[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-34":3,"related-34":44},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":22,"tags":24,"primary_topic":8,"secondary_topics":29,"classification":30,"search_phrases":37,"slug":40,"view_count":41,"doi":42,"paper":8,"created_at":43},34,"灾害多发地区食品集散中心商业模式框架：增强韧性与可持续运营绩效","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1870883\u002Ffull","在印度尼西亚西爪哇省（年均3,172起灾害、人口5,220万、灾害空间暴露强度124.18人\u002F平方公里\u002F事件）开展经验性定性案例研究，在三层商业模式画布（TLBMC）基础上新增韧性层，提出整合鲁棒性、适应性、恢复性和可重构性四维的韧性增强版框架，包含9个互相关联组件。研究发现食品集散中心作为去中心化聚合节点既能履行商业食品分销职能，又可在灾害中提供人道主义响应，通过双模式运营、应急储备、灵活渠道和针对性脆弱群体支持等机制实现可持续性。作者指出框架后续应通过基于代理的建模（ABM）和仿真方法在跨地区跨灾害情境下进一步验证。",null,"Frontiers in Sustainable Food Systems · 2026-07-24","2026-07-24T00:00:00Z","论文",10,false,74,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,12,4,1,"论文提出韧性增强版商业模式框架，结合印尼案例，对灾害多发地区农业供应链有参考价值，但时效性较差。",[23],{"name":9,"url":6},[25,26,27,28],"农业供应链","韧性","食品集散中心","印尼",[],{"status":31,"locked":13,"version":32,"method":33,"evidence":34},"needs_review","2026-10-22.2","rules",{"candidates":35,"agricultural_evidence":13,"reason":36},[],"农业相关性需要复核",[38,39],"食品集散中心 农业供应链 印尼 韧性","食品集散中心 农业供应链","食品集散中心农业供应链印尼韧性-34",15,"10.3389\u002Ffsufs.2026.1870883\u002Ffull","2026-07-28T03:05:27.086978Z",{"total":45,"page":20,"page_size":45,"items":46},6,[47,118,192,268,344,412],{"id":48,"title":49,"url":50,"summary":51,"summary_zh":52,"content":8,"source_name":53,"source_url":50,"published_at":54,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":55,"score_detail":56,"sources":61,"tags":63,"primary_topic":68,"secondary_topics":74,"classification":75,"search_phrases":93,"slug":96,"view_count":97,"doi":98,"paper":99,"created_at":117},5493,"Mapping Research on the Implementation of Smart Village Policies in Indonesia: A Bibliometric Study for the Years 2017-2025","https:\u002F\u002Fdoi.org\u002F10.66254\u002Fjgssvol5issue2page333-347","This research aims to analyze the role of public sector policies in the development of Smart Villages in Indonesia, focusing on the utilization of information and communication technology (ICT) to improve the quality of life in rural communities. Although the Indonesian government has launched various programs such as the Digital Village Program and Smart City, the implementation of these policies still faces various challenges, including limited infrastructure, low digital literacy, and lack of inter-agency coordination. This research uses a bibliometric approach to map relevant research and policy trends, as well as to identify challenges and opportunities in the development of Smart Villages. The research findings indicate that despite progress, existing public sector policies have not yet been fully effective in addressing the digital divide between villages and cities. This research recommends the need for more inclusive and integrated policy improvements, as well as strengthening human resource capacities in villages to support the creation of sustainable and competitive Smart Villages.","本研究旨在分析公共部门政策在印度尼西亚智慧村（Smart Villages）发展中的作用，重点关注利用信息通信技术（ICT）提升农村社区生活质量。尽管印度尼西亚政府已推出数字村计划（Digital Village Program）和智慧城市（Smart City）等多项举措，但这些政策的实施仍面临诸多挑战，包括基础设施有限、数字素养偏低以及跨机构协调不足。本研究采用文献计量学方法，梳理相关研究与政策趋势，并识别智慧村发展中的挑战与机遇。研究结果表明，尽管取得了一定进展，现有公共部门政策在弥合城乡数字鸿沟方面尚未充分发挥效用。