[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4319":3,"related-4319":95},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":70,"slug":73,"view_count":74,"doi":75,"paper":76,"created_at":94},4319,"Closing the opportunity gap: Exploring micro-enterprises' behavioral intention to integrate with digital platforms for a broader agri-food system","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.techfore.2026.124906","Digital agriculture platforms offer marginalized micro-enterprises a vital pathway to bridge the opportunity gap and overcome structural dependencies on focal companies. However, mainstream literature's focal-firm bias leaves the adoption logic of these grassroots operators underexplored. Addressing this gap, we operationalize an integrated Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) framework. Using PLS-SEM on data from 167 micro-enterprises, this study investigates their platform integration behaviors. Results reveal distinct adoption pathways: a platform's operational simplicity cannot trigger adoption without first cultivating a favorable organizational mindset (full mediation). Conversely, its tangible strategic benefits—unexpectedly anchored in macro-systemic food safety guarantees and ecological conservation rather than mere short-term profits—motivate integration both directly and indirectly (partial mediation). Socio-psychologically, although micro-enterprises clearly perceive external pressures like government mandates and peer emulation, these fail to translate into adoption intent—a recognition-action gap that leaves adoption strongly conditioned by financial affordability and technical readiness instead. Ultimately, these dynamics reframe the presumed myopic rationality of micro-enterprises: viewed through the lens of push-pull theory, the strategic draw of sustainable platform value is offset by baseline capability constraints, such that this value becomes actionable only when matched by sufficient capability. Theoretically, this demonstrates that cultivating truly inclusive digital ecosystems necessitates shifting the analytical focus from top-down focal designs to bottom-up grassroots decision-making. Practically, it advises policymakers and platform sponsors to move beyond normative persuasion toward tangible capability empowerment and value-driven platform architectures.","数字农业平台为边缘化微型企业提供了弥合机会差距、克服对焦点企业结构性依赖的重要路径。然而，主流文献的焦点企业偏误使得这些草根运营者的采纳逻辑未得到充分探讨。为填补这一空白，我们操作化了一个整合技术接受模型（TAM）与计划行为理论（TPB）的框架。基于167家微型企业的数据，运用偏最小二乘结构方程模型（PLS-SEM），本研究考察了其平台整合行为。结果揭示了不同的采纳路径：平台的操作简便性若未首先培育有利的组织心态，则无法触发采纳（完全中介）。相反，其切实的战略收益——出乎意料地锚定于宏观系统性的食品安全保障与生态保护，而非单纯的短期利润——直接和间接地激励了整合（部分中介）。在社会心理层面，尽管微型企业清晰感知到政府指令和同行模仿等外部压力，但这些压力未能转化为采纳意愿——这一认知-行动差距使得采纳强烈受制于财务可负担性和技术准备度。最终，这些动态重新框定了微型企业被预设的短视理性：从推拉理论视角看，可持续平台价值的战略吸引力被基线能力约束所抵消，使得该价值只有在能力匹配时才可付诸行动。在理论上，这表明培育真正包容的数字生态系统需要将分析焦点从自上而下的焦点设计转向自下而上的草根决策。