[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1240":3,"related-1240":83},{"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":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":55,"slug":58,"view_count":19,"doi":59,"paper":60,"created_at":82},1240,"Food security governance in complex environments: how digital technologies can enhance the stability of agricultural food systems?","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1914452","Introduction The Chinese agricultural food system is confronted with multiple complex environmental challenges, such as extreme climate events and market fluctuations. Digital technology (DT), as a key element in reshaping the resilience of the entire value chain, provides important support for enhancing the stability of agricultural food systems (SAFS) and ensuring stable food consumption. Methods Based on panel data from 31 provinces in China from 2011 to 2023, this study employs a two-way fixed-effects model and a moderation model to examine the effect of DT on the SAFS. It further investigates regional heterogeneity in this effect and the moderating role of the urbanization rate (UR). Results First, DT has a significant positive effect on the SAFS. Second, the effect of DT exhibits regional heterogeneity, with a particularly pronounced positive effect in western China. Third, UR positively moderates the relationship between DT and the SAFS. Discussion The findings suggest that government departments should strengthen policy coordination and institutional support for the digital transformation of the agricultural food system, improve digital infrastructure and data governance, promote coordinated urbanization, and enhance resilience and risk-warning capabilities throughout the agricultural food value chain, thereby improving the capacity of agricultural food systems to cope with external risks and promoting sustainable agricultural development.",null,"Frontiers in Sustainable Food Systems","2026-08-26T00:00:00Z","论文",10,false,77,{"impact":16,"substance":16,"depth":17,"authority":18,"freshness":19,"relevant":20,"comment":21},22,18,13,2,1,"基于省级面板数据的实证研究，揭示数字技术对农业食物系统稳定性的促进作用及区域异质性，为政策制定提供依据。",[23],{"name":9,"url":6},[25,26,27,28,29],"智慧农业","粮食安全","农业韧性","数字技术","城镇化",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":38,"locked":13,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45},[43,50],{"code":31,"score":44,"supported":45,"title":46,"abstract":48,"tags":49},9,true,[47],"food security",[],[26],{"code":51,"score":19,"supported":13,"title":52,"abstract":53,"tags":54},"I1",[],[],[28,25],[56,57],"农业韧性 数字技术 智慧农业 粮食安全","农业韧性 数字技术","农业韧性数字技术智慧农业粮食安全-1240","10.3389\u002Ffsufs.2026.1914452",{"doi":59,"openalex_id":61,"authors":62,"venue":9,"cited_by_count":73,"oa_url":74,"card":75,"direction":79,"ingested_from":81},"W7204270185",[63,65,67,70],{"name":64,"orcid":8},"Yuang Guo",{"name":66,"orcid":8},"Yujie Yang",{"name":68,"orcid":69},"Qing Qin","https:\u002F\u002Forcid.org\u002F0000-0001-9176-5727",{"name":71,"orcid":72},"Ying Bai","https:\u002F\u002Forcid.org\u002F0000-0003-4887-2716",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1914452\u002Fpdf",{"tldr":76,"method":77,"finding":78,"direction":79,"opportunity":80},"研究数字技术对中国农业食物系统稳定性的影响及机制。","基于2011-2023年省级面板数据，采用双向固定效应和调节效应模型。","数字技术显著提升农业食物系统稳定性，西部效应更强，城镇化率正向调节。","农业人工智能与决策模型","可探索数字技术在不同农业子系统（如生产、供应链）中的差异化作用，以及与其他政策因素的交互效应。","openalex","2026-09-01T04:03:09.255875Z",{"total":84,"page":20,"page_size":84,"items":85},6,[86,166,234,324,398,464],{"id":87,"title":88,"url":89,"summary":90,"summary_zh":91,"content":8,"source_name":92,"source_url":89,"published_at":93,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":94,"sources":98,"tags":100,"primary_topic":104,"secondary_topics":105,"classification":118,"search_phrases":146,"slug":149,"view_count":20,"doi":150,"paper":151,"created_at":165},5308,"Geopolitics