本研究建议有必要进行更具包容性和整合性的政策改进，同时加强农村人力资源能力建设，以支持创建可持续且具有竞争力的智慧村。","Journal of Government Science Studies\u002FJournal Of Government Science Studies","2026-10-20T00:00:00Z",71,{"impact":57,"substance":16,"depth":41,"authority":58,"freshness":59,"relevant":20,"comment":60},16,13,9,"该文献计量研究系统梳理了印尼智慧乡村政策实施进展与数字鸿沟挑战，对数字乡村国际比较有参考价值，但属区域性研究，影响层级有限。",[62],{"name":53,"url":50},[64,28,65,66,67],"数字乡村","数字鸿沟","文献计量","智慧乡村",{"code":69,"slug":70,"name":71,"path":72,"parent_code":73},"I6","digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":76,"locked":13,"version":32,"method":33,"evidence":77},"classified",{"candidates":78,"agricultural_evidence":81},[79,86],{"code":80,"score":41,"supported":81,"title":82,"abstract":84,"tags":85},"I7",true,[83],"bibliometric",[66,83],[66],{"code":69,"score":87,"supported":81,"title":88,"abstract":89,"tags":92},11,[],[65,90,91],"digital village","digital divide",[64,65],[94,95],"印尼 智慧乡村","印尼 数字村 数字鸿沟","印尼智慧乡村-5493",0,"10.66254\u002Fjgssvol5issue2page333-347",{"doi":98,"openalex_id":100,"authors":101,"venue":53,"cited_by_count":97,"oa_url":50,"card":110,"direction":114,"ingested_from":116},"W7223067869",[102,104,107],{"name":103,"orcid":8},"Syaifulrijal Mahulauw",{"name":105,"orcid":106},"Wahab Tuanaya","https:\u002F\u002Forcid.org\u002F0009-0001-9236-8149",{"name":108,"orcid":109},"Marno Wance","https:\u002F\u002Forcid.org\u002F0000-0001-6663-7598",{"tldr":111,"method":112,"finding":113,"direction":114,"opportunity":115},"用文献计量法梳理2017-2025年印尼智慧村政策实施研究，识别挑战与机会。","文献计量分析，覆盖2017-2025年相关文献与政策趋势。","政策尚未有效弥合城乡数字鸿沟，需更包容整合的政策与人力建设。","数字乡村与农业信息化","可延伸至跨国比较或政策效果量化评估，聚焦数字鸿沟与跨部门协同机制。","openalex","2026-10-21T23:30:33.962760Z",{"id":119,"title":120,"url":121,"summary":122,"summary_zh":123,"content":8,"source_name":124,"source_url":121,"published_at":125,"category":11,"cover_url":8,"hotness":126,"is_selected":13,"score":127,"score_detail":128,"sources":131,"tags":136,"primary_topic":140,"secondary_topics":146,"classification":147,"search_phrases":173,"slug":176,"view_count":97,"doi":177,"paper":178,"created_at":191},5310,"Beyond Adjacency: Measuring Direct Evidence at the Intersection of Climate-Smart Agriculture and Nutrition. A Scoping Review and Evidence-Gap Map Copy","https:\u002F\u002Fdoi.org\u002F10.17605\u002Fosf.io\u002Fw8x7s","This Open Science Framework (OSF) repository provides the research protocol, search documentation, screening decisions, validation data, analytical code, evidence-gap maps, and supplementary materials supporting the systematic scoping review entitled \"Beyond Adjacency: Measuring Direct Evidence at the Intersection of Climate-Smart Agriculture and Nutrition.\" The review examines how climate-smart agriculture (CSA) research addresses food security and nutrition outcomes, with particular attention to remote island communities, rural food systems, and eastern Indonesia. It investigates the reliance on food-security proxies, geographical disparities, and the availability of direct evidence linking agricultural interventions, climate adaptation, and nutrition outcomes. Using a structured literature retrieval and three-anchor screening framework, the study identified 18,137 records for evidence mapping, including 1,033 records in the target and regional evidence tiers. Sixteen records met the four-dimensional intersection at metadata level, but none satisfied all direct-evidence criteria following full-text assessment. The repository