[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-118":3,"related-118":59},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":29,"primary_topic":8,"secondary_topics":33,"classification":34,"search_phrases":52,"slug":55,"view_count":56,"doi":57,"paper":8,"created_at":58},118,"涉农数智技术采纳现状与现实挑战：基于两套具有代表性农户调查的研究","https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001","易红梅等基于两套具有代表性的全国农户调查数据,系统分析涉农数智技术的采纳现状与现实挑战,为理解数字技术与农业农村深度融合提供实证依据。",null,"欢迎您访问《智慧农业（中英文）》官方网站！[English](https:\u002F\u002Fwww.smartag.net.cn\u002FEN\u002F2096-8094\u002Fhome.shtml)\n\n[![Image 1](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002F2096-8094\u002Fimages\u002Fbanner.png)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F2096-8094\u002Fhome.shtml)\n\n[![Image 2](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002F2096-8094\u002Fimages\u002Fbanner_mobile.png)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F2096-8094\u002Fhome.shtml)\n\n[![Image 3](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002F2096-8094\u002Fimages\u002Fyyzkj.png)](https:\u002F\u002Fpano.bookan.com.cn\u002F?id=60704&cid=352)\n\nToggle navigation[智慧农业](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001)\n\n*   [网站首页](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F2096-8094\u002Fhome.shtml)\n*   [期刊介绍](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn133.shtml)\n*   [编委会](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn153.shtml)\n*   [投稿指南](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn135.shtml)\n*   [期刊服务](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn124.shtml)\n*   [下载中心](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn126.shtml)\n*   [联系我们](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fcolumn\u002Fcolumn127.shtml)\n\n[Smart Agriculture](https:\u002F\u002Fwww.smartag.net.cn\u002F) ›› [2026](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Farticle\u002FshowTenYearVolumnDetail.do?nian=2026), [Vol. 8](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Farticle\u002FshowTenYearVolumnDetail.do?nian=2026) ›› [Issue (3)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fvolumn\u002Fvolumn_841.shtml): 51-66.doi: [10.12133\u002Fj.smartag.SA202601001](https:\u002F\u002Fdoi.org\u002F10.12133\u002Fj.smartag.SA202601001)\n\n• 专刊--数字技术赋能与农业经济范式转型 •[上一篇](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fabstract\u002Fabstract22558.shtml)[下一篇](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Fabstract\u002Fabstract22804.shtml)\n\n### 涉农数智技术采纳现状与现实挑战：基于两套具有代表性农户调查的研究\n\n易红梅 1, 何煦 1, 智华勇 1, 黄季焜 1([![Image 4](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Femail.png)](mailto:jkhuang.ccap@pku.edu.cn)), 陈曦 2\n\n1.   1. 北京大学现代农学院\u002F中国农业政策研究中心，北京 100871，中国\n\n2. 台州科技职业学院，浙江 台州 318020，中国\n\n*   `收稿日期:`2025-12-31 `出版日期:`2026-05-30 \n\n*   `作者简介:`易红梅，博士，教授，研究方向为农业经济学、数字技术、农村人力资本。E-mail：[hmyi.ccap@pku.edu.cn](mailto:hmyi.ccap@pku.edu.cn) \n*   `通信作者:`黄季焜，博士，教授，研究方向为农业经济学、发展经济学。E-mail：[jkhuang.ccap@pku.edu.cn](mailto:jkhuang.ccap@pku.edu.cn) \n\n### Adoption and Challenges of Digital and Intelligent Technologies in Agriculture: Evidence from Two Representative Household Surveys\n\nYI Hongmei 1, HE Xu 1, ZHI Huayong 1, HUANG Jikun 1([![Image 5](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Femail.png)](mailto:jkhuang.ccap@pku.edu.cn)), CHEN Xi 2\n\n1.   