and food security: A comprehensive review of emerging risks and responses","https:\u002F\u002Fdoi.org\u002F10.51200\u002Fjsffs.v2i2.7666","This review paper examines the relationship between geopolitics and food security through a Systematic Literature Review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. A total of 15 peer-reviewed journal articles published between 2015 and 2026 were reviewed to identify emerging geopolitical risks and responses affecting global food systems. The study synthesizes literature on armed conflicts, trade restrictions, climate change, supply chain disruptions, energy market instability, and technological transformation in agriculture. The findings identified four major themes. First, geopolitical conflicts and protectionist trade policies significantly disrupt global food supply chains and increase food price volatility. Second, climate-related shock such as droughts, floods, and extreme weather events intensifies food insecurity, particularly in import-dependent and developing economies. Third, weaknesses in global logistics and energy dependence expose food systems to external shocks and market instability. Fourth, technological innovations, including smart farming, precision agriculture, and digital monitoring systems, play an increasingly important role in strengthening agricultural productivity, improving resource efficiency, and enhancing resilience against geopolitical and environmental uncertainties. The policy implications of this study include strengthening regional food reserves, diversifying import sources, investing in climate-resilient agriculture, promoting the adoption of smart farming technologies, and enhancing institutional cooperation between governments and international organizations. The relevance of smart farming is increasingly evident, as precision agriculture, Internet of Things (IoT)-based monitoring systems, and data-driven farming technologies play a critical role in improving productivity, reducing resource inefficiency, and enhancing food system resilience under geopolitical stress. The study contributes to a broader understanding of how geopolitical dynamics shape food security and provides recommendations for building sustainable, resilient, and technology-driven food systems in an increasingly uncertain global environment.","本文通过遵循系统评价与荟萃分析首选报告条目（Preferred Reporting Items for Systematic Reviews and Meta-Analyses）框架的系统文献综述，考察地缘政治与粮食安全之间的关系。共 review 了2015年至2026年间发表的15篇同行评审期刊论文，以识别影响全球粮食系统的新兴地缘政治风险与应对措施。本研究综合了关于武装冲突、贸易限制、气候变化、供应链中断、能源市场不稳定以及农业技术转型的文献。研究结果识别出四大主题。第一，地缘政治冲突和保护主义贸易政策显著扰乱全球粮食供应链并加剧粮食价格波动。第二，干旱、洪水和极端天气事件等气候相关冲击加剧粮食不安全，尤其是在依赖进口的经济体和发展中经济体中。第三，全球物流的薄弱环节和能源依赖使粮食系统暴露于外部冲击和市场不稳定之中。第四，包括智慧农业、精准农业和数字监测系统在内的技术创新，在增强农业生产力、提高资源效率以及增强应对地缘政治和环境不确定性的韧性方面发挥着日益重要的作用。本研究的政策启示包括加强区域粮食储备、多元化进口来源、投资气候韧性农业、促进智慧农业技术的采用，以及加强政府与国际组织之间的制度合作。智慧农业的相关性日益明显，因为精准农业、基于物联网（IoT）的监测系统和数据驱动农业技术在提高生产力、减少资源低效以及增强地缘政治压力下粮食系统韧性方面发挥着关键作用。