[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-129":3,"related-129":80},{"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":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":74,"slug":77,"view_count":78,"doi":8,"paper":8,"created_at":79},129,"数字赋能\"中国蜜桃之都\"——山东蒙阴联合中国联通建桃产业数字赋能中心,打造全国首个蜜桃产业集群数字化标杆","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7668277811458736640","蒙阴县作为\"中国蜜桃之都\"(71万亩种植面积、20余亿斤年产量、108亿元全产业链产值均居全国县级首位,\"蒙阴蜜桃\"品牌价值257.81亿元),联合中国联通总投资600万元建成桃产业数字赋能中心,打造全国首个蜜桃产业集群数字化标杆。中心在露天桃园、大棚桃园、集散市场、加工企业四大示范点部署田间气象站、土壤墒情站、虫情测报、智能水肥一体化及视频监控设备;桃产业大数据平台归集地块、气象、墒情、虫情、交易、加工、品牌等全维度信息,打破信息孤岛;实时监测全国28个品种价格指数,提前发布滞销预警引导错峰采收与冷链仓储(800公里内次日送达),鲜果损耗率大幅下降;农产品质量安全追溯系统覆盖种植、检测、交易、加工全流程。",null,"## 数字赋能“中国蜜桃之都”\n\n**鲁网7月30日讯** 七月盛夏，蒙阴蜜桃正值丰收季，漫山桃香四溢。\n\n作为“中国蜜桃之都”，蒙阴县71万亩种植面积、20余亿斤年产量、108亿元全产业链产值均居全国县级首位，“蒙阴蜜桃”品牌价值高达257.81亿元。然而，传统模式长期面临生产管理粗放、数据孤岛严重、质量管控薄弱、产销信息不对称等痛点，阻碍产业进一步做大做强。为破解这一困局，蒙阴县农业农村发展服务中心联合中国联通，总投资600万元建成桃产业数字赋能中心，打造全国首个蜜桃产业集群数字化标杆，目前已全面投入应用。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F8dbd998763a9461794af39201f112adb~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786168964&x-signature=tSLd7fsNNXs%2BEhq9vfRa1l%2F7%2BKM%3D)\n\n看得见的是桃农丰收的喜悦，看不见的是背后联通搭建的产业“智慧中枢”。中国联通依托5G物联网络与视联网平台，在露天桃园、大棚桃园、集散市场、加工企业四大示范点部署田间气象站、土壤墒情站、虫情测报、智能水肥一体化及视频监控等设备，实现数据实时采集与云端存储。桃产业大数据平台整合多源数据，建成产业资源“一张图”，归集地块、气象、墒情、虫情、交易、加工、品牌等全维度信息，彻底打破信息孤岛，推动产业治理从“线下摸排”迈向“数据决策”。\n\n在生产端，联通搭建的数字化种植管理系统，可自动推送精准农事建议——什么时候浇水、施什么肥、防什么虫，桃农打开手机一目了然，种出来的果品糖度、外观统一度显著提升。智能水肥一体化系统实现远程调控，节约人力及农资成本，优质果占比显著提升，绿色生态种植加速落地。\n\n在流通端，平台实时监测全国28个品种价格指数，结合本地产能提前发布滞销预警，引导果农错峰采收、冷链仓储。如今，全县建成标准化分拣、预冷、冷链直发一体化体系，当日采摘、当日分拣，800公里内次日送达，鲜果损耗率大幅下降。\n\n在消费端，联通打造的农产品质量安全追溯系统，覆盖种植、检测、交易、加工全流程，配套农残快检和合格证自助终端，对超标主体自动预警。消费者扫码即可查看这颗桃从哪个园子来、哪天采摘、经谁检测，真正实现“来源可查、去向可追、责任可究”，为“蒙阴蜜桃”品牌筑牢了保护防线。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F98222500a6e14e13aa5adebb8f530f0e~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786168964&x-signature=xY0w4czBHUWba%2BhSVtlwAsG6w4I%3D)\n\n在品牌端，品牌数字化管理系统统一录入品种、分级、加工标准，开通防伪查验与假冒举报功能，持续放大“蒙阴蜜桃”品牌附加值。同时支持加工企业开发冻干桃、桃酒等高附加值产品，带动果品加工业产值新飞跃。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F96d144f562c342a6a91a47e3bcc1a7e7~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1786168964&x-signature=5pKLro1pcpYDayBPCvG9xc30BvU%3D)\n\n管好种好只是第一步，让数据红利惠及更多人才是关键。平台通过公共信息窗口免费开放卫星遥感、气象虫情、行情查询等功能，普惠全县桃农、客商和消费者，培育新型数字化经营主体，推动一二三产深度融合。\n\n中国联通将以蒙阴为起点，总结提炼桃产业集群数字赋能模式的实践经验，形成可复制、可推广的标准化方案，为鲁中山区乃至全国特色果品产业数字化转型提供有益借鉴。（通讯员 沈慧卿 贺子哲）","鲁网临沂频道 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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":93,"substance":94,"depth":95,"authority":17,"freshness":13,"relevant":20,"comment":96},22,20,17,"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。",[98],{"name":89,"url":86},[100,101,102,27,103,104],"数字乡村","智慧农业","种业振兴","嘉鱼蔬菜","黄鳝产业",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":108},{"candidates":109,"agricultural_evidence":45},[110,114,120,126,130,135,139],{"code":31,"score":44,"supported":45,"title":111,"abstract":112,"tags":113},[],[27],[27],{"code":115,"score":52,"supported":45,"title":116,"abstract":117,"tags":119},"B1",[],[118],"蔬菜",[],{"code":121,"score":52,"supported":45,"title":122,"abstract":123,"tags":125},"F4",[],[124],"绿色防控",[],{"code":64,"score":52,"supported":45,"title":127,"abstract":128,"tags":129},[],[67],[],{"code":131,"score":20,"supported":14,"title":132,"abstract":133,"tags":134},"F1",[],[],[102],{"code":70,"score":20,"supported":14,"title":136,"abstract":137,"tags":138},[],[],[101],{"code":140,"score":20,"supported":14,"title":141,"abstract":142,"tags":143},"I6",[],[],[100],[145,146],"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",0,"2026-09-20T00:03:00.593647Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":8,"content":155,"source_name":156,"source_url":8,"published_