在实践上，它建议政策制定者和平台发起者超越规范性说服，转向切实的能力赋权和价值驱动的平台架构。",null,"Technological Forecasting and Social Change","2026-10-05T00:00:00Z","论文",10,false,81,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,9,1,"基于TAM-TPB整合框架与167家微型企业PLS-SEM实证，揭示数字农业平台采纳的“认知-行动鸿沟”与能力约束，对包容性数字生态政策有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","小农户","农业数字化转型","数字农业平台","平台采纳",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"E4","food-safety","质量安全与溯源","\u002Ftopic\u002Ffood-supply\u002Ffood-safety","E",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":47},[44,53,60,65],{"code":45,"score":46,"supported":47,"title":48,"abstract":49,"tags":52},"I1",7,true,[],[50,51],"数字农业","digital agriculture",[28],{"code":32,"score":54,"supported":47,"title":55,"abstract":56,"tags":59},6,[],[57,58],"食品安全","food safety",[],{"code":61,"score":21,"supported":14,"title":62,"abstract":63,"tags":64},"G2",[],[],[27],{"code":66,"score":21,"supported":14,"title":67,"abstract":68,"tags":69},"I6",[],[],[26],[71,72],"农业数字平台 微型企业 采纳行为","TAM TPB 农业平台 整合","农业数字平台微型企业采纳行为-4319",5,"10.1016\u002Fj.techfore.2026.124906",{"doi":75,"openalex_id":77,"authors":78,"venue":10,"cited_by_count":86,"oa_url":6,"card":87,"direction":91,"ingested_from":93},"W7220358562",[79,81,84],{"name":80,"orcid":9},"Dong Xuemei",{"name":82,"orcid":83},"Guoqun Ma","https:\u002F\u002Forcid.org\u002F0000-0002-9619-8423",{"name":85,"orcid":9},"Feiyu Chen",0,{"tldr":88,"method":89,"finding":90,"direction":91,"opportunity":92},"基于TAM-TPB模型调查167家农业微型企业，揭示其融入数字平台的决策逻辑。","整合TAM与TPB框架，对167家微型企业问卷做PLS-SEM分析。","外部压力不转化为采纳意愿，平台价值需匹配财务与技术能力才起作用。","数字乡村与农业信息化","可研究能力赋能型平台设计如何弥合微型企业数字采纳的知行差距。","openalex","2026-10-06T23:30:25.320336Z",{"total":54,"page":21,"page_size":54,"items":96},[97,145,208,273,328,366],{"id":98,"title":99,"url":100,"summary":101,"summary_zh":9,"content":9,"source_name":102,"source_url":9,"published_at":103,"category":104,"cover_url":9,"hotness":13,"is_selected":14,"score":105,"score_detail":106,"sources":111,"tags":113,"primary_topic":118,"secondary_topics":119,"classification":120,"search_phrases":140,"slug":143,"view_count":21,"doi":9,"paper":9,"created_at":144},5294,"云南省农科院质标所举办\"特色农产品数字化品控及标准体系构建\"成果推介会","https:\u002F\u002Fwww.yn.xinhuanet.com\u002F20261016\u002F4e2d2462c42e41f8b2d9d5bf525cbed7\u002Fc.html","10月16日云南省农科院质标所发布由云南省科技厅支持的\"特色农产品全产业链可信数字化技术研究\"项目下产出的3个数字化平台系统(产地环境质量监测调控系统、特色农产品质量可信追溯系统、特色农产品可信供应订单定制系统),覆盖产地环境、质量追溯、订单供应三大环节;相关数字化成果已在元阳梯田红米、绥江半边红李、香格里拉草莓、盈江优质软米中应用。","新华网云南频道(2026-10-16)","2026-10-16T00:00:00Z","报道",72,{"impact":17,"substance":107,"depth":19,"authority":108,"freshness":109,"relevant":21,"comment":110},20,12,8,"省级科研机构发布三大数字化平台并落地多品类应用，信息增量与实操价值较高，值得进入每日精选。",[112],{"name":102,"url":100},[26,114,115,116,117],"标准体系","农产品追溯","数字化品控","一物一码",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":121},{"candidates":122,"agricultural_evidence":47},[123,129,136],{"code":32,"score":124,"supported":47,"title":125,"abstract":126,"tags":128},4,[],[127],"农产品质量",[115],{"code":130,"score":131,"supported":47,"title":132,"abstract":133,"tags":135},"B1",3,[],[134],"草莓",[],{"code":66,"score":21,"supported":14,"title":137,"abstract":138,"tags":139},[],[],[26],[141,142],"云南省农科院 质标所 数字化品控","特色农产品 可信追溯 元阳梯田红米","云南省农科院质标所数字化品控-5294","2026-10-19T00:07:42.258537Z",{"id":146,"title":147,"url":148,"summary":149,"summary_zh":150,"content":9,"source_name":151,"source_url":148,"published_at":152,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":153,"score_detail":154,"sources":159,"tags":161,"primary_topic":166,"secondary_topics":167,"classification":168,"search_phrases":186,"slug":189,"view_count":86,"doi":190,"paper":191,"created_at":207},4978,"Fixed