[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1215":3,"related-1215":70},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":17,"tags":19,"primary_topic":21,"secondary_topics":27,"classification":28,"search_phrases":47,"slug":48,"view_count":43,"doi":49,"paper":50,"created_at":69},1215,"Beyond the trees: Exploring the determinants of intercrop management intensity in smallholder immature rubber systems in Thailand","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104943","Beyond the trees: Exploring the determinants of intercrop management intensity in smallholder immature rubber systems in Thailand。Agricultural Systems",null,"Agricultural Systems","2026-08-29T00:00:00Z","论文",10,false,0,{"impact":14,"substance":14,"depth":14,"authority":14,"freshness":14,"relevant":14,"comment":16},"该论文研究泰国橡胶农林复合系统，与国内三农及农业信息化主题无关，不予精选。",[18],{"name":9,"url":6},[20],"智慧农业",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[],{"status":29,"locked":13,"version":30,"method":31,"evidence":32},"classified","2026-10-22.2","rules",{"candidates":33,"agricultural_evidence":36},[34,41],{"code":22,"score":35,"supported":36,"title":37,"abstract":39,"tags":40},11,true,[38],"smallholder",[38],[],{"code":42,"score":43,"supported":13,"title":44,"abstract":45,"tags":46},"I1",1,[],[],[20],[],"Beyondthetrees:Exploringthedeterminantso-1215","10.1016\u002Fj.agsy.2026.104943",{"doi":49,"openalex_id":51,"authors":52,"venue":9,"cited_by_count":14,"oa_url":8,"card":8,"direction":8,"ingested_from":68},"W7204646048",[53,55,58,61,63,65],{"name":54,"orcid":8},"Charlotte Simon",{"name":56,"orcid":57},"Alexis Thoumazeau","https:\u002F\u002Forcid.org\u002F0000-0003-0758-139X",{"name":59,"orcid":60},"Aurélie Metay","https:\u002F\u002Forcid.org\u002F0000-0002-8588-0785",{"name":62,"orcid":8},"Patjima Kongplub",{"name":64,"orcid":8},"Kannika Sajjaphan",{"name":66,"orcid":67},"Bénédicte Chambon","https:\u002F\u002Forcid.org\u002F0000-0002-2436-4058","openalex","2026-09-01T04:03:05.889902Z",{"total":71,"page":43,"page_size":71,"items":72},6,[73,140,194,254,309,370],{"id":74,"title":75,"url":76,"summary":77,"summary_zh":78,"content":8,"source_name":79,"source_url":76,"published_at":80,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":81,"score_detail":82,"sources":88,"tags":90,"primary_topic":95,"secondary_topics":96,"classification":103,"search_phrases":119,"slug":122,"view_count":14,"doi":123,"paper":124,"created_at":139},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":83,"substance":84,"depth":85,"authority":86,"freshness":12,"relevant":43,"comment":87},8,21,18,12,"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。",[89],{"name":79,"url":76},[20,91,92,93,94],"农业人工智能","小农户","植物病害识别","可解释性",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[97],{"code":98,"slug":99,"name":100,"path":101,"parent_code":102},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":29,"locked":13,"version":30,"method":31,"evidence":104},{"candidates":105,"agricultural_evidence":36},[106,110,115],{"code":22,"score":86,"supported":36,"title":107,"abstract":108,"tags":109},[38],[38],[92],{"code":98,"score":12,"supported":36,"title":111,"abstract":113,"tags":114},[112],"computer vision",[],[91,93],{"code":42,"score":43,"supported":13,"title":116,"abstract":117,"tags":118},[],[],[20],[120,121],"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":123,"openalex_id":125,"authors":126,"venue":79,"cited_by_count":14,"oa_url":76,"card":133,"direction":137,"ingested_from":68},"W7223137323",[127,129,131],{"name":128,"orcid":8},"Akshay Ramgoolam",{"name":130,"orcid":8},"Priya Bundhoo Appadoo",{"name":132,"orcid":8},"Jean-Noël