本研究有助于更广泛地理解地缘政治动态如何塑造粮食安全，并为在日益不确定的全球环境中构建可持续、有韧性且技术驱动的粮食系统提供建议。","Journal of Smart Farming and Food Security","2026-10-19T00:00:00Z",{"impact":17,"substance":95,"depth":96,"authority":18,"freshness":44,"relevant":20,"comment":97},20,17,"系统综述梳理地缘政治与粮食安全风险，并强调智慧农业的韧性价值，具政策与产业参考意义，但属综述性论文，非突破性成果。",[99],{"name":92,"url":89},[25,101,26,102,103],"农业供应链","精准农业","地缘政治",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[106,112],{"code":107,"slug":108,"name":109,"path":110,"parent_code":111},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"code":113,"slug":114,"name":115,"path":116,"parent_code":117},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"status":38,"locked":13,"version":39,"method":40,"evidence":119},{"candidates":120,"agricultural_evidence":45},[121,126,132,139],{"code":31,"score":122,"supported":45,"title":123,"abstract":124,"tags":125},15,[47],[26,47],[26],{"code":51,"score":127,"supported":45,"title":128,"abstract":129,"tags":131},11,[],[25,102,130],"precision agriculture",[25,102],{"code":107,"score":44,"supported":45,"title":133,"abstract":134,"tags":138},[],[135,136,137],"气候变化","干旱","climate change",[],{"code":113,"score":44,"supported":45,"title":140,"abstract":141,"tags":145},[],[142,143,144],"物联网","internet of things","IoT",[],[147,148],"地缘政治 粮食安全","智慧农业 粮食系统韧性","地缘政治粮食安全-5308","10.51200\u002Fjsffs.v2i2.7666",{"doi":150,"openalex_id":152,"authors":153,"venue":92,"cited_by_count":73,"oa_url":89,"card":159,"direction":163,"ingested_from":81},"W7222902031",[154,156],{"name":155,"orcid":8},"Parameswaran Mahendran",{"name":157,"orcid":158},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":160,"method":161,"finding":162,"direction":163,"opportunity":164},"系统综述地缘政治风险对粮食安全的影响及应对，强调智慧农业的韧性作用。","按PRISMA框架系统综述2015-2026年15篇同行评议文献。","冲突、贸易限制、气候与能源冲击威胁粮食安全，智慧农业可提升韧性与效率。","智慧农业 \u002F 农业物联网","可量化研究物联网与精准农业在地缘政治冲击下对粮食系统韧性的实证贡献。","2026-10-19T23:30:07.850994Z",{"id":167,"title":168,"url":169,"summary":170,"summary_zh":8,"content":8,"source_name":171,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":172,"is_selected":13,"score":14,"score_detail":173,"sources":177,"tags":181,"primary_topic":185,"secondary_topics":186,"classification":187,"search_phrases":216,"slug":219,"view_count":84,"doi":220,"paper":221,"created_at":233},4969,"Digital technology, agricultural resilience, and food security: A mini review","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.2002109\u002Ffull","Shen在《Frontiers in Sustainable Food Systems》(2026)发表的综述综合了国际数字农业文献与中国'数字经济—农业经济韧性'研究两条主线。提出三点发现:一是数字技术通过不同机制强化食物安全的四个维度——可获得性(生产力与投入效率)、可及性(市场信息与数字金融)、稳定性(溯源、预警与保险)、利用性(溯源、营养信息与移动支付);二是准自然实验证据显示数字基础设施、数字金融和人工智能主要通过社会化服务、土地流转、产业融合、人力资本而非仅'采纳'提升粮食生产与价值链韧性;三是收益分布不均,空间溢出方向取决于吸收能力、市场整合与要素流动性。","Frontiers in Sustainable Food Systems 2026",25,{"impact":16,"substance":174,"depth":17,"authority":175,"freshness":19,"relevant":20,"comment":176},21,14,"核心期刊综述，系统梳理数字技术强化粮食安全四维度的机制与准自然实验证据，兼具国际文献与中国经验，但发布日期不明、时效性偏弱，适合作为主题页深度聚合素材。",[178,179],{"name":171,"url":169},{"name":9,"url":180},"https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.2002109",[182,26,27,183,184],"数字农业","空间溢出","数字金融",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":188},{"candidates":189,"agricultural_evidence":45},[190,194,201,206,211],{"code":31,"score":44,"supported":45,"title":191,"abstract":192,"tags":193},[47],[],[26],{"code":195,"score":84,"supported":45,"title":196,"abstract":197,"tags":200},"G2",[],[198,199],"土地流转","社会化服务",[],{"code":51,"score":202,"supported":45,"title":203,"abstract":204,"tags":205},4,[],[182],[182],{"code":207,"score":20,"supported":13,"title":208,"abstract":209,"tags":210},"G3",[],[],[184],{"code":212,"score":20,"supported":13,"title":213,"abstract":214,"tags":215},"I4",[],[],[183],[217,218],"Frontiers