[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3273":3,"related-3273":85},{"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":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":62,"slug":65,"view_count":66,"doi":67,"paper":68,"created_at":84},3273,"Determinants of the Use and Extent of Digital Agriculture Among Moroccan Farmers","https:\u002F\u002Fdoi.org\u002F10.22004\u002Fag.econ.412776","Digital agriculture, driven by advancements in financial engineering, holds significant potential to enhance productivity and sustainability in agricultural production. However, the adoption and extent of these technologies fundamentally depend on farmers’ willingness to accept and use them. While recent studies have identified key factors influencing the adoption of digital agriculture, to the best of our knowledge, no academic study has specifically examined the determinants of both the use and the extent of adoption, particularly within the Moroccan context. This study investigates both the adoption and intensity of digital agriculture among a sample of 250 Moroccan farmers, utilizing a paper-based survey and two econometric approaches: a multinomial logit model and the Heckman model. The findings reveal that farmer age has a negative and significant impact on digital agriculture adoption. At the same time, crop type and risk aversion emerge as significant positive determinants of both the adoption and the extent of smart farming use. Specifically, technology adoption is mainly influenced by age, crop type, and risk aversion, whereas the extent of use is primarily driven by risk aversion and the type of crops cultivated. These results highlight the importance of implementing targeted policies and training programs to promote broader and more intensive use of digital agriculture technologies. Additionally, these findings open up avenues for further research aimed at better understanding the underlying factors that shape Moroccan farmers' behavior toward digital agriculture adoption.","由金融工程进步所驱动的数字农业，在提升农业生产率与可持续性方面具有巨大潜力。然而，这些技术的采用及其程度从根本上取决于农民接受和使用它们的意愿。尽管近期研究已识别出影响数字农业采用的关键因素，但据我们所知，尚无学术研究专门考察使用与采用程度的决定因素，尤其是在摩洛哥背景下。本研究基于250名摩洛哥农民的样本，采用纸质问卷调查和两种计量经济学方法——多项Logit模型与Heckman模型——考察了数字农业的采用情况及使用强度。研究发现，农民年龄对数字农业采用具有显著负向影响。与此同时，作物类型与风险规避对智慧农业的采用及使用程度均呈现显著正向决定作用。具体而言，技术采用主要受年龄、作物类型和风险规避影响，而使用程度则主要由风险规避和所种植作物类型驱动。这些结果凸显了实施有针对性的政策与培训项目以促进数字农业技术更广泛、更深入应用的重要性。此外，这些发现为后续研究开辟了方向，有助于更深入理解塑造摩洛哥农民数字农业采用行为的潜在因素。",null,"AgEcon Search (University of Minnesota, USA)","2026-09-21T00:00:00Z","论文",10,false,72,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,13,9,1,"基于250户摩洛哥农户调查，用多项Logit与Heckman模型揭示年龄、作物类型与风险规避对数字农业采纳及使用强度的差异化影响，方法规范、结论有新意，对发展中国家数字农业推广有借鉴价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字农业","智慧农业","农业技术推广","农户采纳","摩洛哥农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I1","smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,57],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},19,true,[49],"digital agriculture",[28,27,49],[27,28],{"code":53,"score":22,"supported":14,"title":54,"abstract":55,"tags":56},"G1",[],[],[29],{"code":58,"score":22,"supported":14,"title":59,"abstract":60,"tags":61},"G2",[],[],[30],[63,64],"摩洛哥 