LEspérance",{"tldr":134,"method":135,"finding":136,"direction":137,"opportunity":138},"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。","农业人工智能与决策模型","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":141,"title":142,"url":143,"summary":144,"summary_zh":145,"content":8,"source_name":79,"source_url":143,"published_at":80,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":146,"score_detail":147,"sources":150,"tags":152,"primary_topic":155,"secondary_topics":156,"classification":158,"search_phrases":174,"slug":177,"view_count":14,"doi":178,"paper":179,"created_at":193},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":83,"substance":148,"depth":85,"authority":86,"freshness":12,"relevant":43,"comment":149},22,"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。",[151],{"name":79,"url":143},[20,91,92,153,154],"作物病害识别","模型审计",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[157],{"code":98,"slug":99,"name":100,"path":101,"parent_code":102},{"status":29,"locked":13,"version":30,"method":31,"evidence":159},{"candidates":160,"agricultural_evidence":36},[161,166,170],{"code":22,"score":162,"supported":36,"title":163,"abstract":164,"tags":165},15,[38],[92,38],[92],{"code":98,"score":12,"supported":36,"title":167,"abstract":168,"tags":169},[112],[],[153,91],{"code":42,"score":43,"supported":13,"title":171,"abstract":172,"tags":173},[],[],[20],[175,176],"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":178,"openalex_id":180,"authors":181,"venue":79,"cited_by_count":14,"oa_url":143,"card":188,"direction":137,"ingested_from":68},"W7223088030",[182,184,186],{"name":183,"orcid":8},"Abdi-Basid Idriss Farah",{"name":185,"orcid":8},"Amina Abdillahi Guedi",{"name":187,"orcid":8},"Moussa Omar Youssouf",{"tldr":189,"method":190,"finding":191,"direction":137,"opportunity":192},"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",{"id":195,"title":196,"url":197,"summary":198,"summary_zh":199,"content":8,"source_name":200,"source_url":197,"published_at":201,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":202,"score_detail":203,"sources":209,"tags":211,"primary_topic":216,"secondary_topics":217,"classification":218,"search_phrases":231,"slug":234,"view_count":14,"doi":235,"paper":236,"created_at":253},4815,"Sustainability of smallholder farming in large-scale mining enclaves in Ghana: the case of Asutifi North District in the Ahafo region, Ghana","https:\u002F\u002Fdoi.org\u002F10.1080\u002F19376812.2026.2692026","This paper argues that Ghana’s land and mineral extraction laws favor large-scale mining against agricultural livelihoods. As a result, the paper examined how large-scale land acquisition affects agrarian land availability, productivity, and sustainability of smallholder farming. Using a case study design, the study employed multiple qualitative methods including focus group discussions, document review, and interviews of officials of relevant institutions and project-affected persons (PAPs). PAPs, key informants and institutions were purposively sampled for interviews. Results show that current land regulations only provide one-time compensation for displaced farmers. This approach fails to consider the long-term needs of affected farming households. The findings further indicate that PAPs often share their compensation with extended family members as part of a cultural obligation. While this practice demonstrates community support, it leaves displaced households with little to nothing left for their own basic needs and long-term sustenance. The paper proposed modern smart agriculture that thrives on smaller lands and the development of a sustainable compensation framework that considers the long-term impacts of land acquisition will help manage land management conflicts and the sustainability of agriculture in mining communities.","本文认为，加纳的土地与矿产开采法律偏向大规模采矿，不利于农业生计。因此，本文考察了大规模土地征用如何影响农户的土地可获得性、生产力及小农农业的可持续性。研究采用案例研究设计，运用多种定性方法，包括焦点小组讨论、文献查阅以及对相关机构官员和受项目影响者（PAPs）的访谈。受项目影响者、关键信息提供者和相关机构均通过目的性抽样选取进行访谈。