compliance costs and producer selection in regional food production: evidence from China's 2006 agricultural product quality and safety law","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1959282","Food-safety law protects consumers, but the mandatory standards, input restrictions, record-keeping, and pre-sale testing it imposes are largely fixed costs that fall hardest on the smallest producers. Whether that incidence survives aggregation, that is, whether output shed by marginal producers is absorbed by survivors or genuinely lost to a region, remains unsettled. We study China's 2006 Agricultural Product Quality and Safety Law, a nationally synchronous mandate, across 284 prefecture-level cities from 2001 to 2018. A continuous-intensity difference-in-differences design links predetermined pre-law exposure to post-law changes in per-capita animal-source food output, measured at the point of production rather than consumption, treating 2006 as a transition year and 2007 as the first full year of implementation. In the baseline specification, more exposed cities produced roughly 5% less animal-source food after implementation, with the contraction emerging over the post-law period. Because exposure is built from a pre-law outcome level, we re-estimate the relationship on a window excluding the years used to measure exposure; the negative gradient persists. Three findings locate the burden. The contraction covers the activities the statute regulates, animal-source food, grain, and primary-sector value added alike, and is absent from secondary and tertiary activity, making a general regional decline less consistent with the observed pattern. Within animal-source food, it concentrates in aquaculture, the most compliance-intensive segment. Further, it weakens as baseline farm scale rises, a gradient that persists under province-by-year fixed effects and under year-specific trends in baseline economic structure, both of which absorb the average exposure gradient entirely. Because the design works on regional quantities rather than producer histories, it identifies output a region no longer produces rather than the departure of identified producers. The findings are therefore consistent with uniform safety obligations having uneven production-side incidence across regions with different producer structures, which points to shared compliance infrastructure as a way to ease fixed compliance burdens without weakening substantive safety standards.","食品安全法保护消费者，但其规定的强制性标准、投入品限制、记录保存和售前检测在很大程度上属于固定成本，对最小规模的生产者冲击最大。这种负担分布能否在加总层面继续成立，即边际生产者减少的产出是被幸存者吸收还是真正从某一地区流失，仍无定论。我们研究中国2006年《农产品质量安全法》，这是一项全国同步实施的强制要求，覆盖2001年至2018年间284个地级市。我们采用连续强度双重差分设计，将法律实施前预先确定的暴露程度与法律实施后人均动物源食品产出的变化联系起来，产出在生产端而非消费端度量，并将2006年视为过渡年份、2007年视为首个完整实施年份。在基准设定中，暴露程度更高的城市在实施后动物源食品产量约减少5%，且收缩在法律实施后逐步显现。由于暴露程度基于法律实施前的产出水平构建，我们在排除用于度量暴露程度的年份的窗口上重新估计该关系；负向梯度依然存在。三项发现定位了负担所在。收缩覆盖了该法规所监管的活动，动物源食品、粮食和第一产业增加值均如此，而第二和第三产业则没有出现收缩，这使得一般性地区衰退与观察到的模式不太一致。在动物源食品内部，收缩集中于水产养殖，这是合规强度最高的部分。此外，随着基线农场规模上升，收缩减弱，这一梯度在省份-年份固定效应以及基线经济结构的年份特定趋势下依然存在，而这两者都完全吸收了平均暴露梯度。