[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4046":3,"related-4046":126},{"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":9,"secondary_topics":31,"classification":32,"search_phrases":89,"slug":92,"view_count":77,"doi":93,"paper":94,"created_at":125},4046,"A comparative description of six public–private consortia in international crop breeding research","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1913809","Public–private partnerships (PPPs) are increasingly important in international agricultural research for delivering improved crop varieties to smallholder farmers in low- and middle-income countries. These partnerships combine public-sector expertise in germplasm and breeding with the private sector’s capacity for product development, technology transfer, and market reach. They also play an increasingly important role in funding international breeding research. As several international crop breeding consortia have been established, there is an opportunity to improve consortium designs through cross-learning. This study offers a comparative description of PPPs in maize, rice, and vegetables—three crops with strong and expanding private-sector interest. Building on the experience of IRRI’s Hybrid Rice Development Consortium (HRDC), CIMMYT’s International Maize Improvement Consortia for Asia, Africa, and Latin America, and the World Vegetable Center’s Vegetable Breeding Consortia in Asia and Africa, this study compares PPP models as they relate to differences in crops and seed systems. The study contributes to a better understanding of where PPPs can be effective and of the evolving role of public breeding research in crops amid increasing private-sector involvement.","公私合作伙伴关系（PPP）在国际农业研究中日益重要，其目标是将改良作物品种推广给中低收入国家的小农户。这些伙伴关系将公共部门在种质资源和育种方面的专业知识，与私营部门在产品开发、技术转移和市场拓展方面的能力相结合。它们在资助国际育种研究方面也发挥着越来越重要的作用。随着多个国际作物育种联盟的建立，通过相互学习来改进联盟设计的机会已经出现。本研究对玉米、水稻和蔬菜——这三种私营部门兴趣浓厚且不断增长的作物——中的PPP进行了比较性描述。基于国际水稻研究所杂交水稻发展联盟（HRDC）、国际玉米小麦改良中心亚洲、非洲和拉丁美洲国际玉米改良联盟，以及世界蔬菜中心亚洲和非洲蔬菜育种联盟的经验，本研究比较了PPP模式在作物和种子体系差异方面的不同。该研究有助于更好地理解PPP在哪些方面能够发挥作用，以及在私营部门参与度不断提高的背景下，公共育种研究在作物领域不断演变的作用。",null,"Frontiers in Sustainable Food Systems","2026-10-02T00:00:00Z","论文",10,false,79,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,8,1,"系统比较六大公私合作育种联盟，对国际种业合作与公共育种定位有实质参考价值，但偏学术综述、时效性一般。",[24],{"name":10,"url":6},[26,27,28,29,30],"种业振兴","小农户","作物育种","公私合作","国际农业研究",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":41,"reason":88},[38,47,53,61,68,75,82],{"code":39,"score":40,"supported":41,"title":42,"abstract":43,"tags":46},"F1",7,true,[],[44,45],"种质资源","germplasm",[26],{"code":48,"score":40,"supported":41,"title":49,"abstract":50,"tags":52},"G2",[],[27,51],"smallholder",[27],{"code":54,"score":55,"supported":41,"title":56,"abstract":57,"tags":60},"A1",6,[],[58,59],"水稻","rice",[],{"code":62,"score":55,"supported":41,"title":63,"abstract":64,"tags":67},"A3",[],[65,66],"玉米","maize",[],{"code":69,"score":55,"supported":41,"title":70,"abstract":71,"tags":74},"B1",[],[72,73],"蔬菜","vegetable",[],{"code":76,"score":77,"supported":41,"title":78,"abstract":79,"tags":81},"A2",3,[],[80],"小麦",[],{"code":83,"score":77,"supported":41,"title":84,"abstract":85,"tags":87},"G1",[],[86],"technology transfer",[],"多个产业证据相当，需要确认主归属",[90,91],"IRRI 杂交水稻 HRDC","CIMMYT 玉米改良联盟","IRRI杂交水稻HRDC-4046","10.3389\u002Ffsufs.2026.1913809",{"doi":93,"openalex_id":95,"authors":96,"venue":10,"cited_by_count":116,"oa_url":117,"card":118,"direction":122,"ingested_from":124},"W7215775126",[97,99,102,104,106,108,110,113],{"name":98,"orcid":9},"Mwasilwa Ambali",{"name":100,"orcid":101},"Jauhar Ali","https:\u002F\u002Forcid.org\u002F0000-0002-3177-2607",{"name":103,"orcid":9},"Linga R. Gutha",{"name":105,"orcid":9},"Aparna Das",{"name":107,"orcid":9},"Ma. Anna Lynn Sevilla",{"name":109,"orcid":9},"Nicholas James Davis",{"name":111,"orcid":112},"Mandy Lin","https:\u002F\u002Forcid.org\u002F0000-0002-5905-7074",{"name":114,"orcid":115},"Pepijn