[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4178":3,"related-4178":140},{"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":108,"slug":111,"view_count":21,"doi":112,"paper":113,"created_at":139},4178,"From agronomic practices to carbon credits: A systematic review of agricultural carbon markets in India","https:\u002F\u002Fdoi.org\u002F10.14719\u002Fpst.16451","Carbon markets are becoming an important tool for reducing greenhouse gas (GHG) emissions from agriculture and they are particularly relevant for India, which is both the world’s third-largest GHG emitter and a major agricultural economy. This systematic review synthesises current evidence on the development, mechanisms and emerging trends of carbon markets in Indian agriculture, situating them within the wider global context. Following a Preferred reporting items for systematic reviews and meta-analyses (PRISMA)-guided search of five databases (247 records identified, 62 studies retained), the review examines five closely connected areas: global and India-specific carbon market mechanisms; agronomic practices that enable market participation; major agricultural GHG sources and mitigation opportunities; soil health and carbon sequestration; and methodological, policy and inclusion gaps. The synthesis demonstrates that sustainable practices such as conservation agriculture, alternate wetting and drying (AWD) in rice systems, biochar application, precision nutrient management and agroforestry can reduce agricultural emissions while also improving soil fertility and carbon storage. Furthermore, emerging tools, including blockchain-based transparency systems and AI-enabled precision agriculture, can strengthen market credibility and make participation more accessible for smallholder farmers. However, agricultural carbon markets in India remain at an early stage and their growth is constrained by weak measurement, reporting and verification (MRV) systems, inadequate smallholder inclusion, concerns around additionality and the lack of a comprehensive domestic regulatory framework. Uncertainties around carbon permanence, leakage, transaction costs and market volatility further temper these prospects and warrant cautious interpretation of reported gains. This review identifies four priority areas for future work: standardising robust MRV systems, developing integrated impact models, designing inclusive market mechanisms and aligning carbon market policies with India’s broader agricultural, climate and livelihood commitments. Addressing these gaps will be essential for realising agriculture’s mitigation potential and supporting a low-carbon, climate-resilient agricultural future in India.","碳市场正成为减少农业温室气体（GHG）排放的重要工具，对印度而言尤其具有现实意义，因为印度既是全球第三大温室气体排放国，也是重要的农业经济体。本系统综述综合了当前关于印度农业碳市场发展、机制及新兴趋势的证据，并将其置于更广泛的全球背景中加以审视。遵循系统综述和荟萃分析优先报告条目（PRISMA）指南，对五个数据库进行检索（识别出247条记录，保留62项研究）后，本综述考察了五个密切关联的领域：全球及印度特有的碳市场机制；能够实现市场参与的农艺实践；主要农业温室气体来源与减排机会；土壤健康与碳固存；以及方法学、政策和包容性方面的差距。综合结果表明，保护性农业、水稻系统中的干湿交替灌溉（AWD）、生物炭施用、精准养分管理和农林业等可持续实践，能够在减少农业排放的同时改善土壤肥力和碳储存。此外，包括基于区块链的透明系统和人工智能驱动的精准农业在内的新兴工具，可以增强市场可信度，并使小农户更容易参与。然而，印度的农业碳市场仍处于早期阶段，其增长受到测量、报告与核查（MRV）体系薄弱、小农户包容性不足、额外性方面的担忧以及缺乏全面的国内监管框架等因素的制约。碳永久性、泄漏、交易成本和市场波动等方面的不确定性进一步削弱了这些前景，因此需要对所报告的收益持谨慎解读。本综述确定了未来工作的四个优先领域：标准化稳健的MRV体系、开发综合影响模型、设计包容性市场机制，以及使碳市场政策与印度更广泛的农业、气候和生计承诺相协调。