supports research transparency and reproducibility by providing documented search strategies, record-level screening decisions, validation statistics, reproducible analytical scripts, and evidence-gap mapping outputs. The protocol is registered retrospectively, following completion of the review's screening and full-text assessment stages. **Research team:** Muaffan Alfaiz Wisaksono, Ani Kartikasari, and Astadi Pangarso.","本开放科学框架（OSF）存储库提供研究方案、检索文档、筛选决定、验证数据、分析代码、证据缺口图谱以及补充材料，用以支持题为“超越邻接性：测量气候智慧型农业与营养交叉领域的直接证据”的系统性范围综述。该综述考察气候智慧型农业（CSA）研究如何应对粮食安全与营养结果，特别关注偏远岛屿社区、农村粮食系统和印度尼西亚东部。它调查了对粮食安全替代指标的依赖、地理差异，以及将农业干预措施、气候适应与营养结果联系起来的直接证据的可获得性。该研究采用结构化文献检索和三锚点筛选框架，识别出18，137条记录用于证据图谱绘制，其中目标证据层级和区域证据层级共有1，033条记录。16条记录在元数据层面满足四维交叉条件，但在全文评估后，没有任何记录满足所有直接证据标准。该存储库通过提供有记录的检索策略、记录级筛选决定、验证统计数据、可复现的分析脚本和证据缺口图谱输出，支持研究透明性和可复现性。该方案是在综述的筛选和全文评估阶段完成后进行回顾性注册的。**研究团队：** Muaffan Alfaiz Wisaksono、Ani Kartikasari 和 Astadi Pangarso。","Open Science Framework","2026-10-18T00:00:00Z",25,67,{"impact":129,"substance":17,"depth":16,"authority":12,"freshness":59,"relevant":20,"comment":130},8,"该研究系统梳理气候智慧农业与营养交叉领域的直接证据缺口，方法严谨、数据规模大，但属预印本协议且地域聚焦印尼，公共影响有限，可作为专业参考而非每日精选头条。",[132,133],{"name":124,"url":121},{"name":134,"url":135},"OSF Preprints (OSF Preprints)","https:\u002F\u002Fosf.io\u002Fw8x7s",[28,137,138,139],"气候智慧农业","营养安全","证据图谱",{"code":141,"slug":142,"name":143,"path":144,"parent_code":145},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[],{"status":76,"locked":13,"version":32,"method":33,"evidence":148},{"candidates":149,"agricultural_evidence":81},[150,156,162,168],{"code":151,"score":87,"supported":81,"title":152,"abstract":154,"tags":155},"I1",[153],"smart agriculture",[153],[],{"code":141,"score":45,"supported":81,"title":157,"abstract":158,"tags":161},[],[159,160],"粮食安全","food security",[],{"code":163,"score":19,"supported":81,"title":164,"abstract":165,"tags":167},"H7",[],[166],"气候适应",[137],{"code":169,"score":20,"supported":13,"title":170,"abstract":171,"tags":172},"E2",[],[],[138],[174,175],"气候智慧农业 营养 证据图谱","印尼 农村食物系统 营养","气候智慧农业营养证据图谱-5310","10.17605\u002Fosf.io\u002Fw8x7s",{"doi":177,"openalex_id":179,"authors":180,"venue":124,"cited_by_count":97,"oa_url":121,"card":184,"direction":190,"ingested_from":116},"W7222887864",[181],{"name":182,"orcid":183},"Muaffan  Alfaiz Wisaksono","https:\u002F\u002Forcid.org\u002F0009-0009-9373-4882",{"tldr":185,"method":186,"finding":187,"direction":188,"opportunity":189},"综述气候智慧型农业与营养交叉领域的直接证据，发现证据严重缺失。","结构化文献检索与三锚筛选框架，映射18137条记录并做证据缺口分析。","仅16条记录达元数据四维交叉，全文评估后无一条满足直接证据标准。","农业绿色发展与碳","可填补气候智慧型农业干预与营养结果间直接证据的空白，尤其关注偏远岛屿与东部印尼农村食物系统。","智慧农业 \u002F 农业物联网","2026-10-19T23:30:07.976475Z",{"id":193,"title":194,"url":195,"summary":196,"summary_zh":197,"content":8,"source_name":198,"source_url":195,"published_at":199,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":200,"score_detail":201,"sources":205,"tags":207,"primary_topic":211,"secondary_topics":212,"classification":223,"search_phrases":249,"slug":252,"view_count":20,"doi":253,"paper":254,"created_at":267},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",77,{"impact":16,"substance":202,"depth":203,"authority":58,"freshness":59,"relevant":20,"comment":204},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。",[206],{"name":198,"url":195},[208,25,159,209,210],"智慧农业","精准农业","地缘政治",{"code":141,"slug":142,"name":143,"path":144