Schreinemachers","https:\u002F\u002Forcid.org\u002F0000-0003-1596-3179",0,"https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1913809\u002Fpdf",{"tldr":119,"method":120,"finding":121,"direction":122,"opportunity":123},"比较了玉米、水稻和蔬菜领域六个公私合作育种联盟的模式与运作。","基于IRRI、CIMMYT和世界蔬菜中心的联盟经验进行案例比较。","PPP设计需适配作物与种子体系差异，公共育种角色正随私企参与而演变。","数字乡村与农业信息化","可研究数字平台如何提升公私育种联盟的知识共享与品种推广效率。","openalex","2026-10-03T23:30:07.627195Z",{"total":55,"page":21,"page_size":55,"items":127},[128,206,294,351,402,460],{"id":129,"title":130,"url":131,"summary":132,"summary_zh":133,"content":9,"source_name":10,"source_url":131,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":134,"score_detail":135,"sources":138,"tags":140,"primary_topic":143,"secondary_topics":146,"classification":152,"search_phrases":182,"slug":185,"view_count":77,"doi":186,"paper":187,"created_at":205},3989,"Different seeds, same pest? Exploring smallholder farmers’ lived experiences of fall armyworm impacts on hybrid and local maize in Kenya","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1925312","Fall Armyworm (FAW) is a persistent threat to maize-based food systems in sub-Saharan Africa, but less is known about how farmers experience its effects across seed types and household livelihoods. This exploratory qualitative study examined smallholder farmers’ lived experiences of FAW damage in hybrid and local maize in Siaya County, Kenya. Face-to-face semi-structured interviews lasting 30–45 min were conducted with 88 purposively selected farmers, and responses were analyzed thematically by two independent researchers. Farmers described FAW as recurrent and difficult to control; 43.2% reported infestation every season. Most participants (77.3%) perceived hybrid maize as more severely affected than local maize, whereas 9.1% perceived local maize as more affected and 9.1% reported similar effects. Participants associated infestation with reduced yields, impaired crop growth, lower-quality harvests, lost income, pesticide and labour costs, depleted maize stocks, food purchases, and stress related to financial and food uncertainty. Reported responses included pesticide use, repeated spraying, purchasing food, crop diversification, and reconsidering maize varieties. Because the study relied on farmers’ accounts rather than controlled varietal comparisons, the perceived differences cannot be attributed to seed characteristics independently of management and growing conditions. The findings indicate that farmers evaluate FAW damage through interconnected production, livelihood, food-security, and seed-choice concerns, supporting locally tested pest-management and seed advisory services.","草地贪夜蛾（Fall Armyworm, FAW）是撒哈拉以南非洲以玉米为基础的粮食系统面临的持续威胁，但人们对农民在不同种子类型和家庭生计条件下如何经历其影响知之甚少。本探索性定性研究考察了肯尼亚西亚亚县小农户在杂交玉米和本地玉米中遭受草地贪夜蛾危害的生活体验。研究对88名有意选取的农民进行了为期30至45分钟的面对面半结构化访谈，并由两名独立研究人员对回答进行主题分析。农民将草地贪夜蛾描述为反复发生且难以控制；43.2%报告每季均发生虫害。大多数参与者（77.3%）认为杂交玉米比本地玉米受害更严重，而9.1%认为本地玉米受害更严重，9.1%报告两者影响相似。参与者将虫害与产量下降、作物生长受损、收成品质量降低、收入损失、农药和劳动力成本、玉米库存耗尽、粮食购买以及与经济和粮食不确定性相关的压力联系起来。报告的应对措施包括使用农药、反复喷药、购买粮食、作物多样化以及重新考虑玉米品种。由于本研究依赖农民叙述而非受控品种比较，所感知的差异不能独立于管理和生长条件而归因于种子特征。研究结果表明，农民通过生产、生计、粮食安全和种子选择等相互关联的关注来评估草地贪夜蛾危害，这支持开展本地化测试的害虫管理和种子咨询服务。",65,{"impact":20,"substance":17,"depth":136,"authority":19,"freshness":13,"relevant":21,"comment":137},16,"基于88户肯尼亚小农户访谈的质性研究，揭示草地贪夜蛾对杂交与本地玉米影响的农户感知差异，对非洲玉米病虫害防控与种子推广有参考价值，但属区域案例、公共影响有限。",[139],{"name":10,"url":131},[26,141,65,27,142],"粮食安全","病虫害防治",{"code":62,"slug":66,"name":65,"path":144,"parent_code":145},"\u002Ftopic\u002Ffield-crops\u002Fmaize","A",[147],{"code":48,"slug":148,"name":149,"path":150,"parent_code":151},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",{"status":153,"locked":14,"version":34,"method":35,"evidence":154},"classified",{"candidates":155,"agricultural_evidence":41},[156,161,165,172,178],{"code":62,"score":157,"supported":41,"title":158,"abstract":159,"tags":160},15,[66],[65,66],[65],{"code":48,"score":157,"supported":41,"title":162,"abstract":163,"tags":164},[51],[27,51],[27],{"code":166,"score":55,"supported":41,"title":167,"abstract":168,"tags":171},"F4",[],[169,170],"农药","pesticide",[],{"code":173,"score":174,"supported":41,"title":175,"abstract":176,"tags":177},"A8",4,[],[141],[141],{"code":39,"score":21,"supported":14,"title":179,"abstract":180,"tags":181},[],[],[26],[183,184],"肯尼亚 草地贪夜蛾 玉米","杂交玉米 本地玉米 虫害","肯尼亚草地贪夜蛾玉米-3989","10.3389\u002Ffsufs.2026.1925312",{"doi":186,"openalex_id":188,"authors":189,"venue":10,"cited_by_count":116,"oa_url":131,"card":200,"direction":122,"ingested_from":124},"W7215042180",[190,193,195,197],{"name":191,"orcid":192},"George Ariya","https:\u002F\u002Forcid.org\u002F0000-0003-2286-9455",{"name":194,"orcid":9},"Beatrice Cheserek",{"name":196,"orcid":9},"Violet Kadenyeka Mugalavai",{"name":198,"orcid":199},"Lizzy