解决这些差距对于实现农业的减排潜力、支持印度低碳且气候适应型的农业未来至关重要。",null,"Plant Science Today","2026-10-03T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,9,1,"系统综述印度农业碳市场机制、减排实践与MRV短板，对国内农业碳汇与数字监测议题有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","小农户","碳汇","农业碳市场","MRV",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":41,"reason":107},[38,46,53,60,68,75,82,89,95,101],{"code":39,"score":40,"supported":41,"title":42,"abstract":43,"tags":45},"G2",7,true,[],[27,44],"smallholder",[27],{"code":47,"score":40,"supported":41,"title":48,"abstract":49,"tags":52},"H4",[],[50,51],"农业碳","carbon sequestration",[28],{"code":54,"score":40,"supported":41,"title":55,"abstract":56,"tags":59},"I1",[],[57,58],"精准农业","precision agriculture",[26],{"code":61,"score":62,"supported":41,"title":63,"abstract":64,"tags":67},"A1",6,[],[65,66],"水稻","rice",[],{"code":69,"score":62,"supported":41,"title":70,"abstract":71,"tags":74},"B7",[],[72,73],"温室","greenhouse",[],{"code":76,"score":62,"supported":41,"title":77,"abstract":78,"tags":81},"H2",[],[79,80],"土壤","soil",[],{"code":83,"score":84,"supported":41,"title":85,"abstract":86,"tags":88},"F3",3,[],[87],"养分管理",[],{"code":90,"score":84,"supported":41,"title":91,"abstract":92,"tags":94},"H3",[],[93],"灌溉",[],{"code":96,"score":84,"supported":41,"title":97,"abstract":98,"tags":100},"H7",[],[99],"气候适应",[],{"code":102,"score":84,"supported":41,"title":103,"abstract":104,"tags":106},"H8",[],[105],"conservation agriculture",[],"多个产业证据相当，需要确认主归属",[109,110],"印度 农业碳市场","农业碳信用 MRV","印度农业碳市场-4178","10.14719\u002Fpst.16451",{"doi":112,"openalex_id":114,"authors":115,"venue":10,"cited_by_count":131,"oa_url":6,"card":132,"direction":136,"ingested_from":138},"W7219112839",[116,119,122,125,128],{"name":117,"orcid":118},"R Sneha","https:\u002F\u002Forcid.org\u002F0009-0007-7779-2885",{"name":120,"orcid":121},"N. Kiruthika","https:\u002F\u002Forcid.org\u002F0000-0002-9332-5220",{"name":123,"orcid":124},"S P Sethuraman","https:\u002F\u002Forcid.org\u002F0000-0003-3283-1629",{"name":126,"orcid":127},"Kandaswamy Mahendran","https:\u002F\u002Forcid.org\u002F0000-0001-5146-6052",{"name":129,"orcid":130},"Samiappan Senthilnathan","https:\u002F\u002Forcid.org\u002F0000-0003-2924-3690",0,{"tldr":133,"method":134,"finding":135,"direction":136,"opportunity":137},"系统综述印度农业碳市场机制、减排实践与挑战，提出四大优先研究方向。","PRISMA系统综述，检索5个数据库，纳入62项研究。","印度农业碳市场尚处早期，受MRV薄弱、小农参与不足和监管缺失制约。","农业绿色发展与碳","可探索区块链与AI赋能MRV、降低小农交易成本及设计包容性碳市场机制。","openalex","2026-10-04T23:30:54.952066Z",{"total":62,"page":21,"page_size":62,"items":141},[142,212,265,337,391,449],{"id":143,"title":144,"url":145,"summary":146,"summary_zh":147,"content":9,"source_name":148,"source_url":145,"published_at":149,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":150,"score_detail":151,"sources":156,"tags":158,"primary_topic":162,"secondary_topics":167,"classification":174,"search_phrases":191,"slug":194,"view_count":131,"doi":195,"paper":196,"created_at":211},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":152,"substance":153,"depth":17,"authority":154,"freshness":13,"relevant":21,"comment":155},8,21,12,"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。",[157],{"name":148,"url":145},[26,159,27,160,161],"农业人工智能","植物病害识别","可解释性",{"code":39,"slug":163,"name":164,"path":165,"parent_code":166},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[168],{"code":169,"slug":170,"name":171,"path":172,"parent_code":173},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":175,"locked":14,"version":34,"method":35,"evidence":176},"classified",{"candidates":177,"agricultural_evidence":41},[178,182,187],{"code":39,"score":154,"supported":41,"title":179,"abstract":180,"tags":181},[44],[44],[27],{"code":169,"score":13,"supported":41,"title":183,"abstract":185,"tags":186},[184],"computer vision",[],[159,160],{"code":54,"score":21,"supported":14,"title":188,"abstract":189,"tags":190},[],[],[26],[192,193],"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":195,"openalex_id":197,"authors":198,"venue":148,"cited_by_count":131,"oa_url":145,"card":205,"direction":209,"ingested_from":138},"W7223137323",[199,201,203],{"name":200,"orcid":9},"Akshay Ramgoolam",{"name":202,"orcid":9},"Priya Bundhoo Appadoo",{"name":204,"orcid":9},"Jean-Noël