由于该设计基于地区总量而非生产者历史，它识别的是某一地区不再生产的产出，而非可识别生产者的退出。因此，这些发现与以下观点一致：统一的安全义务在不同生产者结构的地区之间产生了不均衡的生产端负担分布，这表明共享合规基础设施是一种在不削弱实质性安全标准的前提下缓解固定合规负担的途径。","Frontiers in Sustainable Food Systems","2026-10-14T00:00:00Z",86,{"impact":18,"substance":155,"depth":156,"authority":157,"freshness":20,"relevant":21,"comment":158},23,19,13,"基于284个地级市2001—2018年数据的准自然实验研究，揭示食品安全法规固定合规成本对区域畜牧水产产出的收缩效应，方法扎实、结论有政策含义，值得进入每日精选。",[160],{"name":151,"url":148},[162,163,27,164,165],"农产品质量安全","水产养殖","食品安全法","合规成本",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":169},{"candidates":170,"agricultural_evidence":47},[171,178,182],{"code":172,"score":46,"supported":47,"title":173,"abstract":174,"tags":177},"D",[],[175,176],"水产","aquaculture",[163],{"code":32,"score":46,"supported":47,"title":179,"abstract":180,"tags":181},[],[57,127],[162],{"code":61,"score":21,"supported":14,"title":183,"abstract":184,"tags":185},[],[],[27],[187,188],"中国 地级市 动物源食品 产出","农产品质量安全 食品安全法 合规成本 水产养殖","中国地级市动物源食品产出-4978","10.3389\u002Ffsufs.2026.1959282",{"doi":190,"openalex_id":192,"authors":193,"venue":151,"cited_by_count":86,"oa_url":148,"card":201,"direction":205,"ingested_from":93},"W7221767515",[194,197,199],{"name":195,"orcid":196},"Xi Feng","https:\u002F\u002Forcid.org\u002F0000-0001-8652-5980",{"name":198,"orcid":9},"毕军涛",{"name":200,"orcid":9},"Mengwei Yang",{"tldr":202,"method":203,"finding":204,"direction":205,"opportunity":206},"研究中国2006年农产品质量安全法，发现合规固定成本使高暴露地区动物源食品产量下降约5%。","连续强度双重差分，2001-2018年284个地级市面板数据，以法律前暴露度识别","合规成本集中于水产养殖，且随农场规模上升而减弱，说明小生产者承担更重固定成本。","农业绿色发展与碳","可研究共享合规基础设施（如区域检测、记录平台）如何降低小农固定合规成本而不放松安全标准。","2026-10-15T23:30:06.488813Z",{"id":209,"title":210,"url":211,"summary":212,"summary_zh":9,"content":213,"source_name":214,"source_url":9,"published_at":215,"category":104,"cover_url":9,"hotness":13,"is_selected":14,"score":216,"score_detail":217,"sources":221,"tags":223,"primary_topic":229,"secondary_topics":230,"classification":231,"search_phrases":268,"slug":271,"view_count":86,"doi":9,"paper":9,"created_at":272},2976,"活力中国调研行·湖北嘉鱼：科技兴农绘就荆楚丰收画卷","https:\u002F\u002Fwww.ce.cn\u002Fxwzx\u002Fgnsz\u002Fgdxw\u002F202609\u002Ft20260919_3224382.shtml","中国经济网9-19报道湖北嘉鱼县蔬菜科技示范园与中国农科院、湖北省农科院等多个科研团队合作，配套建成农业数字化服务站对蔬菜生产实施全天候监测，实时采集气象、土壤、水肥等农情信息实现水肥精准调控、病虫害绿色防控及生产全过程溯源。嘉鱼整合农作物生长数据建成400亩农产品溯源基地给蔬菜赋予\"二维码身份证\"，直供上海、广州、武汉等商超并远销日本、俄罗斯及东南亚市场。","新华社武汉9月19日电 题：科技兴农绘就荆楚丰收画卷\n\n新华社记者宋立崑、高敬、曹佩弦\n\n鱼肥鳝美，莲藕盈塘，9月的湖北，处处涌动着丰收气息。\n\n近日，记者跟随“活力中国调研行”采访团走访了解到，湖北正持续推动农业科技创新与产业创新深度融合，形成多项核心技术，培育出一批特色优质农产品，农业产业提质增效成果丰硕。\n\n在仙桃市张沟镇先锋村，记者来到仙桃市黄鳝农产品供应链有限公司的培苗间，只见蓝色培育箱整齐排布，一条条黄鳝幼苗在箱内缓缓游动。\n\n“等长到筷子长短，这些鳝苗就能分发到农户手里。”先锋村党总支书记朱传宝说，“过去村里黄鳝种苗大多依赖外地引种，养殖成本高。如今本地种苗自给率持续提升，养殖户的投入压力也减轻了。”\n\n黄鳝规模化全人工繁育，长期以来都是世界性难题。仙桃市联合湖北黄鳝产业集团、湖北省农科院组建湖北省黄鳝产业技术研究院，成功攻克这一技术瓶颈，培育的鳝苗存活率明显提升。\n\n![Image 1](http:\u002F\u002Fi.ce.cn\u002Fce\u002Fxwzx\u002Fgnsz\u002Fgdxw\u002F202609\u002FW020260919732410114462_ORIGIN.jpg)\n\n这是9月16日在仙桃市黄鳝农产品供应链有限公司拍摄的黄鳝培苗间。新华社记者鲁金博 摄\n\n与此同时，仙桃市还联合高校、科研院所研发出开口饵料、液氮速冻、自动化卤制等10余项专利技术，覆盖黄鳝养殖、冷链运输、精深加工全链条，撑起完整的本地产业体系。目前，全市黄鳝产业年产值突破120亿元。\n\n仙桃黄鳝产业的蓬勃发展，正是湖北依托农业科技创新，持续壮大特色农业产业的生动缩影。近年来，一大批农业科技成果在荆楚大地不断涌现、落地生根。ARC生物耦合技术破解花生、大豆提质固氮等难题，相关成果在湖北就地转化；科研团队在洪湖围绕煲汤、清炒、凉拌等不同烹饪场景与口感需求，培育出多个莲藕新品种并实现规模化推广种植……\n\n湖北省农业农村厅相关负责人表示，近年来，湖北持续推动农业企业与科研院校深度协同，建成一批产学研合作创新基地，累计形成专利2000余件。