[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-378":3,"related-378":54},{"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":29,"secondary_topics":35,"classification":36,"search_phrases":49,"slug":52,"view_count":20,"doi":8,"paper":8,"created_at":53},378,"物联网区块链提升资金受限的绿色农业供应链的韧性——基于Stackelberg博弈分析","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260806103759189.htm","研究构建了由资金约束农户、企业和银行组成的绿色农业供应链博弈模型,采用Stackelberg博弈框架分析信息对称和信息不对称两种情形下,传统采购订单融资(TPOF)与基于区块链物联网(BPOF)对供应链韧性的影响。研究发现,BoT通过三大机制提升韧性:扩大高融资需求农户的融资可及性、在特定条件下重新分配供应链利润、优化信息不对称下的成本信息传递。但BoT并非始终优于TPOF,在传统作物价格极低时TPOF下的韧性更高。案例研究基于上市公司宏辉果蔬的公开数据,样本覆盖山东寿光、福建漳州等22个县的218户合作农户。",null,"《NJAS: Impact in Agricultural and Life Sciences》：Blockchain of Things Enhances Resilience of Capital-Constrained Green Agricultural Supply Chains\n\n_【字体： 大 中 小 】_ _时间：2026年08月06日_ _来源：NJAS: Impact in Agricultural and Life Sciences 1.6_\n\n融资约束和绿色产出的波动性是导致绿色农业供应链韧性低的关键因素。本研究开发了一个新颖的博弈论框架，以研究区块链物联网（Blockchain of Things, BoT）如何增强资金约束型绿色农业供应链的韧性。通过比较传统采购订单融资（Traditional Purchase Order Financing, TPOF，依赖于固定资产抵押并承担价格信号的高成本）与基于BoT的采购订单融资（BoT-based Purchase Order Financing, BPOF，利用流动资产抵押并实现可验证的努力信号），研究人员发现BoT可以通过以下三种核心机制增强供应链韧性：（1）当传统作物价格较高时，它通过允许高融资需求的农户参与融资过程来扩大融资可及性；（2）在特定市场条件下，它促进供应链利润的有利再分配；（3）当关于绿色努力成本存在信息不对称时，BoT对高效和低效农户的供应韧性产生显著异质性影响，且BPOF可以通过优化成本信息的传递机制来增强韧性。然而，当传统作物价格极低时，TPOF下的供应链韧性更高。本研究的发现可以为农业利益相关者提供管理建议，并促进农业的数字化和绿色转型。\n\n**论文解读：区块链物联网（BoT）增强资金约束型绿色农业供应链韧性的研究**\n\n**研究背景与问题** \n\n绿色农业产品因其环境友好属性受到政府和消费者的日益关注，但其供应在数量和质量上均表现出显著的韧性不足。联合国数据显示，小农户是大多数发展中国家的主要生产力量，但他们普遍面临严重的收入约束，需要外部融资来覆盖绿色农业生产的较高成本。然而，传统采购订单融资（TPOF）模式下，银行常因农户缺乏可抵押固定资产、信用体系薄弱以及绿色产出不确定性而拒绝贷款。同时，非货币性绿色努力（如精细育苗、科学灌溉、轮作等）的投入难以监测，导致信息不透明，进一步加剧了融资困难。区块链物联网（BoT）技术通过整合物联网传感器和区块链不可篡改特性，为实时监控农户生产行为、实现流动资产抵押提供了可能，从而有望解决上述问题。本研究旨在探讨BoT如何通过改变融资模式和信息传递机制，增强资金约束型绿色农业供应链的韧性。\n\n**研究内容与结论** \n\n研究人员构建了一个由资金约束农户、企业和银行组成的绿色农业供应链博弈模型，采用Stackelberg博弈框架，分析信息对称和信息不对称两种情形下，TPOF与基于BoT的采购订单融资（BPOF）对供应链韧性的影响。研究发现，BoT通过三大机制提升韧性：扩大高融资需求农户的融资可及性、在特定条件下重新分配供应链利润、以及优化信息不对称下的成本信息传递。但BoT并非始终优于TPOF，在传统作物价格极低时，TPOF下的韧性更高。论文发表在《NJAS: Impact in Agricultural and Life Sciences》，为农业利益相关者提供了数字化与绿色转型的管理建议。\n\n**主要关键技术方法** \n\n研究采用博弈论方法，包括Stackelberg博弈和信号博弈，构建了包含企业（领导者）、农户（追随者）和银行的三方决策模型。在信息对称情形下，求解最优合同参数（批发价格、绿色努力水平、利率）；在信息不对称情形下，通过分离均衡分析价格信号（TPOF）和投入信号（BPOF）的传递机制。案例研究基于上市公司宏辉果蔬（Honghui Fruit and Vegetable Co., Ltd.）的公开数据，样本覆盖山东寿光、福建漳州等22个县的218户合作农户，并结合农业银行、蚂蚁链等机构的数据进行验证。\n\n**研究结果**\n\n**4. 信息对称情形** \n\n**4.1 传统采购订单融资（TPOF）** \n\n通过求解逆向归纳的Stackelberg博弈，得到最优合同和均衡结果。当农户融资需求较低时，企业可提供有效合同；若传统农产品价格高于抵押品价值，农户有动力增加绿色努力以提高供应弹性；若价格较低，企业需扭曲批发价格以确保农户获得保留收益。绿色努力水平与替代采购成本（z）正相关，与普通农产品价格（w 0）、绿色努力成本系数（k）负相关，与抵押品价值（c）正相关。\n\n**4.2 基于BoT的采购订单融资（BPOF）** \n\n类似地，求解BPOF下的均衡。当融资需求高且普通农产品价格低时，企业不会从农户采购；仅当融资需求低或价格高时，合同可行。绿色努力水平的影响因素与TPOF一致，但农户始终获得超额收益而非保留收益。\n\n**4.3 TPOF与BPOF的比较** \n\n通过对比发现，BoT在两种情况下提升韧性：（1）当普通农产品价格高于抵押品价值且融资需求低时，BPOF可重新分配利润（企业利润转向农户或反之），而不改变总供应链利润和绿色努力；（2）当普通农产品价格高且融资需求高时，仅有BPOF可行，使高融资需求农户参与绿色生产。但当普通农产品价格低且融资需求高时，仅有TPOF可行；当两者均低时，TPOF下的绿色努力高于BPOF，但企业利润更低。\n\n**5. 信息不对称情形** \n\n**5.1 价格信号：通过TPOF方式借款** \n\n在信息不对称下，企业通过批发价格向银行传递农户成本类型信号。求解分离均衡发现，仅当融资需求低时企业从高效农户采购。当普通农产品价格低时，企业无需支付信息租金；价格中等时，需扭曲价格以区分类型；价格高时，同样需扭曲但不会将低效农户伪装为高效。绿色努力水平受z、w 0、c和融资需求（m-c）的影响。\n\n**5.2 投入信号：通过BPOF方式借款** \n\nBoT使银行可直接观察农户绿色努力水平。求解分离均衡表明，当融资需求较低时，存在无成本分离均衡；融资需求中等时，企业需提供更高价格以激励农户投入更多绿色努力，支付信息租金；融资需求高时，无分离均衡。绿色努力水平与z和m正相关，与w 0 负相关。\n\n**5.3 价格信号与投入信号的比较** \n\n比较两种融资模式，BoT在信息不对称下改变了信息传递渠道。当普通农产品价格高于抵押品价值时，企业通过BPOF获得更高利润；当价格低于抵押品价值但利差较小时，BPOF仍可能更优，因为BoT增加信息造假难度。此外，在融资需求高且价格高时，仅有BPOF存在分离均衡；在融资需求高且价格低时，仅有TPOF存在分离均衡。对于高效农户，当普通农产品价格较高或略低于抵押品价值时，BPOF下的供应中断概率更低，但企业利润更高；当价格显著低于抵押品价值时，TPOF下的供应韧性更高。