结果表明，现行土地法规仅对被征地农民提供一次性补偿。这种做法未能考虑受影响农户的长期需求。研究结果进一步显示，受项目影响者往往将补偿金与大家庭成员分享，这被视为一种文化义务。尽管这种做法体现了社区互助，却使被征地农户几乎无余力满足自身基本需求和长期生计。本文提出，发展依托较小土地的现代智慧农业，并建立考虑土地征用长期影响的可持续补偿框架，将有助于管理土地管理冲突以及矿区农业的可持续性。","African Geographical Review","2026-10-11T00:00:00Z",67,{"impact":83,"substance":204,"depth":205,"authority":206,"freshness":207,"relevant":43,"comment":208},20,17,13,9,"加纳采矿飞地小农可持续性案例研究，揭示一次性补偿缺陷并提出智慧农业与长效补偿框架，对矿区农业治理有参考价值。",[210],{"name":200,"url":197},[20,212,213,214,215],"小农生计","土地征收","采矿冲突","补偿机制",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[],{"status":29,"locked":13,"version":30,"method":31,"evidence":219},{"candidates":220,"agricultural_evidence":36},[221,225],{"code":22,"score":35,"supported":36,"title":222,"abstract":223,"tags":224},[38],[38],[],{"code":42,"score":226,"supported":36,"title":227,"abstract":228,"tags":230},7,[],[20,229],"smart agriculture",[20],[232,233],"加纳 Asutifi North 小农","大型采矿 土地征收 补偿","加纳AsutifiNorth小农-4815","10.1080\u002F19376812.2026.2692026",{"doi":235,"openalex_id":237,"authors":238,"venue":200,"cited_by_count":14,"oa_url":8,"card":246,"direction":252,"ingested_from":68},"W7221569207",[239,241,244],{"name":240,"orcid":8},"Natalia Poku-Boansi",{"name":242,"orcid":243},"Clifford Amoako","https:\u002F\u002Forcid.org\u002F0000-0001-9751-3037",{"name":245,"orcid":8},"John Tiah Bugri",{"tldr":247,"method":248,"finding":249,"direction":250,"opportunity":251},"研究加纳大型采矿征地对小农农业可持续性的影响，并提出智慧农业与补偿框架建议。","案例研究，采用焦点小组、文献审查和访谈等定性方法。","一次性补偿忽视长期需求，且补偿被分享后农户难以维持生计。","数字乡村与农业信息化","可探索在采矿影响区推广小地块智慧农业技术，并设计长期补偿与生计恢复机制。","智慧农业 \u002F 农业物联网","2026-10-13T23:30:12.118168Z",{"id":255,"title":256,"url":257,"summary":258,"summary_zh":8,"content":8,"source_name":259,"source_url":8,"published_at":260,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":261,"score_detail":262,"sources":265,"tags":267,"primary_topic":272,"secondary_topics":273,"classification":274,"search_phrases":296,"slug":299,"view_count":14,"doi":8,"paper":300,"created_at":308},4733,"基于多模态叶片感知的群体协作多机器人田间早期胁迫检测","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.08603","提出低成本地面多机器人系统,主从机器人通过颜色与环境数据逐行连续监测作物健康,经空间映射形成实时网页仪表盘。63次观测整体识别准确率84.12%,无线通信成功率100%,验证了面向中小农户的早期胁迫低成本方案。未实地验证未经同行评议","arXiv 2026-10-06 [预印本]","2026-10-06T00:00:00Z",60,{"impact":86,"substance":85,"depth":263,"authority":71,"freshness":83,"relevant":43,"comment":264},16,"低成本多机器人田间早期胁迫检测方案有数据支撑，但属未经同行评议的预印本且未实地验证，可作为技术动态参考。",[266],{"name":259,"url":257},[20,268,269,270,271],"农业机器人","多模态感知","作物胁迫","精准农业",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[],{"status":29,"locked":13,"version":30,"method":31,"evidence":275},{"candidates":276,"agricultural_evidence":36},[277,282,287,292],{"code":22,"score":278,"supported":36,"title":279,"abstract":280,"tags":281},3,[],[92],[],{"code":42,"score":283,"supported":13,"title":284,"abstract":285,"tags":286},2,[],[],[20,271],{"code":288,"score":43,"supported":13,"title":289,"abstract":290,"tags":291},"F6",[],[],[268],{"code":98,"score":43,"supported":13,"title":293,"abstract":294,"tags":295},[],[],[269],[297,298],"多机器人 田间 胁迫检测","叶片感知 作物健康 监测","多机器人田间胁迫检测-4733",{"doi":8,"openalex_id":8,"authors":301,"venue":8,"cited_by_count":14,"oa_url":8,"card":302,"direction":252,"ingested_from":307},[],{"tldr":303,"method":304,"finding":305,"direction":252,"opportunity":306},"提出低成本主从多机器人系统，通过多模态叶片感知实现田间作物早期胁迫检测。","多机器人颜色与环境数据逐行监测，空间映射生成实时网页仪表盘。","63次观测识别准确率84.12%，无线通信成功率100%，验证低成本方案可行。","可探索多模态融合算法优化与多地块实地验证，提升复杂田间环境下的泛化能力。","agent","2026-10-12T00:11:14.852590Z",{"id":310,"title":311,"url":312,"summary":313,"summary_zh":314,"content":8,"source_name":315,"source_url":312,"published_at":316,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":317,"score_detail":318,"sources":320,"tags":322,"primary_topic":326,"secondary_topics":327,"classification":328,"search_phrases":353,"slug":356,"view_count":14,"doi":357,"paper":358,"created_at":369},4601,"Digital