[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4011":3,"related-4011":135},{"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":24,"tags":26,"primary_topic":9,"secondary_topics":32,"classification":33,"search_phrases":114,"slug":117,"view_count":118,"doi":119,"paper":120,"created_at":134},4011,"Climate-Smart Agriculture (CSA): An Alternative to Relief for Producers in Southeastern Benin","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijecc\u002F2026\u002Fv16i105711","Climate variability represents a major challenge for rain-fed agricultural production systems in southeastern Benin. This study analyses the relationships between climate variability, agro-climatic constraints, and crop production and examines potential adaptation and environmental sustainability options within the framework of Climate-Smart Agriculture (CSA). The methodological approach combines long-term rainfall data from Météo-Bénin, agricultural statistics from the Ministry of Agriculture, Livestock and Fisheries (MAEP) for the period 1995–2018, demographic and socio-economic data from the 2013 Population and Housing Census, and field surveys conducted among 205 farming households. The results show marked interannual rainfall variability, with 50% of the years analysed classified as dry, 38.16% as wet, and 11.84% as normal. However, no consistent relationship was found between annual rainfall totals and interannual variations in maize, cassava, cowpea, and groundnut yields. Crop performance appears to be more closely associated with rainfall distribution during the growing season and with the occurrence of critical events such as dry spells, delayed onset and early cessation of the rainy season, floods, and high-temperature events at sensitive stages of crop development. Farmers’ perceptions support this interpretation: delayed onset of the rainy season was the most frequently reported climatic constraint (25%), followed by early cessation of rainfall (20%). These disturbances can induce water stress and disrupt cropping calendars and crop development, thereby contributing to production losses and reduced farm income, with potential consequences for household food security. Adaptation options include the use of improved varieties (short-cycle and\u002For drought- and disease-resistant varieties), soil mulching (using crop residues or polyethylene film), and the Improved Production System (IPS)—involving crop sequencing and rotation—as well as sowing management (re-sowing, overseeding, stale seedbed techniques, dry sowing, and adjusting sowing dates). Agroforestry, capacity building for family farmers, and climate micro-insurance and safety nets for Climate-Smart Agriculture constitute the main mitigation measures in southern Benin. Overall, the results highlight the importance of combining climatic observations with farmers’ local knowledge to identify critical agro-climatic events better and support locally appropriate Climate-Smart Agriculture strategies.","气候变率对贝宁东南部雨养农业生产系统构成重大挑战。本研究分析了气候变率、农业气候限制因素与作物生产之间的关系，并在气候智慧型农业（Climate-Smart Agriculture, CSA）框架下探讨了潜在的适应对策与环境可持续性方案。研究方法结合了贝宁气象局（Météo-Bénin）的长期降雨数据、农业、畜牧与渔业部（MAEP）1995—2018年的农业统计数据、2013年人口与住房普查的人口与社会经济数据，以及对205个农户开展的实地调查。结果表明，降雨年际变率显著，所分析年份中有50%被归类为干旱年，38.16%为湿润年，11.84%为正常年。然而，年降雨总量与玉米、木薯、豇豆和花生产量的年际变化之间未发现一致的关系。作物表现似乎与生长季降雨分布以及关键事件的发生更为密切，如干旱期、雨季推迟到来和提前结束、洪水以及作物发育敏感期的高温事件。农户的感知支持这一解释：雨季推迟到来是报告频率最高的气候限制因素（25%），其次是降雨提前结束（20%）。这些扰动可引发水分胁迫，打乱种植历和作物发育，从而导致产量损失和农业收入下降，并可能对家庭粮食安全产生影响。适应对策包括使用改良品种（短周期和\u002F或抗旱、抗病品种）、土壤覆盖（利用作物残茬或聚乙烯薄膜）、改良生产体系（Improved Production System, IPS）——涉及作物接茬与轮作——以及播种管理（补种、过量播种、假播种技术、干播和调整播期）。