,"parent_code":145},[213,218],{"code":163,"slug":214,"name":215,"path":216,"parent_code":217},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"code":219,"slug":220,"name":221,"path":222,"parent_code":73},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"status":76,"locked":13,"version":32,"method":33,"evidence":224},{"candidates":225,"agricultural_evidence":81},[226,230,235,242],{"code":141,"score":41,"supported":81,"title":227,"abstract":228,"tags":229},[160],[159,160],[159],{"code":151,"score":87,"supported":81,"title":231,"abstract":232,"tags":234},[],[208,209,233],"precision agriculture",[208,209],{"code":163,"score":59,"supported":81,"title":236,"abstract":237,"tags":241},[],[238,239,240],"气候变化","干旱","climate change",[],{"code":219,"score":59,"supported":81,"title":243,"abstract":244,"tags":248},[],[245,246,247],"物联网","internet of things","IoT",[],[250,251],"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":253,"openalex_id":255,"authors":256,"venue":198,"cited_by_count":97,"oa_url":195,"card":262,"direction":190,"ingested_from":116},"W7222902031",[257,259],{"name":258,"orcid":8},"Parameswaran Mahendran",{"name":260,"orcid":261},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",{"tldr":263,"method":264,"finding":265,"direction":190,"opportunity":266},"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。","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":269,"title":270,"url":271,"summary":272,"summary_zh":273,"content":8,"source_name":274,"source_url":271,"published_at":275,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":55,"score_detail":276,"sources":279,"tags":281,"primary_topic":285,"secondary_topics":290,"classification":291,"search_phrases":316,"slug":319,"view_count":320,"doi":321,"paper":322,"created_at":343},4219,"Cognitive Causal Modeling of Blockchain Adoption in Agri-Food Supply Chains: A Fuzzy-DEMATEL Approach","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12559-026-10660-0","Background \u002F Introduction: Blockchain can improve agri-food supply-chain transparency, but adoption decisions are cognitively complex because managers judge interdependent criteria under uncertainty. This study frames adoption as cognitive causal decision modeling, aligning with cognitive computation through expert judgment, linguistic uncertainty, causal reasoning, and explainable decision support. Methods: We applied Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to judgments from 20 experts. Eight technology-adoption criteria were modeled using triangular fuzzy numbers, and an impact relationship map was used to classify criteria by outgoing influence (R), incoming influence (C), prominence (R + C), and net causality (R − C). Results: Smart Contracts showed the strongest net causal influence (R = 3.46; R − C = + 0.78). Food Traceability was the most prominent criterion (R + C = 6.40) and the most influenced by other criteria (C = 3.17). Smart Contracts, Payment Transactions, Food Traceability, Fraud Prevention, and Secure Storage were net causes, whereas Food Waste Prevention, Carbon Emission Detection, and Power Consumption were net effects. Sensitivity analysis confirmed a stable cause\u002Feffect partition across threshold and prominence-cutoff variation, with Fraud Prevention the only criterion whose sign reverses at the lower fuzzy bound. Payment Transactions and Secure Storage sit close to the core-driving boundary. Conclusions: The findings support an explainable prioritization logic: transactional and information-security capabilities should be addressed before downstream sustainability outcomes. Because the evidence is expert-elicited rather than longitudinal field performance data, the results should be interpreted as structured decision-support guidance.","背景\u002F引言：区块链可以提高农业食品供应链的透明度，但其采纳决策在认知上较为复杂，因为管理者需要在不确定性下判断相互依赖的标准。