at":157,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":158,"score_detail":159,"sources":163,"tags":165,"primary_topic":171,"secondary_topics":172,"classification":173,"search_phrases":186,"slug":189,"view_count":148,"doi":8,"paper":8,"created_at":190},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":160,"substance":95,"depth":161,"authority":161,"freshness":81,"relevant":20,"comment":162},16,13,"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。",[164],{"name":156,"url":153},[166,167,168,169,170],"国际合作","农产品质量安全","产地溯源","农业污染物","跨境供应链",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":174},{"candidates":175,"agricultural_evidence":45},[176,181],{"code":31,"score":177,"supported":45,"title":178,"abstract":179,"tags":180},9,[48],[],[167],{"code":182,"score":20,"supported":14,"title":183,"abstract":184,"tags":185},"J3",[],[],[166],[187,188],"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":192,"title":193,"url":194,"summary":195,"summary_zh":196,"content":8,"source_name":197,"source_url":194,"published_at":157,"category":198,"cover_url":8,"hotness":13,"is_selected":14,"score":199,"score_detail":200,"sources":204,"tags":206,"primary_topic":211,"secondary_topics":217,"classification":219,"search_phrases":261,"slug":264,"view_count":148,"doi":265,"paper":266,"created_at":289},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","论文",80,{"impact":18,"substance":93,"depth":18,"authority":201,"freshness":202,"relevant":20,"comment":203},14,8,"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。",[205],{"name":197,"url":194},[101,207,208,209,210],"农业人工智能","机器学习","食品安全","文献计量",{"code":212,"slug":213,"name":214,"path":215,"parent_code":216},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[218],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":220},{"candidates":221,"agricultural_evidence":45},[222,233,238,244,251,257],{"code":212,"score":223,"supported":45,"title":224,"abstract":226,"tags":232},19,[225],"artificial intelligence",[227,208,228,229,230,225,231],"深度学习","计算机视觉","machine learning","deep learning","computer vision",[207,208],{"code":31,"score":17,"supported":45,"title":234,"abstract":236,"tags":237},[235],"food safety",[209,235],[209],{"code":239,"score":17,"supported":45,"title":240,"abstract":242,"tags":243},"I7",[241],"bibliometric",[210,241],[210],{"code":245,"score":81,"supported":45,"title":246,"abstract":247,"tags":250},"H7",[],[248,249],"气候变化","climate change",[],{"code":252,"score":52,"supported":45,"title":253,"abstract":254,"tags":256},"A8",[],[255],"food security",[],{"code":70,"score":20,"supported":14,"title":258,"abstract":259,"tags":260},[],[],[101],[262,263],"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":265,"openalex_id":267,"authors":268,"venue":197,"cited_by_count":148,"oa_url":8,"card":282,"direction":286,"ingested_from":288},"W7222920742",[269,271,273,276,279],{"name":270,"orcid":8},"Harang Lee",{"name":272,"orcid":8},"지은서",{"name":274,"orcid":275},"Yoonbin Kim","https:\u002F\u002Forcid.org\u002F0000-0002-5625-2560",{"name":277,"orcid":278},"Joon-Goo Lee","https:\u002F\u002Forcid.org\u002F0000-0003-3617-5518",{"name":280,"orcid":281},"Woo‐Ju Kim","https:\u002F\u002Forcid.org\u002F0000-0002-6954-1580",{"tldr":283,"method":284,"finding":285,"direction":286,"opportunity":287},"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。","openalex","2026-10-20T23:30:31.567802Z",{"id":291,"title":292,"url":293,"summary":294,"summary_zh":8,"content":8,"source_name":295,"source_url":8,"published_at":296,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":297,"score_detail":298,"sources":300,"tags":302,"primary_topic":307,"secondary_topics":308,"classification":309,"search_phrases":325,"slug":328,"view_count":20,"doi":8,"paper":8,"created_at":329},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