1. School of Advanced Agricultural Sciences, China Center for Agricultural Policy, Peking Univeristy, Beijing 100871, China\n\n2. Taizhou Vocational College of Sicence Technology, Taizhou 318020, China\n\n*   `Received:`2025-12-31 `Online:`2026-05-30 \n*   `Foundation items:`Project of Peking University Institute of Advanced Agricultural Sciences (Weifang, Shandong) \n*   `About author:`YI Hongmei, E-mail: [hmyi.ccap@pku.edu.cn](mailto:hmyi.ccap@pku.edu.cn) \n*   `Corresponding author:`HUANG Jikun, E-mail: [jkhuang.ccap@pku.edu.cn](mailto:jkhuang.ccap@pku.edu.cn) \n\n## [在线阅读 5](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)\n\n## [知网下载](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001)\n\n## [本地下载 21](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#1)\n\n## [补充材料 1](javascript:void(0);)\n\n[_![Image 6](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Fknowledge\\_map1.png)_ ## 可视化 0](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Flexeme\u002FshowArticleByLexeme.do?articleID=22759)\n\n*   [1. 《涉农数智技术采纳现状与现实挑战：基于两套具有代表性农户调查的研究》回归模型.pdf(1146KB)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001)\n\n#### [摘要\u002FAbstract](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001)\n\n**摘要：**\n\n**【目的\u002F意义】** 评估涉农数智技术在中国农业农村微观生产主体中的采纳现状，识别涉农数智技术应用在农业农村未来发展中面临的主要挑战。 **【方法】** 基于两套具有代表性的农户调查数据，首先使用描述性统计方法刻画了各类涉农数智技术在中国农业农村的采纳情况；进一步结合文献综述，梳理了技术采纳的潜在影响及其作用机制，并进一步联系理论与实践，分析了这些数智技术在普及过程中面临的挑战及其成因。 **【结果和讨论】** 研究表明，非嵌入式数智技术在农业中的应用总体呈现“重生活、轻生产”的特征。农业主要决策者智能手机使用率已达76%，但其主要用于社交与娱乐（如微信、抖音、快手），在农业生产、销售及政策信息获取中的应用明显不足；约三分之二的受访者未关注农业类公众号，78%的受访者表示较少通过智能手机获取农业政策信息。在电商与数字金融领域，农户“消费端参与较多、生产端应用不足”的特征同样突出：2023年约52%的农户有网购行为，但通过网络销售农产品的比例仅为0.32%，开展网络贷款的农户占比亦不足2%。与之形成对比的是，嵌入式数智技术在农业生产中的扩散相对较快。以无人机和北斗导航为代表的技术已在关键生产环节中得到应用：2023年约8%的农户在植保环节使用无人机，粮食主产区无人机植保作业覆盖耕地面积占比达39.3%，且主要依托社会化服务体系实现；配备北斗导航的农机占比按农户数量与耕地面积加权分别达到8%和12.5%。进一步分析表明，非嵌入式数智技术应用不足，主要受制于农户认知与数字素养约束、基础设施条件及政策支持不足；而嵌入式技术的加速扩散，则与其成本下降、社会化服务组织发展以及行业标准逐步完善密切相关。 **【结论】** 总体来看，中国农业农村数智化转型正在起步阶段。推动农业农村数智化转型，需积极提升农户数字素养、培育高人力资本水平的新型农业经营主体，继续推动农业适度规模化发展，培育社会化服务主体，加强服务供给能力，从而实现更广泛、更有效的数智技术普及与农业现代化提升。\n\n**关键词:**[数智技术,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[数智化转型,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[农业社会化服务,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[农村电商,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[数字金融,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[北斗导航,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[无人机](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)\n\n**Abstract:**\n\n**[Objective]** In recent years, China has issued a series of policy documents, which emphasize digital transformation as a key driver for deepening the integration of digital and intelligent technologies (DITs) with the agricultural and rural economy, promoting high-quality agricultural development, and advancing the goal of building a strong agricultural sector. However, the ultimate impact of these technologies depends not only on their potential effectiveness but also on the extent to which they are adopted by farmers. Against this backdrop, the aim of