A. Mwamburi","https:\u002F\u002Forcid.org\u002F0000-0002-8435-8194",{"tldr":201,"method":202,"finding":203,"direction":122,"opportunity":204},"通过访谈肯尼亚88位小农户，探究其对杂交与本地玉米受草地贪夜蛾影响的真实体验。","对88位农户进行半结构化访谈，采用主题分析法。","77.3%农户认为杂交玉米受害更重，虫害带来减产、收入损失与粮食不安全。","可结合农户感知数据与遥感虫害监测，构建面向小农户的本地化预警与品种推荐决策模型。","2026-10-02T23:30:09.411010Z",{"id":207,"title":208,"url":209,"summary":210,"summary_zh":211,"content":9,"source_name":10,"source_url":209,"published_at":212,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":213,"score_detail":214,"sources":216,"tags":218,"primary_topic":222,"secondary_topics":225,"classification":238,"search_phrases":267,"slug":270,"view_count":174,"doi":271,"paper":272,"created_at":293},3263,"Identifying drought-responsive candidate genes in root and shoot tissues of wheat (Triticum aestivum L.) through RNA sequencing, cluster analysis, weighted gene co-expression network analysis, and machine learning models","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1952456","Drought stress severely affects the growth, development, and yield formation of wheat. However, the differentiated regulatory mechanisms of wheat roots and shoots during drought adaptation remain to be further analyzed. Therefore, this study used RNA-seq datasets of roots and shoots from multiple wheat varieties, combined with differential expression analysis, Gene Ontology (GO) enrichment analysis, clustering analysis, weighted gene co-expression network analysis (WGCNA), and machine learning were used to characterize drought-responsive transcriptional changes. Differential expression analysis identified 90 and 3,991 differentially expressed genes (DEGs) in roots under DS1 and DS2 respectively, compared with 34 and 1,940 DEGs in shoots. Functional enrichment analysis indicated that root DEGs were mainly involved in root growth, cell wall remodeling, water transport, and osmotic adjustment processes, whereas shoot DEGs are mainly enriched in processes related to stomatal regulation, photosynthesis, lipid metabolism, and oxidative stress responses. WGCNA identified 18 and 19 co-expression modules in roots and shoots, respectively, among which the yellow module was significantly correlated with the response to drought stress in root and shoot tissues. To further screen drought-responsive candidate genes from these modules, we compared multiple machine learning models. The XGBoost model achieved the highest and AUC in both roots and shoots. Combined with SHAP feature contribution analysis, 30 drought-responsive candidate genes with high discriminatory power were identified separately in roots and shoots. Analysis of cis -acting elements in candidate gene promoters revealed abundant drought- and stress-responsive elements, including MYB, G-box, ABRE, MYC, MBS, and LTR. MYB (183 in roots and 164 in shoots), G-box (168 and 98), and ABRE (148 and 86) were particularly abundant, and several candidate genes contained more than five ABRE copies in their promoters, suggesting potential involvement in ABA-mediated drought responses. This study reveals the different transcriptional response processes of wheat roots and shoots under drought stress, and identifies key co-expression modules and core candidate genes through WGCNA combined with XGBoost and SHAP analysis. These findings provide a basis for understanding organ-specific molecular responses to drought stress and offer potential targets for improving drought tolerance in wheat.","干旱胁迫严重影响小麦的生长发育和产量形成。然而，小麦根系和地上部在干旱适应过程中的差异化调控机制仍有待深入解析。因此，本研究利用多个小麦品种根系和地上部的RNA-seq数据集，结合差异表达分析、基因本体（GO）富集分析、聚类分析、加权基因共表达网络分析（WGCNA）和机器学习方法，表征干旱响应转录变化。差异表达分析在DS1和DS2条件下分别鉴定出根系中90个和3,991个差异表达基因（DEGs），而地上部中分别为34个和1,940个DEGs。功能富集分析表明，根系DEGs主要参与根系生长、细胞壁重塑、水分运输和渗透调节过程，而地上部DEGs主要富集于气孔调控、光合作用、脂质代谢和氧化胁迫响应相关过程。WGCNA在根系和地上部中分别鉴定出18个和19个共表达模块，其中黄色模块与根系和地上部组织对干旱胁迫的响应显著相关。为进一步从这些模块中筛选干旱响应候选基因，我们比较了多种机器学习模型。XGBoost模型在根系和地上部中均取得了最高的AUC。结合SHAP特征贡献分析，分别在根系和地上部中鉴定出30个具有高判别力的干旱响应候选基因。候选基因启动子中的顺式作用元件分析揭示了丰富的干旱和胁迫响应元件，包括MYB、G-box、ABRE、MYC、MBS和LTR。其中MYB（根系183个，地上部164个）、G-box（168个和98个）和ABRE（148个和86个）尤为丰富，且多个候选基因的启动子中含有超过5个ABRE拷贝，表明其可能参与ABA介导的干旱响应。本研究揭示了小麦根系和地上部在干旱胁迫下不同的转录响应过程，并通过WGCNA结合XGBoost和SHAP分析鉴定了关键共表达模块和核心候选基因。