[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1488":3,"related-1488":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":23,"tags":25,"primary_topic":31,"secondary_topics":36,"classification":37,"search_phrases":74,"slug":77,"view_count":78,"doi":8,"paper":8,"created_at":79},1488,"河北农林科学院专家团下沉衡水三县一策：指导防灾减灾、\"一喷多促\"促进玉米大面积单产提升","https:\u002F\u002Fwww.heb.chinanews.com.cn\u002Fshfz\u002F20260831459938.shtml","由河北省农林科学院旱作农业研究所和衡水市农业技术推广站组成的技术专家团来到武邑县、冀州区、枣强县等玉米大面积单产提升整建制推进县，\"一县一策\"推进落实单产提升关键技术措施，开展指导服务。技术专家团与县级农技推广部门和种植主体进行座谈，详细了解基地玉米生产特点、当前管理难点和种植技术需求；深入田间地头，实地查看玉米苗情长势、群体结构、水肥管理及病虫害发生情况，现场针对当前防灾减灾、\"一喷多促\"等关键环节开展技术指导。",null,"*   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All Rights Reserved","中新网河北","2026-08-31T00:00:00Z","报道",10,false,62,{"impact":17,"substance":18,"depth":19,"authority":13,"freshness":20,"relevant":21,"comment":22},18,15,12,7,1,"省级农科院专家下沉指导玉米单产提升，具有区域示范意义，但内容为常规技术服务报道，信息增量有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"防灾减灾","一喷多促","玉米单产提升","科技包县","农业技术服务",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},"A","field-crops","大田作物","\u002Ftopic\u002Ffield-crops",[],{"status":38,"locked":14,"version":39,"method":40,"evidence":41},"partial","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45,"reason":73},[43,50,56,61,68],{"code":44,"score":19,"supported":45,"title":46,"abstract":48,"tags":49},"A3",true,[47],"玉米",[47],[28],{"code":51,"score":19,"supported":45,"title":52,"abstract":54,"tags":55},"A8",[53],"单产提升",[53],[28],{"code":57,"score":19,"supported":45,"title":58,"abstract":59,"tags":60},"H7",[26],[26],[26],{"code":62,"score":63,"supported":45,"title":64,"abstract":65,"tags":67},"G1",3,[],[66],"农技推广",[],{"code":69,"score":21,"supported":14,"title":70,"abstract":71,"tags":72},"F4",[],[],[27],"一级领域明确，二级方向需要细分",[75,76],"农业技术服务 玉米单产提升 一喷多促 科技包县","农业技术服务 玉米单产提升","农业技术服务玉米单产提升一喷多促科技包县-1488",2,"2026-09-03T00:06:42.853324Z",{"total":81,"page":21,"page_size":81,"items":82},6,[83,141,190,305,350,412],{"id":84,"title":85,"url":86,"summary":87,"summary_zh":8,"content":88,"source_name":89,"source_url":8,"published_at":90,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":91,"score_detail":92,"sources":95,"tags":97,"primary_topic":101,"secondary_topics":102,"classification":103,"search_phrases":136,"slug":139,"view_count":63,"doi":8,"paper":8,"created_at":140},1574,"黑龙江省玉米产业技术协同创新推广体系 9 月 2 日黑河召开：寒区玉米单产提升关键技术观摩会","https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002F2026-09\u002F03\u002Fcontent_574682.html","9 月 2 日，黑龙江省玉米产业技术协同创新推广体系 2026 年玉米单产提升关键技术田间现场观摩会在黑龙江省黑河市举行。本次会议由黑龙江省玉米产业技术协同创新推广体系、东北农业大学联合主办，黑龙江省农业科学院黑河分院承办，聚焦玉米单产提升核心技术，集中展示最新科研与示范成果。