LEspérance",{"tldr":206,"method":207,"finding":208,"direction":209,"opportunity":210},"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":213,"title":214,"url":215,"summary":216,"summary_zh":217,"content":9,"source_name":148,"source_url":215,"published_at":149,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":218,"score_detail":219,"sources":221,"tags":223,"primary_topic":226,"secondary_topics":227,"classification":229,"search_phrases":245,"slug":248,"view_count":131,"doi":249,"paper":250,"created_at":264},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":152,"substance":18,"depth":17,"authority":154,"freshness":13,"relevant":21,"comment":220},"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。",[222],{"name":148,"url":215},[26,159,27,224,225],"作物病害识别","模型审计",{"code":39,"slug":163,"name":164,"path":165,"parent_code":166},[228],{"code":169,"slug":170,"name":171,"path":172,"parent_code":173},{"status":175,"locked":14,"version":34,"method":35,"evidence":230},{"candidates":231,"agricultural_evidence":41},[232,237,241],{"code":39,"score":233,"supported":41,"title":234,"abstract":235,"tags":236},15,[44],[27,44],[27],{"code":169,"score":13,"supported":41,"title":238,"abstract":239,"tags":240},[184],[],[224,159],{"code":54,"score":21,"supported":14,"title":242,"abstract":243,"tags":244},[],[],[26],[246,247],"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":249,"openalex_id":251,"authors":252,"venue":148,"cited_by_count":131,"oa_url":215,"card":259,"direction":209,"ingested_from":138},"W7223088030",[253,255,257],{"name":254,"orcid":9},"Abdi-Basid Idriss Farah",{"name":256,"orcid":9},"Amina Abdillahi Guedi",{"name":258,"orcid":9},"Moussa Omar Youssouf",{"tldr":260,"method":261,"finding":262,"direction":209,"opportunity":263},"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":266,"title":267,"url":268,"summary":269,"summary_zh":9,"content":9,"source_name":270,"source_url":9,"published_at":271,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":272,"score_detail":273,"sources":278,"tags":280,"primary_topic":9,"secondary_topics":282,"classification":283,"search_phrases":323,"slug":326,"view_count":131,"doi":9,"paper":327,"created_at":336},4784,"Smart Farming and Modern Agricultural Technologies","https:\u002F\u002Fscientiafoundation.in\u002Fpopular-science--article\u002Fsmart-farming-and-modern-agricultural","Reddy等学者在Scientia Review 2026年第2卷第10期发表综述,系统梳理智慧农业从传统实践到数字农业的演进路径。文章解析精准农业、物联网、遥感与无人机、人工智能、机器人、智能灌溉、保护地栽培、畜牧监测、数字市场与溯源等关键技术的工作原理与效益,讨论成本、数字素养、融资、培训等阻碍因素,特别关注小农户和边缘农户的采纳瓶颈。","Scientia Review 2026-10-07","2026-10-07T00:00:00Z",73,{"impact":17,"substance":274,"depth":275,"authority":19,"freshness":276,"relevant":21,"comment":277},20,17,5,"系统梳理智慧农业关键技术与小农户采纳瓶颈的综述，信息增量足但属学术综述、时效一般，可作主题聚合素材。",[279],{"name":270,"url":268},[26,159,281,57,27],"农业物联网",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":284},{"candidates":285,"agricultural_evidence":41,"reason":107},[286,292,297,303,309,313,319],{"code":54,"score":287,"supported":41,"title":288,"abstract":289,"tags":291},11,[],[26,57,290],"数字农业",[26,57],{"code":39,"score":293,"supported":41,"title":294,"abstract":295,"tags":296},4,[],[27],[27],{"code":298,"score":293,"supported":41,"title":299,"abstract":300,"tags":302},"I5",[],[301],"物联网",[281],{"code":304,"score":84,"supported":41,"title":305,"abstract":306,"tags":308},"C",[],[307],"畜牧",[],{"code":90,"score":84,"supported":41,"title":310,"abstract":311,"tags":312},[],[93],[],{"code":314,"score":84,"supported":41,"title":315,"abstract":316,"tags":318},"I3",[],[317],"遥感",[],{"code":169,"score":21,"supported":14,"title":320,"abstract":321,"tags":322},[],[],[159],[324,325],"Scientia Review 智慧农业","Reddy 智慧农业 