in Sustainable Food Systems 数字农业","数字技术 农业韧性 粮食安全","FrontiersinSustainableFoodSystems数字农业-4969","10.3389\u002Ffsufs.2026.2002109\u002Ffull",{"doi":220,"openalex_id":222,"authors":223,"venue":9,"cited_by_count":73,"oa_url":180,"card":227,"direction":231,"ingested_from":81},"W7223134273",[224],{"name":225,"orcid":226},"Yang Shen","https:\u002F\u002Forcid.org\u002F0000-0002-6781-6915",{"tldr":228,"method":229,"finding":230,"direction":231,"opportunity":232},"综述数字技术通过多机制强化食物安全四维度并提升农业韧性，但收益分布不均。","综合国际数字农业文献与中国数字经济—农业经济韧性研究两条主线。","数字技术经社会化服务、土地流转等提升韧性，收益不均且空间溢出取决于吸收能力。","数字乡村与农业信息化","可探究数字技术收益不均的成因及吸收能力、市场整合对空间溢出方向的调节机制。","2026-10-15T00:06:08.890950Z",{"id":235,"title":236,"url":237,"summary":238,"summary_zh":239,"content":8,"source_name":240,"source_url":237,"published_at":241,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":242,"score_detail":243,"sources":246,"tags":248,"primary_topic":253,"secondary_topics":254,"classification":260,"search_phrases":304,"slug":307,"view_count":73,"doi":308,"paper":309,"created_at":323},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",76,{"impact":17,"substance":95,"depth":96,"authority":18,"freshness":244,"relevant":20,"comment":245},8,"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。",[247],{"name":240,"url":237},[25,249,26,250,251,252],"撒哈拉以南非洲","气候智慧型农业","本土知识","数字创新",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[255],{"code":256,"slug":257,"name":258,"path":259,"parent_code":111},"H6","biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",{"status":38,"locked":13,"version":39,"method":40,"evidence":261},{"candidates":262,"agricultural_evidence":45},[263,267,274,281,287,294,299],{"code":31,"score":122,"supported":45,"title":264,"abstract":265,"tags":266},[47],[26,47],[26],{"code":256,"score":44,"supported":45,"title":268,"abstract":269,"tags":273},[],[270,271,257,272],"生物多样性","生态系统服务","ecosystem service",[],{"code":107,"score":275,"supported":45,"title":276,"abstract":277,"tags":280},7,[],[278,279],"气候适应","climate resilience",[250],{"code":195,"score":84,"supported":45,"title":282,"abstract":283,"tags":286},[],[284,285],"小农户","smallholder",[],{"code":288,"score":84,"supported":45,"title":289,"abstract":290,"tags":293},"H2",[],[291,292],"土壤","soil",[],{"code":51,"score":202,"supported":45,"title":295,"abstract":296,"tags":298},[],[297],"smart agriculture",[25],{"code":300,"score":20,"supported":13,"title":301,"abstract":302,"tags":303},"J3",[],[],[249],[305,306],"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":308,"openalex_id":310,"authors":311,"venue":240,"cited_by_count":73,"oa_url":237,"card":318,"direction":163,"ingested_from":81},"W7220921430",[312,315],{"name":313,"orcid":314},"Adetomiwa Kolapo","https:\u002F\u002Forcid.org\u002F0000-0002-0808-1293",{"name":316,"orcid":317},"Wale Ayojimi","https:\u002F\u002Forcid.org\u002F0000-0003-0038-3462",{"tldr":319,"method":320,"finding":321,"direction":231,"opportunity":322},"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。","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":325,"title":326,"url":327,"summary":328,"summary_zh":329,"content":8,"source_name":330,"source_url":327,"published_at":331,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":332,"score_detail":333,"sources":336,"tags":338,"primary_topic":341,"secondary_topics":342,"classification":343,"search_phrases":381,"slug":384,"view_count":19,"doi":385,"paper":386,"created_at":397},3826,"From