本研究将采纳行为界定为认知因果决策建模，通过专家判断、语言不确定性、因果推理和可解释决策支持与认知计算相契合。方法：我们采用模糊决策试验与评价实验室方法（Fuzzy Decision-Making Trial and Evaluation Laboratory，Fuzzy-DEMATEL）对20位专家的判断进行分析。使用三角模糊数对八项技术采纳标准进行建模，并利用影响关系图按输出影响（R）、输入影响（C）、中心度（R + C）和净因果性（R − C）对标准进行分类。结果：智能合约表现出最强的净因果影响（R = 3.46；R − C = + 0.78）。食品追溯是最突出的标准（R + C = 6.40），也是受其他标准影响最大的标准（C = 3.17）。智能合约、支付交易、食品追溯、欺诈预防和安全存储为净原因，而食品浪费预防、碳排放检测和电力消耗为净结果。敏感性分析证实，在阈值和中心度截断值变化下，原因\u002F结果划分保持稳定，欺诈预防是唯一在较低模糊边界下符号发生反转的标准。支付交易和安全存储接近核心驱动边界。结论：研究结果支持一种可解释的优先排序逻辑：交易和信息安全能力应先于下游可持续性结果加以处理。由于证据来自专家 elicitation 而非纵向实地绩效数据，结果应被解释为结构化的决策支持指导。","Cognitive Computation","2026-10-02T00:00:00Z",{"impact":18,"substance":202,"depth":203,"authority":277,"freshness":129,"relevant":20,"comment":278},14,"核心期刊论文，用模糊DEMATEL方法对20位专家判断建模，识别智能合约与食品溯源为区块链采纳的关键驱动因素，方法新颖、结论有决策参考价值，但属专家主观判断而非实地数据，产业影响偏细分领域。",[280],{"name":274,"url":271},[208,25,282,283,284],"农产品溯源","区块链","决策支持",{"code":286,"slug":287,"name":288,"path":289,"parent_code":217},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon",[],{"status":76,"locked":13,"version":32,"method":33,"evidence":292},{"candidates":293,"agricultural_evidence":81},[294,300,306,312],{"code":286,"score":45,"supported":81,"title":295,"abstract":296,"tags":299},[],[297,298],"碳排放","carbon emission",[],{"code":301,"score":19,"supported":81,"title":302,"abstract":303,"tags":305},"E4",[],[304],"food traceability",[282],{"code":307,"score":19,"supported":81,"title":308,"abstract":309,"tags":311},"I2",[],[310],"decision support",[284],{"code":151,"score":20,"supported":13,"title":313,"abstract":314,"tags":315},[],[],[208],[317,318],"区块链 农产品供应链 溯源","Fuzzy-DEMATEL 区块链","区块链农产品供应链溯源-4219",3,"10.1007\u002Fs12559-026-10660-0",{"doi":321,"openalex_id":323,"authors":324,"venue":274,"cited_by_count":97,"oa_url":336,"card":337,"direction":190,"ingested_from":116},"W7216251074",[325,328,331,334],{"name":326,"orcid":327},"Ali Ala","https:\u002F\u002Forcid.org\u002F0000-0003-4552-4732",{"name":329,"orcid":330},"Behnam Malmir","https:\u002F\u002Forcid.org\u002F0000-0003-1771-9751",{"name":332,"orcid":333},"Hamed Baziyad","https:\u002F\u002Forcid.org\u002F0000-0002-5770-7766",{"name":335,"orcid":8},"Vladimir Simic","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs12559-026-10660-0.pdf",{"tldr":338,"method":339,"finding":340,"direction":341,"opportunity":342},"用模糊DEMATEL对20位专家判断建模，分析农业食品供应链区块链采纳的因果优先级。","模糊DEMATEL、三角模糊数、20位专家判断、敏感性分析","智能合约净因果影响最强，食品溯源最突出；交易与信息安全能力应先于可持续性结果。","农业人工智能与决策模型","可结合纵向田间绩效数据验证专家因果结论，并研究交易安全能力向碳减排等可持续结果的传导机制。","2026-10-05T23:30:12.085269Z",{"id":345,"title":346,"url":347,"summary":348,"summary_zh":349,"content":8,"source_name":350,"source_url":347,"published_at":351,"category":11,"cover_url":8,"hotness":12,"is_selected":81,"score":352,"score_detail":353,"sources":356,"tags":358,"primary_topic":8,"secondary_topics":362,"classification":363,"search_phrases":391,"slug":394,"view_count":367,"doi":395,"paper":396,"created_at":411},3535,"Policy