此次观摩会集中展示了早熟极早熟区玉米新品种、早熟玉米种质资源改良创新成果及新品种大面积示范场景，示范了玉米单产提升病虫害绿色防控、水肥一体化集成等关键核心技术。","![Image 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7](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Fimg\u002F20240301dzv.png)0\n\n[](javascript:; \"新浪微博\")[](javascript:; \"微信\")\n\n**科技日报记者 朱虹**\n\n9月2日，黑龙江省玉米产业技术协同创新推广体系2026年玉米单产提升关键技术田间现场观摩会在黑龙江省黑河市举行。本次会议由黑龙江省玉米产业技术协同创新推广体系、东北农业大学联合主办，黑龙江省农业科学院黑河分院承办，聚焦玉米单产提升核心技术，集中展示最新科研与示范成果，为农业经营主体搭建技术交流、成果转化平台。\n\n![Image 8](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-09\u002F03\u002F574682_8f39b4a8-72fe-483e-8c0d-729fc202e215.jpeg)\n\n本次观摩会阵容专业、覆盖面广，汇聚多方农业科研与推广力量，100余人参会观摩、交流学习。\n\n东北农业大学科学技术研究院副院长马靖林在致辞中表示，东北农业大学将持续深耕玉米产业科技创新领域，全力支持省玉米产业技术协同创新推广体系各项工作开展，严格落实任务监督与配套保障，助力农业科技成果落地生根、赋能产业。黑河市农业农村局局长李玉冬结合黑河寒区农业生产区位特点与种植实际，深入阐述了玉米产业技术体系对当地玉米稳产增产、产业转型升级的重要支撑作用，并围绕后续新技术示范推广、规模化普及、本土化适配等工作提出具体优化建议。黑龙江省农业科学院黑河分院院长鹿文成详细介绍了黑河市玉米综合技术示范场所的建设运营情况、技术研发方向及阶段性核心成果。\n\n此次观摩会集中展示了早熟极早熟区玉米新品种、早熟玉米种质资源改良创新成果及新品种大面积示范场景，示范了玉米单产提升病虫害绿色防控、水肥一体化集成等关键核心技术。参会人员结合黑河寒区玉米种植实际，围绕早熟玉米品种选育、密植高产栽培模式、病虫害科学防控、田间水肥精准管理等关键生产问题，与专家团队面对面深入交流、答疑解惑，精准破解种植难题，吸纳先进种植技术与管理经验，切实提升技术能力。\n\n![Image 9](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Fgdxw\u002Fpic\u002F2026-09\u002F03\u002F574682_a25d6d2b-f27f-4285-8db6-63e80bffd197.jpeg)\n\n体系首席专家、东北农业大学张林教授表示，此次观摩会精准对接黑龙江寒区玉米产业发展需求，有效打通了科研成果与田间生产的衔接通道。下一步，黑龙江省玉米产业技术协同创新推广体系将聚焦科技创新、技术推广、人才培养三大核心任务，持续强化跨单位、跨领域协同联动，加快玉米高产技术的试验、熟化、集成与推广应用。同时，深度推动农业科技创新与玉米产业深度融合，充分释放科技赋能效能，持续提升全省玉米种业创新能力与规模化种植水平，引领黑龙江玉米产业高质量、可持续发展。\n\n（受访单位供图）\n\n责任编辑：冷媚\n\n相关稿件：\n\n![Image 10](https:\u002F\u002Fstatics.kjrb.com.cn\u002Fresource\u002Fkjw\u002Fimages\u002Fpinglun.png)网友评论\n\n评论\n\n最热评论\n\n没有更多评论了\n\n[热点](https:\u002F\u002Fwww.stdaily.com\u002Fweb\u002Frdxw\u002Fnode_327.html)\n\n[![Image 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3.暂不升级，继续浏览\n\n[继续浏览](javascript:;)","科技日报","2026-09-03T00:00:00Z",65,{"impact":17,"substance":18,"depth":19,"authority":19,"freshness":93,"relevant":21,"comment":94},8,"省级玉米产业技术观摩会，展示新品种与关键技术，对寒区玉米增产有实质推动作用。",[96],{"name":89,"url":86},[98,99,28,100],"种业振兴","技术推广","寒区农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":104},{"candidates":105,"agricultural_evidence":45,"reason":73},[106,110,114,121,127,132],{"code":44,"score":19,"supported":45,"title":107,"abstract":108,"tags":109},[47],[47],[28],{"code":51,"score":19,"supported":45,"title":111,"abstract":112,"tags":113},[53],[53],[28],{"code":115,"score":116,"supported":45,"title":117,"abstract":118,"tags":120},"F1",4,[],[119],"种质资源",[98],{"code":122,"score":63,"supported":45,"title":123,"abstract":124,"tags":126},"F3",[],[125],"水肥一体化",[],{"code":69,"score":63,"supported":45,"title":128,"abstract":129,"tags":131},[],[130],"绿色防控",[],{"code":62,"score":21,"supported":14,"title":133,"abstract":134,"tags":135},[],[],[99],[137,138],"玉米单产提升 寒区农业 技术推广 种业振兴","玉米单产提升 