this research is to assess the current adoption of agricultural DITs among agricultural producers in China and to identify the main challenges facing their application in the future development of agriculture and rural areas. **[Methods]** Using two representative household survey datasets—the China Agriculture and Rural Development Survey and a 2023 survey of farmers in major grain-producing regions—this study employs descriptive statistics to document the adoption of various DITs. Then they were combined with a review of the literature to examine the potential impacts and underlying mechanisms of technology adoption, and to analyze the challenges and their causes in the diffusion of these technologies by linking theory with practice. **[Results and Discussions]** The results showed that, for non-embedded digital technologies, smartphone use among primary agricultural decision-makers was widespread, with an average penetration rate of 76%. The most frequently used applications were WeChat, TikTok, and Kuaishou. Despite the high usage of WeChat, its application in agricultural production and marketing remains limited: about two-thirds of respondents report rarely or never following agriculture-related official accounts. Similarly, access to agricultural policy information via smartphones was limited, with approximately 78% of respondents indicating that they seldom or only occasionally followed such information. In terms of e-commerce, about 52% of rural households engaged in online shopping in 2023, but very few used online channels for sales: only 0.32% sold agricultural products and 0.15% sold other goods online. In digital finance, only 27% of surveyed households were aware that loans could be applied for online, and the share that had actually applied for online loans in the past two years was even lower, at around 2%. By contrast, embedded digital technologies, such as drones and Beidou-based navigation systems, were more widely used in agricultural production. Data from nine provinces show that about 8% of farmers used drones for crop protection in 2023, reflecting a clear upward trend. In major grain-producing regions, drones covered 39.3% of cultivated land for plant protection, largely through service outsourcing. In addition, the share of farmers using machinery equipped with Beidou navigation systems, weighted by the number of households and cultivated land area, reaches 8% and 12.5%, respectively. Building on these findings, the study analyzes the relatively low adoption of non-embedded technologies in agricultural settings from the perspectives of farmer awareness, digital literacy, infrastructure, and policy support. It also explores the diffusion of embedded technologies from the angles of cost, agricultural organization (particularly the development of service providers), and industry standards. **[Conclusions]** Overall, China's agricultural and rural digital transformation is still at an early stage. The adoption of non-embedded applications in agricultural production and marketing remains very limited, while the use of embedded technologies exhibits substantial heterogeneity across farm sizes and application contexts. In addition, although smallholders rarely