Agriculture and Sector Transformation in South Africa","https:\u002F\u002Fdoi.org\u002F10.36096\u002Fijbes.v8i4.1274","Digitalisation is increasingly promoted as a catalyst for agricultural productivity, climate resilience, and market integration. However, there is limited systematic analysis of how digital agricultural transformation unfolds within South Africa’s institutional and socio-economic context. This study examines the trajectory, drivers, and governance implications of digitalisation in South African agriculture. Anchored in an integrated Socio-Technical Systems and Digital Agriculture Ecosystem framework, the study applies a structured qualitative document analysis of 82 academic and policy documents published between 2013 and 2025. The findings reveal highly uneven digital adoption patterns that reflect a structural dualism between capital-intensive commercial agriculture and resource-constrained smallholder systems. While South Africa has developed a relatively advanced digital policy architecture, implementation fragmentation, infrastructure constraints, and limited capacity for extension impede inclusive digital outcomes. The study contributes by integrating socio-technical and ecosystem perspectives to analyse digital transitions in emerging economies and by providing a transparent analytical protocol for document-based research. Policy implications highlight the need for coordinated governance, investment in rural connectivity, and targeted support mechanisms to ensure equitable digital transformation.","数字化日益被视为提升农业生产力、增强气候韧性和促进市场整合的催化剂。然而，对于数字农业转型如何在南非的制度与社会经济语境中展开，尚缺乏系统性分析。本研究考察南非农业数字化的演进轨迹、驱动因素及治理意涵。研究以社会技术系统与数字农业生态系统的整合框架为依托，对2013年至2025年间发表的82份学术与政策文件进行了结构化定性文献分析。研究发现，数字技术采纳模式高度不均衡，反映出资本密集型商业农业与资源受限的小农体系之间的结构性二元分化。尽管南非已建立起相对先进的数字政策架构，但实施碎片化、基础设施制约以及推广能力有限等因素阻碍了包容性数字成果的实现。本研究的贡献在于整合社会技术与生态系统视角以分析新兴经济体的数字转型，并为基于文献的研究提供了透明的分析方案。政策启示强调，需通过协调治理、农村互联互通投资以及有针对性的支持机制，确保公平的数字转型。","International Journal of Business Ecosystem and Strategy (2687-2293)","2026-10-09T00:00:00Z",80,{"impact":85,"substance":148,"depth":85,"authority":206,"freshness":207,"relevant":43,"comment":319},"基于82份文献的系统性分析，揭示南非数字农业的结构性二元分化与治理碎片化，对新兴经济体数字乡村研究有参考价值。",[321],{"name":315,"url":312},[323,20,92,324,325],"数字农业","南非农业","农村数字治理",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[],{"status":29,"locked":13,"version":30,"method":31,"evidence":329},{"candidates":330,"agricultural_evidence":36},[331,336,341,347],{"code":42,"score":263,"supported":36,"title":332,"abstract":334,"tags":335},[333],"digital agriculture",[323,333],[323,20],{"code":22,"score":337,"supported":36,"title":338,"abstract":339,"tags":340},4,[],[38],[92],{"code":342,"score":278,"supported":36,"title":343,"abstract":344,"tags":346},"H6",[],[345],"农业生态",[],{"code":348,"score":278,"supported":36,"title":349,"abstract":350,"tags":352},"H7",[],[351],"climate resilience",[],[354,355],"南非 数字农业 转型","南非 小农户 数字鸿沟","南非数字农业转型-4601","10.36096\u002Fijbes.v8i4.1274",{"doi":357,"openalex_id":359,"authors":360,"venue":315,"cited_by_count":14,"oa_url":312,"card":364,"direction":250,"ingested_from":68},"W7221113328",[361],{"name":362,"orcid":363},"Mokgadi Julia Ngoepe-Ntsoane","https:\u002F\u002Forcid.org\u002F0000-0001-7995-4824",{"tldr":365,"method":366,"finding":367,"direction":250,"opportunity":368},"系统分析南非农业数字化轨迹、驱动因素与治理影响，揭示数字鸿沟与政策碎片化。","社会技术系统与数字农业生态框架，对82份2013-2025年文献政策进行结构化质","数字采用高度不均，商业农业与小农二元分化；政策先进但实施碎片化、基建与推广能力不足阻碍包容性转型。","可延伸至新兴经济体小农数字包容性治理机制与农村连接性投资评估的实证研究。","2026-10-10T23:30:34.991942Z",{"id":371,"title":372,"url":373,"summary":374,"summary_zh":375,"content":8,"source_name":376,"source_url":373,"published_at":377,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":378,"score_detail":379,"sources":381,"tags":383,"primary_topic":386,"secondary_topics":387,"classification":393,"search_phrases":420,"slug":423,"view_count":424,"doi":425,"paper":426,"created_at":445},3829,"Towards