寒区农业","玉米单产提升寒区农业技术推广种业振兴-1574","2026-09-04T00:05:32.898269Z",{"id":142,"title":143,"url":144,"summary":145,"summary_zh":8,"content":8,"source_name":146,"source_url":8,"published_at":147,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":148,"score_detail":149,"sources":152,"tags":154,"primary_topic":157,"secondary_topics":158,"classification":159,"search_phrases":185,"slug":188,"view_count":81,"doi":8,"paper":8,"created_at":189},556,"农民日报 8-13 要闻:安徽秋粮播种 6450 万亩,稳中有增,苗情好于去年","https:\u002F\u002Fszb.farmer.com.cn\u002Fnmrb\u002Fhtml\u002F2026\u002F20260813\u002F20260813_1\u002Fnmrb_20260813_13376_1_2087657300626083855.html","安徽省今年秋粮播种面积达 6450 万亩,稳中有增,大豆、玉米、一季稻苗情长势整体好于去年:大豆一、二类苗占比 92.3%、玉米 94.5%、一季稻预计 85% 以上。省财政紧急下达 500 万元支持黄山灾后恢复,并争取中央财政资金 9910 万元指导抗逆减灾。","农民日报要闻1版 2026-08-13","2026-08-13T00:00:00Z",69,{"impact":17,"substance":17,"depth":150,"authority":19,"freshness":20,"relevant":21,"comment":151},14,"省级秋粮生产数据详实，含财政支持信息，具一定参考价值。",[153],{"name":146,"url":144},[53,26,155,156],"安徽","秋粮生产",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":160},{"candidates":161,"agricultural_evidence":45,"reason":73},[162,166,172,176,180],{"code":44,"score":63,"supported":45,"title":163,"abstract":164,"tags":165},[],[47],[],{"code":167,"score":63,"supported":45,"title":168,"abstract":169,"tags":171},"A4",[],[170],"大豆",[],{"code":51,"score":21,"supported":14,"title":173,"abstract":174,"tags":175},[],[],[53],{"code":57,"score":21,"supported":14,"title":177,"abstract":178,"tags":179},[],[],[26],{"code":181,"score":21,"supported":14,"title":182,"abstract":183,"tags":184},"J4",[],[],[156],[186,187],"单产提升 秋粮生产 防灾减灾 安徽","单产提升 秋粮生产","单产提升秋粮生产防灾减灾安徽-556","2026-08-15T23:54:30.784742Z",{"id":191,"title":192,"url":193,"summary":194,"summary_zh":195,"content":8,"source_name":196,"source_url":193,"published_at":197,"category":198,"cover_url":8,"hotness":13,"is_selected":14,"score":199,"score_detail":200,"sources":205,"tags":207,"primary_topic":213,"secondary_topics":214,"classification":215,"search_phrases":255,"slug":258,"view_count":259,"doi":260,"paper":261,"created_at":304},5550,"Integrated effects of fermented organic manure on soil fertility, productivity, and economic performance of the rice–wheat cropping system in Uttar Pradesh","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1968370","The rice–wheat cropping system (RWCS) is a major cereal-based production system in Uttar Pradesh, India, where sustaining crop productivity and soil fertility under intensive cultivation is a major challenge. This study evaluated the field-level performance of fermented organic manure (FOM) integrated with inorganic fertilizers in terms of crop productivity, selected soil fertility indicators, and economic returns during 2025–2026. A total of 224 frontline demonstrations (FLDs) were conducted through 25 Krishi Vigyan Kendras (KVKs) across Uttar Pradesh. The analysis included demonstrations with sufficiently complete and consistent