这些科技成果，不仅显著提升农业综合生产能力，还帮助农户化解多项风险，让乡村沃土引得来人、留得住人、能够致富。\n\n“小菜小菜，请告诉我5号地块的实时数据。”在嘉鱼县蔬菜科技示范园，湖北省农科院首席科学家邱正明站在田埂上，对着数字大屏发出指令，AI语音助手即刻播报土壤温度、湿度等田间监测数据。\n\n近年来，园区与中国农科院、湖北省农科院等多个科研团队合作，配套建成农业数字化服务站，对蔬菜生产实施全天候监测，实时采集气象、土壤、水肥等农情信息，实现水肥精准调控、病虫害绿色防控以及生产全过程溯源，有效提升田间管理效能。\n\n![Image 2](http:\u002F\u002Fi.ce.cn\u002Fce\u002Fxwzx\u002Fgnsz\u002Fgdxw\u002F202609\u002FW020260919732410241881_ORIGIN.jpg)\n\n这是9月15日在嘉鱼县潘家湾镇拍摄的农业数字化服务站显示屏。新华社记者鲁金博 摄\n\n邱正明介绍，蔬菜生长周期短，抗极端天气能力弱，暴雨内涝、高温干旱、寒潮霜冻都可能导致减产甚至绝收；部分病虫害在田间扩散速度快，若防控不及时，将给农户带来难以挽回的损失。依托这套数智化管护体系，农户能第一时间捕捉田间异常，心里更有底。\n\n有了数智基础，嘉鱼整合农作物生长数据，建成400亩农产品溯源基地，给蔬菜赋予“二维码身份证”，让好生态、好技术、好产品能被看见并验证。如今，嘉鱼蔬菜直供上海、广州、武汉等多地大型商超，还远销日本、俄罗斯及东南亚市场。\n\n“湖北既是科教大省，也是农业大省，具备以科技赋能农业的独特优势。”中国农科院农业经济与发展研究所研究员麻吉亮表示，以种苗技术攻关、新品种研发为引领，湖北大力发展智慧种植与农产品精深加工，走出了一条符合荆楚特色的现代农业发展之路。","中国经济网","2026-09-19T01:00:00Z",84,{"impact":18,"substance":107,"depth":218,"authority":219,"freshness":13,"relevant":21,"comment":220},17,15,"央媒调研报道，呈现湖北种苗攻关、数智化管护与溯源基地等实质进展，产业级参考价值较高。",[222],{"name":214,"url":211},[26,224,225,226,227,228],"智慧农业","种业振兴","农产品溯源","嘉鱼蔬菜","黄鳝产业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":232},{"candidates":233,"agricultural_evidence":47},[234,238,243,249,255,260,264],{"code":32,"score":124,"supported":47,"title":235,"abstract":236,"tags":237},[],[226],[226],{"code":130,"score":131,"supported":47,"title":239,"abstract":240,"tags":242},[],[241],"蔬菜",[],{"code":244,"score":131,"supported":47,"title":245,"abstract":246,"tags":248},"F4",[],[247],"绿色防控",[],{"code":250,"score":131,"supported":47,"title":251,"abstract":252,"tags":254},"H2",[],[253],"土壤",[],{"code":256,"score":21,"supported":14,"title":257,"abstract":258,"tags":259},"F1",[],[],[225],{"code":45,"score":21,"supported":14,"title":261,"abstract":262,"tags":263},[],[],[224],{"code":66,"score":21,"supported":14,"title":265,"abstract":266,"tags":267},[],[],[26],[269,270],"湖北嘉鱼 蔬菜 数字化服务站","仙桃 黄鳝 全人工繁育","湖北嘉鱼蔬菜数字化服务站-2976","2026-09-20T00:03:00.593647Z",{"id":274,"title":275,"url":276,"summary":277,"summary_zh":9,"content":278,"source_name":279,"source_url":9,"published_at":280,"category":104,"cover_url":9,"hotness":13,"is_selected":14,"score":281,"score_detail":282,"sources":285,"tags":287,"primary_topic":291,"secondary_topics":292,"classification":293,"search_phrases":323,"slug":326,"view_count":86,"doi":9,"paper":9,"created_at":327},2552,"数智助农成服贸会金融专题展亮点 农业银行展示AI数字人农小耘","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7685207598819279360\u002F","9月14日服贸会报道。中国农业银行以数智助农乡村振兴为主题展示智能化金融服务体系，AI能力嵌入信贷评估、风险核查等环节；农户在村里线上提交申请后系统可辅助完成信息核验与初步授信。北京农商银行展示非接触AI健康检测机器人；北京银行展示的科创企业技术已在智慧农业、农产品溯源等场景落地。","## 数智助农成服贸会金融专题展亮点\n\n2026-09-14 10:12·[中国网三农](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAbAvyMQxxaA9sEwA2aUWsAOJjrH-pK95hBvQUB6GaSEg\u002F?source=tuwen_detail)\n\n近日，北京首钢园迎来2026年中国国际服务贸易交易会（以下简称“服贸会”），金融服务专题展区以“智焕新生 金融聚力”为主题。记者在展区现场看到，各家展台前人头攒动，数智金融如何下沉乡村，成为不少观众关注的焦点。\n\n中国农业银行展台以绿色为主调，“数智助农”“乡村振兴”字样醒目。一位观众朝屏幕招手，AI数字人“农小耘”随即回应。工作人员介绍，农行此次展示了智能化金融服务体系，AI能力可嵌入信贷评估、风险核查等环节，农户在村里线上提交申请后，系统可辅助完成信息核验与初步授信，不必再往返县城网点。服务半径由此延伸到村口，数字技术让金融支农更直达。