农林复合经营、家庭农民能力建设以及气候小额保险和气候智慧型农业安全网构成了贝宁南部的主要缓解措施。总体而言，研究结果凸显了将气候观测与农户地方知识相结合的重要性，以更好地识别关键农业气候事件并支持因地制宜的气候智慧型农业策略。",null,"International Journal of Environment and Climate Change","2026-10-01T00:00:00Z","论文",10,false,71,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,13,8,1,"基于1995—2018年长期降雨与农业统计及205户农户调查，揭示降雨分布而非总量决定作物产量，并提出CSA适应与缓解措施，方法扎实、结论有参考价值，但属西非区域研究，对国内三农信息化直接借鉴有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"粮食安全","气候智慧型农业","农业适应","贝宁","雨养农业",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"needs_review","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":42,"reason":113},[39,47,54,61,69,76,83,90,96,102,108],{"code":40,"score":41,"supported":42,"title":43,"abstract":45,"tags":46},"I1",11,true,[44],"smart agriculture",[44],[],{"code":48,"score":49,"supported":42,"title":50,"abstract":51,"tags":53},"A8",7,[],[27,52],"food security",[27],{"code":55,"score":49,"supported":42,"title":56,"abstract":57,"tags":60},"H7",[],[58,59],"干旱","drought",[28],{"code":62,"score":63,"supported":42,"title":64,"abstract":65,"tags":68},"A3",6,[],[66,67],"玉米","maize",[],{"code":70,"score":63,"supported":42,"title":71,"abstract":72,"tags":75},"C",[],[73,74],"畜牧","livestock",[],{"code":77,"score":63,"supported":42,"title":78,"abstract":79,"tags":82},"H2",[],[80,81],"土壤","soil",[],{"code":84,"score":85,"supported":42,"title":86,"abstract":87,"tags":89},"A4",3,[],[88],"花生",[],{"code":91,"score":85,"supported":42,"title":92,"abstract":93,"tags":95},"A7",[],[94],"轮作",[],{"code":97,"score":85,"supported":42,"title":98,"abstract":99,"tags":101},"D",[],[100],"渔业",[],{"code":103,"score":85,"supported":42,"title":104,"abstract":105,"tags":107},"I7",[],[106],"研究方法",[],{"code":109,"score":22,"supported":14,"title":110,"abstract":111,"tags":112},"H3",[],[],[31],"多个产业证据相当，需要确认主归属",[115,116],"贝宁 气候智慧型农业 雨养农业","贝宁 玉米 木薯 产量 降雨","贝宁气候智慧型农业雨养农业-4011",4,"10.9734\u002Fijecc\u002F2026\u002Fv16i105711",{"doi":119,"openalex_id":121,"authors":122,"venue":10,"cited_by_count":125,"oa_url":6,"card":126,"direction":132,"ingested_from":133},"W7215083619",[123],{"name":124,"orcid":9},"Guy Cossi Wokou",0,{"tldr":127,"method":128,"finding":129,"direction":130,"opportunity":131},"分析贝宁东南部气候变率与作物产量关系，提出气候智慧型农业适应策略。","结合1995–2018年降雨与农业统计数据及205户农户调查。","产量与年降雨总量无关，更受雨季内降雨分布和关键极端事件影响。","农业绿色发展与碳","可研究将农户感知与气象观测融合，构建本地化关键农业气候事件预警指标。","智慧农业 \u002F 农业物联网","openalex","2026-10-02T23:30:11.924622Z",{"total":63,"page":22,"page_size":63,"items":136},[137,245,313,389,440,509],{"id":138,"title":139,"url":140,"summary":141,"summary_zh":142,"content":9,"source_name":143,"source_url":140,"published_at":144,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":145,"score_detail":146,"sources":150,"tags":152,"primary_topic":155,"secondary_topics":160,"classification":171,"search_phrases":228,"slug":231,"view_count":232,"doi":233,"paper":234,"created_at":244},3156,"Climate Adaptation and Sustainable Agriculture in Africa: Strategies for Food Security","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.11.no2.2025.pg8.32","This study investigates the role of Climate-Smart Agriculture (CSA) and agroecology in enhancing agricultural resilience and food security in the face of climate change in Africa. Through a comprehensive review of existing literature, case studies, and policy frameworks, the research explores how these adaptive strategies are being implemented across the continent and assesses their effectiveness. The findings reveal that while CSA techniques—such as droughtresistant crop