field-level records, comprising 40 rice and 110 wheat demonstrations under farmers’ field conditions and 6 rice and 11 wheat demonstrations at KVK instructional farms. Seven nutrient management treatments were evaluated at KVK farms, compared with three treatments under farmers’ field conditions. Crop performance, post-harvest soil fertility indicators, and economic returns were assessed. The treatment combining 100% recommended inorganic fertilizers with 125% FOM (T₃) recorded the highest numerical means for most growth and yield attributes and grain yield in both crops. Compared with 100% recommended inorganic fertilizers alone, T₃ increased grain yield by 6.4–7.3% in rice and 10.8–12.7% in wheat. FOM-integrated treatments also showed higher numerical values of soil organic carbon (SOC) and available nitrogen, phosphorus, and potassium after the rice–wheat cropping cycle. Under T₃, SOC increased from 0.271% to 0.304% at KVK instructional farms and from 0.447% to 0.515% under farmers’ field conditions. Although T₃ generally recorded the highest numerical gross returns, the additional costs of FOM reduced net returns and benefit–cost (B) ratios in several cases. Under farmers’ field conditions, inorganic fertilizers alone recorded higher numerical net returns and B ratios for both crops. The findings indicate that integrating FOM with recommended inorganic fertilizers was associated with improved crop productivity and selected soil fertility indicators under the demonstrated rice–wheat systems. However, the economic advantage depended on the costs of FOM production, transportation, and application. As the demonstrations were participatory and lacked formal plot-level randomization and inferential statistical testing, the observed differences represent descriptive numerical responses rather than statistically established treatment effects. Further controlled trials and cost optimization are needed to establish the agronomic and economic viability of FOM-integrated nutrient management.","稻麦种植制度（RWCS）是印度北方邦以谷类作物为主的重要生产体系，在集约化种植下维持作物生产力与土壤肥力是该体系面临的主要挑战。本研究评估了发酵有机肥（FOM）与无机肥料配合施用在2025—2026年度对作物生产力、选定土壤肥力指标及经济效益的田间表现。研究通过北方邦25个农业科技推广中心（KVKs）开展了224项前线示范（FLDs）。分析纳入了田间记录足够完整且一致的示范，包括农民田块条件下的40项水稻和110项小麦示范，以及KVK教学农场的6项水稻和11项小麦示范。在KVK农场评估了7个养分管理处理，并与农民田块条件下的3个处理进行比较。评估了作物表现、收获后土壤肥力指标及经济效益。100%推荐无机肥料配合125% FOM的处理（T₃）在两种作物的多数生长和产量性状及籽粒产量上记录了最高的数值均值。与单施100%推荐无机肥料相比，T₃使水稻籽粒产量提高6.4%—7.3%，小麦提高10.8%—12.7%。整合FOM的处理在稻麦轮作周期后也表现出较高的土壤有机碳（SOC）及有效氮、磷、钾数值。在T₃处理下，KVK教学农场的SOC从0.271%提高到0.304%，农民田块条件下从0.447%提高到0.515%。尽管T₃总体上记录了最高的数值总收益，但FOM的额外成本在多种情况下降低了净收益和效益成本比（B）。在农民田块条件下，单施无机肥料在两种作物上均记录了较高的数值净收益和B比。研究结果表明，在示范的稻麦系统中，FOM与推荐无机肥料配合施用与作物生产力及选定土壤肥力指标的改善相关。然而，经济优势取决于FOM的生产、运输和施用成本。