invest in digital machinery themselves, they can still benefit from digital transformation through outsourced services and socialized service provision. Further analysis suggests that advancing agricultural digitalization requires improving farmers' digital literacy, fostering new agricultural business entities with higher human capital, promoting the development of appropriately scaled farming, and strengthening the capacity of service providers. These measures are essential to enable broader and more effective diffusion of DITs and to support agricultural modernization.\n\n**Key words:**[digital and intelligent technologies (DITs),](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[digital-intelligent transformation,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[agricultural socialized services,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[rural e-commerce,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[digital finance,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[Beidou navigation,](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)[drones](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)\n\n**中图分类号:**\n\n*   [［TP-9］](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)\n\n*   [［S-9］](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#)\n\n#### 引用本文\n\n易红梅, 何煦, 智华勇, 黄季焜, 陈曦. 涉农数智技术采纳现状与现实挑战：基于两套具有代表性农户调查的研究[J]. 智慧农业(中英文), 2026, 8(3): 51-66.\n\nYI Hongmei, HE Xu, ZHI Huayong, HUANG Jikun, CHEN Xi. Adoption and Challenges of Digital and Intelligent Technologies in Agriculture: Evidence from Two Representative Household Surveys[J]. Smart Agriculture, 2026, 8(3): 51-66.\n\n#### 使用本文\n\n**[[收藏文章](javascript:;)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#) \u002F[推荐](javascript:void(null))**\n**导出引用管理器**[EndNote](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Farticle\u002FgetTxtFile.do?fileType=EndNote&id=22759)|[Ris](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Farticle\u002FgetTxtFile.do?fileType=Ris&id=22759)|[BibTeX](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002Farticle\u002FgetTxtFile.do?fileType=BibTeX&id=22759)\n\n**链接本文:**[https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001)\n\n[https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002FY2026\u002FV8\u002FI3\u002F51](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002FY2026\u002FV8\u002FI3\u002F51)\n\n#### [图\u002F表 17](javascript:;)\n\n[![Image 7](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14768)\n\n**表 1**\n\n九省调查样本量及户权重\n\n| 区域 | 省份 | 县（市）\u002F个 | 乡（镇）\u002F个 | 村\u002F个 | 农户\u002F个 | 户权重 |\n| :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n| 合计 | 57 | 136 | 288 | 3 080 | — |\n| 东北 | 辽宁 | 5 | 10 | 10 | 200 | 1\u002F1 800 |\n| 华北 | 河北 | 5 | 10 | 10 | 200 | 1\u002F1 800 |\n|  | 山东 | 10 | 30 | 60 | 600 | 1\u002F5 400 |\n| 华东 | 浙江 | 5 | 10 | 20 | 200 | 1\u002F1 800 |\n| 华中 | 湖北 | 5 | 10 | 20 | 200 | 1\u002F1 800 |\n|  | 江西 | 12 | 36 | 108 | 1 080 | 1\u002F9 720 |\n| 华南 | 广东 | 5 | 10 | 20 | 200 | 1\u002F1 800 |\n| 西南 | 四川 | 5 | 10 | 20 | 200 | 1\u002F1 800 |\n| 西北 | 陕西 | 5 | 10 | 20 | 200 | 1\u002F1 800 |\n\n 表 1 \n\n[![Image 8](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14769)\n\n**表 