[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2516":3,"related-2516":99},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":68,"slug":71,"view_count":53,"doi":72,"paper":73,"created_at":98},2516,"Scaling climate-smart agriculture through multi-channel advisory services: economic evaluation of weather information systems in sub-Saharan Africa","https:\u002F\u002Fdoi.org\u002F10.1080\u002F14735903.2026.2731746","Smallholder agriculture in sub-Saharan Africa is 95% rain-fed and exposed to climate variability. This post-implementation evaluation applies activity-based costing to weather advisory services delivered by PlantVillage in Kenya and Burkina Faso from 2022 to 2024 across television, radio, short message service (SMS), and community-based channels. A combined investment of USD 551,966 reached 9.41 million farmers at confirmed exposure and an estimated 14.5 million under a moderate-reach scenario (USD 0.038 per farmer). Because extended reach relies on literature-derived multipliers rather than direct measurement, we report a sensitivity range of USD 0.034 to 0.058; even at the conservative end, the cost advantage over Farmer Field Schools (USD 36 to 70 per participant) remains a factor of 620 to 1,200. Mass media achieved the lowest unit cost (USD 0.027 to 0.031), with evidence limited to confirmed exposure, whereas SMS supported intensive engagement at USD 0.60. In a convenience sample of 4,272 registered iShamba users in Kenya, 83.7% (n = 3,577) reported that advisories influenced their decisions, predominantly planting timing (51%) and farm-activity planning (23%). No comparable data were collected in Burkina Faso, and channel contributions appear complementary rather than demonstrably synergistic. Yields and income were not measured; causal impact requires experimental and longitudinal designs.","撒哈拉以南非洲的小农农业95%依赖雨养，易受气候变率影响。本项实施后评估采用作业成本法，对PlantVillage于2022至2024年间在肯尼亚和布基纳法索通过电视、广播、短信服务（SMS）及社区渠道提供的天气咨询服务进行成本核算。合计投资551,966美元，在确认触达口径下覆盖941万农民，在中度触达情景下估计覆盖1,450万农民（每农民0.038美元）。由于扩展触达依赖文献推导的乘数而非直接测量，我们报告0.034至0.058美元的敏感性区间；即使在保守端，相较于农民田间学校（每位参与者36至70美元）的成本优势仍达620至1,200倍。大众媒体的单位成本最低（0.027至0.031美元），但证据仅限于确认触达；短信则以每农民0.60美元支持深度参与。在肯尼亚4,272名注册iShamba用户的便利样本中，83.7%（n = 3,577）报告咨询信息影响了其决策，主要是种植时间（51%）和农事活动规划（23%）。布基纳法索未收集可比数据，各渠道的贡献似乎互补，而非可证明的协同。产量和收入未予测量；因果影响需要实验和纵向设计。",null,"International Journal of Agricultural Sustainability","2026-09-13T00:00:00Z","论文",10,false,78,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,7,1,"基于成本核算的天气信息服务大规模评估，单位成本数据与渠道对比结论扎实，对农业气象信息化推广有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","智慧农业","撒哈拉以南非洲","小农户","农业气象服务",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"G2","farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services","G",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":47},[44,52,58,63],{"code":45,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},"I1",9,true,[49],"smart agriculture",[],[27],{"code":32,"score":53,"supported":47,"title":54,"abstract":55,"tags":57},4,[],[56],"smallholder",[29],{"code":59,"score":21,"supported":14,"title":60,"abstract":61,"tags":62},"I6",[],[],[26],{"code":64,"score":21,"supported":14,"title":65,"abstract":66,"tags":67},"J3",[],[],[28],[69,70],"撒哈拉以南非洲 农业气象服务 数字乡村 智慧农业","撒哈拉以南非洲 