coordination of public data openness and supercomputing center for agricultural chain resilience","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1882123","Strengthening agricultural supply chain resilience is critical for safeguarding food security and promoting high-quality agricultural development in the face of escalating external shocks, including climate extremes, market volatility, and geopolitical uncertainties. Although public data openness and supercomputing infrastructure represent critical pillars of digital transformation, how their coordinated deployment enhances agricultural resilience remains both theoretically underdeveloped and empirically underexamined. Using provincial panel data from 31 Chinese provinces over 2011–2024, we exploit the staggered rollout of public data platforms and supercomputing centers as quasi-natural experiments, constructing a synergistic difference-in-differences (DID) model to isolate their coordinated policy effects. The causal identification is further fortified using event-study parallel trend tests, placebo simulations, propensity score matching (PSM-DID), and double\u002Fdebiased machine learning (DDML). Our baseline estimates demonstrate that policy synergy between public data openness and supercomputing infrastructure substantially enhances agricultural supply chain resilience, with effects remaining robust across multiple specifications and economically significant. Mechanistic analysis reveals two primary transmission channels through which policy synergy strengthens resilience: (i) industrial structure rationalization, and (ii) agricultural electrification enhancement. Specifically, policy coordination (1) reduces informational barriers between agricultural and related industries, (2) facilitates optimal factor reallocation across sectors, and (3) accelerates the adoption of electricity-intensive precision agriculture technologies. Heterogeneity analysis reveals that policy effectiveness is substantially greater in central and western regions (coefficient ~0.089) compared to eastern regions (coefficient ~0.036), suggesting a ‘technology compensation effect’ whereby digital infrastructure offsets traditional regional disparities. Policy effects remain robustly positive across both major grain-producing and grain-consuming zones, indicating broad applicability. By unpacking the complementary and sequential dynamics between data factors and computing capacity, this study moves beyond the traditional “black box” treatment of the digital economy, providing critical policy insights for the coordinated deployment of digital public goods to secure modern food systems.","在气候极端事件、市场波动和地缘政治不确定性等外部冲击日益加剧的背景下，增强农业供应链韧性对于保障粮食安全和推动农业高质量发展至关重要。尽管公共数据开放和超算基础设施是数字化转型的关键支柱，但二者协同部署如何增强农业韧性，在理论上尚不成熟，在实证上也缺乏充分检验。本文利用2011—2024年中国31个省份的面板数据，将公共数据平台和超算中心的交错 rollout 作为准自然实验，构建协同双重差分（DID）模型以识别其协调政策效应。因果识别进一步通过事件研究平行趋势检验、安慰剂模拟、倾向得分匹配（PSM-DID）以及双重\u002F去偏机器学习（DDML）加以强化。基准估计表明，公共数据开放与超算基础设施之间的政策协同显著增强了农业供应链韧性，该效应在多种设定下保持稳健且具有经济显著性。机制分析揭示了政策协同增强韧性的两条主要传导渠道：（i）产业结构合理化，以及（ii）农业电气化水平提升。具体而言，政策协调（1）降低了农业与相关产业之间的信息壁垒，（2）促进了要素在部门间的优化再配置，（3）加速了电力密集型精准农业技术的采用。异质性分析表明，政策效果在中西部地区（系数约0.089）显著大于东部地区（系数约0.036），暗示存在“技术补偿效应”，即数字基础设施抵消了传统的区域差距。政策效应在粮食主产区和主销区均保持稳健为正，表明其具有广泛适用性。