这些发现为理解干旱胁迫的器官特异性分子响应提供了基础，并为提高小麦耐旱性提供了潜在靶点。","2026-09-23T00:00:00Z",81,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":13,"relevant":21,"comment":215},"该研究结合多组学与机器学习挖掘小麦抗旱候选基因，方法新颖、数据扎实，对分子育种有参考价值，值得进入每日精选。",[217],{"name":10,"url":209},[219,26,220,28,221],"农业人工智能","基因挖掘","小麦抗旱",{"code":76,"slug":223,"name":80,"path":224,"parent_code":145},"wheat","\u002Ftopic\u002Ffield-crops\u002Fwheat",[226,232],{"code":227,"slug":228,"name":229,"path":230,"parent_code":231},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"code":233,"slug":234,"name":235,"path":236,"parent_code":237},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":153,"locked":14,"version":34,"method":35,"evidence":239},{"candidates":240,"agricultural_evidence":41},[241,247,252,258,262],{"code":227,"score":157,"supported":41,"title":242,"abstract":244,"tags":246},[243],"machine learning",[245,243],"机器学习",[219],{"code":76,"score":248,"supported":41,"title":249,"abstract":250,"tags":251},14,[223],[80,223],[],{"code":233,"score":248,"supported":41,"title":253,"abstract":255,"tags":257},[254],"drought",[256,254],"干旱",[],{"code":39,"score":21,"supported":14,"title":259,"abstract":260,"tags":261},[],[],[26],{"code":263,"score":21,"supported":14,"title":264,"abstract":265,"tags":266},"F2",[],[],[220],[268,269],"小麦 抗旱基因 RNA测序","小麦 根系 地上部 干旱响应","小麦抗旱基因RNA测序-3263","10.3389\u002Ffsufs.2026.1952456",{"doi":271,"openalex_id":273,"authors":274,"venue":10,"cited_by_count":116,"oa_url":209,"card":287,"direction":291,"ingested_from":124},"W7214062209",[275,277,280,282,284],{"name":276,"orcid":9},"Tianle Ji",{"name":278,"orcid":279},"Baoyue Cui","https:\u002F\u002Forcid.org\u002F0009-0000-5881-9682",{"name":281,"orcid":9},"Jinjie Yin",{"name":283,"orcid":9},"Xianyong Meng",{"name":285,"orcid":286},"Jun Yan","https:\u002F\u002Forcid.org\u002F0000-0001-6883-8529",{"tldr":288,"method":289,"finding":290,"direction":291,"opportunity":292},"通过RNA-seq、WGCNA和XGBoost-SHAP分析，鉴定小麦根和茎中响应干旱的候选基因。","RNA-seq、差异表达、WGCNA、XGBoost与SHAP特征分析。","根和茎干旱响应机制不同，各鉴定出30个候选基因，启动子富含MYB、G-box和ABRE元件。","农业人工智能与决策模型","可结合多组学与深度学习构建器官特异性干旱调控网络，并开展候选基因功能验证。","2026-09-23T23:30:07.062126Z",{"id":295,"title":296,"url":297,"summary":298,"summary_zh":299,"content":9,"source_name":10,"source_url":297,"published_at":300,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":213,"score_detail":301,"sources":303,"tags":305,"primary_topic":309,"secondary_topics":310,"classification":311,"search_phrases":329,"slug":332,"view_count":333,"doi":334,"paper":335,"created_at":350},3138,"The role of improved seed variety and information access in moderating the effect of cluster farming on climate resilience: a global meta-analysis with a focus on Ethiopia","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1718735","Climate change increasingly threatens rain-fed agriculture in developing countries like Ethiopia. Cluster farming has emerged as a potential strategy to enhance smallholder resilience; however, existing evidence remains fragmented. Following PRISMA guidelines, we conducted a systematic review and meta-analysis of 18 peer-reviewed studies (2000–2025), including eight from Ethiopia. Random-effects models were used to calculate pooled standardized mean differences (SMDs). Subgroup analysis, meta-regression, and publication bias assessments were performed. Cluster farming had a significant positive effect on climate resilience [pooled SMD = 0.55 (95% CI: 0.48–0.62), p \u003C 0.001]. Heterogeneity was substantial (I 2 = 63.86%) but fully explained by outcome measurement type. Composite resilience indices showed the largest effects (SMD = 0.74), followed by practice counts (SMD 0.52) and binary outcomes (SMD = 0.51). Meta-regression analysis revealed that neither information access (coef. =0.2819, p = 0.722), nor access to improved seed (coef. = 0.0384, p = 0.502) were statistically significant moderators. Cluster farming significantly enhances smallholder climate resilience, and the benefits appear consistent across different levels of information access and seed quality. Policymakers should promote integrated resilience measurement and contextualize interventions based on local infrastructure and extension capabilities.","气候变化日益威胁着埃塞俄比亚等发展中国家的雨养农业。集群农业（cluster farming）已成为提升小农户韧性的潜在策略，然而现有证据仍较为零散。遵循PRISMA指南，我们对18项同行评审研究（2000—2025年）进行了系统综述与元分析，其中8项来自埃塞俄比亚。采用随机效应模型计算合并标准化均数差（SMDs）。进行了亚组分析、元回归及发表偏倚评估。集群农业对气候韧性具有显著正向效应[合并SMD = 0.55（95% CI：0.48–0.62），p \u003C 0.001]。异质性较大（I² = 63.86%），但可由结果测量类型完全解释。综合韧性指数显示最大效应（SMD = 0.74），其次为实践计数（SMD = 0.52）和二元结果（SMD = 0.51）。