数字农业","ScientiaReview智慧农业-4784",{"doi":9,"openalex_id":9,"authors":328,"venue":9,"cited_by_count":131,"oa_url":9,"card":329,"direction":333,"ingested_from":335},[],{"tldr":330,"method":331,"finding":332,"direction":333,"opportunity":334},"综述智慧农业从传统到数字化的演进，梳理关键技术、效益与采纳障碍。","文献综述，覆盖精准农业、物联网、遥感、AI、机器人等关键技术。","技术效益显著，但成本、数字素养与融资障碍制约小农户采纳。","数字乡村与农业信息化","可针对小农户低成本、低门槛的智慧农业适配方案与采纳机制开展实证研究。","agent","2026-10-13T00:08:38.433355Z",{"id":338,"title":339,"url":340,"summary":341,"summary_zh":9,"content":9,"source_name":342,"source_url":340,"published_at":343,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":344,"score_detail":345,"sources":348,"tags":350,"primary_topic":9,"secondary_topics":353,"classification":354,"search_phrases":372,"slug":375,"view_count":21,"doi":376,"paper":377,"created_at":390},4651,"A systems-oriented framework for wise, equitable, and sustainable digital agricultural transformation in sub-Saharan Africa: A critical review","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.105004","A systems-oriented framework for wise, equitable, and sustainable digital agricultural transformation in sub-Saharan Africa: A critical review。Agricultural Systems","Agricultural Systems","2026-10-10T00:00:00Z",79,{"impact":17,"substance":274,"depth":17,"authority":346,"freshness":20,"relevant":21,"comment":347},14,"发表于核心期刊的系统性综述，提出面向撒哈拉以南非洲的公平可持续数字农业转型框架，对数字乡村与智慧农业研究有参考价值，但属区域外学术成果，公共影响有限。",[349],{"name":342,"url":340},[290,26,351,27,352],"撒哈拉以南非洲","农业数字化转型",[],{"status":355,"locked":14,"version":34,"method":35,"evidence":356},"unclassified",{"candidates":357,"agricultural_evidence":41,"reason":371},[358,362,366],{"code":54,"score":84,"supported":14,"title":359,"abstract":360,"tags":361},[],[],[352,290,26],{"code":39,"score":21,"supported":14,"title":363,"abstract":364,"tags":365},[],[],[27],{"code":367,"score":21,"supported":14,"title":368,"abstract":369,"tags":370},"J3",[],[],[351],"缺少足够的主题证据",[373,374],"撒哈拉以南非洲 数字农业 转型","农业数字化转型 撒哈拉以南非洲 数字农业 智慧农业","撒哈拉以南非洲数字农业转型-4651","10.1016\u002Fj.agsy.2026.105004",{"doi":376,"openalex_id":378,"authors":379,"venue":342,"cited_by_count":131,"oa_url":340,"card":9,"direction":389,"ingested_from":138},"W7221333092",[380,383,386],{"name":381,"orcid":382},"Kibrom T. Sibhatu","https:\u002F\u002Forcid.org\u002F0000-0002-3063-8369",{"name":384,"orcid":385},"Maurice Tschopp","https:\u002F\u002Forcid.org\u002F0000-0001-6032-8823",{"name":387,"orcid":388},"Nicole Harari","https:\u002F\u002Forcid.org\u002F0000-0002-3730-5030","智慧农业 \u002F 农业物联网","2026-10-11T23:30:03.913169Z",{"id":392,"title":393,"url":394,"summary":395,"summary_zh":396,"content":9,"source_name":397,"source_url":394,"published_at":398,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":399,"sources":401,"tags":403,"primary_topic":406,"secondary_topics":407,"classification":408,"search_phrases":432,"slug":435,"view_count":131,"doi":436,"paper":437,"created_at":448},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",{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":400},"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。",[402],{"name":397,"url":394},[290,26,27,404,405],"南非农业","农村数字治理",{"code":39,"slug":163,"name":164,"path":165,"parent_code":166},[],{"status":175,"locked":14,"version":34,"method":35,"evidence":409},{"candidates":410,"agricultural_evidence":41},[411,417,421,427],{"code":54,"score":412,"supported":41,"title":413,"abstract":415,"tags":416},16,[414],"digital agriculture",[290,414],[290,26],{"code":39,"score":293,"supported":41,"title":418,"abstract":419,"tags":420},[],[44],[27],{"code":422,"score":84,"supported":41,"title":423,"abstract":424,"tags":426},"H6",[],[425],"农业生态",[],{"code":96,"score":84,"supported":41,"title":428,"abstract":429,"tags":431},[],[430],"climate