varieties, water-efficient irrigation, and soil management practices—offer tangible benefits to agricultural productivity and resilience, their widespread adoption remains constrained by limited access to finance, inadequate infrastructure, and insufficient extension services. Similarly, agroecological approaches, including crop diversification, agroforestry, and organic farming, have proven successful in fostering sustainable agricultural practices and enhancing biodiversity, yet face significant challenges from prevailing agricultural policies and institutional frameworks that favor large-scale industrial agriculture. The study recommends scaling up the adoption of CSA and agroecology by improving access to financing, technology, and farmer training programs. It also advocates for policy reforms that support agroecological practices and climate adaptation, as well as increased investment in research and development. Additionally, fostering multi-stakeholder collaborations, including public-private partnerships, is critical to overcoming institutional barriers and ensuring the effective implementation of climate adaptation strategies. The conclusion underscores the need for integrated policy frameworks that combine the strengths of CSA and agroecology to build a resilient, sustainable, and food-secure agricultural sector in Africa. By addressing both environmental and socioeconomic challenges, these strategies can significantly contribute to combating the impacts of climate change on African agriculture, ensuring long-term food security and sustainable development.","本研究探讨了气候智能型农业（Climate-Smart Agriculture, CSA）和农业生态学在增强非洲农业应对气候变化韧性和粮食安全方面的作用。通过系统梳理现有文献、案例研究和政策框架，本研究考察了这些适应性策略在非洲大陆的实施情况并评估其有效性。研究发现，尽管气候智能型农业技术——如抗旱作物品种、节水灌溉和土壤管理措施——对提高农业生产力和韧性具有切实效益，但其广泛采用仍受限于融资渠道有限、基础设施不足和推广服务欠缺。同样，农业生态学方法，包括作物多样化、农林业和有机农业，已被证明在促进可持续农业实践和增强生物多样性方面卓有成效，但仍面临来自有利于大规模工业化农业的现行农业政策和制度框架的重大挑战。本研究建议通过改善融资渠道、技术获取和农民培训项目来扩大气候智能型农业和农业生态学的采用。研究还倡导支持农业生态实践和气候适应的政策改革，以及增加研发投入。此外，促进多方利益相关者合作，包括公私合作伙伴关系，对于克服制度障碍和确保气候适应策略的有效实施至关重要。结论强调，需要建立综合性政策框架，将气候智能型农业和农业生态学的优势相结合，以在非洲构建具有韧性、可持续且粮食安全的农业部门。通过同时应对环境和社会经济挑战，这些策略能够为抵御气候变化对非洲农业的影响、确保长期粮食安全和可持续发展作出重大贡献。","IIARD INTERNATIONAL JOURNAL OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT","2026-09-21T00:00:00Z",76,{"impact":147,"substance":148,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":149},18,20,"系统综述非洲气候智慧型农业与生态农业的适应策略及政策障碍，结论可靠但属文献综述，非突破性成果。",[151],{"name":143,"url":140},[27,153,28,29,154],"非洲农业","生态农业",{"code":48,"slug":156,"name":157,"path":158,"parent_code":159},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[161,167],{"code":162,"slug":163,"name":164,"path":165,"parent_code":166},"H8","sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture","H",{"code":55,"slug":168,"name":169,"path":170,"parent_code":166},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"status":172,"locked":14,"version":35,"method":36,"evidence":173},"classified",{"candidates":174,"agricultural_evidence":42},[175,180,186,193,203,207,213,218,222],{"code":48,"score":176,"supported":42,"title":177,"abstract":178,"tags":179},15,[52],[27,52],[27],{"code":162,"score":17,"supported":42,"title":181,"abstract":183,"tags":185},[182],"sustainable agriculture",[184],"可持续农业",[154],{"code":55,"score":13,"supported":42,"title":187,"abstract":188,"tags":192},[],[189,190,191],"气候变化","气候适应","climate