",72,{"impact":18,"substance":94,"depth":201,"authority":78,"freshness":202,"relevant":20,"comment":299},"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。",[301],{"name":295,"url":293},[100,303,304,305,306],"标准体系","农产品追溯","数字化品控","一物一码",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":310},{"candidates":311,"agricultural_evidence":45},[312,316,321],{"code":31,"score":44,"supported":45,"title":313,"abstract":314,"tags":315},[],[48],[304],{"code":115,"score":52,"supported":45,"title":317,"abstract":318,"tags":320},[],[319],"草莓",[],{"code":140,"score":20,"supported":14,"title":322,"abstract":323,"tags":324},[],[],[100],[326,327],"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":331,"title":332,"url":333,"summary":334,"summary_zh":8,"content":8,"source_name":335,"source_url":8,"published_at":336,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":337,"score_detail":338,"sources":341,"tags":343,"primary_topic":347,"secondary_topics":348,"classification":349,"search_phrases":366,"slug":369,"view_count":148,"doi":8,"paper":8,"created_at":370},5060,"云南省农科院质标所参与2026年云南省食品安全宣传周主场活动 自主研发快检技术现场演示","https:\u002F\u002Fwww.yn.xinhuanet.com\u002F20261010\u002F59bfd10da16b4a36ad8de9272595ce5e\u002Fc.html","10月9日,云南省食品安全宣传周在昆明启动,云南省农科院质标所受邀参加主场活动,围绕\"从农田到餐桌\"的源头检测提供技术支撑。重点演示薄层色谱法(2分钟快速鉴别肥料中隐性添加的禁限用农药)、自主研发的丙溴磷等金纳米抗体侧流层析核酸试纸条(灵敏度较商品试纸条提升10倍)以及合成诱导圆偏振发光探针和微针贴片技术(10秒内捕捉稳定信号)。","新华网云南频道 2026年10月10日","2026-10-10T00:00:00Z",68,{"impact":160,"substance":94,"depth":17,"authority":78,"freshness":339,"relevant":20,"comment":340},5,"省级食品安全宣传周活动，含自主研发快检技术现场演示，技术细节具体，具备一定行业参考价值。",[342],{"name":335,"url":333},[344,209,345,346],"云南省农科院","农业科技","快检技术",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":350},{"candidates":351,"agricultural_evidence":45},[352,356,361],{"code":31,"score":78,"supported":45,"title":353,"abstract":354,"tags":355},[209],[209],[209],{"code":58,"score":52,"supported":45,"title":357,"abstract":358,"tags":360},[],[359],"肥料",[],{"code":121,"score":52,"supported":45,"title":362,"abstract":363,"tags":365},[],[364],"农药",[],[367,368],"云南农科院 质标所 快检技术","食品安全宣传周 云南","云南农科院质标所快检技术-5060","2026-10-16T00:13:12.742863Z",{"id":372,"title":373,"url":374,"summary":375,"summary_zh":376,"content":8,"source_name":377,"source_url":374,"published_at":378,"category":198,"cover_url":8,"hotness":13,"is_selected":14,"score":379,"score_detail":380,"sources":383,"tags":385,"primary_topic":390,"secondary_topics":391,"classification":392,"search_phrases":411,"slug":414,"view_count":148,"doi":415,"paper":416,"created_at":432},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":93,"substance":381,"depth":223,"authority":161,"freshness":177,"relevant":20,"comment":382},23,"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。",[384],{"name":377,"url":374},[167,386,387,388,389],"水产养殖","小农户","食品安全法","合规成本",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":393},{"candidates":394,"agricultural_evidence":45},[395,402,406],{"code":396,"score":19,"supported":45,"title":397,"abstract":398,"tags":401},"D",[],[399,400],"水产","aquaculture",[386],{"code":31,"score":19,"supported":45,"title":403,"abstract":404,"tags":405},[],[209,48],[167],{"code":407,"score":20,"supported":14,"title":408,"abstract":409,"tags":410},"G2",[],[],[387],[412,413],"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":415,"openalex_id":417,"authors":418,"venue":377,"cited_by_count":148,"oa_url":374,"card":426,"direction":430,"ingested_from":288},"W7221767515",[419,422,424],{"name":420,"orcid":421},"Xi Feng","https:\u002F\u002Forcid.org\u002F0000-0001-8652-5980",{"name":423,"orcid":8},"毕军涛",{"name":425,"orcid":8},"Mengwei Yang",{"tldr":427,"method":428,"finding":429,"direction":430,"opportunity":431},"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"]