由于示范为参与式，缺乏正式的田块水平随机化和推断性统计检验，观察到的差异代表描述性数值响应，而非统计学上确立的处理","Frontiers in Sustainable Food Systems","2026-10-21T00:00:00Z","论文",71,{"impact":201,"substance":17,"depth":18,"authority":202,"freshness":203,"relevant":21,"comment":204},16,13,9,"基于224个前线示范的实地数据，结论有参考价值，但缺乏随机化与统计检验，且为印度区域研究，属细分领域进展。",[206],{"name":196,"url":193},[208,209,210,211,212],"有机肥","土壤肥力","养分管理","印度农业","水稻小麦轮作",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":216},{"candidates":217,"agricultural_evidence":45,"reason":73},[218,225,232,239,244,250],{"code":219,"score":18,"supported":45,"title":220,"abstract":222,"tags":224},"H2",[221],"soil",[223,221],"土壤",[209],{"code":226,"score":150,"supported":45,"title":227,"abstract":229,"tags":231},"A1",[228],"rice",[230,228],"水稻",[],{"code":233,"score":150,"supported":45,"title":234,"abstract":236,"tags":238},"A2",[235],"wheat",[237,235],"小麦",[],{"code":122,"score":93,"supported":45,"title":240,"abstract":241,"tags":243},[],[242,210],"肥料",[210,208],{"code":245,"score":63,"supported":45,"title":246,"abstract":247,"tags":249},"A7",[],[248],"轮作",[],{"code":251,"score":21,"supported":14,"title":252,"abstract":253,"tags":254},"J3",[],[],[211],[256,257],"发酵有机肥 稻麦轮作","Uttar Pradesh 稻麦系统","发酵有机肥稻麦轮作-5550",0,"10.3389\u002Ffsufs.2026.1968370",{"doi":260,"openalex_id":262,"authors":263,"venue":196,"cited_by_count":259,"oa_url":296,"card":297,"direction":301,"ingested_from":303},"W7223144837",[264,266,269,270,273,276,278,279,281,284,286,289,291,293],{"name":265,"orcid":8},"Raghwendra Singh",{"name":267,"orcid":268},"Ajay Kumar Singh","https:\u002F\u002Forcid.org\u002F0000-0002-8743-6477",{"name":267,"orcid":268},{"name":271,"orcid":272},"Preeti P. Yadav","https:\u002F\u002Forcid.org\u002F0000-0001-7843-9783",{"name":274,"orcid":275},"Seema Yadav","https:\u002F\u002Forcid.org\u002F0000-0002-9773-6641",{"name":277,"orcid":8},"Abhishek Singh",{"name":277,"orcid":8},{"name":280,"orcid":8},"Saurabh Raj Pandey",{"name":282,"orcid":283},"Vinod Kumar Singh","https:\u002F\u002Forcid.org\u002F0009-0004-2583-6565",{"name":285,"orcid":8},"Narendra Raghubanshi",{"name":287,"orcid":288},"Yash Pal Singh","https:\u002F\u002Forcid.org\u002F0000-0001-8345-9084",{"name":290,"orcid":8},"Mahesh Kumar",{"name":292,"orcid":8},"Shivangi Singh",{"name":294,"orcid":295},"Reena Kumari","https:\u002F\u002Forcid.org\u002F0000-0002-1101-5473","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1968370\u002Fpdf",{"tldr":298,"method":299,"finding":300,"direction":301,"opportunity":302},"评估发酵有机肥配施化肥对稻麦轮作产量、土壤肥力与经济收益的综合影响。","印度北方邦224个农户与KVK示范基地田间示范，比较7种养分管理处理。","全量化肥配125%发酵有机肥增产稻6.4-7.3%、麦10.8-12.7%并提升有机碳，但净收益常因","农业绿色发展与碳","可研究有机肥成本分摊与碳交易补偿机制，量化其经济可行性与土壤固碳协同效益。","openalex","2026-10-22T11:20:16.098808Z",{"id":306,"title":307,"url":308,"summary":309,"summary_zh":8,"content":310,"source_name":311,"source_url":8,"published_at":312,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":313,"score_detail":314,"sources":316,"tags":318,"primary_topic":323,"secondary_topics":324,"classification":325,"search_phrases":345,"slug":348,"view_count":259,"doi":8,"paper":8,"created_at":349},5437,"上海农科院揭榜天长市粮食单产提升项目 