\n\n**6. 案例研究** \n\n以宏辉果蔬为例，验证理论模型。数据来源包括企业年报、农业银行报告、农业农村部统计及蚂蚁链技术认证。通过比较BPOF组（36户）与TPOF组（53户），发现BPOF模式下农户融资参与率从26.4%提升至83.3%，平均贷款利率从7.4%降至4.75%，企业采购成本降低12.3%，供应链利润率提升2.9个百分点，绿色生产投入比例从11.2%增至29.8%，农药残留合格率从88.7%升至98%。案例证实了BoT在中等以上普通农产品价格且高融资需求情景下的有效性。\n\n**讨论与结论** \n\n**总结讨论**：BoT技术通过引入流动资产抵押和可验证的绿色努力信号，解决了传统融资中固定资产抵押不足和信息不对称问题。在信息对称下，BoT通过扩大融资范围、重新分配利润提升韧性，但并非万能；在信息不对称下，BoT通过改变信号传递机制，使企业在特定条件下获得更高利润，但绿色努力水平可能低于TPOF。案例进一步验证了理论结果。\n\n**研究结论**（翻译） \n\n（1）在信息对称下，当农户融资需求高且普通农产品价格高时，企业仅能通过BPOF采购绿色农产品，BoT扩大了农户参与；当融资需求低且价格高时，BoT可重新分配利润而不改变总利润和绿色努力；当融资需求低且价格低时，TPOF下的绿色努力更高。（2）在信息不对称下，当普通农产品价格高或融资需求高时，BPOF使企业更易获得分离均衡，而TPOF在价格低时占优；BoT改变了信息传递渠道，使得在普通农产品价格略低于抵押品价值时，企业通过BPOF获得更高利润，但农户绿色努力较小。总体而言，BoT通过增强融资可及性、优化利润分配和改善信息传递，有效提升了资金约束型绿色农业供应链的韧性，但需结合具体市场条件选择融资模式。","NJAS: Impact in Agricultural and Life Sciences 2026-08-06","2026-08-06T00:00:00Z","论文",10,false,76,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,5,1,"论文提出BoT增强绿色农业供应链韧性的博弈模型，有理论创新和案例验证，但发表于国际期刊，国内影响有限。",[24],{"name":10,"url":6},[26,27,28],"农业供应链","区块链","Stackelberg NJAS",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":37,"locked":14,"version":38,"method":39,"evidence":40},"classified","2026-10-22.2","rules",{"candidates":41,"agricultural_evidence":44},[42],{"code":30,"score":43,"supported":44,"title":45,"abstract":47,"tags":48},11,true,[46],"物联网",[46],[],[50,51],"农业供应链 区块链 Stackelberg NJAS","农业供应链 区块链","农业供应链区块链StackelbergNJAS-378","2026-08-10T23:54:46.320601Z",{"total":55,"page":21,"page_size":55,"items":56},6,[57,142,246,309,379,439],{"id":58,"title":59,"url":60,"summary":61,"summary_zh":62,"content":8,"source_name":63,"source_url":60,"published_at":64,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":65,"score_detail":66,"sources":71,"tags":73,"primary_topic":78,"secondary_topics":84,"classification":92,"search_phrases":120,"slug":123,"view_count":21,"doi":124,"paper":125,"created_at":141},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":17,"substance":67,"depth":68,"authority":19,"freshness":69,"relevant":21,"comment":70},20,17,9,"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。",[72],{"name":63,"url":60},[74,26,75,76,77],"智慧农业","粮食安全","精准农业","地缘政治",{"code":79,"slug":80,"name":81,"path":82,"parent_code":83},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[85,91],{"code":86,"slug":87,"name":88,"path":89,"parent_code":90},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},{"status":37,"locked":14,"version":38,"method":39,"evidence":93},{"candidates":94,"agricultural_evidence":44},[95,101,107,114],{"code":79,"score":96,"supported":44,"title":97,"abstract":99,"tags":100},15,[98],"food security",[75,98],[75],{"code":102,"score":43,"supported":44,"title":103,"abstract":104,"tags":106},"I1",[],[74,76,105],"precision agriculture",[74,76],{"code":86,"score":69,"supported":44,"title":108,"abstract":109,"tags":113},[],[110,111,112],"气候变化","干旱","climate change",[],{"code":30,"score":69,"supported":44,"title":115,"abstract":116,"tags":119},[],[46,117,118],"internet of things","IoT",[],[121,122],"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":124,"openalex_id":126,"authors":127,"venue":63,"cited_by_count":133,"oa_url":60,"card":134,"direction":138,"ingested_from":140},"W7222902031",[128,130],{"name":129,"orcid":8},"Parameswaran Mahendran",{"name":131,"orcid":132},"Wong Sing