农户 数字农业","Heckman 模型 智慧农业 采纳","摩洛哥农户数字农业-3273",3,"10.22004\u002Fag.econ.412776",{"doi":67,"openalex_id":69,"authors":70,"venue":10,"cited_by_count":75,"oa_url":6,"card":76,"direction":82,"ingested_from":83},"W7213999238",[71,73],{"name":72,"orcid":9},"Adil Jouamaa Mohammed",{"name":74,"orcid":9},"I. Mubarak Abdulilah",0,{"tldr":77,"method":78,"finding":79,"direction":80,"opportunity":81},"研究摩洛哥250位农民采用数字农业及其使用程度的决定因素。","纸质问卷，多项Logit模型与Heckman模型。","年龄负向影响采用，作物类型和风险规避正向影响采用与使用程度。","数字乡村与农业信息化","可针对不同作物和风险偏好农民设计差异化推广策略，并开展跨区域比较研究。","智慧农业 \u002F 农业物联网","openalex","2026-09-23T23:30:11.088448Z",{"total":86,"page":22,"page_size":86,"items":87},6,[88,135,190,241,320,365],{"id":89,"title":90,"url":91,"summary":92,"summary_zh":9,"content":9,"source_name":93,"source_url":91,"published_at":94,"category":12,"cover_url":9,"hotness":95,"is_selected":14,"score":96,"score_detail":97,"sources":100,"tags":104,"primary_topic":107,"secondary_topics":108,"classification":109,"search_phrases":117,"slug":120,"view_count":75,"doi":121,"paper":122,"created_at":134},5396,"Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.","https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.22601.71520","Understanding the Digital Agriculture Landscape in Central Africa: 2000-2026 Systematic Review.。OpenAlex","OpenAlex","2026-10-19T00:00:00Z",25,37,{"impact":98,"substance":86,"depth":98,"authority":86,"freshness":21,"relevant":22,"comment":99},8,"中非数字农业系统综述，主题相关但摘要信息极少，仅题录级元数据，增量与权威性有限，不建议进入每日精选。",[101,102],{"name":93,"url":91},{"name":93,"url":103},"https:\u002F\u002Fdoi.org\u002F10.13140\u002Frg.2.2.16146.41922",[27,28,105,106],"农业信息化","中非",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":110},{"candidates":111,"agricultural_evidence":47},[112],{"code":33,"score":113,"supported":47,"title":114,"abstract":115,"tags":116},14,[49],[49],[105,27,28],[118,119],"中非 数字农业","农业信息化 数字农业 智慧农业 中非","中非数字农业-5396","10.13140\u002Frg.2.2.22601.71520",{"doi":121,"openalex_id":123,"authors":124,"venue":9,"cited_by_count":75,"oa_url":91,"card":9,"direction":80,"ingested_from":83},"W7222930115",[125,127,129,132],{"name":126,"orcid":9},"Anani Ogou",{"name":128,"orcid":9},"Henry Chotangui",{"name":130,"orcid":131},"Honoré Beyegue-Djonko","https:\u002F\u002Forcid.org\u002F0009-0004-6447-5889",{"name":133,"orcid":9},"Christopher Mubeteneh Tankou","2026-10-20T23:30:22.542913Z",{"id":136,"title":137,"url":138,"summary":139,"summary_zh":140,"content":9,"source_name":141,"source_url":138,"published_at":142,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":143,"score_detail":144,"sources":147,"tags":149,"primary_topic":153,"secondary_topics":154,"classification":155,"search_phrases":173,"slug":176,"view_count":66,"doi":177,"paper":178,"created_at":189},4061,"Being Granular, Becoming Sustainable:","https:\u002F\u002Fdoi.org\u002F10.21248\u002Fka-notizen.88.61","This article examines the integration of digitization and environmental concerns in digital agriculture from the perspective of actors in smart farming in Switzerland. Those actors, previously unconnected to farming, promote the use of granular