resilience",[],[433,434],"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":436,"openalex_id":438,"authors":439,"venue":397,"cited_by_count":131,"oa_url":394,"card":443,"direction":333,"ingested_from":138},"W7221113328",[440],{"name":441,"orcid":442},"Mokgadi Julia Ngoepe-Ntsoane","https:\u002F\u002Forcid.org\u002F0000-0001-7995-4824",{"tldr":444,"method":445,"finding":446,"direction":333,"opportunity":447},"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":450,"title":451,"url":452,"summary":453,"summary_zh":454,"content":9,"source_name":455,"source_url":452,"published_at":456,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":457,"score_detail":458,"sources":460,"tags":462,"primary_topic":9,"secondary_topics":466,"classification":467,"search_phrases":488,"slug":491,"view_count":492,"doi":9,"paper":493,"created_at":507},4369,"Adopsi Mobile Farming dan DSS dalam Pengambilan Keputusan Usaha Tani Sugihwaras","https:\u002F\u002Fjournal.udn.ac.id\u002Findex.php\u002Feduscotech\u002Farticle\u002Fview\u002F604","Digital agriculture can reduce information asymmetry and support farm decisions, yet adoption among smallholders depends on perceived benefits, usability, and enabling conditions. This study draft examines the adoption of mobile farming applications and decision support systems (DSS) for farm decision-making in Sugihwaras Village, Maospati, Magetan. An explanatory cross-sectional design is proposed. Because primary field data were not supplied, the present results use an explicitly simulated dataset of 96 farmers for manuscript development. Descriptive analysis and multiple regression indicate a relatively high mobile farming adoption score, moderate DSS use, and high perceived decision quality. Performance expectancy, facilitating conditions, social influence, and age are associated with mobile adoption, while mobile farming and DSS use are positively associated with decision quality. The findings framework highlights the need for user-friendly applications, reliable connectivity, farmer-group-based training, and extension support. Empirical field data are required before publication.","数字农业能够减少信息不对称并支持农场决策，但小农户的采用取决于其感知收益、可用性和使能条件。本研究初稿考察了在Magetan县Maospati镇Sugihwaras村，移动农业应用程序和决策支持系统（DSS）在农场决策中的采用情况。研究拟采用解释性横断面设计。由于未提供一手实地数据，当前结果使用了一个明确标注为模拟的96户农民数据集，用于稿件开发。描述性分析和多元回归表明，移动农业采用得分相对较高，DSS使用处于中等水平，感知决策质量较高。绩效期望、便利条件、社会影响和年龄与移动农业采用相关，而移动农业和DSS使用与决策质量呈正相关。研究结果框架强调了需要用户友好的应用程序、可靠的网络连接、基于农民小组的培训以及推广支持。在发表前仍需实证实地数据。","Eduscotech","2026-10-05T00:00:00Z",32,{"impact":62,"substance":152,"depth":40,"authority":84,"freshness":152,"relevant":21,"comment":459},"印尼小农户移动农业与DSS采纳研究，但数据为模拟、尚未发表，仅具参考价值。",[461],{"name":455,"url":452},[463,26,464,27,465],"数字乡村","决策支持系统","移动农业应用",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":468},{"candidates":469,"agricultural_evidence":41,"reason":107},[470,474,478,483],{"code":54,"score":40,"supported":41,"title":471,"abstract":472,"tags":473},[],[290,414],[26],{"code":39,"score":293,"supported":41,"title":475,"abstract":476,"tags":477},[],[27],[27],{"code":169,"score":293,"supported":41,"title":479,"abstract":480,"tags":482},[],[481],"decision support",[464],{"code":484,"score":21,"supported":14,"title":485,"abstract":486,"tags":487},"I6",[],[],[463],[489,490],"Sugihwaras 移动农业 采纳","Magetan 农户 决策支持系统","Sugihwaras移动农业采纳-4369",2,{"doi":9,"openalex_id":494,"authors":495,"venue":455,"cited_by_count":131,"oa_url":452,"card":502,"direction":333,"ingested_from":138},"W7220753702",[496,498,500],{"name":497,"orcid":9},"Paramita Wisnuwardhani",{"name":499,"orcid":9},"Eko Pujianto Eko Pujianto",{"name":501,"orcid":9},"Nunik Indarwati",{"tldr":503,"method":504,"finding":505,"direction":333,"opportunity":506},"基于模拟数据研究印尼小农采用移动农业应用与决策支持系统对农场决策质量的影响。","模拟96户农民数据，描述性分析与多元回归，基于UTAUT框架。","绩效期望、便利条件、社会影响和年龄影响移动应用采用，移动应用与DSS使用正向关联决策质量。","需真实田野数据验证，可探究小农数字工具采用障碍与决策质量提升机制。","2026-10-07T23:30:38.824339Z"]