Yun","https:\u002F\u002Forcid.org\u002F0000-0001-5776-8852",0,{"tldr":135,"method":136,"finding":137,"direction":138,"opportunity":139},"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。","openalex","2026-10-19T23:30:07.850994Z",{"id":143,"title":144,"url":145,"summary":146,"summary_zh":147,"content":8,"source_name":148,"source_url":145,"published_at":149,"category":12,"cover_url":8,"hotness":150,"is_selected":14,"score":151,"score_detail":152,"sources":157,"tags":161,"primary_topic":164,"secondary_topics":165,"classification":166,"search_phrases":214,"slug":217,"view_count":155,"doi":218,"paper":219,"created_at":245},4016,"THE IMPACT OF MODERN TECHNOLOGICAL INNOVATIONS ON FOOD","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.34037571.v1","This study empirically examines how modern technological innovations affect food security in Nigerian technology-based farming organizations. The goal of this study is to ascertain the nature of connections between modern technological innovation and food security. It’s also aimed at identifying modern technological innovations that guarantee food security and determining their effectiveness and profitability for the food security business. This study used a cross-sectional survey research design to examine a few technology-based and digital-farming organizations in Delta State that were reachable by the study population. From the managers who were the study objects, 60 of the remaining managerial personnel were reported. To assess the data from the respondents, Spearman's rank-order correlation coefficient was used. The findings demonstrated a strong positive connection between food security and modern technological innovations. The study identified the modern technological innovations that guarantees food security such as nanotechnology in agriculture, Artificial Intelligence (AI) in Quality Control, Robotics in Food Processing, The Blockchain Technology and Supply chain management, The Use of Drones in Agriculture, Internet of Things (IoT) in Food Safety, Climate-Resilient Crops, Automated Harvesting using Robot and Post-Harvest Technologies, digital farming, responsible innovation, Vertical Farming, Precision Agriculture, micro-innovation. This study concludes that all the identified modern technological innovations are effective and profitable for the food security business. The study recommends that farmers adopt modern technological innovations to ensure food security and, to a greater extent, sustain the economy.","本研究实证考察了现代技术创新如何影响尼日利亚技术型农业组织的粮食安全。本研究旨在厘清现代技术创新与粮食安全之间联系的性质，同时识别能够保障粮食安全的现代技术创新，并确定其对粮食安全产业的有效性和盈利性。本研究采用横断面调查研究设计，对三角洲州若干可被研究总体接触到的技术型和数字农业组织进行了考察。研究对象为管理者，报告了其余60名管理人员的情况。为评估受访者的数据，采用了斯皮尔曼等级相关系数。研究结果表明，粮食安全与现代技术创新之间存在强烈的正相关关系。本研究识别出能够保障粮食安全的现代技术创新，包括农业中的纳米技术、质量控制中的人工智能（AI）、食品加工中的机器人技术、区块链技术与供应链管理、农业中无人机的使用、食品安全中的物联网（IoT）、气候适应性作物、利用机器人进行的自动化收割与采后技术、数字农业、负责任创新、垂直农业、精准农业、微创新。本研究得出结论，所有已识别的现代技术创新对粮食安全产业均具有有效性和盈利性。研究建议农民采用现代技术创新以保障粮食安全，并在更大程度上维持经济可持续发展。","Figshare","2026-10-01T00:00:00Z",25,45,{"impact":153,"substance":154,"depth":43,"authority":155,"freshness":153,"relevant":21,"comment":156},8,14,4,"论文主题契合农业信息化，但样本仅60人、来源为预印本平台，权威性与影响层级有限，暂不建议进入每日精选。",[158,159],{"name":148,"url":145},{"name":148,"url":160},"https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.34037571",[74,162,163,76,27],"无人机","农业人工智能",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":167},{"candidates":168,"agricultural_evidence":44},[169,174,178,182,189,196,202,209],{"code":102,"score":43,"supported":44,"title":170,"abstract":171,"tags":173},[],[76,172,105],"数字农业",[74,76],{"code":30,"score":69,"supported":44,"title":175,"abstract":176,"tags":177},[],[46,117,118],[],{"code":79,"score":55,"supported":44,"title":179,"abstract":180,"tags":181},[],[75,98],[],{"code":183,"score":55,"supported":44,"title":184,"abstract":185,"tags":188},"E1",[],[186,187],"食品加工","food