data to achieve more sustainable practices. Considering granularity as a practitioner-made achievement rather than a technical property alone, I draw on interviews and ethnographic observations, and rely on material-semiotic insights from STS (Law, 2008; Mol, 1999; Lien & Law, 2011) to examine how granularity data is brought into existence through heterogeneous practices. I first analyze how the connection between digital agriculture and more sustainable practices is operated as a motto, an aspirational principle that draws from different sources and comparisons. I then show how the production and interpretation of granular data depend on experimental infrastructures, interdisciplinary collaboration, and ongoing human interpretation, all of which contribute to the existence of granularity while enacting specific definitions of sustainability.","本文从瑞士智慧农业行动者的视角，考察数字农业中数字化与环境关切的融合。这些行动者此前与农业并无关联，他们推动利用细粒度数据来实现更可持续的实践。本文将细粒度视为实践者的成就而非单纯的技术属性，基于访谈和民族志观察，并借助STS（科学技术与社会研究）的物质-符号学洞见（Law, 2008; Mol, 1999; Lien & Law, 2011），考察细粒度数据如何通过异质性实践被带入存在。我首先分析数字农业与更可持续实践之间的关联如何作为一种箴言（motto）运作——这是一种从不同来源和比较中汲取的愿景性原则。随后我展示细粒度数据的生产和解读如何依赖于实验性基础设施、跨学科协作以及持续的人类解释活动，所有这些共同促成了细粒度的存在，同时也在 enact（制定\u002F施行）可持续性的特定定义。","Kulturanthropologie Notizen","2026-10-02T00:00:00Z",64,{"impact":98,"substance":145,"depth":19,"authority":20,"freshness":98,"relevant":22,"comment":146},18,"从STS视角剖析瑞士智慧农业中数据粒度与可持续性的建构过程，方法新颖、结论可靠，但属学术个案研究，公共影响有限。",[148],{"name":141,"url":138},[27,28,150,151,152],"可持续农业","农业数据","瑞士",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":156},{"candidates":157,"agricultural_evidence":47},[158,163,168],{"code":33,"score":159,"supported":47,"title":160,"abstract":161,"tags":162},11,[],[28,27,49],[27,28],{"code":164,"score":22,"supported":14,"title":165,"abstract":166,"tags":167},"H8",[],[],[150],{"code":169,"score":22,"supported":14,"title":170,"abstract":171,"tags":172},"I6",[],[],[151],[174,175],"瑞士 智慧农业 数据粒度","可持续农业 农业数据 数字农业 智慧农业","瑞士智慧农业数据粒度-4061","10.21248\u002Fka-notizen.88.61",{"doi":177,"openalex_id":179,"authors":180,"venue":141,"cited_by_count":75,"oa_url":138,"card":184,"direction":82,"ingested_from":83},"W7216220972",[181],{"name":182,"orcid":183},"Mylène Tanferri","https:\u002F\u002Forcid.org\u002F0000-0003-1650-8442",{"tldr":185,"method":186,"finding":187,"direction":80,"opportunity":188},"从瑞士智慧农业行动者视角，探讨数字化与可持续性如何通过颗粒化数据实践结合。","访谈与民族志观察，结合STS物质符号学分析。","颗粒化数据是实践成就，依赖实验设施、跨学科协作和持续人为解释，并塑造特定可持续定义。","可研究颗粒化数据实践中不同行动者如何协商可持续性定义，及其对农户采纳的影响。","2026-10-03T23:30:10.168598Z",{"id":191,"title":192,"url":193,"summary":194,"summary_zh":9,"content":9,"source_name":195,"source_url":193,"published_at":196,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":197,"score_detail":198,"sources":201,"tags":203,"primary_topic":207,"secondary_topics":208,"classification":209,"search_phrases":222,"slug":225,"view_count":226,"doi":227,"paper":228,"created_at":240},3520,"Factors influencing digital technology investments on French farms","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11119-026-10429-3","Factors influencing digital technology investments on French farms。