change",[28],{"code":194,"score":195,"supported":42,"title":196,"abstract":197,"tags":202},"H6",9,[],[198,199,200,201],"生物多样性","农业生态","biodiversity","agroecology",[],{"code":77,"score":63,"supported":42,"title":204,"abstract":205,"tags":206},[],[80,81],[],{"code":109,"score":63,"supported":42,"title":208,"abstract":209,"tags":212},[],[210,211],"灌溉","irrigation",[],{"code":214,"score":118,"supported":42,"title":215,"abstract":216,"tags":217},"J3",[],[153],[153],{"code":40,"score":85,"supported":42,"title":219,"abstract":220,"tags":221},[],[44],[],{"code":223,"score":85,"supported":42,"title":224,"abstract":225,"tags":227},"J1",[],[226],"农业政策",[],[229,230],"气候智慧型农业 非洲","生态农业 粮食安全","气候智慧型农业非洲-3156",5,"10.56201\u002Fijgem.vol.11.no2.2025.pg8.32",{"doi":233,"openalex_id":235,"authors":236,"venue":143,"cited_by_count":22,"oa_url":9,"card":239,"direction":132,"ingested_from":133},"W7213982962",[237],{"name":238,"orcid":9},"Ayobami Samuel Owoyemi",{"tldr":240,"method":241,"finding":242,"direction":130,"opportunity":243},"综述气候智慧型农业与生态农业在非洲提升农业韧性与粮食安全的成效及障碍。","文献综述、案例研究与政策框架分析。","两类策略有效但受资金、基建、推广服务及政策偏向制约。","可量化评估CSA与生态农业在非洲不同区域的适配性与政策协同效果。","2026-09-22T23:30:10.505058Z",{"id":246,"title":247,"url":248,"summary":249,"summary_zh":250,"content":9,"source_name":251,"source_url":248,"published_at":252,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":253,"score_detail":254,"sources":257,"tags":259,"primary_topic":261,"secondary_topics":262,"classification":263,"search_phrases":296,"slug":299,"view_count":118,"doi":300,"paper":301,"created_at":312},2508,"Food Insecurity: The Hungry Face of Climate Change","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fjbgr.vol.11.no4.2025.pg88.95","Climate change is rapidly reshaping global food systems, intensifying food insecurity across both the Global North and South. Rising temperatures, erratic precipitation, extreme weather events, and land degradation are undermining agricultural productivity and destabilizing food access, particularly among marginalized and low-income populations. This paper examines the complex interplay between climate change and food insecurity, drawing on recent empirical studies and cross-regional data to analyze environmental, economic, and social dimensions. It highlights how climate-related disruptions disproportionately affect women, children, indigenous groups, and smallholder farmers, compounding existing structural inequities. The review evaluates current adaptation and mitigation efforts, including climate-smart agriculture, water resource management, and renewable energy integration. It also assesses policy gaps and proposes a holistic, equity-centered framework that integrates sustainable agriculture, community empowerment, and climate resilience. The study emphasizes the urgency of embedding food security into climate policy at all levels to safeguard livelihoods and promote sustainable development in an era of intensifying climate risk.","气候变化正在迅速重塑全球粮食系统，加剧全球北方和全球南方的粮食不安全。气温上升、降水异常、极端天气事件和土地退化正在削弱农业生产力并破坏粮食获取的稳定性，尤其是对边缘化和低收入群体而言。本文借鉴近期实证研究和跨区域数据，分析环境、经济和社会维度，考察气候变化与粮食不安全之间复杂的相互作用。文章强调，与气候相关的扰动对妇女、儿童、原住民群体和小农的影响尤为不成比例，并加剧了现有的结构性不平等。本文评估了当前的适应和减缓努力，包括气候智慧型农业、水资源管理和可再生能源整合。文章还评估了政策缺口，并提出一个以公平为中心的整体框架，将可持续农业、社区赋权和气候韧性相结合。