攻关水稻秸秆田边发酵技术","https:\u002F\u002Fwww.tianchang.gov.cn\u002Fzwdt\u002Ftzgg\u002F392406342.html","天长市农业农村局公示 2026 年粮食单产提升「揭榜挂帅」项目实施单位，上海市农业科院与南京农业大学工学院分别揭榜水稻秸秆田边发酵技术研究与示范、秸秆田间就地焚燎消杀还田技术模式示范推广两个项目，公示期为 2026 年 10 月 20 日至 26 日。该举措旨在破解秸秆直接还田弊端、缓解秸秆禁烧压力，同时提高粮食单产，是科研院所参与县域粮食单产提升「揭榜挂帅」的具体落地案例。","403\n\nForbidden\n\nError Times: Wed, 21 Oct 2026 00:10:36 GMT   \nIP: 2600:1900:0:2105::1c01 Node information: PS-ATL-017OX49   \nURL: https:\u002F\u002Fwww.tianchang.gov.cn\u002Fzwdt\u002Ftzgg\u002F392406342.html   \nRequest-Id: 6ad802fc_PS-ATL-017OX49_7380-31487   \nCheck: Details\n\nERROR\n\nThe Requested URL could not be retrieved\n\nWhile trying to retrieve the URL:\n\nhttps:\u002F\u002Fwww.tianchang.gov.cn\u002Fzwdt\u002Ftzgg\u002F392406342.html\n\nThe following error was encountered:\n\n*   Invalid Request\n\nThe access control configuration prevents your request at this time.\n\nPlease contact your service provider if you feel this is incorrect.\n\n[return](https:\u002F\u002Fwww.tianchang.gov.cn\u002Fzwdt\u002Ftzgg\u002F392406342.html#)","天长市人民政府 2026-10-20","2026-10-20T00:00:00Z",41,{"impact":19,"substance":93,"depth":81,"authority":81,"freshness":203,"relevant":21,"comment":315},"地市级院地合作动态，主题相关但正文仅403字且原文不可访问，信息增量与专业深度有限，暂不宜进入每日精选。",[317],{"name":311,"url":308},[230,319,320,321,322],"院地合作","秸秆利用","粮食单产提升","天长市",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":326},{"candidates":327,"agricultural_evidence":45,"reason":73},[328,332,336,340],{"code":226,"score":19,"supported":45,"title":329,"abstract":330,"tags":331},[230],[230],[230],{"code":51,"score":19,"supported":45,"title":333,"abstract":334,"tags":335},[53],[53],[321],{"code":62,"score":21,"supported":14,"title":337,"abstract":338,"tags":339},[],[],[319],{"code":341,"score":21,"supported":14,"title":342,"abstract":343,"tags":344},"H5",[],[],[320],[346,347],"上海农科院 天长市 水稻秸秆","天长市 粮食单产提升 秸秆发酵","上海农科院天长市水稻秸秆-5437","2026-10-21T00:10:01.423686Z",{"id":351,"title":352,"url":353,"summary":354,"summary_zh":355,"content":8,"source_name":356,"source_url":353,"published_at":357,"category":198,"cover_url":8,"hotness":13,"is_selected":14,"score":91,"score_detail":358,"sources":361,"tags":363,"primary_topic":369,"secondary_topics":370,"classification":371,"search_phrases":393,"slug":396,"view_count":259,"doi":397,"paper":398,"created_at":411},5404,"Validation of a Day-of-Year Standardized Canopy Indicator for Regional Crop Monitoring: Suitability and Decoupling Boundaries","https:\u002F\u002Fdoi.org\u002F10.20944\u002Fpreprints202610.1707.v1","Translating satellite-derived crop canopy anomalies into regional production