元回归分析表明，信息获取（系数 = 0.2819，p = 0.722）和改良种子获取（系数 = 0.0384，p = 0.502）均非统计学显著的调节变量。集群农业显著增强了小农户的气候韧性，且其效益在不同信息获取水平和种子质量下似乎保持一致。政策制定者应推动综合性韧性测量，并根据当地基础设施和推广能力对干预措施进行情境化调整。","2026-09-22T00:00:00Z",{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":13,"relevant":21,"comment":302},"基于18项研究的全球荟萃分析，方法规范、结论明确，对气候韧性农业与信息服务的政策设计有参考价值。",[304],{"name":10,"url":297},[26,27,306,307,308],"气候韧性","集群农业","信息获取",{"code":233,"slug":234,"name":235,"path":236,"parent_code":237},[],{"status":153,"locked":14,"version":34,"method":35,"evidence":312},{"candidates":313,"agricultural_evidence":41},[314,321,325],{"code":233,"score":17,"supported":41,"title":315,"abstract":317,"tags":320},[316],"climate resilience",[318,319,316],"气候变化","climate change",[306],{"code":48,"score":40,"supported":41,"title":322,"abstract":323,"tags":324},[],[27,51],[27],{"code":39,"score":21,"supported":14,"title":326,"abstract":327,"tags":328},[],[],[26],[330,331],"埃塞俄比亚 集群农业 气候韧性","改良品种 信息获取 小农户","埃塞俄比亚集群农业气候韧性-3138",5,"10.3389\u002Ffsufs.2026.1718735",{"doi":334,"openalex_id":336,"authors":337,"venue":10,"cited_by_count":116,"oa_url":297,"card":344,"direction":348,"ingested_from":124},"W7213897466",[338,341],{"name":339,"orcid":340},"Haile Tamiru","https:\u002F\u002Forcid.org\u002F0000-0003-3641-5809",{"name":342,"orcid":343},"Jun He","https:\u002F\u002Forcid.org\u002F0000-0003-4839-3950",{"tldr":345,"method":346,"finding":347,"direction":348,"opportunity":349},"通过荟萃分析评估集群农业对气候韧性的影响，并检验改良种子与信息获取的调节作用。","遵循PRISMA，对18项研究（含8项埃塞俄比亚）做随机效应荟萃分析、亚组与元回","集群农业显著提升小农气候韧性（SMD=0.55），但信息获取和改良种子无显著调节作用。","农业绿色发展与碳","可探索不同信息渠道与种子体系下集群农业韧性的异质性机制及长期动态效应。","2026-09-22T23:30:07.548501Z",{"id":352,"title":353,"url":354,"summary":355,"summary_zh":9,"content":356,"source_name":357,"source_url":9,"published_at":358,"category":359,"cover_url":9,"hotness":13,"is_selected":14,"score":360,"score_detail":361,"sources":364,"tags":366,"primary_topic":368,"secondary_topics":372,"classification":373,"search_phrases":396,"slug":399,"view_count":400,"doi":9,"paper":9,"created_at":401},2850,"安徽农业大学举办《Agriculture and Biology》刊物建设及作物学发展研讨会","https:\u002F\u002Fkjc.ahau.edu.cn\u002Finfo\u002F1061\u002F16769.htm","9月18日,《Agriculture and Biology》刊物建设及作物学发展研讨会在安徽农业大学生物科技楼举行,会议由安徽农业大学校长操海群致辞、农学院院长王晓波主持。来自中国农业科学院作物科学研究所、中国农业大学、华东理工大学、河南省农业科学院、中国农业科学院生物技术研究所、安徽省农科院水稻研究所、江南大学、浙江大学的9位专家学者作大会报告,围绕玉米抗倒伏基因挖掘、玉米多位点抗灰斑协同机制、植物免疫激活剂创制、油料种质资源学科发展、花生新种质创制、水稻耐盐性遗传改良、杂交水稻轻简化制种的分子设计等议题展开研讨。","地点: 安徽农业大学 生物科技楼 B438 会议室\n\n时间：2026 年 9 月 18 日\n\n**时段****内容**\n**开幕式**\n主持人：姜东\n8:00-8:05 领导致辞：操海群（安徽农业大学校长）\n8:05-8:10 学科介绍：王晓波（安徽农业大学农学院院长）\n8:10-8:15 AB 期刊介绍：魏鹏程（安徽农业大学生物育种研究中心常务副主任）\n******时段****报告题目****报告人****单位**\n**大会报告**\n主持人：王晓波\n8:15-8:3 0 玉米抗倒伏基因的挖掘与利用 李文学 中国农业科学院作物科学研究所\n8:3 0-8:4 5 玉米多位点抗灰斑的协同机制及基于基因组序列的精准改良 徐明良 中国农业大学农学院\n8:4 5-9:00 植物免疫激活剂创制及应用 徐玉芳 华东理工大学\n9:00-9:1 5 油料种质资源学科发展与趋势 蔡光勤 中国农业科学院油料作物研究所\n9:1 5-9:30 花生新种质创制及其部分重要基因应用 韩锁义 河南省农业科学院\n主持人：魏鹏程\n9:30-9:45 水稻耐盐性的遗传改良 黄荣峰 中国农业科学院生物技术研究所\n9:45-10:00 杂交水稻轻简化制种的分子设计 倪大虎 安徽省农科院水稻研究所\n10:00-10:15 合成生物学关键技术与产业化应用 刘立明 江南大学\n10:1 5-10:30 水稻优异抗逆基因挖掘与育种应用 宋士勇 浙江大学\n10:30-10:40 赋能学术，共创未来：EIVX出版集团期刊发展报告 李恋 EIVX出版集团AB期刊出版人\n10:40-10:45 领导总结：江海洋（安徽农业大学 副 校长）\n**期刊建设****与学科发展研讨****会**\n10:50-1 2:0 0 地点：生物科技楼 B420 会议室 主持人：姜东\n\n**大会报告专家简介**\n\n### ![Image 1: 17CA3](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F8\u002F33\u002F52\u002F7954483132FE74AB3860E7B4F1E_3668424C_17CA3.png)\n\n### **李文学**\n\n### 中国农业科学院作物科学研究所二级研究员，博士生导师。入选国家级人才计划领军人才（2017年），科技部创新人才推进计划“中青年科技创新领军人才”（2017年），教育部“新世纪优秀人才支持计划”（2009年）。2019年被聘为中国农科院作物分子育种技术与创新团队首席专家，兼任The Crop Journal编委。课题组重点解析玉米养分高效利用的分子机制及玉米倒伏的分子通路，主持国家自然科学基金重点项目、国家自然科学基金国际合作项目等多项课题。研究成果发表在Science、Nulceic Acids Research、Plant Cell、Molecular Plant、New Phytologist等学术期刊，多篇为ESI高被引文章。\n\n### **报告题目：**玉米抗倒伏基因的挖掘与利用\n\n### ![Image 2: C954](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F7\u002F4A\u002FDA\u002F62E2125D3D8895A135251EF407C_35F5A044_C954.png)**徐明良**\n\n### 中国农业大学农学院教授，国家杰出青年科学基金获得者，全国百篇优秀博士学位论文指导教师，中国高被引学者。长期从事玉米功能基因组学与分子生物学研究，历经二十余年攻关，围绕玉米茎腐病、丝黑穗病、矮花叶病、粗缩病、灰斑病等主要病害，成功克隆 ZmWAKL、ZmCPK39 等多个数量抗病基因并阐明其抗性机制，相关成果发表于 Nature Genetics、Molecular Plant、Nature Communications、PNAS、Plant Cell等国际权威学术期刊；建立的抗病分子标记辅助导入技术已在全国二十多家骨干育种单位应用，为玉米抗病分子育种提供了重要的理论、技术与基因资源支撑。\n\n### **报告题目：**玉米多位点抗灰斑的协同机制及基于基因组序列的精准改良\n\n### ![Image 3: 547D4](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002FF\u002F7E\u002FD5\u002FEE4341CDEAD26371F4A36D257DE_6AB6BDEF_547D4.png)**徐玉芳**\n\n### 华东理工大学教授、博士生导师，国家重点研发计划“新型植物免疫激活剂创制与产业化”项目首席科学家，享受国务院政府特殊津贴，上海市优秀学科带头人。