2**\n\n主要农业决策者的性别、年龄和受教育水平\n\n| 特征 | 东北 | 华北 | 华东 | 华中 | 华南 | 西南 | 西北 | 合计 |\n| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n| 男性占比\u002F% | 85 | 84 | 86 | 82 | 78 | 61 | 86 | 81 |\n| 年龄\u002F岁 | 63.43 | 61.28 | 67.22 | 63.15 | 62.58 | 59.36 | 60.42 | 62.25 |\n| 受教育水平\u002F年 | 8.60 | 7.84 | 6.51 | 7.47 | 7.47 | 7.10 | 8.37 | 7.65 |\n| 样本数量 | 120 | 662 | 92 | 921 | 144 | 165 | 187 | 2 291 |\n\n 表 2 \n\n[![Image 9](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14770)\n\n**表 3**\n\n农业主要决策者的性别差异\n\n| 特征 | 女 | 男 | _P_ 值 |\n| :---: | :---: | :---: | :---: |\n| 年龄\u002F岁 | 59.73 | 62.82 | 0.001 |\n|  | （10.20） | （10.01） |  |\n| 受教育水平\u002F年 | 6.82 | 7.81 | 0.001 |\n|  | （5.97） | （4.24） |  |\n| 样本数量 | 425 | 1 866 |  |\n\n 表 3 \n\n[![Image 10](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14771)\n\n**表 4**\n\n农业主要决策者使用智能手机的比例 ( %)\n\n| 区域 | 合计 | 男 | 女 |\n| :---: | :---: | :---: | :---: |\n| 东北 | 80.8 | 78.4 | 94.4 |\n| 华北 | 77.0 | 77.8 | 73.7 |\n| 华东 | 55.4 | 58.2 | 38.5 |\n| 华中 | 72.6 | 74.2 | 69.8 |\n| 华南 | 75.7 | 72.3 | 87.5 |\n| 西南 | 82.4 | 80.2 | 85.9 |\n| 西北 | 82.9 | 84.4 | 74.1 |\n| 全样本合计 | 76.3 | 76.3 | 76.6 |\n\n 表 4 \n\n[![Image 11](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F001.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14772)\n\n**图1**\n\n农业主要决策者智能手机上常用的App分布\n\n![Image 12](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F001.jpg)\n\n 图1 \n\n[![Image 13](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F002.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14773)\n\n**图2**\n\n各区域农业主要决策者中常用App为微信的比例\n\n![Image 14](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F002.jpg)\n\n 图2 \n\n[![Image 15](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14774)\n\n**表5**\n\n各区域农业主要决策者使用微信的频率 ( %)\n\n| 区域 | 基本不用 | 偶尔使用 | 经常使用或每天都使用 | 合计 |\n| :---: | :---: | :---: | :---: | :---: |\n| 东北 | 1.2 | 19.3 | 79.5 | 100 |\n| 华北 | 3.2 | 12.4 | 84.4 | 100 |\n| 华东 | 4.9 | 19.5 | 75.6 | 100 |\n| 华中 | 1.7 | 15.0 | 83.3 | 100 |\n| 华南 | 5.0 | 11.0 | 84.0 | 100 |\n| 西南 | 3.2 | 10.2 | 86.6 | 100 |\n| 西北 | 1.3 | 3.4 | 95.3 | 100 |\n| 全样本合计 | 2.6 | 11.9 | 85.5 | 100 |\n\n 表5 \n\n[![Image 16](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F003.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14775)\n\n**图3**\n\n各区域使用微信的农业主要决策者中使用朋友圈和关注朋友圈中销售信息的比例\n\n![Image 17](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F003.jpg)\n\n 图3 \n\n[![Image 18](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14776)\n\n**表6**\n\n各区域使用微信的农业主要决策者关注农业公众号的比例 ( %)\n\n| 区域 | 基本不用 | 偶尔使用 | 经常使用 或每天都在使用 | 合计 |\n| :---: | :---: | :---: | :---: | :---: |\n| 东北 | 50.6 | 33.7 | 15.7 | 100 |\n| 华北 | 64.6 | 23.2 | 12.2 | 100 |\n| 华东 | 68.3 | 17.1 | 14.6 | 100 |\n| 华中 | 67.7 | 21.5 | 10.8 | 100 |\n| 华南 | 75.0 | 17.0 | 8.0 | 100 |\n| 西南 | 77.0 | 15.8 | 7.2 | 100 |\n| 西北 | 58.4 | 23.5 | 18.1 | 100 |\n| 全样本合计 | 66.1 | 21.7 | 12.2 | 100 |\n\n 表6 \n\n[![Image 19](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14777)\n\n**表7**\n\n各区域农业主要决策者用手机关注农业政策的比例 ( %)\n\n| 区域 | 基本不用 | 偶尔使用 | 经常使用 或每天都在使用 | 合计 |\n| :---: | :---: | :---: | :---: | :---: |\n| 东北 | 38.5 | 35.4 | 26.1 | 100 |\n| 华北 | 53.7 | 26.7 | 19.6 | 100 |\n| 华东 | 58.9 | 19.6 | 21.5 | 100 |\n| 华中 | 56.0 | 28.5 | 15.5 | 100 |\n| 华南 | 59.6 | 18.4 | 22.0 | 100 |\n| 西南 | 58.8 | 28.7 | 12.5 | 100 |\n| 西北 | 30.3 | 31.0 | 38.7 | 100 |\n| 全样本合计 | 50.7 | 27.4 | 21.9 | 100 |\n\n 表7 \n\n[![Image 20](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F004.