Precision Agriculture","Precision Agriculture","2026-09-25T00:00:00Z",68,{"impact":17,"substance":145,"depth":199,"authority":113,"freshness":98,"relevant":22,"comment":200},16,"核心期刊论文，方法数据扎实，但研究对象为法国农场，对国内三农实践的直接参考价值有限，时效性尚可。",[202],{"name":195,"url":193},[27,28,204,205,206],"精准农业","农业投资","法国农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":210},{"candidates":211,"agricultural_evidence":47},[212,217],{"code":33,"score":86,"supported":47,"title":213,"abstract":214,"tags":216},[],[215],"precision agriculture",[27,28,204],{"code":218,"score":22,"supported":14,"title":219,"abstract":220,"tags":221},"G3",[],[],[205],[223,224],"法国农场 数字技术 投资","Precision Agriculture 法国","法国农场数字技术投资-3520",2,"10.1007\u002Fs11119-026-10429-3",{"doi":227,"openalex_id":229,"authors":230,"venue":195,"cited_by_count":75,"oa_url":9,"card":9,"direction":80,"ingested_from":83},"W7214319682",[231,234,237],{"name":232,"orcid":233},"Maha Ben Jaballah","https:\u002F\u002Forcid.org\u002F0000-0002-4489-278X",{"name":235,"orcid":236},"Aude Ridier","https:\u002F\u002Forcid.org\u002F0000-0002-7893-735X",{"name":238,"orcid":239},"Karine Daniel","https:\u002F\u002Forcid.org\u002F0000-0001-9550-5666","2026-09-26T23:30:02.695117Z",{"id":242,"title":243,"url":244,"summary":245,"summary_zh":246,"content":9,"source_name":247,"source_url":244,"published_at":248,"category":12,"cover_url":9,"hotness":95,"is_selected":14,"score":249,"score_detail":250,"sources":254,"tags":259,"primary_topic":263,"secondary_topics":264,"classification":265,"search_phrases":292,"slug":295,"view_count":296,"doi":297,"paper":298,"created_at":319},3470,"AI-generated advice as a reinforcement layer in climate-smart agriculture","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landusepol.2026.108336","Climate-smart agricultural (CSA) practices are central to food-system decarbonisation, yet adoption often falls short of farmers’ stated intentions, weakening the impact of incentives and extension under capacity constraints. We test whether spatially targeted, AI-generated advice can narrow this intention-action gap in a randomised field experiment with 1529 row crop farmers in Iowa, Illinois and Indiana during the cover crop decision window. Farmers assigned to receive four AI-generated emails were 4.45 %age points more likely to plant cover crops than controls (z = 2.81, p = 0.005), despite high baseline intentions in both groups. Effects operated on the extensive margin: there was no detectable change in the share of land planted among adopters. Survey responses indicate high engagement and a shift from untested optimism to more calibrated trust after exposure. Supervised AI advice can provide a low-cost, scalable complement to existing extension, improving follow-through and modestly expanding uptake without displacing human expertise.","气候智慧型农业（CSA）实践是食品系统脱碳的核心，然而在能力受限的情况下，农户的实际采用往往低于其声称的意愿，削弱了激励措施和推广服务的效果。我们在爱荷华州、伊利诺伊州和印第安纳州开展了一项随机田间试验，覆盖1529名大田作物种植户，在覆盖作物决策窗口期测试了空间靶向的AI生成建议能否缩小这一意愿—行动差距。被分配接收四封AI生成电子邮件的农户种植覆盖作物的概率比对照组高4.45个百分点（z = 2.81，p = 0.005），尽管两组基线意愿均较高。效应体现在广延边际上：采用者中种植土地比例未检测到显著变化。调查回复表明参与度较高，且在接触建议后，农户从未经检验的乐观转向更为校准的信任。