主要从事化学生物技术研究，涵盖荧光传感技术与新型植物免疫激活剂创制，主持国家自然科学基金、国家重大新药创制项目、973及863课题等多项国家级项目；已在J. Am. Chem. Soc.、Angew. Chem. Int. Ed.等国际SCI期刊发表论文150余篇，申请发明专利59项，获国家科技进步二等奖。\n\n### **报告题目：**植物免疫激活剂创制及应用\n\n### ![Image 4: A84D](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F6\u002FE1\u002FE0\u002F744F70FBA37AE51D5BBAEBD0F99_3D0FEDB6_A84D.png)**蔡光勤**\n\n### 中国农业科学院油料作物研究所特聘研究员、博士生导师，油菜种质资源创新团队首席科学家，国家油料作物种质资源中期库主任，国家油菜产业技术体系副首席科学家兼种质资源鉴定与新种质创制岗位科学家，国家自然科学基金优秀青年科学基金获得者，中国农业科学院“农科英才”领军人才（B类），湖北省“知名专家”入选者。主要从事油菜种质资源发掘鉴定与创新利用研究，主持国家重点研发计划、国家自然科学基金优青项目等国家级课题6项，在 Molecular Plant、Nature Communications、New Phytologist 等期刊发表论文40余篇，授权国家发明专利15项；指导创制的油菜新品系 Q924 含油量达65.2%，创世界油菜含油量最高纪录。兼任《Oil Crop Science》副主编，《中国油料作物学报》《植物遗传资源学报》编委。\n\n**报告题目：**油料种质资源学科发展与趋势\n\n### ![Image 5: 140D8](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F8\u002FAC\u002F78\u002FCF19931B85000EF29FA8E48A58E_11B7A4D9_140D8.png)**韩锁义**\n\n### 河南省农业科学院研究员，神农种业实验室花生团队副主任。2008年获南京农业大学生物化学与分子生物学专业博士学位，曾为美国塔斯基吉大学访问学者。长期从事花生分子遗传与新种质创制研究，先后主持国家自然科学基金面上项目、河南省联合基金重点项目、河南省科技攻关等项目，围绕花生晚斑病抗性基因定位克隆、籽仁大小调控及黄曲霉抗性等开展系统研究，参与培育豫花9326、豫花47号等高油花生新品种，相关成果获河南省科技进步特等奖、一等奖多项，发表学术论文80余篇。\n\n**报告题目：**花生新种质创制及其部分重要基因应用\n\n### ![Image 6: 719FD](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F4\u002FA9\u002F71\u002F7FF46BC888D94E3C4B44DF0F605_7A1DF664_719FD.png)**黄荣峰**\n\n### 中国农业科学院生物技术研究所二级研究员、博士生导师，国家杰出青年科学基金获得者（2005年），农业农村部有突出贡献的中青年专家，“新世纪知名专家”国家级人选，享受国务院政府特殊津贴。长期从事作物逆境胁迫适应与遗传改良研究，以水稻和拟南芥为材料，系统解析乙烯与其他植物激素互作协同调控作物生长发育与耐盐性的分子机制，发掘OsDSK2a等耐盐关键基因。主持国家自然科学基金重大研究计划、重点和面上项目、国家转基因植物专项等课题20余项，在Plant Cell、Molecular Plant、New Phytologist等国际期刊发表SCI论文80余篇，授权发明专利19项。\n\n**报告题目：**水稻耐盐性的遗传改良\n\n### ![Image 7: 1580E](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F1\u002FB6\u002FB7\u002FE4BEA6D471AF70EA4F896123757_FE52EA35_1580E.png)**倪大虎**\n\n### 安徽省农业科学院水稻研究所所长、研究员，享受安徽省特殊津贴，入选安徽省学术和技术带头人。长期从事水稻遗传育种、水稻分子遗传与新品种选育研究，主持国家“863”计划课题“抗逆高产水稻分子育种与品种创制”、国家自然科学基金等多项课题；利用分子标记辅助选择将广谱抗稻瘟病基因Pi9与抗白叶枯病基因Xa21\u002FXa23聚合到优良株系，培育多个多抗基因聚合株系和杂交水稻亲本。获安徽省科技进步一等奖、二等奖及神农中华农业科技奖一等奖，近年围绕杂交水稻轻简化制种与再生稻开展分子设计与成果转化，示范推广面积显著。\n\n**报告题目：**杂交水稻轻简化制种的分子设计\n\n### ![Image 8: 28A18](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F2\u002F5A\u002F6A\u002F1115CD50A3CBE6332F3C6B38177_F05A5E35_28A18.png)**刘立明**\n\n### 江南大学生物工程学院二级教授、博士生导师，教育部知名专家计划特聘教授，中国化工学会精细化学品专委会副主任委员。长期从事合成生物学与微生物制造研究，主持国家重点研发计划、国家自然科学基金重点及优青项目等国家或省部级项目20余项；在 Nature Catalysis、Nature Communications、Chemical Reviews、Metabolic Engineering 等期刊发表SCI论文220余篇，授权发明专利120余项，出版科技著作6部；与发酵行业头部企业深度合作，实现11 个精细化学品的工业化生产，年生产规模达千吨至十万吨级。相关成果获国家技术发明二等奖、教育部科技进步一等奖、中国石油与化学工业联合会科技进步一等奖等。\n\n**报告题目：**合成生物学关键技术与产业化应用\n\n### ![Image 9: 9607](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002FE\u002F75\u002FFC\u002F0A358E82F1532D1F50A1DFF14A3_03A7E639_9607.png)**宋士勇**\n\n### 浙江大学农业与生物技术学院研究员、博士生导师，现代种业研究所副所长。2008—2013年于中国科学院植物研究所硕博连读获博士学位，2012—2017 年在新加坡国立大学俞皓院士实验室从事博士后研究，2017年回国创建水稻抗逆分子育种团队，2020年获浙江省杰出青年科学基金资助，2023 年获国家自然科学基金优秀青年科学基金资助。团队长期聚焦水稻优异抗逆基因发掘与育种应用，深入解析蛋白转运系统、植物激素及转录因子调控水稻干旱、极端温度等逆境响应的分子机制，以通讯作者在Nature Plants、Science Advances、The Plant Cell、Molecular Plant、Cell Reports等期刊发表系列成果，任JIPB、New Crops、Crop Design等期刊编委。\n\n**报告题目：**水稻优异抗逆基因挖掘与育种应用\n\n### ![Image 10: 1879B](https:\u002F\u002Fkjc.ahau.edu.cn\u002F__local\u002F6\u002FA0\u002F40\u002F3C0DF307340ECB1EDA6F3EB6572_BFD0907C_1879B.png)**李恋**\n\n### EIVX出版集团AB期刊出版人，长期从事学术期刊出版、运营与国际化传播工作，致力于搭建高水平学术交流与成果传播平台，推动农业与生命科学领域科技期刊的集群化建设与高质量发展。\n\n### **报告****题目：**赋能学术，共创未来：EIVX出版集团期刊发展报告","安徽农业大学科技处","2026-09-18T00:00:00Z","报道",61,{"impact":362,"substance":248,"depth":362,"authority":19,"freshness":13,"relevant":21,"comment":363},12,"高校主办的作物学与期刊建设研讨会，含多位国家级专家报告，专业信息量尚可但属会议通稿，影响面限于学术圈。",[365],{"name":357,"url":354},[58,26,65,28,367],"学术期刊",{"code":145,"slug":369,"name":370,"path":371,"parent_code":9},"field-crops","大田作物","\u002Ftopic\u002Ffield-crops",[],{"status":374,"locked":14,"version":34,"method":35,"evidence":375},"partial",{"candidates":376,"agricultural_evidence":41,"reason":395},[377,381,385,389],{"code":54,"score":174,"supported":41,"title":378,"abstract":379,"tags":380},[],[58],[58],{"code":62,"score":174,"supported":41,"title":382,"abstract":383,"tags":384},[],[65],[65],{"code":39,"score":174,"supported":41,"title":386,"abstract":387,"tags":388},[],[44],[26],{"code":390,"score":77,"supported":41,"title":391,"abstract":392,"tags":394},"A4",[],[393],"花生",[],"一级领域明确，二级方向需要细分",[397,398],"作物育种 