农业气象服务","撒哈拉以南非洲农业气象服务数字乡村智慧农业-2516","10.1080\u002F14735903.2026.2731746",{"doi":72,"openalex_id":74,"authors":75,"venue":10,"cited_by_count":88,"oa_url":89,"card":90,"direction":96,"ingested_from":97},"W7212902218",[76,79,82,84,86],{"name":77,"orcid":78},"Rimnoma S. Ouedraogo","https:\u002F\u002Forcid.org\u002F0000-0003-3339-300X",{"name":80,"orcid":81},"Bipana Paudel Timilsena","https:\u002F\u002Forcid.org\u002F0000-0003-3584-0563",{"name":83,"orcid":9},"Nebnoma R. Tiendrebeogo",{"name":85,"orcid":9},"Derek Morr",{"name":87,"orcid":9},"D M Hughes",0,"https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F14735903.2026.2731746?needAccess=true",{"tldr":91,"method":92,"finding":93,"direction":94,"opportunity":95},"评估撒哈拉以南非洲多渠天气信息服务成本与农户决策影响。","采用活动成本法，分析2022-2024年肯尼亚和布基纳法索四类渠道数据。","人均成本仅0.038美元，远低于农民田间学校，83.7%用户称信息影响决策。","数字乡村与农业信息化","需实验与纵向设计验证天气信息对产量收入的因果影响及渠道协同效应。","智慧农业 \u002F 农业物联网","openalex","2026-09-15T23:30:10.644934Z",{"total":100,"page":21,"page_size":100,"items":101},6,[102,178,235,287,329,379],{"id":103,"title":104,"url":105,"summary":106,"summary_zh":107,"content":9,"source_name":108,"source_url":105,"published_at":109,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":110,"score_detail":111,"sources":113,"tags":115,"primary_topic":118,"secondary_topics":119,"classification":126,"search_phrases":158,"slug":161,"view_count":100,"doi":162,"paper":163,"created_at":177},3512,"AI-Driven Agricultural Advisory and Diagnostic Systems for Smallholder Farming: Technical Architectures, Evidence and Deployment Priorities for North-East India","https:\u002F\u002Fdoi.org\u002F10.9734\u002Farja\u002F2026\u002Fv19i4919","Artificial intelligence (AI) is being introduced into agricultural advisory services through machine learning, computer vision, conversational large language models, retrieval-augmented generation and multimodal interfaces. For smallholder farming, the central question is not whether these technologies can produce technically plausible outputs, but whether they can provide locally correct, actionable and safe recommendations under heterogeneous agronomic, linguistic and connectivity conditions. This critical narrative review integrates evidence on digital extension, AI-enabled agricultural advice, image-based diagnosis and responsible digital agriculture, with particular reference to North-East India. Literature published from 1 January 2010 to 17 July 2026 was considered, with emphasis on peer-reviewed field evaluations, technical validation studies, reviews and regionally relevant research. Evidence from digital extension provides the strongest causal baseline: mobile and personalised advisory services frequently improve information recall, agronomic knowledge and adoption of recommended practices, yet effects on yield, profit and welfare are inconsistent. Recent generative-AI studies show that large language models can produce useful agricultural responses, but site-specific rates, timing and local practice remain recurrent failure points. Retrieval grounding and expert feedback improve local relevance, although multi-season farm-level effectiveness evidence remains scarce. Image-based plant-disease systems achieve high accuracy in curated datasets, but performance can deteriorate sharply under