Dry Fields To Smart Resilience: Climate-Smart Agriculture, Digital Early-Warning Systems And Household Food Security In Chivi District, Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.36923\u002Fsq.v3i1.435","This paper examines how climate-smart agriculture (CSA) and digital early-warning systems can jointly support household food-security resilience in Chivi District, a drought-prone area of south-eastern Zimbabwe dominated by rain-fed smallholder agriculture. Using a structured qualitative evidence synthesis with a district-centred case orientation, the study reviews 47 academic, policy and institutional sources published from 2021 to 14 September 2026. The study prioritises direct Chivi evidence, while using Zimbabwean, southern African, and wider African evidence comparatively where district-specific studies are limited. The synthesis identifies six interrelated themes concerning climate shocks, CSA adoption, small grains and water management, digital early warning, gender and institutional capacity, and integrated resilience. The findings indicate that CSA can strengthen food security when extension, inputs, finance, and markets support conservation agriculture, crop diversification, small grains, soil-fertility management, and water harvesting. However, digital early-warning information contributes to resilience only when it is timely, trusted, localised and translated into feasible action. Accordingly, the paper's principal contribution is an integrated smart-resilience framework centred on an information-to-action pathway: climate information can influence household food-security resilience only when farmers have viable adaptation options and the material, social and institutional capacity to act. The paper therefore treats digital information, agronomic adaptation, gender, household resources and local institutions as interdependent rather than separate interventions.","本文考察气候智慧型农业（climate-smart agriculture, CSA）与数字预警系统如何共同支撑津巴布韦东南部干旱易发区奇维（Chivi）地区以雨养小农农业为主的家庭粮食安全韧性。研究采用以地区为中心的案例导向结构化定性证据综合方法，梳理了2021年至2026年9月14日期间发表的47份学术、政策与机构文献。研究优先采用奇维地区的直接证据，在地区性专门研究有限时，则比较性地参考津巴布韦、南部非洲及更广泛非洲的证据。该综合识别出六个相互关联的主题，涉及气候冲击、气候智慧型农业采纳、小粒谷物与水资源管理、数字预警、性别与制度能力，以及综合韧性。研究结果表明，当推广服务、投入品、金融和市场支持保护性农业、作物多样化、小粒谷物、土壤肥力管理和集水时，气候智慧型农业能够增强粮食安全。然而，数字预警信息只有在及时、可信、本地化并转化为可行行动时，才能促进韧性。因此，本文的主要贡献在于提出了一个以信息到行动路径为核心的综合智慧韧性框架：气候信息只有在农民拥有可行的适应选项以及采取行动所需的物质、社会和制度能力时，才能影响家庭粮食安全韧性。据此，本文将数字信息、农艺适应、性别、家庭资源和地方制度视为相互依存的干预措施，而非彼此分离的干预措施。","Sustainability Quest","2026-09-29T00:00:00Z",56,{"impact":244,"substance":17,"depth":334,"authority":84,"freshness":244,"relevant":20,"comment":335},16,"以津巴布韦Chivi区为案例的定性证据综述，提出信息到行动的气候智慧农业韧性框架，对数字预警落地条件有参考价值，但属区域案例研究，公共影响有限。",[337],{"name":330,"url":327},[25,26,284,339,340],"气候智慧农业","数字预警",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":344},{"candidates":345,"agricultural_evidence":45},[346,350,355,360,364,368,375],{"code":31,"score":122,"supported":45,"title":347,"abstract":348,"tags":349},[47],[26,47],[26],{"code":51,"score":351,"supported":45,"title":352,"abstract":353,"tags":354},12,[297],[297],[25],{"code":107,"score":275,"supported":45,"title":356,"abstract":357,"tags":359},[],[136,358],"drought",[339],{"code":288,"score":84,"supported":45,"title":361,"abstract":362,"tags":363},[],[291,292],[],{"code":195,"score":202,"supported":45,"title":365,"abstract":366,"tags":367},[],[285],[284],{"code":369,"score":370,"supported":45,"title":371,"abstract":372,"tags":374},"H3",3,[],[373],"水资源",[],{"code":376,"score":370,"supported":45,"title":377,"abstract":378,"tags":380},"H8",[],[379],"conservation