合报道，内容详实，有具体案例和数据，但时效性较差。",[24],{"name":10,"url":6},[26,27,28,29],"数字农业","智慧农业","山东","实数融合",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"needs_review","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":40,"reason":68},[37,44,50,56,62],{"code":38,"score":39,"supported":40,"title":41,"abstract":42,"tags":43},"I1",8,true,[],[27,26],[26,27],{"code":45,"score":20,"supported":40,"title":46,"abstract":47,"tags":49},"A8",[],[48],"单产提升",[],{"code":51,"score":20,"supported":40,"title":52,"abstract":53,"tags":55},"C",[],[54],"畜牧",[],{"code":57,"score":20,"supported":40,"title":58,"abstract":59,"tags":61},"D",[],[60],"渔业",[],{"code":63,"score":20,"supported":40,"title":64,"abstract":65,"tags":67},"H2",[],[66],"盐碱地",[],"多个产业证据相当，需要确认主归属",[70,71],"实数融合 数字农业 智慧农业 山东","实数融合 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1: 图片](https:\u002F\u002Finews.gtimg.com\u002Fom_bt\u002FO9999ugLiBwGPkfvkq4wFHgLyWHhyNb7p4vYw8IG3KxxkAA\u002F641)\n\n**数字技术如何与现代农业碰撞出火花？**禾丰种业生态无人农场无人驾驶农机采用卫星导航，作业效率提升了10倍；冠县打通灵芝产业数字采收、云仓仓储、定制代工、线上交易全流程，全产业链综合产值达43.2亿元；鼎立集团自主研发智慧养殖大数据平台，搭载国际首条AI视觉成像种蛋分级系统，大幅提升孵化出雏率与鸡苗品质；明波水产建成“蓝钻一号”大型生态围栏，首创全封闭循环水智能化养殖系统，实现节水95%、节能69%。这些场景，正是山东农业数字化转型的生动切片。\n\n**当前，山东加快应用场景落地，赋能农业转型升级，通过聚焦粮食单产提升以及设施农业、畜牧业、海洋渔业、盐碱地综合利用，培育起智慧农业应用场景近1000个。**其中，在作物种植精准化方面，26万台机械加装北斗农用终端，植保无人机保有量超过18万架；在设施种植数字化方面，建成智能化玻璃温室超过2万亩；在畜牧养殖智慧化方面，建成各类智能牧场168个；在渔业养殖智能化方面，建成71个国家级海洋牧场。\n\n这些应用场景能够从“盆景”变成“风景”，离不开数字底座建设。**山东打造“数字大脑”，开发建设了全省农业农村综合性数字化管理服务平台——“齐鲁农云”，它汇聚全省29.4亿条涉农数据，完成388项资源目录分类治理，并建成片区建设、渔船渔港、远洋渔业等16个典型应用场景。**有了数据中枢，还要打通产销两端。“齐鲁农超”农副产品交易服务平台应运而生。目前，平台已入驻企业5600余家，活跃用户超10万人，线上线下融合交易额超2.5亿元，让数据不仅服务于生产，也直接服务于市场。\n\n技术要推广、场景要复制，离不开强有力的支撑保障。在优化顶层设计方面，省农业农村厅研究起草了《关于大力发展智慧农业的指导意见》，进一步明确“十五五”期间全省智慧农业建设时间表、路线图、任务书；在开展试点探索方面，会同省大数据局在40个县开展实数融合数字农业发展县建设；在强化产业融合方面，推动建立政府行业领军企业、高等院校及科研院所产研融合工作机制，搭建资源共享协同创新的合作交流平台，加快技术成果高效转化与应用与产业应用。\n\n实数融合注入现代农业发展新动能。当前，山东正积蓄起从“大”到“强”的深层动能，实数融合的“数字强音”在广袤沃野上愈发清晰而有力。\n\n（大众新闻记者 修从涛 吕乐 设计 杨雅晴 尹亚琪）","大众日报 \u002F 山东省农业农村厅 · 2026-07-24","2026-07-24T00:00:00Z",77,{"impact":87,"substance":88,"depth":18,"authority":89,"freshness":90,"relevant":21,"comment":91},24,22,11,2,"省级农业数字化成果综述，数据详实，场景丰富，但时效性不足。",[93],{"name":83,"url":80},[26,27,29,95,96],"应用场景","齐鲁农云",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":99},{"candidates":100,"agricultural_evidence":40,"reason":68},[101,105,110,116,122],{"code":38,"score":19,"supported":40,"title":102,"abstract":103,"tags":104},[27],[27,26],[26,27],{"code":45,"score":20,"supported":40,"title":106,"abstract":107,"tags":109},[],[108],"粮食安全",[],{"code":111,"score":20,"supported":40,"title":112,"abstract":113,"tags":115},"B7",[],[114],"温室",[],{"code":117,"score":20,"supported":40,"title":118,"abstract":119,"tags":121},"D2",[],[120],"海洋牧场",[],{"code":123,"score":20,"supported":40,"title":124,"abstract":125,"tags":127},"F4",[],[126],"植保",[],[129,130],"实数融合 应用场景 数字农业 智慧农业","实数融合 