有监督的AI建议可作为现有推广服务的低成本、可扩展补充，改善后续落实并适度扩大采用，而不会取代人类专业知识。","Land Use Policy","2026-09-24T00:00:00Z",87,{"impact":251,"substance":252,"depth":46,"authority":113,"freshness":21,"relevant":22,"comment":253},22,23,"随机对照试验证实AI生成建议可低成本缩小农户意愿与行动差距，对智慧农业推广具参考价值。",[255,256],{"name":247,"url":244},{"name":257,"url":258},"Apollo","https:\u002F\u002Fdoi.org\u002F10.17863\u002Fcam.134741",[28,260,29,261,262],"农业人工智能","覆盖作物","气候智慧农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":266},{"candidates":267,"agricultural_evidence":47},[268,273,278,282,287],{"code":33,"score":21,"supported":47,"title":269,"abstract":271,"tags":272},[270],"smart agriculture",[],[28],{"code":274,"score":22,"supported":14,"title":275,"abstract":276,"tags":277},"A7",[],[],[261],{"code":53,"score":22,"supported":14,"title":279,"abstract":280,"tags":281},[],[],[29],{"code":283,"score":22,"supported":14,"title":284,"abstract":285,"tags":286},"H7",[],[],[262],{"code":288,"score":22,"supported":14,"title":289,"abstract":290,"tags":291},"I2",[],[],[260],[293,294],"AI生成建议 覆盖作物","爱荷华 伊利诺伊 印第安纳 覆盖作物","AI生成建议覆盖作物-3470",7,"10.1016\u002Fj.landusepol.2026.108336",{"doi":297,"openalex_id":299,"authors":300,"venue":247,"cited_by_count":75,"oa_url":244,"card":313,"direction":82,"ingested_from":83},"W7214223143",[301,304,306,308,311],{"name":302,"orcid":303},"Callum Alexander","https:\u002F\u002Forcid.org\u002F0009-0007-5275-4583",{"name":305,"orcid":9},"Aiora Zabala",{"name":307,"orcid":9},"Andreas Kontoleon",{"name":309,"orcid":310},"Shalamar Armstrong","https:\u002F\u002Forcid.org\u002F0000-0002-1326-9936",{"name":312,"orcid":9},"Anuoluwa Sangotayo",{"tldr":314,"method":315,"finding":316,"direction":317,"opportunity":318},"随机试验检验AI生成建议能否缩小农户覆盖作物种植的意图-行动差距。","1529户美国中西部农户随机对照试验，四次AI生成邮件干预。","AI建议使覆盖作物种植率提高4.45个百分点，效果体现在是否采纳而非种植面积。","农业人工智能与决策模型","可探索AI建议与人工推广协同、长期持续效果及不同作物区域的异质性影响。","2026-09-25T23:30:09.887867Z",{"id":321,"title":322,"url":323,"summary":324,"summary_zh":325,"content":9,"source_name":326,"source_url":323,"published_at":327,"category":12,"cover_url":9,"hotness":95,"is_selected":14,"score":328,"score_detail":329,"sources":331,"tags":335,"primary_topic":338,"secondary_topics":339,"classification":340,"search_phrases":347,"slug":350,"view_count":66,"doi":351,"paper":352,"created_at":364},3272,"Smart Agriculture in Northern Nigeria: Prospects and Challenges for Graduate Farmers","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22891268","Smart Agriculture in Northern Nigeria: Prospects and Challenges for Graduate Farmers。Zenodo (CERN European Organization for Nuclear Research)","尼日利亚北部智慧农业：研究生农民的前景与挑战。Zenodo（CERN欧洲核子研究组织）","Zenodo (CERN European Organization for Nuclear Research)","2026-09-22T00:00:00Z",45,{"impact":98,"substance":86,"depth":13,"authority":17,"freshness":21,"relevant":22,"comment":330},"主题相关但为尼日利亚区域研究，缺乏新数据与实质结论，仅具参考价值，不宜进入每日精选。",[332,333],{"name":326,"url":323},{"name":326,"url":334},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22891267",[27,28,336,337],"尼日利亚","农业人才",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":341},{"candidates":342,"agricultural_evidence":47},[343],{"code":33,"score":199,"supported":47,"title":344,"abstract":345,"tags":346},[270],[28,270],[27,28],[348,349],"尼日利亚 