processing",[],{"code":190,"score":55,"supported":44,"title":191,"abstract":192,"tags":195},"E4",[],[193,194],"食品安全","food safety",[],{"code":197,"score":155,"supported":44,"title":198,"abstract":199,"tags":201},"I2",[],[200],"artificial intelligence",[163],{"code":203,"score":204,"supported":44,"title":205,"abstract":206,"tags":208},"B7",3,[],[207],"垂直农业",[],{"code":86,"score":204,"supported":44,"title":210,"abstract":211,"tags":213},[],[212],"气候适应",[],[215,216],"尼日利亚 数字农业 粮食安全","农业人工智能 智慧农业 精准农业 区块链","尼日利亚数字农业粮食安全-4016","10.6084\u002Fm9.figshare.34037571.v1",{"doi":218,"openalex_id":220,"authors":221,"venue":148,"cited_by_count":133,"oa_url":145,"card":239,"direction":138,"ingested_from":140},"W7215054315",[222,225,228,230,232,234,236],{"name":223,"orcid":224},"Ernest Jebolise Chukwuka","https:\u002F\u002Forcid.org\u002F0000-0002-7876-9974",{"name":226,"orcid":227},"Clara Dumebi Moemeke","https:\u002F\u002Forcid.org\u002F0000-0003-1848-0623",{"name":229,"orcid":8},"Ugboh Onyemaechi",{"name":231,"orcid":8},"Nwaka Rita Nneka",{"name":233,"orcid":8},"Okpako Abugor Ejaita",{"name":235,"orcid":8},"Glory Ewere Chukwuka",{"name":237,"orcid":238},"Apaokueze Tessy Nkechi","https:\u002F\u002Forcid.org\u002F0000-0002-6581-0384",{"tldr":240,"method":241,"finding":242,"direction":243,"opportunity":244},"实证研究尼日利亚技术型农场中现代技术创新与粮食安全的关系。","对60名管理者进行横断面问卷调查，采用斯皮尔曼等级相关分析。","现代技术创新与粮食安全呈强正相关，所列技术均有效且有利可图。","数字乡村与农业信息化","可拓展至不同国家或小农户场景，量化各技术对粮食安全的贡献差异与成本效益。","2026-10-02T23:30:16.060799Z",{"id":247,"title":248,"url":249,"summary":250,"summary_zh":251,"content":8,"source_name":252,"source_url":249,"published_at":253,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":254,"score_detail":255,"sources":257,"tags":259,"primary_topic":263,"secondary_topics":264,"classification":265,"search_phrases":290,"slug":293,"view_count":21,"doi":8,"paper":294,"created_at":308},4015,"Development of a Blockchain-Internet of Things (IoT) Security Framework","https:\u002F\u002Fcigrjournal.org\u002Findex.php\u002FEjounral\u002Farticle\u002Fview\u002F10447","Internet of Things (IoT) has revolutionized data connectivity, fostering advancements across various sectors enabling real-time monitoring. The integration of blockchain technology to enhance the security of agricultural IoT data presents significant opportunities for improving data integrity and confidentiality in farming operations. The challenge lies in developing reliable framework that ensures securing of data transmission and storage in agricultural IoT networks. This study aims to develop and evaluate a blockchain-IoT framework to enhance security in agricultural data management systems, specifically designed for soil moisture sensors and weather stations. The method adopted involved developing a proof-of-concept mechanisms using JavaScript, Web3.js, and Ethereum smart contracts with Advanced Encryption Standard (AES-256) symmetric encryption cryptography. Results show that the framework maintained unbreachable encryption in man-in-the-middle (MITM) and replay attack simulations, while achieving transaction throughput of up to 100 transactions per second (TPS) with an average confirmation time of under 10 seconds. Network performance remained stable up to 500 simultaneous device connections, with only minor delays noted at 600 devices and significant delays at 1,000, where confirmation times increased to 25-30 seconds. Blockchain framework successfully enhances the security and integrity of agricultural data collected from IoT devices, providing a practical solution to secure farm data management and monitoring systems","物联网（IoT）彻底改变了数据连接方式，推动了各行业的进步，实现了实时监测。