通过揭示数据要素与算力之间的互补性和序贯动态，本研究超越了数字经济传统的“黑箱”处理方式，为协调部署数字公共产品以保障现代粮食体系提供了关键政策启示。","Frontiers in Sustainable Food Systems","2026-09-25T00:00:00Z",85,{"impact":17,"substance":354,"depth":16,"authority":277,"freshness":129,"relevant":20,"comment":355},23,"基于31省面板数据的准自然实验，证实公共数据开放与超算中心协同显著提升农业供应链韧性，方法严谨、结论有政策价值，值得进入每日精选。",[357],{"name":350,"url":347},[64,25,359,360,361],"农业数字化","公共数据开放","超算中心",[],{"status":31,"locked":13,"version":32,"method":33,"evidence":364},{"candidates":365,"agricultural_evidence":81,"reason":390},[366,371,375,381,386],{"code":151,"score":367,"supported":81,"title":368,"abstract":369,"tags":370},7,[],[209,233],[359],{"code":141,"score":45,"supported":81,"title":372,"abstract":373,"tags":374},[],[159,160],[],{"code":307,"score":45,"supported":81,"title":376,"abstract":377,"tags":380},[],[378,379],"机器学习","machine learning",[],{"code":69,"score":19,"supported":81,"title":382,"abstract":383,"tags":385},[],[384],"数据要素",[64],{"code":73,"score":20,"supported":13,"title":387,"abstract":388,"tags":389},[],[],[359],"多个产业证据相当，需要确认主归属",[392,393],"公共数据开放 超算中心 农业供应链韧性","农业供应链韧性 准自然实验","公共数据开放超算中心农业供应链韧性-3535","10.3389\u002Ffsufs.2026.1882123",{"doi":395,"openalex_id":397,"authors":398,"venue":350,"cited_by_count":97,"oa_url":347,"card":406,"direction":114,"ingested_from":116},"W7214402306",[399,401,403],{"name":400,"orcid":8},"Zhaoqun Chen",{"name":402,"orcid":8},"Jiewen Zheng",{"name":404,"orcid":405},"Cheng Chi","https:\u002F\u002Forcid.org\u002F0000-0002-3823-6735",{"tldr":407,"method":408,"finding":409,"direction":114,"opportunity":410},"基于中国省级面板数据，用交错DID识别公共数据开放与超算中心协同对农业供应链韧性的因果效应。","2011–2024年31省面板数据，交错DID、PSM-DID、DDML与事件研","政策协同显著提升农业供应链韧性，经产业结构合理化与农业电气化传导，中西部效应更强。","可探究数据开放与算力协同的时序互补机制，并下沉到县域或产业链微观主体验证技术补偿效应。","2026-09-26T23:30:07.920756Z",{"id":413,"title":414,"url":415,"summary":416,"summary_zh":417,"content":8,"source_name":350,"source_url":415,"published_at":351,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":418,"score_detail":419,"sources":421,"tags":423,"primary_topic":427,"secondary_topics":428,"classification":430,"search_phrases":459,"slug":462,"view_count":20,"doi":463,"paper":464,"created_at":480},3531,"Extreme climate shocks and agricultural net carbon sinks: the moderating role of supply chain resilience in China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1940685","Introduction Extreme climate shocks increasingly challenge the ability of agricultural systems to sustain crop carbon fixation while controlling production-related emissions. Methods Using panel data for 240 Chinese cities from 2002 to 2023, this study examines the relationships between four climate shocks—extreme high temperature (HTD), extreme low temperature (LTD), extreme rainfall (ERD), and extreme drought (EED)—and agricultural net carbon sinks (NCS), together with the moderating role of agricultural supply chain resilience. NCS is measured as annual crop-biomass carbon fixation net of selected agricultural production emissions, thereby providing an integrated, production-based indicator of agricultural carbon performance. Results Two-way fixed-effects estimates show that all four climate shocks are negatively associated with NCS, and the direction of these relationships remains stable across alternative accounting boundaries, sample adjustments, leave-one-province-out tests, and double machine learning specifications. Agricultural supply chain