agriculture",[],[382,383],"气候智慧农业 数字预警 智慧农业 粮食安全","气候智慧农业 数字预警","气候智慧农业数字预警智慧农业粮食安全-3826","10.36923\u002Fsq.v3i1.435",{"doi":385,"openalex_id":387,"authors":388,"venue":330,"cited_by_count":73,"oa_url":327,"card":392,"direction":163,"ingested_from":81},"W7214743351",[389],{"name":390,"orcid":391},"Victor Madziyauswa","https:\u002F\u002Forcid.org\u002F0000-0002-6122-6666",{"tldr":393,"method":394,"finding":395,"direction":231,"opportunity":396},"综述津巴布韦Chivi地区气候智慧农业与数字预警系统如何共同提升家庭粮食安全韧性。","结构化定性证据综合，分析47份2021-2026年学术、政策与机构文献。","数字预警须及时、可信、本地化并转化为可行行动，且需配套适应选项与能力才能提升韧性。","可实证检验“信息—行动”路径，研究数字预警与农户适应能力、性别和制度条件的交互机制。","2026-09-30T23:30:09.849166Z",{"id":399,"title":400,"url":401,"summary":402,"summary_zh":403,"content":8,"source_name":9,"source_url":401,"published_at":404,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":405,"sources":407,"tags":409,"primary_topic":413,"secondary_topics":414,"classification":415,"search_phrases":443,"slug":446,"view_count":370,"doi":447,"paper":448,"created_at":463},3766,"The food security dividend: how green finance-induced rural revitalisation strengthens agricultural resilience","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1708484","Introduction Green finance (GF) has become crucial for improving agricultural infrastructure in rural areas. This study aims to identify the role of GF-induced rural revitalisation in enhancing agricultural resilience (AR). At the same time, the association between food security and AR is determined, followed by the impact of education and environmental regulation on AR. Methods The quantitative data were collected from the “Food and Agriculture Organisation of the United Nations” for different Asian countries (Cambodia, China, Pakistan, Myanmar, India, Indonesia, Laos, Mongolia, Nepal, Sri Lanka, the Philippines, Thailand, Uzbekistan and Vietnam). The selected timeframe ranged from 2012 to 2022. The descriptive statistics, correlation analysis and multiple old regression models were applied to the data. Results The results obtained show that GF, environmental regulation, and education boost agricultural productivity ( p \u003C 0.05), whereas higher climate risk reduces it. GF and rural income significantly improve productivity ( p \u003C 0.05), leading to an enhancement of AR. This helps in decreasing food insecurity. Environmental regulation and education are both key drivers of better productivity. AR has generally increased over the years with some ups and downs. Moreover, GF levels differ widely between countries. However, agricultural leaders such as China, Thailand, Indonesia and India tend to have stronger AR and GF. Higher education scores are associated with better agricultural productivity and stronger environmental regulations to attain AR. Finally, productivity levels vary greatly between the selected countries. Discussion This study emphasises the integration of GF in agricultural infrastructure to enhance AR and food security.","引言 绿色金融（GF）已成为改善农村地区农业基础设施的关键。本研究旨在明确绿色金融驱动的乡村振兴在增强农业韧性（AR）中的作用。同时，确定粮食安全与农业韧性之间的关联，并进一步探讨教育和环境规制对农业韧性的影响。方法 定量数据收集自联合国粮食及农业组织，涵盖多个亚洲国家（柬埔寨、中国、巴基斯坦、缅甸、印度、印度尼西亚、老挝、蒙古、尼泊尔、斯里兰卡、菲律宾、泰国、乌兹别克斯坦和越南）。所选时间范围为2012年至2022年。对数据应用了描述性统计、相关性分析和多元旧回归模型。结果 所得结果表明，绿色金融、环境规制和教育提升了农业生产力（p \u003C 0.05），而较高的气候风险则降低了农业生产力。