研究强调，在气候风险日益加剧的时代，将粮食安全纳入各级气候政策以保障生计和促进可持续发展具有紧迫性。","JOURNAL OF BIOLOGY AND GENETIC RESEARCH","2026-09-14T00:00:00Z",78,{"impact":255,"substance":147,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":256},22,"跨区域综述揭示气候变化对全球粮食安全的系统性冲击，并提出以公平为核心的适应框架，对农业政策与气候韧性建设具参考价值。",[258],{"name":251,"url":248},[27,260,189,28,29],"小农户",{"code":55,"slug":168,"name":169,"path":170,"parent_code":166},[],{"status":172,"locked":14,"version":35,"method":36,"evidence":264},{"candidates":265,"agricultural_evidence":42},[266,272,276,282,286,292],{"code":55,"score":267,"supported":42,"title":268,"abstract":269,"tags":271},19,[191],[189,191,270],"climate resilience",[189,28],{"code":48,"score":49,"supported":42,"title":273,"abstract":274,"tags":275},[],[27,52],[27],{"code":109,"score":63,"supported":42,"title":277,"abstract":278,"tags":281},[],[279,280],"水资源","water resource",[],{"code":162,"score":63,"supported":42,"title":283,"abstract":284,"tags":285},[],[184,182],[],{"code":287,"score":118,"supported":42,"title":288,"abstract":289,"tags":291},"G2",[],[290],"smallholder",[260],{"code":40,"score":85,"supported":42,"title":293,"abstract":294,"tags":295},[],[44],[],[297,298],"气候智慧型农业 农业适应 气候变化 粮食安全","气候智慧型农业 农业适应","气候智慧型农业农业适应气候变化粮食安全-2508","10.56201\u002Fjbgr.vol.11.no4.2025.pg88.95",{"doi":300,"openalex_id":302,"authors":303,"venue":251,"cited_by_count":125,"oa_url":306,"card":307,"direction":132,"ingested_from":133},"W7212575816",[304],{"name":305,"orcid":9},"Ahmed Farida Mohammed","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FJBGR\u002FVOL. 11 NO. 4 2025\u002FFood Insecurity The Hungry 88-95.pdf",{"tldr":308,"method":309,"finding":310,"direction":130,"opportunity":311},"综述气候变化与粮食不安全的复杂关联，提出以公平为中心的综合应对框架。","基于近期实证研究与跨区域数据，分析环境、经济和社会维度。","气候冲击对妇女、儿童、原住民和小农影响尤甚，需将粮食安全嵌入各级气候政策。","可量化气候智能农业与水资源管理对弱势群体粮食安全的公平性效益，填补政策评估空白。","2026-09-15T23:30:08.313374Z",{"id":314,"title":315,"url":316,"summary":317,"summary_zh":318,"content":9,"source_name":319,"source_url":316,"published_at":320,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":145,"score_detail":321,"sources":323,"tags":325,"primary_topic":330,"secondary_topics":331,"classification":335,"search_phrases":368,"slug":371,"view_count":125,"doi":372,"paper":373,"created_at":388},4488,"Harnessing Indigenous Knowledge for Climate-Smart Agri-Food Systems: A Review of Adaptation Strategies, Food Security, Ecosystem Services, Governance, and Digital Innovation in Sub-Saharan Africa","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fconservation6040120","Sub-Saharan Africa (SSA) faces escalating climate challenges that threaten agricultural productivity, food security, ecosystem sustainability, and rural livelihoods. Indigenous knowledge (IK), developed through generations of interaction with local environments, offers context-specific and culturally embedded solutions for climate adaptation and resilient agri-food systems. This scoping review synthesizes evidence on the role of indigenous knowledge in advancing climate-smart agriculture (CSA) and resilient agri-food systems across SSA. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), the review analyzed 17 studies published between 2000 and 2026. The findings reveal that indigenous knowledge contributes significantly to climate resilience through traditional weather forecasting, crop diversification, indigenous seed preservation, agroforestry, water harvesting, soil fertility management, and community-based natural resource governance. These practices enhance food security, livelihood resilience, biodiversity conservation, and ecosystem service provision while strengthening adaptive capacity among smallholder farmers. The review further highlights the importance of inclusive governance frameworks, knowledge co-production, and policy support for integrating indigenous knowledge into climate adaptation and agricultural development strategies. Emerging digital technologies and innovation platforms also present opportunities for documenting, preserving, and scaling indigenous agricultural knowledge. However, challenges related to weak policy recognition, inadequate documentation, knowledge erosion, and limited digital infrastructure continue to constrain its effective utilization. The study concludes that integrating indigenous knowledge with scientific innovation is essential for building inclusive, sustainable, and climate-resilient agri-food systems in SSA.","撒哈拉以南非洲（Sub-Saharan Africa, SSA）面临日益加剧的气候挑战，威胁着农业生产力、粮食安全、生态系统可持续性和农村生计。