学术期刊 种业振兴 水稻","作物育种 学术期刊","作物育种学术期刊种业振兴水稻-2850",2,"2026-09-18T00:03:29.377237Z",{"id":403,"title":404,"url":405,"summary":406,"summary_zh":407,"content":9,"source_name":408,"source_url":405,"published_at":409,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":410,"score_detail":411,"sources":414,"tags":416,"primary_topic":420,"secondary_topics":421,"classification":423,"search_phrases":440,"slug":443,"view_count":116,"doi":444,"paper":445,"created_at":459},5592,"Evaluation of Concept-Rank Collapse Audits for Computer Vision Agriculture Disease Classifiers Under Low-Label Regimes: An Interpretability Capacity Bound for Smallholder Fungicide Selectivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545193","Concept-based interpretability methods for plant-disease classifiers are typically evaluated by whether their concept activations correlate with human-annotated labels, but this criterion is silent on a prior question: whether the classifier's internal representation retains enough concept-rank structure for any audit to be informative. the present analysis formalises that prior question as an interpretability capacity bound. A classifier is modelled as a concept-rank operator whose singular values govern how much concept-level signal survives the projection from pixel space to class logits, and a collapse audit is defined as the ratio of retained concept-rank energy to total concept energy. Under a low-label regime, where concept annotations are scarce and the audit must be estimated from few labelled examples, the bound predicts that audit reliability degrades as a function of the concept-rank spectrum and the label budget. The analysis is a theoretical and methodological contribution: it derives the bound, states the conditions under which a collapse audit is identifiable, and characterises the operating characteristics of the audit as a decision procedure under a declared variance structure (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.64). Power was estimated across 2000 design cells for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points; 52 clusters were required for 5 percentage points at 80% power. The bound reframes concept audits as capacity tests rather than fidelity tests, with consequences for how smallholder fungicide-selectivity decisions should be supported by interpretable disease classifiers.","面向植物病害分类器的基于概念的可解释性方法，通常以其概念激活是否与人工标注标签相关作为评价标准，但该标准对一个更先前的问题保持沉默：分类器的内部表征是否保留了足够的概念秩结构，从而使任何审计具有信息量。本分析将该先前问题形式化为一个可解释性容量上界。分类器被建模为概念秩算子，其奇异值支配着从像素空间到类别logits的投影中概念级信号得以保留的程度，并将坍缩审计定义为保留的概念秩能量与总概念能量之比。在低标签情形下，概念标注稀缺且审计必须由少量标注样本估计，该上界预测审计可靠性会随概念秩谱和标签预算的函数而退化。本分析是一项理论和方法论贡献：推导出该上界，陈述坍缩审计可识别的条件，并在声明的方差结构（簇间SD = 6.0，残差SD = 4.5，组内相关系数 = 0.64）下刻画审计作为决策程序的操作特征。在2000个设计单元中，针对簇数为8、16、24和32以及效应量为3、5和8个百分点的情形估计了功效；在80%功效下达到5个百分点需要52个簇。该上界将概念审计重新框定为容量检验而非保真度检验，并对可解释病害分类器应如何支持小农杀菌剂选择性决策具有启示意义。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",69,{"impact":20,"substance":412,"depth":17,"authority":362,"freshness":13,"relevant":21,"comment":413},21,"理论方法论文，提出可解释性容量上界并给出审计功效分析，对智慧农业病害识别可信度有参考价值，但属小众方法学研究、缺乏田间实证，暂不宜进入每日精选。",[415],{"name":408,"url":405},[417,219,27,418,419],"智慧农业","植物病害识别","可解释性",{"code":48,"slug":148,"name":149,"path":150,"parent_code":151},[422],{"code":227,"slug":228,"name":229,"path":230,"parent_code":231},{"status":153,"locked":14,"version":34,"method":35,"evidence":424},{"candidates":425,"agricultural_evidence":41},[426,430,435],{"code":48,"score":362,"supported":41,"title":427,"abstract":428,"tags":429},[51],[51],[27],{"code":227,"score":13,"supported":41,"title":431,"abstract":433,"tags":434},[432],"computer vision",[],[219,418],{"code":436,"score":21,"supported":14,"title":437,"abstract":438,"tags":439},"I1",[],[],[417],[441,442],"农业人工智能 植物病害识别 可解释性 智慧农业","农业人工智能 植物病害识别","农业人工智能植物病害识别可解释性智慧农业-5592","10.5281\u002Fzenodo.23545193",{"doi":444,"openalex_id":446,"authors":447,"venue":408,"cited_by_count":116,"oa_url":405,"card":454,"direction":291,"ingested_from":124},"W7223137323",[448,450,452],{"name":449,"orcid":9},"Akshay Ramgoolam",{"name":451,"orcid":9},"Priya Bundhoo Appadoo",{"name":453,"orcid":9},"Jean-Noël