绿色金融和农村收入显著提高了生产力（p \u003C 0.05），从而增强了农业韧性。这有助于减少粮食不安全。环境规制和教育都是提高生产力的关键驱动因素。农业韧性总体上多年来有所提升，但伴有起伏。此外，各国绿色金融水平差异较大。然而，中国、泰国、印度尼西亚和印度等农业领先国家往往具有更强的农业韧性和绿色金融。较高的教育得分与更好的农业生产力和更强的环境规制相关联，从而实现农业韧性。最后，所选国家之间的生产力水平差异很大。讨论 本研究强调将绿色金融纳入农业基础设施，以增强农业韧性和粮食安全。","2026-09-28T00:00:00Z",{"impact":17,"substance":174,"depth":96,"authority":18,"freshness":244,"relevant":20,"comment":406},"基于FAO多国面板数据的实证研究，揭示绿色金融通过乡村振兴提升农业韧性与粮食安全的机制，对农业信息化与农村金融政策有参考价值。",[408],{"name":9,"url":401},[410,26,27,411,412],"数字乡村","绿色金融","农村振兴",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":416},{"candidates":417,"agricultural_evidence":45},[418,422,428,434,438],{"code":31,"score":122,"supported":45,"title":419,"abstract":420,"tags":421},[47],[26,47],[26],{"code":423,"score":370,"supported":45,"title":424,"abstract":425,"tags":427},"G",[],[426],"乡村振兴",[],{"code":429,"score":370,"supported":45,"title":430,"abstract":431,"tags":433},"G6",[],[432],"rural income",[],{"code":207,"score":20,"supported":13,"title":435,"abstract":436,"tags":437},[],[],[411],{"code":439,"score":20,"supported":13,"title":440,"abstract":441,"tags":442},"I6",[],[],[410],[444,445],"绿色金融 农业韧性 粮食安全","亚洲 农业韧性 绿色金融","绿色金融农业韧性粮食安全-3766","10.3389\u002Ffsufs.2026.1708484",{"doi":447,"openalex_id":449,"authors":450,"venue":9,"cited_by_count":73,"oa_url":401,"card":457,"direction":461,"ingested_from":81},"W7214667116",[451,453,455],{"name":452,"orcid":8},"Zixiang Zhao",{"name":454,"orcid":8},"Chengcheng Lin",{"name":456,"orcid":8},"Po-Wen Tsai",{"tldr":458,"method":459,"finding":460,"direction":461,"opportunity":462},"研究绿色金融驱动的乡村振兴如何通过提升农业生产率增强农业韧性并保障粮食安全。","基于FAO 2012-2022年14个亚洲国家面板数据，用描述统计、相关分析和多","绿色金融、环境规制与教育显著提升农业生产率和农业韧性，气候风险则降低生产率。","农业绿色发展与碳","可深入探究绿色金融影响农业韧性的微观传导机制，并比较不同国家制度环境的调节效应。","2026-09-29T23:30:07.494934Z",{"id":465,"title":466,"url":467,"summary":468,"summary_zh":469,"content":8,"source_name":470,"source_url":467,"published_at":471,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":472,"score_detail":473,"sources":475,"tags":477,"primary_topic":481,"secondary_topics":482,"classification":494,"search_phrases":525,"slug":528,"view_count":370,"doi":529,"paper":530,"created_at":541},3613,"AI-Assisted Demand Forecasting and Production Scheduling for High-Volume Food Manufacturing in Saudi Arabia: A Food Security Framework for Vision 2030","https:\u002F\u002Fdoi.org\u002F10.64388\u002Firev10i3-1723457","High-volume food manufacturing in Saudi Arabia is increasingly exposed to volatile demand, short product life cycles, promotion-driven peaks, imported input dependencies, capacity bottlenecks, and the operational consequences of seasonal and religious events. These conditions make demand forecasting and production scheduling inseparable rather than sequential planning tasks. This review synthesizes research published between 2020 and 2025 on artificial intelligence-assisted demand forecasting, perishable-product planning, finite-capacity scheduling, digital-twin-enabled decision support, and food supply-chain resilience. The study develops an integrated framework in which demand sensing produces probabilistic forecasts that are translated into production decisions through capacity, shelf-life, sanitation, changeover, labour, inventory, and service constraints. Evidence indicates that machine-learning and deep-learning methods can improve forecast accuracy when promotions, weather, calendar events, regional variation, and censored demand are represented appropriately, while