将区块链技术集成以增强农业物联网数据的安全性，为提升农业运营中的数据完整性和保密性提供了重要机遇。当前的挑战在于开发一个可靠的框架，确保农业物联网网络中数据传输和存储的安全性。本研究旨在开发并评估一个区块链-物联网框架，以增强农业数据管理系统的安全性，该框架专门针对土壤湿度传感器和气象站设计。所采用的方法包括使用JavaScript、Web3.js和以太坊智能合约，结合高级加密标准（AES-256）对称加密密码学，开发概念验证机制。结果表明，该框架在中间人攻击（MITM）和重放攻击模拟中保持了不可突破的加密性，同时实现了高达每秒100笔交易（TPS）的交易吞吐量，平均确认时间低于10秒。网络性能在多达500个同时设备连接的情况下保持稳定，仅在600个设备时出现轻微延迟，在1，000个设备时出现显著延迟，确认时间增加至25-30秒。该区块链框架成功增强了从物联网设备收集的农业数据的安全性和完整性，为保障农场数据管理和监测系统提供了一种实用的解决方案。","Agricultural Engineering International: CIGR Journal","2026-09-29T00:00:00Z",73,{"impact":96,"substance":67,"depth":68,"authority":19,"freshness":153,"relevant":21,"comment":256},"该论文提出并验证了面向农业物联网的区块链安全框架，方法具体、数据翔实，对智慧农业数据可信管理有参考价值，但属细分技术进展，影响层级有限。",[258],{"name":252,"url":249},[74,260,27,261,262],"农业物联网","数据安全","土壤墒情监测",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":266},{"candidates":267,"agricultural_evidence":44},[268,273,280,286],{"code":30,"score":269,"supported":44,"title":270,"abstract":271,"tags":272},26,[117,118],[46,117,118],[260],{"code":274,"score":55,"supported":44,"title":275,"abstract":276,"tags":279},"H2",[],[277,278],"土壤","soil",[],{"code":281,"score":155,"supported":44,"title":282,"abstract":283,"tags":285},"I6",[],[284],"agricultural data",[261],{"code":102,"score":21,"supported":14,"title":287,"abstract":288,"tags":289},[],[],[74],[291,292],"区块链 农业物联网 数据安全","土壤湿度传感器 气象站 区块链","区块链农业物联网数据安全-4015",{"doi":8,"openalex_id":295,"authors":296,"venue":252,"cited_by_count":133,"oa_url":8,"card":303,"direction":138,"ingested_from":140},"W7215549195",[297,299,301],{"name":298,"orcid":8},"Opeyemi Abisoye",{"name":300,"orcid":8},"Kiddams JOSHUA",{"name":302,"orcid":8},"Blessing Abisoye",{"tldr":304,"method":305,"finding":306,"direction":138,"opportunity":307},"开发并评估基于区块链与物联网的农业数据安全框架，保障土壤湿度与气象站数据。","用JavaScript、Web3.js、以太坊智能合约及AES-256加密构建概","框架可抵御中间人与重放攻击，达100 TPS，500设备连接稳定，1000设备时延迟显著。","可研究轻量级共识与边缘计算结合，提升大规模农业物联网下的吞吐与实时性。","2026-10-02T23:30:15.081491Z",{"id":310,"title":311,"url":312,"summary":313,"summary_zh":314,"content":8,"source_name":315,"source_url":312,"published_at":316,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":317,"score_detail":318,"sources":320,"tags":322,"primary_topic":325,"secondary_topics":326,"classification":327,"search_phrases":359,"slug":362,"view_count":155,"doi":363,"paper":364,"created_at":378},3471,"A secure federated learning framework with blockchain-based authentication for anomaly detection in cooperative smart farming","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.engappai.2026.116072","Agriculture is still a crucial global pillar of the world economy, ensuring food security and livelihood. But changing climate conditions and increasing reliance on the Internet of Things (IoT) based precision agriculture have brought new challenges, mainly cybersecurity. Cooperative Smart Farming (CSF) schemes promote resource pooling among small farmers and thus, the adoption of cutting-edge technologies. Although democratizing precision farming also makes it more accessible to cyber threats. To sort out all these problems, the proposed method introduces a secure federated learning framework along with blockchain-based authentication for anomaly detection in CSFs. The proposed method employs a federated transfer learning-based shadow attention mechanism, in conjunction with the Zeiler and Fergus network, to amplify the performance of the anomaly detection technique. This allows farms to detect threats in premises while protecting