土著知识（Indigenous Knowledge, IK）经由世代与当地环境的互动而积累，为气候适应和韧性农业食品系统提供了契合具体情境且深植于文化的解决方案。本范围综述综合了关于土著知识在推动撒哈拉以南非洲气候智慧型农业（Climate-Smart Agriculture, CSA）和韧性农业食品系统中作用的证据。在系统综述和荟萃分析首选报告条目扩展版——范围综述（PRISMA-ScR）的指导下，本综述分析了2000年至2026年间发表的17项研究。研究结果表明，土著知识通过传统天气预报、作物多样化、土著种子保存、农林业、集水、土壤肥力管理和社区为基础的自然资源治理，对气候韧性作出了显著贡献。这些实践增强了粮食安全、生计韧性、生物多样性保护和生态系统服务供给，同时强化了小农户的适应能力。本综述进一步强调了包容性治理框架、知识共同生产以及政策支持对于将土著知识纳入气候适应和农业发展战略的重要性。新兴数字技术和创新平台也为记录、保存和推广土著农业知识提供了机遇。然而，政策认可薄弱、记录不足、知识流失和数字基础设施有限等挑战持续制约着其有效利用。研究结论认为，将土著知识与科学创新相结合，对于在撒哈拉以南非洲构建包容、可持续且具有气候韧性的农业食品系统至关重要。","Conservation","2026-10-08T00:00:00Z",{"impact":147,"substance":148,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":322},"系统综述揭示本土知识与数字创新融合路径，对气候适应型农业与农业信息化有参考价值，但属区域研究、非国内政策事件。",[324],{"name":319,"url":316},[326,327,27,28,328,329],"智慧农业","撒哈拉以南非洲","本土知识","数字创新",{"code":48,"slug":156,"name":157,"path":158,"parent_code":159},[332],{"code":194,"slug":200,"name":333,"path":334,"parent_code":166},"生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",{"status":172,"locked":14,"version":35,"method":36,"evidence":336},{"candidates":337,"agricultural_evidence":42},[338,342,348,352,356,360,364],{"code":48,"score":176,"supported":42,"title":339,"abstract":340,"tags":341},[52],[27,52],[27],{"code":194,"score":195,"supported":42,"title":343,"abstract":344,"tags":347},[],[198,345,200,346],"生态系统服务","ecosystem service",[],{"code":55,"score":49,"supported":42,"title":349,"abstract":350,"tags":351},[],[190,270],[28],{"code":287,"score":63,"supported":42,"title":353,"abstract":354,"tags":355},[],[260,290],[],{"code":77,"score":63,"supported":42,"title":357,"abstract":358,"tags":359},[],[80,81],[],{"code":40,"score":118,"supported":42,"title":361,"abstract":362,"tags":363},[],[44],[326],{"code":214,"score":22,"supported":14,"title":365,"abstract":366,"tags":367},[],[],[327],[369,370],"撒哈拉以南非洲 本土知识 气候智慧型农业","撒哈拉以南非洲 气候智慧型农业 数字创新 智慧农业","撒哈拉以南非洲本土知识气候智慧型农业-4488","10.3390\u002Fconservation6040120",{"doi":372,"openalex_id":374,"authors":375,"venue":319,"cited_by_count":125,"oa_url":316,"card":382,"direction":132,"ingested_from":133},"W7220921430",[376,379],{"name":377,"orcid":378},"Adetomiwa Kolapo","https:\u002F\u002Forcid.org\u002F0000-0002-0808-1293",{"name":380,"orcid":381},"Wale Ayojimi","https:\u002F\u002Forcid.org\u002F0000-0003-0038-3462",{"tldr":383,"method":384,"finding":385,"direction":386,"opportunity":387},"综述撒哈拉以南非洲本土知识在气候智慧型农业与食物系统中的作用与挑战。","PRISMA-ScR范围综述，分析2000-2026年17项研究。","本土知识通过传统预报、作物多样化等提升气候韧性，但政策认可与数字化不足制约其应用。","数字乡村与农业信息化","可研究本土知识与数字技术协同的知识共生产机制，及适配小农的低成本数字化记录与传播工具。","2026-10-09T23:30:07.725864Z",{"id":390,"title":391,"url":392,"summary":393,"summary_zh":9,"content":9,"source_name":394,"source_url":392,"published_at":395,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":396,"score_detail":397,"sources":399,"tags":401,"primary_topic":403,"secondary_topics":408,"classification":409,"search_phrases":428,"slug":431,"view_count":118,"doi":432,"paper":433,"created_at":439},2924,"Climate-Smart Agriculture Package Combinations and Household Food and Nutrition Security among Smallholder Farmers in Southwestern Ethiopia","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11073051\u002Fv1","Climate-Smart Agriculture Package Combinations and Household Food and Nutrition Security among Smallholder Farmers in Southwestern Ethiopia。