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14778)\n\n**图4**\n\n各区域农业主要决策者对“用手机查看农业信息对农业生产是否有帮助”的看法\n\n![Image 21](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F004.jpg)\n\n 图4 \n\n[![Image 22](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14779)\n\n**表 8**\n\n2023年样本农户电商参与与网络贷款情况\n\n| 区域 | 2023年进行过网购的农户占比\u002F% | 2023年有网络销售活动的农户\u002F% | 知道可以通过网络进行贷款的农户占比\u002F% | 2022—2023年通过网络贷过款的农户占比\u002F% | 其中1，2022—2023年网贷农户的网贷数量\u002F笔 | 其中2，2022—2023年通过网络分期付款的网贷农户占比\u002F% |\n| :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n| 农产品 | 其他商品 |\n| 东北 | 40.0 | 0.5 | 0.0 | 29.5 | 2.0 | 1.0 | 5.0 |\n| 华北 | 43.5 | 0.2 | 0.6 | 27.7 | 2.0 | 1.1 | 8.0 |\n| 华东 | 50.5 | 0.0 | 0.0 | 13.0 | 2.0 | 2.0 | 7.0 |\n| 华中 | 57.9 | 0.3 | 0.1 | 21.1 | 2.0 | 1.4 | 13.0 |\n| 华南 | 51.5 | 1.5 | 0.0 | 23.8 | 1.9 | 1.7 | 14.0 |\n| 西南 | 57.0 | 0.0 | 0.0 | 29.5 | 2.0 | 1.0 | 9.5 |\n| 西北 | 66.3 | 0.0 | 0 | 49.5 | 1.9 | 1.8 | 15.0 |\n| 全样本合计 | 52.0 | 0.3 | 0.2 | 27.0 | 2.0 | 1.5 | 10.0 |\n\n 表 8 \n\n[![Image 23](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F005.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14780)\n\n**图5**\n\n不同网贷渠道占所有网贷批次的比例\n\n![Image 24](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F005.jpg)\n\n 图5 \n\n[![Image 25](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F006.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14781)\n\n**图6**\n\n各区域使用无人机进行植保作业的农户比例\n\n![Image 26](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F006.jpg)\n\n 图6 \n\n[![Image 27](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002Fthumbnail\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F007.jpg)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#figureClass14782)\n\n**图7**\n\n各区域2023年使用无人机进行除草、施肥和播种作业的农户比例\n\n![Image 28](https:\u002F\u002Fwww.smartag.net.cn\u002Ffileup\u002F2096-8094\u002FFIGURE\u002F2026-8-3\u002FImages\u002F2096-8094-2026-8-3-51\u002F1A4616E7-8F14-4a9d-99EF-44A84A675564-F007.jpg)\n\n 图7 \n\n[![Image 29](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14783)\n\n**表9**\n\n粮食主产区样本中无人机的应用现状\n\n| 无人机使用途径 | 大规模户\u002F% | 小规模户\u002F% | 全样本 （未加权）\u002F% | 全样本 （按照户数占比加权）\u002F% | 全样本 （按面积占比加权）\u002F% |\n| :---: | :---: | :---: | :---: | :---: | :---: |\n| 自家是否有植保无人机 | 5 | 0 | 2.5 | 0.3 | 3.9 |\n|  | （22） | （0） |  |  |  |\n| 使用植保无人机社会化服务 | 42 | 12 | 26 | 13.6 | 35.4 |\n|  | （49） | （32） |  |  |  |\n| 样本数量 | 320 | 328 | 648 | 648 | 648 |\n\n 表9 \n\n[![Image 30](https:\u002F\u002Fwww.smartag.net.cn\u002Fimages\u002Ftable-icon.gif)](https:\u002F\u002Fwww.smartag.net.cn\u002FCN\u002F10.12133\u002Fj.smartag.SA202601001#inline_content14784)\n\n**表10**\n\n粮食主产区样本中北斗导航技术的应用现状\n\n| 北斗导航技术的使用途径 | 大规模户\u002F% | 小规模户\u002F% | 全样本（未加权）\u002F% | 全样本（按照户数占比加权）\u002F% | 全样本（按面积占比加权）\u002F% |\n| :---: | :---: | :---: | :---: | :---: | :---: |\n| 自家是否有农机 | 82 | 41 | 61.5 | 43.2 | 73.0 |\n|  | （39） | （0.49） |  |  |  |\n| 自家农机是否装北斗导航（仅限自家有农机的户） | 16 | 0 | 0.08 | 0.8 | 12.5 |\n| （37） | （0） |  |  |  |\n| 耕种收环节是否使用农机社会化服务 | 76 | 79 | 