data privacy, as only model updates that are encrypted are transmitted. A blockchain-backed decentralized authentication scheme based on the proof of authentication consensus protocol is built to provide trust and resistance to tampering. Moreover, the random k-sparsification technique with changing rank adjustment has a positive impact on communication efficiency, which results in the same level of accuracy but with less communication overhead. The proposed method is executed on four datasets, CSE-CIS-IDS2018, MQTTset, ToN-IoT, and Edge IoT, achieving classification accuracies of 99.99%,99.93%,99.94%, and 99.91%, respectively, and it performs better than the current techniques. This comprehensive framework provides a scalable and trusted method for anomaly detection in CSFs, enabling resilient, privacy-preserving, and intelligent smart farming ecosystems.","农业仍然是全球经济的重要支柱，保障着粮食安全和生计。然而，不断变化的气候条件以及日益依赖基于物联网（IoT）的精准农业，带来了新的挑战，主要是网络安全问题。合作智慧农业（Cooperative Smart Farming, CSF）方案促进了小农户之间的资源共享，从而推动了前沿技术的采用。尽管精准农业的民主化使其更加普及，但也使其更容易受到网络威胁。为解决上述问题，所提出的方法引入了一种安全的联邦学习框架，并结合基于区块链的身份验证，用于CSF中的异常检测。所提出的方法采用基于联邦迁移学习的阴影注意力机制，结合Zeiler和Fergus网络，以提升异常检测技术的性能。这使得农场能够在本地检测威胁，同时保护数据隐私，因为仅传输加密的模型更新。构建了一种基于认证证明共识协议的区块链支持的去中心化身份验证方案，以提供信任和防篡改能力。此外，具有变化秩调整的随机k稀疏化技术对通信效率产生了积极影响，在保持相同精度的同时减少了通信开销。所提出的方法在四个数据集CSE-CIS-IDS2018、MQTTset、ToN-IoT和Edge IoT上执行，分别达到了99.99%、99.93%、99.94%和99.91%的分类准确率，且性能优于当前技术。该综合框架为CSF中的异常检测提供了一种可扩展且可信的方法，实现了具有韧性、隐私保护和智能化的智慧农业生态系统。","Engineering Applications of Artificial Intelligence","2026-09-24T00:00:00Z",81,{"impact":17,"substance":18,"depth":17,"authority":154,"freshness":69,"relevant":21,"comment":319},"提出联邦学习与区块链认证结合的农业异常检测框架，在四个数据集上验证高精度，方法新颖且具产业应用潜力，值得入选每日精选。",[321],{"name":315,"url":312},[74,163,323,27,324],"联邦学习","物联网安全",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":328},{"candidates":329,"agricultural_evidence":44},[330,334,338,342,348,354],{"code":102,"score":13,"supported":44,"title":331,"abstract":332,"tags":333},[],[74,76,105],[74],{"code":30,"score":69,"supported":44,"title":335,"abstract":336,"tags":337},[],[46,117,118],[],{"code":79,"score":55,"supported":44,"title":339,"abstract":340,"tags":341},[],[75,98],[],{"code":343,"score":204,"supported":44,"title":344,"abstract":345,"tags":347},"G2",[],[346],"小农户",[],{"code":349,"score":204,"supported":44,"title":350,"abstract":351,"tags":353},"H6",[],[352],"农业生态",[],{"code":197,"score":355,"supported":14,"title":356,"abstract":357,"tags":358},2,[],[],[163,323],[360,361],"联邦学习 区块链 异常检测","协同智慧农业 物联网安全","联邦学习区块链异常检测-3471","10.1016\u002Fj.engappai.2026.116072",{"doi":363,"openalex_id":365,"authors":366,"venue":315,"cited_by_count":133,"oa_url":312,"card":373,"direction":138,"ingested_from":140},"W7214230618",[367,369,371],{"name":368,"orcid":8},"Ramesh Pandharinath Daund",{"name":370,"orcid":8},"Mohammad Junedul Haque",{"name":372,"orcid":8},"Prof. Umesh B. Pawar",{"tldr":374,"method":375,"finding":376,"direction":138,"opportunity":377},"提出融合联邦迁移学习与区块链认证的异常检测框架，保障协作智慧农业数据隐私与安全。","联邦迁移学习、影子注意力机制、Zeiler-Fergus网络、区块链认证、随机k","在四个IoT数据集上分类准确率均超99.9%，且通信开销更低，优于现有方法。","可探索轻量级区块链共识与联邦学习在资源受限农业边缘设备上的能效与实时性优化。","2026-09-25T23:30:09.960528Z",{"id":380,"title":381,"url":382,"summary":383,"summary_zh":384,"content":8,"source_name":385,"source_url":382,"published_at":386,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":387,"score_detail":388,"sources":392,"tags":394,"primary_topic":395,"secondary_topics":396,"classification":397,"search_phrases":417,"slug":420,"view_count":355,"doi":421,"paper":422,"created_at":438},1723,"Bridging challenges with technology: A scientometric and systematic study on sustainability in smart agriculture","https:\u002F\u002Fdoi.org\u002F10.59953\u002Fpaperasia.v42i4b.1489","The rapid evolution of agricultural practices driven by population growth, climate change, and technological advancements has necessitated the integration of smart technologies to enhance productivity and sustainability. This study aims to achieve two research objectives: (1) to provide a comprehensive overview of research patterns and key contributors in the domain of technology integration in smart agriculture, and (2) to evaluate the advantages of integrating technology in smart agriculture to address existing challenges. A scientometric analysis and a systematic literature review (SLR) were employed to examine the research landscape and synthesize current evidence. Following the PRISMA screening process, 18 articles were retained for the final systematic review. The findings reveal the transformative role of the Internet of Things (IoT), artificial intelligence (AI), blockchain, and unmanned aerial vehicles (UAVs) in improving resource management, reducing labour costs, enhancing real-time monitoring, and strengthening farm safety. The scientometric analysis further highlights global research collaborations, influential contributors, and emerging technological trends shaping the field of smart agriculture. These findings demonstrate the significant potential of advanced technologies to address contemporary agricultural challenges while promoting sustainable and resilient farming practices worldwide.","人口增长、气候变化和技术进步推动农业实践快速演变，这要求整合智能技术以提升生产力和可持续性。本研究旨在实现两个研究目标：（1）全面概述智能农业技术整合领域的研究模式及主要贡献者；（2）评估智能农业中技术整合的优势，以应对现有挑战。采用科学计量分析和系统文献综述（SLR）来考察研究格局并综合现有证据。经过PRISMA筛选流程，最终纳入18篇文章进行系统综述。研究结果揭示了物联网（IoT）、人工智能（AI）、区块链和无人机（UAVs）在改善资源管理、降低劳动力成本、增强实时监测及强化农场安全方面的变革性作用。科学计量分析进一步凸显了全球研究合作、有影响力的贡献者以及塑造智能农业领域的新兴技术趋势。这些发现表明，先进技术在应对当代农业挑战、同时促进全球可持续和韧性农业实践方面具有巨大潜力。","PaperAsia","2026-09-04T00:00:00Z",56,{"impact":389,"substance":17,"depth":390,"authority":153,"freshness":355,"relevant":21,"comment":391},12,16,"系统综述与科学计量分析，梳理智慧农业技术应用与挑战，但时效性较低。",[393],{"name":385,"url":382},[74,162,163,46,27],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":398},{"candidates":399,"agricultural_evidence":44},[400,405,409,413],{"code":102,"score":389,"supported":44,"title":401,"abstract":403,"tags":404},[402],"smart agriculture",[402],[74],{"code":30,"score":13,"supported":44,"title":406,"abstract":407,"tags":408},[],[46,117,118],[46],{"code":86,"score":55,"supported":44,"title":410,"abstract":411,"tags":412},[],[110,112],[],{"code":197,"score":155,"supported":44,"title":414,"abstract":415,"tags":416},[],[200],[163],[418,419],"农业人工智能 智慧农业 区块链 无人机","农业人工智能 智慧农业","农业人工智能智慧农业区块链无人机-1723","10.59953\u002Fpaperasia.v42i4b.1489",{"doi":421,"openalex_id":423,"authors":424,"venue":385,"cited_by_count":133,"oa_url":382,"card":433,"direction":138,"ingested_from":140},"W7208757733",[425,427,429,431],{"name":426,"orcid":8},"Nor Suzylah Sohaimi",{"name":428,"orcid":8},"Nor Syahidah Ishak",{"name":430,"orcid":8},"Rozaimi Majid",{"name":432,"orcid":8},"Siti Noor Zilawati Mingat@Minhad",{"tldr":434,"method":435,"finding":436,"direction":138,"opportunity":437},"通过科学计量和系统综述，评估智能农业中技术整合的研究格局与优势。","科学计量分析结合PRISMA系统文献综述，筛选18篇文章。","IoT、AI、区块链和无人机提升资源管理、降低成本、增强监测与安全。","可深入探究区块链与AI在农业中的协同应用，或针对特定作物\u002F区域的实证研究。","2026-09-05T23:30:09.377361Z",{"id":440,"title":441,"url":442,"summary":443,"summary_zh":444,"content":8,"source_name":445,"source_url":442,"published_at":446,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":447,"score_detail":448,"sources":450,"tags":452,"primary_topic":453,"secondary_topics":454,"classification":455,"search_phrases":472,"slug":474,"view_count":20,"doi":475,"paper":476,"created_at":487},1419,"Smart