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Fc75fa582de054ded9aaf0da332891c36~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790121915&x-signature=%2FPNFaboCnXA%2F%2F0wpGhoOm4cWxLI%3D)\n\n中国农业银行展区，观众正在智能点餐机前扫码点单\n\n另一侧，北京农商银行展区排起小队。观众刘女士坐到一台智能检测机前，无需接触硬件，数秒后健康筛查报告呈现在显示屏上。“这是我们研发的非接触AI健康检测机器人，数秒完成多维度生理指标筛查。”耀眼科技副经理王俊才介绍，该设备已在北京亦庄荣华街道智慧康养机器人养老驿站试点，千余名体验者中农民占三分之一。由于部分农村地区居民健康筛查不便，银行网点正好可以成为服务下沉的入口。北京农商银行与耀眼科技合作，计划将AI健康检测机器人嵌入网点，依托养老助残卡、第三代社保卡，构建“金融网点+健康服务”便民模式。\n\n北京银行展台同样热闹。环抱式“金融会客厅”里，中轴线手绘长卷与科技产品相映成趣。环廊陈列的25件前沿科技产品，多来自该行长期支持的科创企业。记者了解到，这些企业的技术已在智慧农业、农产品溯源等场景落地，部分科创企业还获得该行专项信贷支持，将AI、物联网技术带入设施农业园区。从支持科创企业到技术反哺农业，金融正成为连接科技与乡村的桥梁。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F21c30bfe934940439449f459252e41d8~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790121915&x-signature=9CqAJQPWYzu3ZBgbNjWmOZ%2FwyxA%3D)\n\n北京银行展区，观众驻足观看机器人演奏\n\n穿行展区，记者感到，本次服贸会金融服务专题展示的不只是技术，更是服务民生、助力“三农”的路径探索。资金、科技与乡村加速融合，数智技术正让服务更贴近乡土，为乡村全面振兴提供持久支撑。\n\n来源：农民日报","中国网三农 2026-09-14","2026-09-14T02:00:00Z",55,{"impact":108,"substance":157,"depth":108,"authority":283,"freshness":46,"relevant":21,"comment":284},11,"服贸会金融展上的数智助农展示，属企业宣传性综合报道，有AI数字人、非接触健康检测等具体案例，但无政策条款或新数据，适合作为主题页聚合素材而非每日精选头条。",[286],{"name":279,"url":276},[26,224,288,289,290],"农业人工智能","乡村振兴","数字金融",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":294},{"candidates":295,"agricultural_evidence":47},[296,301,305,309,314,319],{"code":297,"score":124,"supported":47,"title":298,"abstract":299,"tags":300},"G",[],[289],[289],{"code":45,"score":124,"supported":47,"title":302,"abstract":303,"tags":304},[],[224],[224],{"code":32,"score":131,"supported":47,"title":306,"abstract":307,"tags":308},[],[226],[],{"code":310,"score":21,"supported":14,"title":311,"abstract":312,"tags":313},"G3",[],[],[290],{"code":315,"score":21,"supported":14,"title":316,"abstract":317,"tags":318},"I2",[],[],[288],{"code":66,"score":21,"supported":14,"title":320,"abstract":321,"tags":322},[],[],[26],[324,325],"农业人工智能 乡村振兴 数字乡村 数字金融","农业人工智能 乡村振兴","农业人工智能乡村振兴数字乡村数字金融-2552","2026-09-16T00:03:45.025672Z",{"id":329,"title":330,"url":331,"summary":332,"summary_zh":9,"content":333,"source_name":334,"source_url":9,"published_at":335,"category":104,"cover_url":9,"hotness":13,"is_selected":14,"score":336,"score_detail":337,"sources":340,"tags":342,"primary_topic":347,"secondary_topics":348,"classification":349,"search_phrases":361,"slug":364,"view_count":86,"doi":9,"paper":9,"created_at":365},5517,"上海农科院代表团赴马来西亚与新西兰 深化农产品质量安全与溯源合作","https:\u002F\u002Fwww.saas.sh.cn\u002Fhzjl\u002Fgjhz\u002Fcontent_57130","10月7日至12日院党委委员姚训率代表团一行4人出访，与马来西亚国立大学签署合作谅解备忘录并出席食品质量安全联合实验室揭牌，交流农业新兴污染物监测与农产品多源指纹真实性鉴别成果。赴新期间访问威世物流新西兰公司、新西兰生物经济科学研究所与梅西大学，调研有机食品认证与追溯管理经验。","2026年10月7-12日，院党委委员、纪委书记姚训率代表团一行4人赴马来西亚和新西兰参加国际学术会议并开展访问交流。代表团成员包括院农业生物安全研究中心副主任董茂锋、刘星副研究员和王献礼助理研究员。此次出访重点围绕农产品质量安全、真实性与产地溯源、农业新兴污染物监测及农食产品跨境供应链管理等领域，深化与两国高校、科研机构及企业的交流合作。\n\n7-9日，姚训代表我院参加与马来西亚国立大学合作谅解备忘录（MOU）交换仪式，出席双方食品质量安全联合实验室揭牌仪式并致辞。联合实验室的揭牌标志着双方合作进一步深化，为推动食品质量安全领域的联合科研、人才培养和成果转化搭建了合作平台。双方围绕科研项目合作、人员互访、研究生联合培养及科研资源共享等事项进行了深入交流。\n\n代表团参加了第三届马来西亚国立大学-宋卡王子大学亚洲科学技术国际研讨会（ISSTUP-Asia 2026）。会议期间，我院宋卫国研究员以线上方式作学术报告，介绍农业新兴污染物环境行为与食品安全风险防控方面的研究进展；刘星现场分享了农产品多源指纹真实性鉴别与产地溯源研究成果；王献礼通过学术墙报展示了绿色超分子溶剂在全氟和多氟烷基物质（PFAS）提取分析中的研究成果，并与参会专家开展交流。