field domain shift, class novelty and variable image quality. North-East Indian studies of mobile advisory systems in Meghalaya, Nagaland and Tripura demonstrate a valuable institutional foundation based on interactive voice response, local expert networks and user-centred service design; they do not, however, establish the effectiveness of autonomous AI. The most defensible deployment model is therefore an offline-tolerant, multilingual, multimodal and human-supervised architecture that grounds recommendations in curated regional knowledge, represents uncertainty, preserves provenance and escalates high-risk or out-of-distribution cases. Future research should prioritise prospective district- and season-spanning evaluations that connect model quality to farmer decisions, agronomic outcomes, equity, safety and cost-effectiveness.","人工智能（AI）正通过机器学习、计算机视觉、对话式大语言模型、检索增强生成和多模态界面被引入农业咨询服务。对于小农户而言，核心问题不在于这些技术能否产生技术上看似合理的输出，而在于它们能否在异质的农艺、语言和网络连接条件下提供本地正确、可操作且安全的建议。本批判性叙事综述整合了数字推广、AI赋能的农业建议、基于图像的诊断和负责任数字农业方面的证据，并特别关注印度东北部。本文考察了2010年1月1日至2026年7月17日期间发表的文献，重点关注同行评议的田间评估、技术验证研究、综述及区域相关研究。来自数字推广的证据提供了最强的因果基线：移动化和个性化咨询服务经常改善信息记忆、农艺知识和对推荐措施的采纳，但对产量、利润和福利的影响并不一致。近期生成式AI研究表明，大语言模型能够产生有用的农业回答，但针对具体地点的用量、时机和本地实践仍是反复出现的失败点。检索 grounding 和专家反馈可提高本地相关性，但多季农场层面的有效性证据仍然稀缺。基于图像的植物病害系统在精选数据集上达到高准确率，但在田间域偏移、类别新颖性和图像质量多变的情况下，性能可能急剧下降。印度东北部在梅加拉亚邦、那加兰邦和特里普拉邦开展的移动咨询系统研究展示了基于交互式语音应答、本地专家网络和以用户为中心的服务设计的宝贵制度基础；然而，这些研究并未确立自主AI的有效性。因此，最可辩护的部署模式是一种容忍离线、多语言、多模态且有人工监督的架构，该架构将建议建立在精选的区域知识之上，表征不确定性，保留来源信息，并对高风险或分布外案例进行升级处理。未来研究应优先开展前瞻性的跨区县和跨季节评估，将模型质量与农户决策、农艺结果、公平性、安全性和成本效益联系起来。","Asian Research Journal of Agriculture","2026-09-24T00:00:00Z",80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":46,"relevant":21,"comment":112},"系统综述AI农业咨询与诊断系统在印度东北小农场景的技术架构与落地证据，指出人机协同、离线多语言与检索增强是可行路径，对智慧农业落地有参考价值。",[114],{"name":108,"url":105},[26,27,116,117,29],"农业人工智能","农业技术推广",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[120],{"code":121,"slug":122,"name":123,"path":124,"parent_code":125},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":39,"locked":14,"version":40,"method":41,"evidence":127},{"candidates":128,"agricultural_evidence":47},[129,134,143,149,154],{"code":32,"score":130,"supported":47,"title":131,"abstract":132,"tags":133},15,[56],[29,56],[29],{"code":121,"score":13,"supported":47,"title":135,"abstract":136,"tags":142},[],[137,138,139,140,141],"机器学习","计算机视觉","machine learning","artificial intelligence","computer vision",[116],{"code":45,"score":20,"supported":47,"title":144,"abstract":145,"tags":148},[],[146,147],"数字农业","digital agriculture",[27],{"code":150,"score":21,"supported":14,"title":151,"abstract":152,"tags":153},"G1",[],[],[117],{"code":59,"score":21,"supported":14,"title":155,"abstract":156,"tags":157},[],[],[26],[159,160],"印度东北部 农业AI 小农户","农业智能诊断 多语言 离线","印度东北部农业AI小农户-3512","10.9734\u002Farja\u002F2026\u002Fv19i4919",{"doi":162,"openalex_id":164,"authors":165,"venue":108,"cited_by_count":88,"oa_url":105,"card":171,"direction":94,"ingested_from":97},"W7214205238",[166,168],{"name":167,"orcid":9},"Pravangkar Boruah",{"name":169,"orcid":170},"Rubul Kumar