signals is critical for agricultural monitoring. However, standard anomaly indicators assume a stable, direct coupling between greenness and production, ignoring phenological shifts, sub-seasonal cropping dynamics, and harvested acreage fluctuations. I evaluate the validation boundaries and expected conditions of a pixel-level, day-of-year (DOY)-first Leaf Area Index (LAI) Z-score anomaly indicator with a leave- year-out baseline (2003–2022) across five contrasting global breadbaskets: Australia, Indo-Gangetic Plains (IGP), North China Plain (NCP), US Corn Belt, and Ukraine. The analysis shows that DOY- first standardization reduces temporal composite timing mismatches, though coupling with regional statistics varies systematically. Retrospective validation reveals that direct canopy-yield coupling remains robust exclusively in rainfed Australia (Pearson’s r = 0.90), where yield variability dominates production variance (explaining 90% of variance) and moisture stress limits canopy development. In contrast, three interpretation boundaries are identified: (1) greening trend-sensitivity in the IGP, where detrending reduces the association to r = 0.53; (2) temporal representativeness bias in the double-cropped NCP, requiring crop-calendar windowing to recover the wheat signal (r = 0.51); and (3) area-shock-sensitivity in Ukraine (where harvested area contractions explain 78% of production variance), decoupling canopy vigor from production (r = 0.40). Furthermore, the LAI Z-score provides a more interpretable canopy-response measure than the Vegetation Condition Index (VCI) in dense canopies where NDVI saturates. These validation levels are synthesized into a prototype diagnostic decision framework to support indicator configuration in operational monitoring systems.","将卫星反演的作物冠层异常转化为区域产量信号对农业监测至关重要。然而，标准异常指标假定绿度与产量之间存在稳定、直接的耦合关系，忽略了物候偏移、次季节作物动态以及收获面积波动。我评估了一种像元级、以年积日（DOY）为首要标准化维度的叶面积指数（LAI）Z分数异常指标在五个对比鲜明的全球粮仓——澳大利亚、印度河-恒河平原（IGP）、华北平原（NCP）、美国玉米带和乌克兰——的验证边界与预期适用条件，该指标采用留一年基线（2003—2022年）。分析表明，以DOY为首要标准化维度可减少时间合成时相不匹配，但其与区域统计数据的耦合关系存在系统性差异。回顾性验证显示，冠层与产量的直接耦合仅在雨养条件下的澳大利亚保持稳健（Pearson's r = 0.90），该地区产量变异性主导产量方差（解释90%的方差），且水分胁迫限制冠层发育。相比之下，识别出三个解释边界：（1）IGP的绿度趋势敏感性，去趋势后关联性降至r = 0.53；（2）双季种植的NCP的时间代表性偏差，需按作物日历开窗以恢复小麦信号（r = 0.51）；（3）乌克兰的面积冲击敏感性（收获面积缩减解释78%的产量方差），导致冠层活力与产量解耦（r = 0.40）。此外，在NDVI饱和的密集冠层中，LAI Z分数提供了比植被条件指数（VCI）更具可解释性的冠层响应度量。这些验证层级被综合为一个原型诊断决策框架，以支持业务化监测系统中的指标配置。","Preprints.org","2026-10-19T00:00:00Z",{"impact":19,"substance":359,"depth":17,"authority":81,"freshness":93,"relevant":21,"comment":360},21,"预印本提出按年积日标准化的LAI异常指标，并在五大农业区验证其适用边界，方法有新意但尚未经同行评审，属细分领域进展。",[362],{"name":356,"url":353},[364,365,366,367,368],"智慧农业","遥感","作物监测","产量估测","叶面积指数",{"code":32,"slug":33,"name":34,"path":35,"parent_code":8},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":372},{