此外，代表团还参访了马来西亚国立大学食品科学相关实验室、甜食技术创新中心及马来西亚可可局可可创新与技术中心，并调研当地有机食品市场，了解食品质量安全检测、产品研发、成果转化及质量追溯管理等方面的实践经验。\n\n10-12日，代表团赴新西兰开展科研与产业交流。代表团访问了威世物流新西兰公司，围绕农产品跨境运输、冷链仓储、质量控制及供应链追溯等开展交流，了解新西兰农食产品出口及进入中国市场的物流与质量管理经验。代表团还与我院柔性引进专家Karyne Rogers教授就农产品真实性鉴别与产地溯源等领域的合作进展及后续研究计划进行交流。随后，代表团访问新西兰生物经济科学研究所及梅西大学马纳瓦图校区相关科研平台，围绕农产品质量安全、环境污染物监测研究及科研成果转化等开展学术交流，并探讨联合研究与人才培养等合作方向。访问期间，代表团还调研了新西兰有机食品市场的认证、质量保障及追溯管理情况。\n\n此次出访进一步深化了我院与马来西亚、新西兰相关高校、科研机构和企业的交流合作，展示了我院在农产品质量安全、真实性与产地溯源及农业新兴污染物研究方面的科技创新成果。下一步，我院将以食品质量安全联合实验室等合作平台为依托，推动联合科研、人才交流及成果转化，促进国际合作取得更多实质性成效，为提升农业科技创新能力提供支持。","上海市农业科学院 2026-10-19","2026-10-19T00:00:00Z",65,{"impact":338,"substance":218,"depth":157,"authority":157,"freshness":54,"relevant":21,"comment":339},16,"省级农科院出访交流，有联合实验室揭牌与学术报告等实质内容，但属机构外事动态，公共影响有限。",[341],{"name":334,"url":331},[343,162,344,345,346],"国际合作","产地溯源","农业污染物","跨境供应链",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":350},{"candidates":351,"agricultural_evidence":47},[352,356],{"code":32,"score":20,"supported":47,"title":353,"abstract":354,"tags":355},[127],[],[162],{"code":357,"score":21,"supported":14,"title":358,"abstract":359,"tags":360},"J3",[],[],[343],[362,363],"上海农科院 马来西亚 联合实验室","农产品 真实性鉴别 产地溯源","上海农科院马来西亚联合实验室-5517","2026-10-22T00:07:04.117432Z",{"id":367,"title":368,"url":369,"summary":370,"summary_zh":371,"content":9,"source_name":372,"source_url":369,"published_at":335,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":373,"score_detail":374,"sources":376,"tags":378,"primary_topic":381,"secondary_topics":386,"classification":388,"search_phrases":428,"slug":431,"view_count":86,"doi":432,"paper":433,"created_at":455},5400,"Artificial intelligence in food safety: a bibliometric and empirical synthesis of emerging technologies and research frontiers","https:\u002F\u002Fdoi.org\u002F10.1108\u002Fbfj-06-2025-0819","Purpose This study aimed to identify recent research trends in the integration of artificial intelligence (AI) with food safety and security through a comprehensive bibliometric analysis. Design\u002Fmethodology\u002Fapproach A total of 2,782 documents published between 2021 and 2025 were retrieved from the Web of Science Core Collection. The dataset was refined by removing duplicates, filtering document types and excluding irrelevant records. VOSviewer was then used to conduct co-authorship, keyword co-occurrence, citation, co-citation and bibliographic coupling analyses. Findings Machine learning and deep learning emerged as core technologies associated with food security, contamination detection and quality prediction. Keyword clustering demonstrated interdisciplinary connections with agriculture, climate change and public health. Citation and co-citation analyses identified three major intellectual foundations: traditional machine learning, computer vision-based deep learning and time-series modeling. China, India and the United States were the most influential contributors in terms of research output and technological development. Bibliographic coupling and source co-citation analyses further indicated increasing convergence between food science and computational science. Originality\u002Fvalue This study provides a comprehensive overview of the