Bania","https:\u002F\u002Forcid.org\u002F0000-0001-6294-0231",{"tldr":172,"method":173,"finding":174,"direction":175,"opportunity":176},"综述AI农业咨询与诊断系统，聚焦印度东北小农，提出人监督多模态部署架构。","批判性叙述综述，整合2010-2026年数字推广、生成式AI与图像诊断证据。","AI输出技术可行但本地化、安全与田间效果证据不足，需人监督与检索增强。","农业人工智能与决策模型","可开展跨区跨季前瞻评估，连接模型质量与农户决策、产量、公平及成本效益。","2026-09-25T23:30:39.745514Z",{"id":179,"title":180,"url":181,"summary":182,"summary_zh":183,"content":9,"source_name":184,"source_url":181,"published_at":185,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":186,"score_detail":187,"sources":192,"tags":194,"primary_topic":197,"secondary_topics":198,"classification":200,"search_phrases":215,"slug":218,"view_count":88,"doi":219,"paper":220,"created_at":234},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":188,"substance":189,"depth":17,"authority":190,"freshness":13,"relevant":21,"comment":191},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。",[193],{"name":184,"url":181},[27,116,29,195,196],"植物病害识别","可解释性",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[199],{"code":121,"slug":122,"name":123,"path":124,"parent_code":125},{"status":39,"locked":14,"version":40,"method":41,"evidence":201},{"candidates":202,"agricultural_evidence":47},[203,207,211],{"code":32,"score":190,"supported":47,"title":204,"abstract":205,"tags":206},[56],[56],[29],{"code":121,"score":13,"supported":47,"title":208,"abstract":209,"tags":210},[141],[],[116,195],{"code":45,"score":21,"supported":14,"title":212,"abstract":213,"tags":214},[],[],[27],[216,217],"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":219,"openalex_id":221,"authors":222,"venue":184,"cited_by_count":88,"oa_url":181,"card":229,"direction":175,"ingested_from":97},"W7223137323",[223,225,227],{"name":224,"orcid":9},"Akshay Ramgoolam",{"name":226,"orcid":9},"Priya Bundhoo Appadoo",{"name":228,"orcid":9},"Jean-Noël LEspérance",{"tldr":230,"method":231,"finding":232,"direction":175,"opportunity":233},"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":236,"title":237,"url":238,"summary":239,"summary_zh":240,"content":9,"source_name":184,"source_url":238,"published_at":185,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":241,"score_detail":242,"sources":244,"tags":246,"primary_topic":249,"secondary_topics":250,"classification":252,"search_phrases":267,"slug":270,"view_count":88,"doi":271,"paper":272,"created_at":286},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":188,"substance":18,"depth":17,"authority":190,"freshness":13,"relevant":21,"comment":243},"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。",[245],{"name":184,"url":238},[27,116,29,247,248],"作物病害识别","模型审计",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[251],{"code":121,"slug":122,"name":123,"path":124,"parent_code":125},{"status":39,"locked":14,"version":40,"method":41,"evidence":253},{"candidates":254,"agricultural_evidence":47},[255,259,263],{"code":32,"score":130,"supported":47,"title":256,"abstract":257,"tags":258},[56],[29,56],[29],{"code":121,"score":13,"supported":47,"title":260,"abstract":261,"tags":262},[141],[],[247,116],{"code":45,"score":21,"supported":14,"title":264,"abstract":265,"tags":266},[],[],[27],[268,269],"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":271,"openalex_id":273,"authors":274,"venue":184,"cited_by_count":88,"oa_url":238,"card":281,"direction":175,"ingested_from":97},"W7223088030",[275,277,279],{"name":276,"orcid":9},"Abdi-Basid Idriss