智慧农业 毕业生","农业人才 尼日利亚 数字农业 智慧农业","尼日利亚智慧农业毕业生-3272","10.5281\u002Fzenodo.22891268",{"doi":351,"openalex_id":353,"authors":354,"venue":326,"cited_by_count":75,"oa_url":323,"card":359,"direction":82,"ingested_from":83},"W7214014972",[355,357],{"name":356,"orcid":9},"Baman Abubakar",{"name":358,"orcid":9},"A.A Akinsoru",{"tldr":360,"method":361,"finding":362,"direction":80,"opportunity":363},"调查尼日利亚北部毕业农户对智慧农业的前景认知与实际挑战。","针对毕业农户的问卷调查与定性分析。","毕业农户认可智慧农业潜力，但受基础设施、资金与技能制约。","可延伸至小农户数字素养培训与低成本智慧农业适配方案研究。","2026-09-23T23:30:09.435022Z",{"id":366,"title":367,"url":368,"summary":369,"summary_zh":370,"content":9,"source_name":371,"source_url":368,"published_at":372,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":373,"score_detail":374,"sources":377,"tags":379,"primary_topic":383,"secondary_topics":384,"classification":385,"search_phrases":392,"slug":395,"view_count":226,"doi":396,"paper":397,"created_at":411},3018,"AGROPORTAL YAGONA PLATFORMASI ORQALI YER RESURSLARI TO‘G‘RISIDAGI MA’LUMOTLARNI INTEGRATSIYALASH: MUAMMOLAR VA YECHIMLAR","https:\u002F\u002Fdoi.org\u002F10.67048\u002Fqxju2026ai128iss7m1054","This scientific article provides a systematic analysis of the current state, achieved results, and existing challenges in implementing digital technologies within the agricultural sector of the Republic of Uzbekistan for 2025–2026. The paper highlights the “Digital Uzbekistan 2030” strategy, the Presidential Decree of August 2025, the unified “Digital Agriculture” platform (Agroportal), and legislative innovations concerning the digitalization of the agricultural support system. Based on statistical data and ongoing projects, prospective directions for the sector’s digital transformation are identified.","本文系统分析了2025—2026年乌兹别克斯坦共和国农业领域数字技术实施的现状、已取得的成果及现有挑战。文章重点阐述了“数字乌兹别克斯坦2030”战略、2025年8月总统令、统一的“数字农业”平台（Agroportal），以及涉及农业支持体系数字化的立法创新。基于统计数据及正在实施的项目，本文明确了该领域数字化转型的前景方向。","Agro ilm","2026-09-18T00:00:00Z",77,{"impact":251,"substance":375,"depth":19,"authority":13,"freshness":98,"relevant":22,"comment":376},20,"系统梳理乌兹别克斯坦农业数字化平台与政策进展，含2025年总统令等实质信息，对农业信息化研究有参考价值。",[378],{"name":371,"url":368},[27,28,380,381,382],"农业政策","农业数据整合","数字乌兹别克斯坦",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":386},{"candidates":387,"agricultural_evidence":47},[388],{"code":33,"score":98,"supported":47,"title":389,"abstract":390,"tags":391},[],[27,49],[27,28],[393,394],"乌兹别克斯坦 Agroportal 数字农业","数字乌兹别克斯坦 农业数据整合 农业政策 数字农业","乌兹别克斯坦Agroportal数字农业-3018","10.67048\u002Fqxju2026ai128iss7m1054",{"doi":396,"openalex_id":398,"authors":399,"venue":371,"cited_by_count":75,"oa_url":368,"card":406,"direction":80,"ingested_from":83},"W7213649986",[400,403],{"name":401,"orcid":402},"Maxfuza Abdullayeva","https:\u002F\u002Forcid.org\u002F0009-0000-6004-6260",{"name":404,"orcid":405},"Islam Akramov","https:\u002F\u002Forcid.org\u002F0009-0009-1574-1534",{"tldr":407,"method":408,"finding":409,"direction":80,"opportunity":410},"分析乌兹别克斯坦农业数字化现状，聚焦Agroportal平台整合土地资源数据的问题与对策。","基于统计数据和政策文件，系统分析2025-2026年农业数字化进展。","Agroportal平台是土地资源数据整合的关键，但面临数据集成与制度障碍。","可研究土地资源数据跨部门整合的互操作机制与农户采纳影响因素。","2026-09-20T23:30:28.150963Z"]