accessible smallholder crop classification in the groundnut basin of Senegal","https:\u002F\u002Fdoi.org\u002F10.1088\u002F2976-601x\u002Faea0b8","Abstract Crop type mapping is a critical lever for decision making in smallholder food systems, yet high cost and expertise requirements of developing remote sensing-driven maps as well as need for recurrent data are persistent barriers to incorporating geospatial tools into decision making. To address this gap, we establish a three-part framework to evaluate crop type mapping: (1) performance, (2) temporal transferability, and (3) accessibility. We evaluate geospatial foundation model embeddings (TESSERA and AlphaEarth) against traditional baselines in Senegal’s groundnut basin. We find that the embedding-based approaches, in particular TESSERA, best fulfill these criteria. The TESSERA-based method shows a 78% reduction in both compute compared to a timeseries approach, a reduction in need for custom feature generation, and 28% higher relative accuracy (an absolute improvement of approximately 0.10 weighted F 1) in one crop type classification temporal transfer test. By reducing the reliance on training data, computational resource use, and expertise for data processing, this approach shows potential to contribute to improved smallholder crop type classification.","摘要 作物类型制图是小农粮食系统决策的关键手段，但开发遥感驱动地图的高成本与专业知识要求，以及 recurring 数据的需求，仍是将地理空间工具纳入决策的持续障碍。为弥补这一差距，我们建立了一个三部分框架来评估作物类型制图：（1）性能，（2）时间可迁移性，（3）可及性。我们在塞内加尔花生盆地评估了地理空间基础模型嵌入（TESSERA 和 AlphaEarth）与传统基线方法。我们发现，基于嵌入的方法，尤其是 TESSERA，最能满足这些标准。基于 TESSERA 的方法显示，与时间序列方法相比，计算量减少 78%，对自定义特征生成的需求降低，并且在一项作物类型分类时间迁移测试中相对精度提高 28%（加权 F1 绝对提升约 0.10）。通过减少对训练数据、计算资源使用和数据处理专业知识的依赖，该方法显示出改善小农作物类型分类的潜力。","Environmental Research Food Systems","2026-09-28T00:00:00Z",79,{"impact":85,"substance":148,"depth":85,"authority":206,"freshness":83,"relevant":43,"comment":380},"该研究提出兼顾性能、时序迁移性与可及性的作物分类评估框架，用地理空间基础模型显著降低算力与训练数据依赖，对小农户农业遥感应用具有实质参考价值。",[382],{"name":376,"url":373},[20,91,384,92,385],"农业遥感","作物分类",{"code":22,"slug":23,"name":24,"path":25,"parent_code":26},[388],{"code":389,"slug":390,"name":391,"path":392,"parent_code":102},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":29,"locked":13,"version":30,"method":31,"evidence":394},{"candidates":395,"agricultural_evidence":36},[396,400,406,412,416],{"code":22,"score":86,"supported":36,"title":397,"abstract":398,"tags":399},[38],[38],[92],{"code":389,"score":83,"supported":36,"title":401,"abstract":402,"tags":405},[],[403,404],"遥感","remote sensing",[385,384],{"code":407,"score":278,"supported":36,"title":408,"abstract":409,"tags":411},"A4",[],[410],"花生",[],{"code":42,"score":43,"supported":13,"title":413,"abstract":414,"tags":415},[],[],[20],{"code":98,"score":43,"supported":13,"title":417,"abstract":418,"tags":419},[],[],[91],[421,422],"塞内加尔 花生盆地 作物分类","TESSERA 遥感 作物制图","塞内加尔花生盆地作物分类-3829",5,"10.1088\u002F2976-601x\u002Faea0b8",{"doi":425,"openalex_id":427,"authors":428,"venue":376,"cited_by_count":14,"oa_url":438,"card":439,"direction":252,"ingested_from":68},"W7214087594",[429,431,433,435],{"name":430,"orcid":8},"Madeline Lisaius",{"name":432,"orcid":8},"Srinivasan Keshav",{"name":434,"orcid":8},"Andrew Blake",{"name":436,"orcid":437},"Clement Atzberger","https:\u002F\u002Forcid.org\u002F0000-0003-2169-8009","https:\u002F\u002Fiopscience.iop.org\u002Farticle\u002F10.1088\u002F2976-601X\u002Faea0b8\u002Fpdf",{"tldr":440,"method":441,"finding":442,"direction":443,"opportunity":444},"评估地理空间基础模型嵌入在塞内加尔花生盆地小农作物分类中的性能、时序迁移性和可及性。","对比TESSERA和AlphaEarth嵌入与传统基线，用加权F1和计算量评估。","TESSERA嵌入精度相对提高28%，计算量减少78%，且无需自定义特征生成。","农业遥感与作物表型","可探索基础模型嵌入在更多小农区域和作物类型上的泛化能力及低成本部署方案。","2026-09-30T23:30:11.490990Z"]