Farah",{"name":278,"orcid":9},"Amina Abdillahi Guedi",{"name":280,"orcid":9},"Moussa Omar Youssouf",{"tldr":282,"method":283,"finding":284,"direction":175,"opportunity":285},"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":288,"title":289,"url":290,"summary":291,"summary_zh":9,"content":292,"source_name":293,"source_url":9,"published_at":185,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":294,"score_detail":295,"sources":297,"tags":299,"primary_topic":303,"secondary_topics":304,"classification":305,"search_phrases":316,"slug":319,"view_count":20,"doi":9,"paper":320,"created_at":328},5537,"农业产业园促进小农户融入数字化供应链：协同机制与制度逻辑","https:\u002F\u002Fkyy.nwafu.edu.cn\u002Fkjjz\u002Fxdkjjz\u002F557ffd662c8e4af98e46fbf90f35d91f.htm","西北农林科技大学阮俊虎教授团队联合德国哥廷根大学于晓华教授，以大荔县国家现代农业产业园等为典型案例，从交易成本理论出发围绕技术赋能、组织整合、规则治理与价值分配四个机制开展案例内分析与跨案例比较，揭示农业产业园作为中国特色制度平台促进小农户融入数字化供应链的深层逻辑。","近日，经济管理学院“数智农业运营管理团队”阮俊虎教授联合德国哥廷根大学于晓华教授在《中国农村经济》发表题为“农业产业园促进小农户融入数字化供应链：协同机制与制度逻辑”的研究论文，通过多案例研究揭示农业产业园促进小农户融入数字化供应链的协同机制，并阐释机制形成与运行的制度逻辑。博士研究生刘晨欢为第一作者，阮俊虎教授为通讯作者，王月博士和于晓华教授为合作学者。\n\n数字技术正深刻重构农产品供应链格局，大型电商平台等供应链核心主体加速构建覆盖生产源头至消费终端的数字化供应链体系，该体系不仅体现为数字技术在生产、销售、物流等环节的应用，更强调不同环节与经营主体之间的系统协同与数据贯通，小农户亟须有效融入数字化供应链以应对市场竞争格局的深刻变化。然而，“大国小农”国情农情下，小农户经营规模较小、土地细碎化程度较高，难以独立对接数字化、规模化的现代供应链体系。促进小农户深度融入数字化供应链，进而实现小农户和现代农业发展有机衔接，成为农业现代化进程中值得关注的重要议题。农业产业园作为区域农业发展的综合性制度平台，兼具资源集聚、组织协同与制度保障三重优势，能够为地方政府及园区经营管理主体协同整合制度资源并协调多元主体关系提供平台支撑，但将资源集聚、组织协同和制度供给优势转化为小农户融入数字化供应链的现实能力，其内在机理尚未得到系统性揭示。\n\n本文立足“农业产业园促进小农户融入数字化供应链的内在机理”这一科学问题，从交易成本理论出发，以大荔县国家现代农业产业园等为典型案例，围绕技术赋能、组织整合、规则治理和价值分配四个机制开展案例内分析与跨案例比较分析，揭示不同园区作用机制的共性、差异及情境适配特征，并从制度层面阐释农业产业园作为中国特色制度平台，促进小农户融入数字化供应链的深层逻辑。研究旨在为农业经营呈现小规模、分散化特征的国家和地区促进小农户和现代农业发展有机衔接提供理论参考与实践借鉴。\n\n该研究得到国家社会科学基金重大项目“我国农产品供应链数字化转型的发展战略与实施路径研究”（23&ZD123）的资助。\n\n论文链接：\n\n[https:\u002F\u002Fzgncjj.ajcass.com\u002F?jumpnotice=201606270007#\u002FissueDetail?contentId=123722&year=2026&issue=10&title=%E5%BD%93%E6%9C%9F%E7%9B%AE%E5%BD%95](https:\u002F\u002Fzgncjj.ajcass.com\u002F?jumpnotice=201606270007#\u002FissueDetail?contentId=123722&year=2026&issue=10&title=%E5%BD%93%E6%9C%9F%E7%9B%AE%E5%BD%95)\n\n编辑：张晴 终审：刘玉峰","中国农村经济 2026-10-21",82,{"impact":17,"substance":18,"depth":17,"authority":130,"freshness":46,"relevant":21,"comment":296},"核心期刊论文，多案例揭示农业产业园促进小农户融入数字化供应链的协同机制与制度逻辑，理论新意足、政策参考价值高，值得进入每日精选。",[298],{"name":293,"url":290},[26,29,300,301,302],"制度逻辑","数字化供应链","农业产业园",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":306},{"candidates":307,"agricultural_evidence":47},[308,312],{"code":32,"score":190,"supported":47,"title":309,"abstract":310,"tags":311},[29],[29],[29],{"code":59,"score":21,"supported":14,"title":313,"abstract":314,"tags":315},[],[],[26],[317,318],"农业产业园 小农户 数字化供应链","大荔县 国家现代农业产业园","农业产业园小农户数字化供应链-5537",{"doi":9,"openalex_id":9,"authors":321,"venue":9,"cited_by_count":88,"oa_url":9,"card":322,"direction":94,"ingested_from":327},[],{"tldr":323,"method":324,"finding":325,"direction":94,"opportunity":326},"以农业产业园为案例，揭示其促进小农户融入数字化供应链的机制与制度逻辑。","交易成本理论，大荔县等典型案例的案例内分析与跨案例比较。","技术赋能、组织整合、规则治理与价值分配四机制共同推动小农户融入数字化供应链。","可量化检验四机制对农户融入绩效的影响，并比较不同产业园模式的适用边界。","agent","2026-10-22T00:07:10.192700Z",{"id":330,"title":331,"url":332,"summary":333,"summary_zh":9,"content":9,"source_name":334,"source_url":9,"published_at":9,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":335,"score_detail":336,"sources":341,"tags":343,"primary_topic":347,"secondary_topics":348,"classification":349,"search_phrases":367,"slug":370,"view_count":21,"doi":9,"paper":371,"created_at":378},4972,"数字赋能:助推小农户融入现代农业发展轨道——基于全国农户微观数据的考察","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fjnxb\u002Fmulu\u002F633014.html","钟文晶、李丹、罗必良(华南农业大学经济管理学院)基于有限理性假设和信息不对称理论,探讨互联网信息技术助推小农户数字赋能的内在机理,并利用中国劳动力动态调查(CLDS)2018年的微观数据进行实证检验。