intellectual structure, collaborative networks and thematic evolution of AI-driven food safety research. Unlike previous studies focusing on specific technologies or applications, it maps global research patterns and interdisciplinary linkages. The findings provide strategic insights for researchers, policymakers and industry stakeholders. Future studies should prioritize explainable AI integration into regulatory frameworks and the development of larger, more diverse datasets to improve model generalizability across food systems.","目的 本研究旨在通过全面的文献计量分析，识别人工智能（AI）与食品安全及保障融合领域的最新研究趋势。设计与方法 从Web of Science核心合集中检索了2021年至2025年间发表的2，782篇文献。通过去除重复记录、筛选文献类型并排除不相关记录对数据集进行精炼。随后使用VOSviewer进行合著、关键词共现、引文、共被引及文献耦合分析。研究发现 机器学习和深度学习成为与食品安全、污染检测和质量预测相关的核心技术。关键词聚类显示了与农业、气候变化和公共卫生的跨学科联系。引文和共被引分析识别出三大主要知识基础：传统机器学习、基于计算机视觉的深度学习和时间序列建模。中国、印度和美国在研究产出和技术发展方面是最具影响力的贡献者。文献耦合和来源共被引分析进一步表明食品科学与计算科学之间的融合日益加深。原创性\u002F价值 本研究全面概述了AI驱动的食品安全研究的知识结构、合作网络和主题演变。与以往聚焦特定技术或应用的研究不同，本研究绘制了全球研究模式和跨学科联系。研究结果为研究人员、政策制定者和行业利益相关者提供了战略性见解。未来研究应优先关注可解释AI融入监管框架以及开发更大、更多样化的数据集，以提高模型在食品系统中的泛化能力。","British Food Journal",80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":109,"relevant":21,"comment":375},"基于2782篇文献的AI食品安全计量分析，方法规范、结论有参考价值，但属综述性研究，产业落地影响有限。",[377],{"name":372,"url":369},[224,288,379,57,380],"机器学习","文献计量",{"code":315,"slug":382,"name":383,"path":384,"parent_code":385},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[387],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":389},{"candidates":390,"agricultural_evidence":47},[391,401,405,411,418,424],{"code":315,"score":156,"supported":47,"title":392,"abstract":394,"tags":400},[393],"artificial intelligence",[395,379,396,397,398,393,399],"深度学习","计算机视觉","machine learning","deep learning","computer vision",[288,379],{"code":32,"score":219,"supported":47,"title":402,"abstract":403,"tags":404},[58],[57,58],[57],{"code":406,"score":219,"supported":47,"title":407,"abstract":409,"tags":410},"I7",[408],"bibliometric",[380,408],[380],{"code":412,"score":54,"supported":47,"title":413,"abstract":414,"tags":417},"H7",[],[415,416],"气候变化","climate change",[],{"code":419,"score":131,"supported":47,"title":420,"abstract":421,"tags":423},"A8",[],[422],"food security",[],{"code":45,"score":21,"supported":14,"title":425,"abstract":426,"tags":427},[],[],[224],[429,430],"AI 食品安全 文献计量","机器学习 食品质量预测","AI食品安全文献计量-5400","10.1108\u002Fbfj-06-2025-0819",{"doi":432,"openalex_id":434,"authors":435,"venue":372,"cited_by_count":86,"oa_url":9,"card":449,"direction":453,"ingested_from":93},"W7222920742",[436,438,440,443,446],{"name":437,"orcid":9},"Harang Lee",{"name":439,"orcid":9},"지은서",{"name":441,"orcid":442},"Yoonbin Kim","https:\u002F\u002Forcid.org\u002F0000-0002-5625-2560",{"name":444,"orcid":445},"Joon-Goo Lee","https:\u002F\u002Forcid.org\u002F0000-0003-3617-5518",{"name":447,"orcid":448},"Woo‐Ju Kim","https:\u002F\u002Forcid.org\u002F0000-0002-6954-1580",{"tldr":450,"method":451,"finding":452,"direction":453,"opportunity":454},"对2021-2025年2782篇文献做文献计量，梳理AI与食品安全交叉研究趋势。","Web of Science文献计量，VOSviewer共被引、关键词共现与耦合","机器学习与深度学习是核心，形成传统ML、计算机视觉、时序建模三大知识基础。","农业人工智能与决策模型","可解释AI嵌入监管框架、构建更大更多样数据集以提升跨食物系统泛化能力。","2026-10-20T23:30:31.567802Z"]