Research Square","Research Square","2026-09-18T00:00:00Z",56,{"impact":21,"substance":147,"depth":176,"authority":63,"freshness":195,"relevant":22,"comment":398},"研究主题契合气候智慧型农业与小农户粮食安全，但属区域性论文且来源为预印本平台，公共影响与权威性有限，暂不建议进入每日精选。",[400],{"name":394,"url":392},[27,260,28,402],"埃塞俄比亚",{"code":287,"slug":404,"name":405,"path":406,"parent_code":407},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[],{"status":172,"locked":14,"version":35,"method":36,"evidence":410},{"candidates":411,"agricultural_evidence":42},[412,416,420,424],{"code":287,"score":17,"supported":42,"title":413,"abstract":414,"tags":415},[290],[290],[260],{"code":40,"score":41,"supported":42,"title":417,"abstract":418,"tags":419},[44],[44],[],{"code":48,"score":22,"supported":14,"title":421,"abstract":422,"tags":423},[],[],[27],{"code":55,"score":22,"supported":14,"title":425,"abstract":426,"tags":427},[],[],[28],[429,430],"埃塞俄比亚 小农户 气候智慧型农业","气候智慧型农业 埃塞俄比亚 粮食安全 小农户","埃塞俄比亚小农户气候智慧型农业-2924","10.21203\u002Frs.3.rs-11073051\u002Fv1",{"doi":432,"openalex_id":434,"authors":435,"venue":394,"cited_by_count":125,"oa_url":392,"card":9,"direction":132,"ingested_from":133},"W7213535845",[436],{"name":437,"orcid":438},"Tesfaye Gafaro Ololo","https:\u002F\u002Forcid.org\u002F0009-0006-7838-5264","2026-09-19T23:30:10.838601Z",{"id":441,"title":442,"url":443,"summary":444,"summary_zh":445,"content":9,"source_name":446,"source_url":443,"published_at":447,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":448,"score_detail":449,"sources":451,"tags":453,"primary_topic":457,"secondary_topics":463,"classification":464,"search_phrases":491,"slug":494,"view_count":125,"doi":495,"paper":496,"created_at":508},5588,"Certified Temporal Fusion of Artificial Intelligence Climate Analytics for Crop Failure Early Warning Under Sparse Agricultural Sensors: Error Bounds and Famine Relief Targeting","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545489","Sparse agricultural sensor networks across sub-Saharan Africa leave crop-failure early-warning systems with too little ground observation to support reliable famine relief targeting. The framework treats sensor sparsity as a missing-data problem with a known observation operator and propagates climate-analytics uncertainty through a temporal Kalman-Buys filter whose gain is constrained by a certified risk envelope. Using NASA POWER monthly reanalysis for Accra, Ghana (2000-2023, 312 observations), the analysis establishes a mean temperature of 26.521 C and a warming trend of 0.1622 C per decade, which calibrates the climate-analytics prior. The derived bounds show that relief-targeting error scales with the square root of sensor density and with the Lipschitz constant of the crop-response function, yielding an explicit sensor-placement rule for a target misclassification rate. The contribution is a certified, assumption-explicit bridge between climate analytics and famine relief targeting that states the conditions under which early warning is trustworthy.","撒哈拉以南非洲稀疏的农业传感器网络使得作物歉收预警系统缺乏足够的地面观测数据，难以支撑可靠的饥荒救援目标定位。该框架将传感器稀疏性视为具有已知观测算子的缺失数据问题，并通过时间Kalman-Buys滤波器传播气候分析不确定性，该滤波器的增益受经认证的风险包络约束。利用NASA POWER对加纳阿克拉的月度再分析数据（2000—2023年，312个观测值），分析确定了平均气温为26.521°C、每十年0.1622°C的增暖趋势，据此校准了气候分析先验。推导出的界限表明，救援目标定位误差随传感器密度的平方根以及作物响应函数的Lipschitz常数缩放，从而为目标误分类率给出了明确的传感器布设规则。该研究的贡献在于构建了一个经认证的、假设明确的气候分析与饥荒救援目标定位之间的桥梁，阐明了早期预警可信赖的条件。