Agriculture with Quantum Intelligence and Blockchain Security","https:\u002F\u002Fdoi.org\u002F10.22214\u002Fijraset.2026.84736","Selecting energy-efficient, trustworthy cluster heads (CHs) remains a key bottleneck in agricultural wireless sensor and Internet of Things (IoT) networks, where heuristic protocols such as LEACH often converge to unstable configurations and cannot verify whether a selected node is trustworthy. This paper proposes a framework that combines a Quantum-Inspired Genetic Algorithm (QIGA) for cluster head selection with a permissioned blockchain trust-verification layer. Unlike prior work that applies quantum classifiers to sensor-data classification, the proposed method encodes candidate cluster head assignments as qubit chromosomes and evolves them through quantum rotation-gate updates, treating cluster formation as a combinatorial optimization problem rather than a classification task. Verified assignments and node reputation scores are recorded as immutable blockchain transactions validated through a lightweight Byzantine fault-tolerant consensus, enabling automatic exclusion of low-trust nodes without a central authority. A discrete-event simulation comparing the proposed framework against LEACH and a classical genetic algorithm baseline shows comparable or improved energy retention and reliable detection of malicious nodes across a range of attack ratios. The results indicate that combining quantum-inspired combinatorial optimization with blockchain-verified trust offers a practical, hardware-independent pathway toward energy-aware, tamperresistant clustering for precision agriculture","在农业无线传感器与物联网（IoT）网络中，选择节能且可信的簇头（CH）仍是关键瓶颈，诸如LEACH等启发式协议往往收敛于不稳定配置，且无法验证所选节点是否可信。本文提出一个框架，将量子启发遗传算法（QIGA）用于簇头选择，并融合许可型区块链信任验证层。与以往将量子分类器应用于传感器数据分类的研究不同，本方法将候选簇头分配编码为量子比特染色体，并通过量子旋转门更新进行演化，将簇形成视为组合优化问题而非分类任务。验证后的分配结果与节点信誉评分被记录为不可篡改的区块链交易，并通过轻量级拜占庭容错共识机制加以验证，从而在无中心权威的情况下自动排除低信任节点。将所提框架与LEACH及经典遗传算法基线进行离散事件仿真对比，结果表明，在不同攻击比率下，该框架在能量保持方面表现相当或更优，并能可靠检测恶意节点。研究结果表明，将量子启发组合优化与区块链验证信任相结合，为实现精准农业中能量感知、防篡改的分簇提供了一条实用且不依赖硬件的路径。","International Journal for Research in Applied Science and Engineering Technology","2026-08-31T00:00:00Z",59,{"impact":389,"substance":17,"depth":390,"authority":13,"freshness":204,"relevant":21,"comment":449},"提出量子启发遗传算法与区块链结合的簇头选择框架，方法新颖，但尚处仿真阶段，影响有限。",[451],{"name":445,"url":442},[74,163,46,27],{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":456},{"candidates":457,"agricultural_evidence":44},[458,462,468],{"code":102,"score":96,"supported":44,"title":459,"abstract":460,"tags":461},[402],[76,105],[74],{"code":30,"score":13,"supported":44,"title":463,"abstract":464,"tags":467},[],[46,465,117,118,466],"无线传感","wireless sensor",[46],{"code":197,"score":21,"supported":14,"title":469,"abstract":470,"tags":471},[],[],[163],[473,419],"农业人工智能 智慧农业 区块链 物联网","农业人工智能智慧农业区块链物联网-1419","10.22214\u002Fijraset.2026.84736",{"doi":475,"openalex_id":477,"authors":478,"venue":445,"cited_by_count":133,"oa_url":442,"card":481,"direction":138,"ingested_from":140},"W7204875790",[479],{"name":480,"orcid":8},"Munta Padmavathi",{"tldr":482,"method":483,"finding":484,"direction":485,"opportunity":486},"提出量子启发遗传算法与区块链结合，用于农业物联网中可信且节能的簇头选择。","量子启发遗传算法（QIGA）优化簇头选择，结合许可区块链和拜占庭容错共识验证信任","相比LEACH和经典遗传算法，QIGA+区块链在能量保持和恶意节点检测上相当或更优。","其他","可探索将量子启发优化与区块链用于动态作物监测场景，或扩展到边缘计算与真实硬件部署验证。","2026-09-02T23:30:17.512521Z"]