resilience significantly conditions the climate–carbon relationship. Its resistance, recovery, and reorientation capacities attenuate the adverse associations of high-temperature, extreme-rainfall, and drought shocks with NCS. The low-temperature result further indicates that the effectiveness of resilience depends on matching supply chain functions with the biological mechanisms and intervention windows of specific climate hazards. Heterogeneity analyses confirm that climate sensitivity and resilience requirements vary with regional location, agricultural productivity, modernization, and irrigation conditions. Complementary machine-learning analysis identifies nonlinear predictive patterns and reinforces the importance of differentiated adaptation. Discussion These findings extend agricultural climate research from production and emissions to an integrated carbon-balance perspective and demonstrate that hazard-specific supply chain resilience can support both climate adaptation and low-carbon agricultural development.","引言 极端气候冲击日益挑战农业系统在维持作物碳固定的同时控制生产相关排放的能力。方法 本研究利用2002年至2023年中国240个城市的面板数据，考察四种气候冲击——极端高温（HTD）、极端低温（LTD）、极端降雨（ERD）和极端干旱（EED）——与农业净碳汇（NCS）之间的关系，以及农业供应链韧性的调节作用。NCS以年度作物生物量碳固定量扣除部分农业生产排放量来衡量，从而提供一个基于生产的综合性农业碳绩效指标。结果 双向固定效应估计表明，四种气候冲击均与NCS呈负相关，且这些关系的方向在替代核算边界、样本调整、逐一剔除省份检验和双重机器学习设定下均保持稳定。农业供应链韧性显著调节气候—碳关系。其抵抗能力、恢复能力和重新定向能力减弱了高温、极端降雨和干旱冲击与NCS之间的不利关联。低温结果进一步表明，韧性的有效性取决于供应链功能与特定气候灾害的生物机制及干预窗口的匹配。异质性分析证实，气候敏感性和韧性需求因区域位置、农业生产率、现代化水平和灌溉条件而异。补充性机器学习分析识别出非线性预测模式，并强化了差异化适应的重要性。讨论 这些发现将农业气候研究从生产和排放拓展至综合碳平衡视角，并表明针对特定灾害的供应链韧性能够同时支持气候适应和农业低碳发展。",80,{"impact":16,"substance":17,"depth":16,"authority":58,"freshness":59,"relevant":20,"comment":420},"基于240城22年面板数据的实证研究，方法扎实、结论稳健，对农业气候适应与低碳发展有参考价值，但属学术论文，公共传播性有限。",[422],{"name":350,"url":415},[208,25,424,425,426],"低碳农业","气候韧性","农业碳汇",{"code":163,"slug":214,"name":215,"path":216,"parent_code":217},[429],{"code":286,"slug":287,"name":288,"path":289,"parent_code":217},{"status":76,"locked":13,"version":32,"method":33,"evidence":431},{"candidates":432,"agricultural_evidence":81},[433,438,444,451,455],{"code":163,"score":12,"supported":81,"title":434,"abstract":435,"tags":437},[],[166,239,436],"drought",[425],{"code":286,"score":129,"supported":81,"title":439,"abstract":440,"tags":443},[],[441,442],"碳汇","农业碳",[424,426],{"code":445,"score":45,"supported":81,"title":446,"abstract":447,"tags":450},"H3",[],[448,449],"灌溉","irrigation",[],{"code":307,"score":45,"supported":81,"title":452,"abstract":453,"tags":454},[],[378,379],[],{"code":151,"score":20,"supported":13,"title":456,"abstract":457,"tags":458},[],[],[208],[460,461],"中国 农业净碳汇 极端气候","农业供应链韧性 气候适应","中国农业净碳汇极端气候-3531","10.3389\u002Ffsufs.2026.1940685",{"doi":463,"openalex_id":465,"authors":466,"venue":350,"cited_by_count":97,"oa_url":415,"card":475,"direction":188,"ingested_from":116},"W7214310732",[467,469,472],{"name":468,"orcid":8},"Chunyan Zhao",{"name":470,"orcid":471},"Jiajie Xia","https:\u002F\u002Forcid.org\u002F0000-0003-3225-0154",{"name":473,"orcid":474},"Guoping Ding","https:\u002F\u002Forcid.org\u002F0000-0002-4865-5044",{"tldr":476,"method":477,"finding":478,"direction":188,"opportunity":479},"基于240个城市2002-2023年面板数据，检验四类极端气候冲击对农业净碳汇的影响及供应链韧性的调","双向固定效应模型、双重机器学习，240城市面板数据，农业净碳汇指标。","四类极端气候冲击均降低农业净碳汇，供应链韧性可显著缓解高温、暴雨和干旱的负面影响。","可探究不同气候灾害下供应链韧性功能与生物机制匹配的差异化适应策略及非线性预测。","2026-09-26T23:30:07.569768Z"]