77.5 | 78.8 | 76.7 |\n|  | （43） | （41） |  |  |  |\n| 耕地环节使用的社会化服务提供的农机是否装北斗导航 | 33 | 18 | 25.5 | 18.8 | 29.7 |\n| （47） | （39） |  |  |  |\n| 播种环节使用的社会化服务提供的农机是否装北斗导航 | 30 | 17 | 22.4 | 17.7 | 19.9 |\n| （46） | （38） |  |  |  |\n| 收获环节使用的社会化服务提供的农机是否装北斗导航 | 27 | 26 | 26.5 | 26.1 | 26.8 |\n| （44） | （44） |  |  |  |\n| 样本数量 | 320 | 328 | 648 | 648 | 648 |\n\n 表10 \n\n[](https:\u002F\u002Fwww.smartag.n","智慧农业(中英文) 2026, 8(3): 51-66","2026-07-26T02:00:00Z","论文",25,false,77,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},20,22,18,15,2,1,"基于两套代表性农户调查，揭示数智技术采纳现状与挑战，数据详实，结论可靠，但发表于5天前，时效性较低。",[25,26],{"name":10,"url":6},{"name":27,"url":28},"智慧农业(中英文) 2026年第3期 2026-08-11","https:\u002F\u002Ffinance.sina.com.cn\u002Fwm\u002F2026-08-11\u002Fdoc-inimyhkc7352205.shtml",[30,31,32],"农户采纳","实证研究","数智技术",[],{"status":35,"locked":14,"version":36,"method":37,"evidence":38},"unclassified","2026-10-22.2","rules",{"candidates":39,"agricultural_evidence":50,"reason":51},[40,45],{"code":41,"score":22,"supported":14,"title":42,"abstract":43,"tags":44},"G2",[],[],[30],{"code":46,"score":22,"supported":14,"title":47,"abstract":48,"tags":49},"I1",[],[],[32],true,"缺少足够的主题证据",[53,54],"农户采纳 实证研究 数智技术","农户采纳 实证研究","农户采纳实证研究数智技术-118",13,"10.12133\u002Fj.smartag.sa202601001","2026-07-31T00:00:56.168290Z",{"total":60,"page":22,"page_size":60,"items":61},6,[62,127,211,277,358,450],{"id":63,"title":64,"url":65,"summary":66,"summary_zh":8,"content":8,"source_name":67,"source_url":8,"published_at":8,"category":12,"cover_url":8,"hotness":68,"is_selected":14,"score":69,"score_detail":70,"sources":73,"tags":75,"primary_topic":80,"secondary_topics":86,"classification":87,"search_phrases":112,"slug":115,"view_count":116,"doi":8,"paper":117,"created_at":126},5361,"数智技术与农民增收:基于 31 省 2012-2023 年面板数据的影响效应与作用机制","https:\u002F\u002Ftwnt.fjnyxb.cn\u002F","基于 2012—2023 年 31 个省份面板数据并构建计量回归模型,系统探究数智技术发展对农民增收的影响效应与作用机制。研究发现:数智技术能显著推动农村居民可支配收入提升,结论经多重稳健性检验后依然成立。增收作用通过提升技术成果转化效率、培育粮食新质生产力两条路径实现。数智技术的增收效应存在显著异质性,在数字基础更优的东部地区、产业结构多元的非粮食主产区表现更为突出。DOI: 10.16006\u002Fj.cnki.twnt.2026.04.004。","《台湾农业探索》48(4):37-45 2026",10,74,{"impact":19,"substance":18,"depth":19,"authority":71,"freshness":21,"relevant":22,"comment":72},14,"基于31省11年面板数据的实证研究，方法规范、结论有新意，但属学术论文且发布日期不明，时效性弱，适合主题聚合而非每日精选。",[74],{"name":67,"url":65},[76,77,32,78,79],"数字乡村","农民增收","面板数据","粮食新质生产力",{"code":81,"slug":82,"name":83,"path":84,"parent_code":85},"G6","rural-integration","帮扶与城乡融合","\u002Ftopic\u002Frural-services\u002Frural-integration","G",[],{"status":88,"locked":14,"version":36,"method":37,"evidence":89},"classified",{"candidates":90,"agricultural_evidence":50},[91,96,103,107],{"code":81,"score":92,"supported":50,"title":93,"abstract":94,"tags":95},12,[77],[77],[77],{"code":97,"score":98,"supported":50,"title":99,"abstract":100,"tags":102},"G1",3,[],[101],"成果转化",[],{"code":46,"score":22,"supported":14,"title":104,"abstract":105,"tags":106},[],[],[32],{"code":108,"score":22,"supported":14,"title":109,"abstract":110,"tags":111},"I6",[],[],[76],[113,114],"数智技术 农民增收","台湾农业探索 