LEspérance",{"tldr":455,"method":456,"finding":457,"direction":291,"opportunity":458},"提出可解释性容量上界，评估低标签下概念秩崩溃审计的可靠性。","将分类器建模为概念秩算子，推导容量上界并做2000格功效模拟。","审计可靠性随概念秩谱与标签预算下降；5个百分点效应需52个聚类达80%功效。","可将容量上界用于小农户杀菌剂选择性决策的可解释模型审计与标签预算设计。","2026-10-22T11:21:10.425290Z",{"id":461,"title":462,"url":463,"summary":464,"summary_zh":465,"content":9,"source_name":408,"source_url":463,"published_at":409,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":466,"score_detail":467,"sources":469,"tags":471,"primary_topic":474,"secondary_topics":475,"classification":477,"search_phrases":492,"slug":495,"view_count":116,"doi":496,"paper":497,"created_at":511},5590,"Evaluation of Concept-Probe Temporal-Stability Audits for Computer Vision Agriculture Disease Classifiers Under Seasonal Phenology Drift: An Interpretability Decay Bound for Smallholder Fungicide Timing","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545234","Concept-probe audits are increasingly used to certify that a crop-disease classifier's internal representations track the pathological concepts a smallholder would act on, but a probe certified at one point in the season may silently decouple from those concepts as phenology shifts the visual statistics of the field. the present analysis treats that decoupling as a formal object. It defines a temporal-stability audit as a sequence of concept-probe accuracies measured across defined phenological windows, and it derives an interpretability decay bound: the rate at which probe accuracy can fall before the fungicide-timing decision it is meant to support becomes unreliable. The bound is expressed as a function of the probe's initial margin, the drift in concept prevalence between windows, and the classifier's sensitivity to the drifted features, and it yields a certified audit interval rather than a single-point certificate. The paper then characterises the operating characteristics of the audit design under a declared variance structure, using a replication-based evaluation of the before-after-control-impact estimator with between-cluster SD = 6.0, residual SD = 4.5 and intraclass correlation = 0.64. Power was estimated across 2000 design cells over cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points; 54 clusters were required for 5 percentage points at 80% power. The contribution is a decision-theoretic account of when a concept-probe certificate expires, and a design rule for scheduling re-audits across the season.","概念探针审计（concept-probe audit）日益被用于验证作物病害分类器的内部表征是否追踪小农户会据以采取行动的病理学概念，但在生长季某一时点获得认证的探针，可能随着物候变化改变田间的视觉统计特征而悄然与这些概念脱钩。本分析将这种脱钩视为一个形式化对象。它将时间稳定性审计（temporal-stability audit）定义为在既定物候窗口内测量的一系列概念探针准确率，并推导出一个可解释性衰减界限（interpretability decay bound）：即探针准确率在其所支持的杀菌剂施用时机决策变得不可靠之前所能下降的速率。该界限表示为探针初始裕度、窗口间概念流行率漂移以及分类器对漂移特征敏感度的函数，并给出一个经认证的审计区间而非单点认证。随后，本文在声明的方差结构下刻画该审计设计的运行特征，采用基于重复的前后对照影响估计量评估，其中组间标准差 = 6.0、残差标准差 = 4.5、组内相关系数 = 0.64。功效在 2000 个设计单元上估计，聚类数取 8、16、24 和 32，效应量取 3、5 和 8 个百分点；在 80% 功效下达到 5 个百分点需要 54 个聚类。本文的贡献在于从决策论角度阐明概念探针认证何时失效，并给出在整个生长季内安排重新审计的设计规则。",70,{"impact":20,"substance":18,"depth":17,"authority":362,"freshness":13,"relevant":21,"comment":468},"该论文提出概念探针审计的时序稳定性框架与可解释性衰减界，方法新颖、统计设计扎实，但属小众方法论研究，产业影响有限，适合作为专业精选而非头条。",[470],{"name":408,"url":463},[417,219,27,472,473],"作物病害识别","模型审计",{"code":48,"slug":148,"name":149,"path":150,"parent_code":151},[476],{"code":227,"slug":228,"name":229,"path":230,"parent_code":231},{"status":153,"locked":14,"version":34,"method":35,"evidence":478},{"candidates":479,"agricultural_evidence":41},[480,484,488],{"code":48,"score":157,"supported":41,"title":481,"abstract":482,"tags":483},[51],[27,51],[27],{"code":227,"score":13,"supported":41,"title":485,"abstract":486,"tags":487},[432],[],[472,219],{"code":436,"score":21,"supported":14,"title":489,"abstract":490,"tags":491},[],[],[417],[493,494],"概念探针 时序稳定性 作物病害分类器","杀菌剂 施药时机 可解释性衰减","概念探针时序稳定性作物病害分类器-5590","10.5281\u002Fzenodo.23545234",{"doi":496,"openalex_id":498,"authors":499,"venue":408,"cited_by_count":116,"oa_url":463,"card":506,"direction":291,"ingested_from":124},"W7223088030",[500,502,504],{"name":501,"orcid":9},"Abdi-Basid Idriss Farah",{"name":503,"orcid":9},"Amina Abdillahi Guedi",{"name":505,"orcid":9},"Moussa Omar Youssouf",{"tldr":507,"method":508,"finding":509,"direction":291,"opportunity":510},"提出概念探针时间稳定性审计与可解释性衰减界，判断何时需重新审计。","定义跨物候窗口探针精度序列，推导衰减界，用BACI复制评估统计功效。","5个百分点效应需54个聚类达80%功效，审计证书会随物候漂移过期。","可将衰减界与再审计调度规则嵌入小农户杀菌剂时机决策支持系统，并验证跨作物泛化。","2026-10-22T11:21:08.978348Z"]