结果表明,互联网使用有效促进了小农户农业生产的机械化、土地经营的规模化以及对农业的生产性投资;异质性分析表明,数字赋能在大规模农户、中老年农户、中部和东北地区的农户组中的作用尤为显著。文章强调应加快推进农村地区的数字基础设施建设,提升农户的数字素养。","《农业经济问题》",79,{"impact":18,"substance":337,"depth":17,"authority":338,"freshness":339,"relevant":21,"comment":340},23,14,2,"基于全国微观数据的实证研究，结论扎实且具政策参考价值，但时效性偏弱，适合主题聚合而非当日精选。",[342],{"name":334,"url":332},[26,344,29,345,346],"数字素养","互联网使用","农村数字基建",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":350},{"candidates":351,"agricultural_evidence":47},[352,356,363],{"code":32,"score":190,"supported":47,"title":353,"abstract":354,"tags":355},[29],[29],[29],{"code":357,"score":358,"supported":47,"title":359,"abstract":360,"tags":362},"F5",3,[],[361],"机械化",[],{"code":59,"score":339,"supported":14,"title":364,"abstract":365,"tags":366},[],[],[26,344],[368,369],"华南农业大学 小农户 数字赋能","CLDS 互联网使用 农业生产","华南农业大学小农户数字赋能-4972",{"doi":9,"openalex_id":9,"authors":372,"venue":9,"cited_by_count":88,"oa_url":9,"card":373,"direction":94,"ingested_from":327},[],{"tldr":374,"method":375,"finding":376,"direction":94,"opportunity":377},"基于CLDS数据实证检验互联网使用如何助推小农户融入现代农业发展。","有限理性与信息不对称理论，CLDS 2018农户微观数据实证。","互联网使用促进小农户机械化、规模化和生产性投资，中老年及中部东北农户效应更显著。","可探究数字素养培训与数字基础设施如何协同提升小农户数字赋能效果。","2026-10-15T00:06:09.096458Z",{"id":380,"title":381,"url":382,"summary":383,"summary_zh":384,"content":9,"source_name":385,"source_url":382,"published_at":386,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":110,"score_detail":387,"sources":389,"tags":391,"primary_topic":394,"secondary_topics":395,"classification":396,"search_phrases":420,"slug":423,"view_count":88,"doi":424,"paper":425,"created_at":436},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":46,"relevant":21,"comment":388},"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。",[390],{"name":385,"url":382},[146,27,29,392,393],"南非农业","农村数字治理",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":397},{"candidates":398,"agricultural_evidence":47},[399,404,408,414],{"code":45,"score":400,"supported":47,"title":401,"abstract":402,"tags":403},16,[147],[146,147],[146,27],{"code":32,"score":53,"supported":47,"title":405,"abstract":406,"tags":407},[],[56],[29],{"code":409,"score":358,"supported":47,"title":410,"abstract":411,"tags":413},"H6",[],[412],"农业生态",[],{"code":415,"score":358,"supported":47,"title":416,"abstract":417,"tags":419},"H7",[],[418],"climate resilience",[],[421,422],"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":424,"openalex_id":426,"authors":427,"venue":385,"cited_by_count":88,"oa_url":382,"card":431,"direction":94,"ingested_from":97},"W7221113328",[428],{"name":429,"orcid":430},"Mokgadi Julia Ngoepe-Ntsoane","https:\u002F\u002Forcid.org\u002F0000-0001-7995-4824",{"tldr":432,"method":433,"finding":434,"direction":94,"opportunity":435},"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"]