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",74,{"impact":17,"substance":255,"depth":147,"authority":17,"freshness":13,"relevant":22,"comment":450},"该研究提出一种带误差界认证的时序融合方法，用于稀疏传感器条件下的作物歉收预警与饥荒救援瞄准，方法新颖、结论明确，但案例局限于加纳阿克拉，产业影响有限，适合作为技术前沿条目收录。",[452],{"name":446,"url":443},[326,454,27,455,456],"农业人工智能","遥感","气候分析",{"code":458,"slug":459,"name":460,"path":461,"parent_code":462},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":172,"locked":14,"version":35,"method":36,"evidence":465},{"candidates":466,"agricultural_evidence":42},[467,472,478,482,486],{"code":458,"score":195,"supported":42,"title":468,"abstract":470,"tags":471},[469],"artificial intelligence",[],[454],{"code":473,"score":85,"supported":42,"title":474,"abstract":475,"tags":477},"I5",[],[476],"农业传感",[],{"code":48,"score":22,"supported":14,"title":479,"abstract":480,"tags":481},[],[],[27],{"code":40,"score":22,"supported":14,"title":483,"abstract":484,"tags":485},[],[],[326],{"code":487,"score":22,"supported":14,"title":488,"abstract":489,"tags":490},"I3",[],[],[455],[492,493],"NASA POWER 加纳 气候分析","作物歉收 早期预警 传感器","NASAPOWER加纳气候分析-5588","10.5281\u002Fzenodo.23545489",{"doi":495,"openalex_id":497,"authors":498,"venue":446,"cited_by_count":125,"oa_url":443,"card":501,"direction":507,"ingested_from":133},"W7223111766",[499],{"name":500,"orcid":9},"Fatima-Zahra El Khattabi",{"tldr":502,"method":503,"finding":504,"direction":505,"opportunity":506},"提出带误差界的时间融合框架，在稀疏传感器下用气候分析预警作物歉收。","卡尔曼-布西滤波+NASA POWER再分析数据，风险包络约束增益。","救济瞄准误差随传感器密度平方根和作物响应Lipschitz常数缩放，给出布点规则。","农业遥感与作物表型","可将该认证误差界框架扩展到多作物多区域，结合卫星遥感弥补地面传感器稀疏。","农业人工智能与决策模型","2026-10-22T11:21:02.682497Z",{"id":510,"title":511,"url":512,"summary":513,"summary_zh":9,"content":514,"source_name":515,"source_url":9,"published_at":516,"category":517,"cover_url":9,"hotness":13,"is_selected":14,"score":518,"score_detail":519,"sources":522,"tags":524,"primary_topic":529,"secondary_topics":534,"classification":535,"search_phrases":556,"slug":559,"view_count":125,"doi":9,"paper":9,"created_at":560},5502,"全国秋粮收获超七成 中晚稻已收购1800万吨","https:\u002F\u002Fwww.peopleweekly.cn\u002Fhtml\u002F2026\u002Fsannong_1019\u002F279469.html","农业农村部最新农情调度显示，全国秋粮收获过七成，其中东北过六成，黄淮海、西南过八成，西北近八成，长江中下游过六成，华南过三成。冬小麦播种过一成，冬油菜播种过三成。国家粮食和物资储备局数据显示，各类经营主体已收购中晚稻1800万吨；秋粮产量占全年粮食产量约四分之三。","本报北京10月18日电  （记者郁静娴）据农业农村部最新农情调度，全国秋粮收获过七成。其中，东北过六成，黄淮海、西南过八成，西北近八成，长江中下游过六成，华南过三成。同时，各地秋冬种有序推进，冬小麦播种过一成，冬油菜播种过三成。\n\n本报北京10月18日电  （记者王东辉）记者从国家粮食和物资储备局获悉：各地秋粮旺季收购正有序展开。初步统计，各类经营主体已收购中晚稻1800万吨。\n\n当前秋粮已开始收获上市，秋粮产量占全年粮食产量的3\u002F4左右，涉及品种多、数量规模大、覆盖区域广。相关部门将加强秋粮收购工作统筹组织，抓好市场化收购和政策性收储，落实落细各项政策举措，全力保障农民售粮渠道顺畅、市场平稳运行。","人民日报 2026-10-19","2026-10-19T00:00:00Z","报道",85,{"impact":520,"substance":255,"depth":176,"authority":176,"freshness":49,"relevant":22,"comment":521},26,"全国性秋粮收获与收购权威数据，信息增量足、信源权威，时效稍滞后但值得进入每日精选。",[523],{"name":515,"url":512},[27,525,526,527,528],"冬小麦","秋粮收购","农情调度","中晚稻",{"code":530,"slug":531,"name":532,"path":533,"parent_code":159},"A2","wheat","小麦","\u002Ftopic\u002Ffield-crops\u002Fwheat",[],{"status":172,"locked":14,"version":35,"method":36,"evidence":536},{"candidates":537,"agricultural_evidence":42},[538,542,547,552],{"code":530,"score":118,"supported":42,"title":539,"abstract":540,"tags":541},[],[532],[525],{"code":84,"score":85,"supported":42,"title":543,"abstract":544,"tags":546},[],[545],"油菜",[],{"code":48,"score":548,"supported":14,"title":549,"abstract":550,"tags":551},2,[],[],[526,27],{"code":487,"score":22,"supported":14,"title":553,"abstract":554,"tags":555},[],[],[527],[557,558],"全国秋粮收获 中晚稻收购","国家粮食和物资储备局 秋粮收购","全国秋粮收获中晚稻收购-5502","2026-10-22T00:06:58.371818Z"]