应用场景","实数融合应用场景数字农业智慧农业-15","2026-07-27T05:05:33.394525Z",{"id":134,"title":135,"url":136,"summary":137,"summary_zh":8,"content":8,"source_name":138,"source_url":8,"published_at":139,"category":140,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":141,"sources":145,"tags":147,"primary_topic":150,"secondary_topics":156,"classification":157,"search_phrases":180,"slug":183,"view_count":184,"doi":185,"paper":186,"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","论文",{"impact":142,"substance":18,"depth":19,"authority":143,"freshness":39,"relevant":21,"comment":144},12,13,"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。",[146],{"name":138,"url":136},[26,27,148,149],"技术采纳","农户行为",{"code":151,"slug":152,"name":153,"path":154,"parent_code":155},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":158,"locked":14,"version":33,"method":34,"evidence":159},"classified",{"candidates":160,"agricultural_evidence":40},[161,165,170,175],{"code":38,"score":143,"supported":40,"title":162,"abstract":163,"tags":164},[26],[26],[26,27],{"code":151,"score":20,"supported":40,"title":166,"abstract":167,"tags":169},[],[168],"大模型",[],{"code":171,"score":21,"supported":14,"title":172,"abstract":173,"tags":174},"G1",[],[],[148],{"code":176,"score":21,"supported":14,"title":177,"abstract":178,"tags":179},"G2",[],[],[149],[181,182],"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",0,"10.3389\u002Ffsufs.2026.1894648\u002Ffull",{"doi":185,"openalex_id":8,"authors":187,"venue":8,"cited_by_count":184,"oa_url":8,"card":188,"direction":192,"ingested_from":194},[],{"tldr":189,"method":190,"finding":191,"direction":192,"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。","数字乡村与农业信息化","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":140,"cover_url":8,"hotness":13,"is_selected":14,"score":204,"score_detail":205,"sources":208,"tags":210,"primary_topic":214,"secondary_topics":220,"classification":221,"search_phrases":248,"slug":251,"view_count":184,"doi":252,"paper":253,"created_at":269},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":88,"depth":18,"authority":142,"freshness":206,"relevant":21,"comment":207},9,"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":158,"locked":14,"version":33,"method":34,"evidence":222},{"candidates":223,"agricultural_evidence":40},[224,231,237,243],{"code":215,"score":225,"supported":40,"title":226,"abstract":228,"tags":230},14,[227],"coffee",[229,227],"咖啡",[],{"code":171,"score":75,"supported":40,"title":232,"abstract":233,"tags":236},[],[234,235],"农业推广","agricultural extension",[],{"code":38,"score":238,"supported":40,"title":239,"abstract":240,"tags":242},5,[],[241],"digital agriculture",[26,27],{"code":176,"score":20,"supported":40,"title":244,"abstract":245,"tags":247},[],[246],"农民合作社",[],[249,250],"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":252,"openalex_id":254,"authors":255,"venue":202,"cited_by_count":184,"oa_url":199,"card":262,"direction":267,"ingested_from":268},"W7223028195",[256,258,260],{"name":257,"orcid":8},"Kedir Biftu",{"name":259,"orcid":8},"Kebede Hailu",{"name":261,"orcid":8},"Tadila Tadessa Qajela",{"tldr":263,"method":264,"finding":265,"direction":192,"opportunity":266},"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。","智慧农业 \u002F 