optimization models can convert these signals into feasible schedules that reduce changeovers, waste, shortages, and unstable resource use [1-8]. The review also identifies a persistent implementation gap: forecasting studies often stop at predictive accuracy, whereas scheduling studies frequently assume demand inputs are fixed and reliable. The proposed framework closes this gap by linking forecast uncertainty, rolling-horizon scheduling, execution feedback, and food-security outcomes. For Saudi manufacturers, the value of this integration lies not only in lower cost, but also in improving product availability, freshness, localized processing capacity, shock recovery, and evidence-based management under Vision 2030. The paper concludes with a staged implementation roadmap and research priorities for explainability, cross-site scheduling, event-aware forecasting, data governance, and resilient planning.","沙特阿拉伯的大规模食品制造日益面临需求波动、产品生命周期短、促销驱动的峰值、进口原料依赖、产能瓶颈以及季节性和宗教事件的运营影响。这些条件使得需求预测与生产调度成为不可分割的任务，而非顺序规划任务。本文综述了2020年至2025年间发表的相关研究，涵盖人工智能辅助需求预测、易腐产品规划、有限产能调度、数字孪生赋能的决策支持以及食品供应链韧性。研究构建了一个集成框架，其中需求感知产生概率预测，并通过产能、保质期、卫生、换产、劳动力、库存和服务约束转化为生产决策。证据表明，当促销、天气、日历事件、区域差异和截尾需求得到适当表征时，机器学习和深度学习方法能够提高预测精度，而优化模型可将这些信号转化为可行的调度方案，从而减少换产、浪费、缺货和不稳定的资源使用[1-8]。本综述还指出了一个持续存在的实施缺口：预测研究往往止步于预测精度，而调度研究则常常假设需求输入是固定且可靠的。所提出的框架通过将预测不确定性、滚动时域调度、执行反馈和食品安全结果联系起来，弥合了这一缺口。对于沙特制造商而言，这种集成的价值不仅在于降低成本，还在于改善产品可得性、新鲜度、本地化加工能力、冲击恢复能力以及“2030愿景”下的循证管理。本文最后提出了分阶段实施路线图以及可解释性、跨厂区调度、事件感知预测、数据治理和韧性规划方面的研究优先事项。","Iconic Research and Engineering Journals","2026-09-25T00:00:00Z",60,{"impact":351,"substance":17,"depth":334,"authority":84,"freshness":244,"relevant":20,"comment":474},"综述性论文，提出AI需求预测与生产排程整合框架，对智慧农业与粮食安全有参考价值，但属境外研究且期刊权威性一般。",[476],{"name":470,"url":467},[25,478,26,479,480],"农业人工智能","供应链韧性","生产调度",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[483,489],{"code":484,"slug":485,"name":486,"path":487,"parent_code":488},"E1","food-processing","加工与食品制造","\u002Ftopic\u002Ffood-supply\u002Ffood-processing","E",{"code":490,"slug":491,"name":492,"path":493,"parent_code":117},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":38,"locked":13,"version":39,"method":40,"evidence":495},{"candidates":496,"agricultural_evidence":45},[497,502,510,514,519],{"code":484,"score":127,"supported":45,"title":498,"abstract":500,"tags":501},[499],"food manufacturing",[499],[],{"code":490,"score":12,"supported":45,"title":503,"abstract":504,"tags":509},[],[505,506,507,508],"深度学习","机器学习","artificial intelligence","decision support",[478],{"code":31,"score":44,"supported":45,"title":511,"abstract":512,"tags":513},[47],[],[26],{"code":51,"score":202,"supported":45,"title":515,"abstract":516,"tags":518},[],[517],"数字孪生",[25],{"code":520,"score":370,"supported":45,"title":521,"abstract":522,"tags":524},"E4",[],[523],"食品安全",[],[526,527],"沙特阿拉伯 食品制造 需求预测","Vision 2030 粮食安全","沙特阿拉伯食品制造需求预测-3613","10.64388\u002Firev10i3-1723457",{"doi":529,"openalex_id":531,"authors":532,"venue":470,"cited_by_count":73,"oa_url":535,"card":536,"direction":163,"ingested_from":81},"W7214295236",[533],{"name":534,"orcid":8},"Atif Maqbool Syed","https:\u002F\u002Fwww.irejournals.com\u002Fformatedpaper\u002F1723457.pdf",{"tldr":537,"method":538,"finding":539,"direction":79,"opportunity":540},"综述2020-2025年AI需求预测与生产调度研究，提出沙特食品制造整合框架以保障Vision 20","文献综述2020-2025年AI预测、易腐品规划、有限产能调度与数字孪生研究。","预测研究止于精度、调度研究假设需求固定，整合框架可弥合实施鸿沟并提升粮食安全。","可研究事件感知预测与滚动调度耦合、跨工厂协同及可解释AI在食品供应链韧性中的应用。","2026-09-27T23:30:14.516185Z"]