"candidates":373,"agricultural_evidence":45,"reason":73},[374,378,383,388],{"code":233,"score":81,"supported":45,"title":375,"abstract":376,"tags":377},[],[237,235],[],{"code":44,"score":81,"supported":45,"title":379,"abstract":380,"tags":382},[],[47,381],"corn",[],{"code":384,"score":63,"supported":14,"title":385,"abstract":386,"tags":387},"I3",[],[],[367,366,368,365],{"code":389,"score":21,"supported":14,"title":390,"abstract":391,"tags":392},"I1",[],[],[364],[394,395],"LAI Z-score 作物监测","遥感 作物产量 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DOY标准化与产量相","仅雨养澳大利亚冠层-产量强耦合(r=0.90)，其余区域受趋势、物候和面积冲击影响而解耦。","农业遥感与作物表型","可发展融合物候窗口、去趋势与收获面积因子的分区自适应冠层异常指标诊断框架。","农业人工智能与决策模型","2026-10-20T23:30:40.675672Z",{"id":413,"title":414,"url":415,"summary":416,"summary_zh":8,"content":417,"source_name":418,"source_url":8,"published_at":419,"category":12,"cover_url":8,"hotness":13,"is_selected":45,"score":420,"score_detail":421,"sources":425,"tags":427,"primary_topic":432,"secondary_topics":433,"classification":434,"search_phrases":463,"slug":466,"view_count":259,"doi":8,"paper":8,"created_at":467},5335,"中国农业科学院「农知育芯 BRIS」智能育种平台在洛阳发布 打造智能育种科研副脑","https:\u002F\u002Fcaas.cn\u002Fxwzx\u002Fmtxw\u002Fa297dd7421fa4a3ba08c08863fbe3eb7.htm","10 月 14—16 日中国农学会图书情报分会 2026 年学术年会在河南洛阳举办。中国农业科学院农业信息研究所副所长赵瑞雪介绍,农知育芯(BRIS,Breeding Research Intelligent Service)集成 8 项分析工具、3 项自研算法,汇聚 2011—2025 年育种相关核心期刊文献,整合 6800 万条 NCBI 基因索引、57 万条 UniProt 专家校验蛋白信息;自主构建的育种知识图谱包含 7.9 万余个知识实体、12.6 万余条实体关系,覆盖水稻、玉米、小麦和拟南芥四类作物。","10月14日至16日，中国农学会图书情报分会2026年学术年会在河南洛阳举办。会议由中国农学会图书情报分会主办，中国农业科学院[农业信息研究所](http:\u002F\u002Faii.caas.cn\u002F)、河南省农业科学院农业信息技术研究所、洛阳市农林科学院联合承办。中国农业科学院[农业信息研究所](http:\u002F\u002Faii.caas.cn\u002F)副所长赵瑞雪在会上介绍农知育芯（BRIS，Breeding Research Intelligent Service）阶段性研究成果。农知育芯融合育种文献、权威数据库、知识图谱和分析算法，集成8项分析工具、3项自研算法，为研究人员提供知识获取、任务规划、证据推理全链条智能科研服务。\n\n智能育种是AI+农业的重要场景。随着高通量测序技术快速发展，育种科研数据快速增长，基因、性状和调控通路等知识分散于海量文献和数据库，候选基因筛选、功能解析和多组学研究面临知识检索繁琐、数据分析复杂、验证周期长和试错成本高等挑战。而通用大模型也难以充分满足专业知识、结果依据和溯源能力等科研要求。\n\n面向这一需求，农知育芯打通问答与计算、分析与决策、知识与工具三类能力。科研人员可通过自然语言提出问题或发起任务，系统自动调度工具与算法，汇聚文献、数据库、知识图谱及用户数据，形成分析结果与科研建议。在关键候选基因发现等任务中，平台可辅助科研人员将筛选过程由“大海捞针”转向“精准发现”，堪称智能育种的“科研副脑”。\n\n该平台以高质量知识图谱引导推理，结合分析工具计算、模型研判和知识增强开展协同验证，并对文献、数据库、工具和参数进行全链路核查，形成“问题—数据—结论”的科研闭环。\n\n据悉，农知育芯已汇聚2011年至2025年育种相关核心期刊文献，整合6800万条NCBI基因索引、57万条UniProt专家校验蛋白信息；自主构建的育种知识图谱包含7.9万余个知识实体、12.6万余条实体关系，覆盖水稻、玉米、小麦和拟南芥四类作物，形成文献、权威数据库和知识图谱互为校验的证据网络。\n\n该平台自主研发差异表达分析、GWAS、QTL定位、WGCNA共表达网络等8项经典生物信息与统计遗传分析工具，并构建多效基因挖掘、基因功能预测、通路与网络挖掘3项自研育种算法。\n\n依托上述知识资源、分析工具和算法能力，农知育芯面向育种科研人员提供智能问答和六大科研场景分析工具，涵盖关键候选基因发现、候选基因功能解析、分子机制与调控通路、基因型—表型—转录组联合研判、种质群体遗传解析和分析结果综合研判。\n\n该平台能提供快速问答、结构化分析和深度研究三类任务模式，可适配知识查询、多组学数据分析和综合育种前景评估等不同需求。系统可自动完成数据分析，汇聚多源文献证据，一键导出标准化PDF科研报告，并提供候选基因优先级排序和后续实验建议，支持PC端科研分析和移动端田间使用，服务育种科研人员和相关专业学生。","中国农业科学院 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