农业物联网","openalex","2026-10-21T23:30:08.879737Z",{"id":271,"title":272,"url":273,"summary":274,"summary_zh":275,"content":8,"source_name":202,"source_url":273,"published_at":203,"category":140,"cover_url":8,"hotness":13,"is_selected":14,"score":276,"score_detail":277,"sources":279,"tags":281,"primary_topic":285,"secondary_topics":291,"classification":292,"search_phrases":331,"slug":334,"view_count":184,"doi":335,"paper":336,"created_at":348},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":19,"substance":18,"depth":78,"authority":142,"freshness":206,"relevant":21,"comment":278},"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。",[280],{"name":202,"url":273},[26,27,282,283,284],"可持续发展","气候韧性","农业ICT",{"code":286,"slug":287,"name":288,"path":289,"parent_code":290},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":158,"locked":14,"version":33,"method":34,"evidence":293},{"candidates":294,"agricultural_evidence":40},[295,302,307,313,320,325],{"code":286,"score":18,"supported":40,"title":296,"abstract":298,"tags":301},[297],"climate resilience",[299,300,297],"气候变化","climate change",[283],{"code":38,"score":89,"supported":40,"title":303,"abstract":304,"tags":306},[],[305,26,241],"精准农业",[26,27],{"code":63,"score":75,"supported":40,"title":308,"abstract":309,"tags":312},[],[310,311],"土壤","soil",[],{"code":314,"score":75,"supported":40,"title":315,"abstract":316,"tags":319},"I3",[],[317,318],"遥感","remote sensing",[],{"code":176,"score":20,"supported":40,"title":321,"abstract":322,"tags":324},[],[323],"小农户",[],{"code":326,"score":20,"supported":40,"title":327,"abstract":328,"tags":330},"H3",[],[329],"水资源",[],[332,333],"Haryana 数字化转型","ICT 气候韧性","Haryana数字化转型-5476","10.5281\u002Fzenodo.23491288",{"doi":335,"openalex_id":337,"authors":338,"venue":202,"cited_by_count":184,"oa_url":273,"card":343,"direction":267,"ingested_from":268},"W7223011965",[339,341],{"name":340,"orcid":8},"Himani Rathi",{"name":342,"orcid":8},"Pardeep Kumar Duhan",{"tldr":344,"method":345,"finding":346,"direction":192,"opportunity":347},"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":350,"title":351,"url":352,"summary":353,"summary_zh":8,"content":8,"source_name":354,"source_url":352,"published_at":139,"category":140,"cover_url":8,"hotness":355,"is_selected":14,"score":356,"score_detail":357,"sources":359,"tags":363,"primary_topic":366,"secondary_topics":370,"classification":371,"search_phrases":378,"slug":381,"view_count":184,"doi":382,"paper":383,"created_at":395},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":39,"substance":75,"depth":39,"authority":75,"freshness":206,"relevant":21,"comment":358},"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。",[360,361],{"name":354,"url":352},{"name":354,"url":362},"https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.16146.41922",[26,27,364,365],"农业信息化","中非",{"code":38,"slug":367,"name":368,"path":369,"parent_code":155},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture",[],{"status":158,"locked":14,"version":33,"method":34,"evidence":372},{"candidates":373,"agricultural_evidence":40},[374],{"code":38,"score":225,"supported":40,"title":375,"abstract":376,"tags":377},[241],[241],[364,26,27],[379,380],"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":382,"openalex_id":384,"authors":385,"venue":8,"cited_by_count":184,"oa_url":352,"card":8,"direction":192,"ingested_from":268},"W7222930115",[386,388,390,393],{"name":387,"orcid":8},"Anani 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