数智技术","数智技术农民增收-5361",0,{"doi":8,"openalex_id":8,"authors":118,"venue":8,"cited_by_count":116,"oa_url":8,"card":119,"direction":123,"ingested_from":125},[],{"tldr":120,"method":121,"finding":122,"direction":123,"opportunity":124},"用31省2012-2023年面板数据检验数智技术对农民增收的影响与机制。","31省面板数据，计量回归模型，多重稳健性检验与异质性分析。","数智技术显著提升农民可支配收入，经技术成果转化与粮食新质生产力两条路径实现。","数字乡村与农业信息化","可深入微观农户或县域层面，探究数智技术增收效应的区域异质性成因与数字鸿沟调节作用。","agent","2026-10-20T02:47:54.217965Z",{"id":128,"title":129,"url":130,"summary":131,"summary_zh":132,"content":8,"source_name":133,"source_url":130,"published_at":134,"category":12,"cover_url":8,"hotness":68,"is_selected":14,"score":135,"score_detail":136,"sources":142,"tags":144,"primary_topic":149,"secondary_topics":155,"classification":156,"search_phrases":191,"slug":194,"view_count":116,"doi":195,"paper":196,"created_at":210},5139,"Association between digital agricultural technology promotion and farmers’ adoption of extreme climate adaptation technologies: evidence from chili pepper farmers in Guizhou Province, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1914305","Adaptation technologies are important for reducing the risks associated with extreme climatic events, particularly in mountainous areas where complex topography can increase agricultural vulnerability. Digital Agricultural Technology Promotion (DATP) provides an increasingly important channel through which farmers access information related to climate adaptation technologies. However, empirical evidence on the association between DATP and farmers’ adoption of such technologies in mountainous areas remains limited. Using survey data from 846 chili pepper farmers in Guizhou Province, China, this study employs baseline regression, mediation analysis, moderation analysis, and heterogeneity analysis to examine the association between DATP and farmers’ adoption of extreme climate adaptation technologies. The results show that DATP is significantly and positively associated with both adoption degree and sustained adoption willingness. Mediation analysis identifies three potential pathways consistent with this association: broader information access channels, greater information trust, and stronger information application ability. Moderation analysis further shows that benefit and risk expectation confirmation significantly condition the association between DATP and adaptation behavior. Heterogeneity analysis indicates that the positive association is strongest for water resource management and biological control technologies and is relatively stronger among pure farmers, farmers with higher digital literacy, and large-scale chili farmers. These findings highlight the relevance of information access, information credibility, digital capabilities, and farmer heterogeneity in understanding digital approaches to climate adaptation in mountainous agricultural areas. The findings provide empirical evidence for developing differentiated digital strategies to support farmers’ climate adaptation.","适应技术对于降低极端气候事件相关风险具有重要意义，在复杂地形加剧农业脆弱性的山区尤为如此。数字农业技术推广（Digital Agricultural Technology Promotion，DATP）为农户获取气候适应技术相关信息提供了日益重要的渠道。然而，关于DATP与山区农户采纳此类技术之间关联的实证证据仍然有限。本研究利用来自中国贵州省846户辣椒种植户的调查数据，采用基准回归、中介分析、调节分析和异质性分析，考察DATP与农户极端气候适应技术采纳之间的关联。结果表明，DATP与采纳程度和持续采纳意愿均呈显著正相关。中介分析识别出与该关联相符的三条潜在路径：更广泛的信息获取渠道、更高的信息信任以及更强的信息应用能力。调节分析进一步表明，收益与风险预期确认显著调节DATP与适应行为之间的关联。异质性分析表明，该正向关联在水资源管理和生物防治技术中最为显著，且在纯农户、数字素养较高的农户和规模化辣椒种植户中相对更强。上述发现凸显了信息获取、信息可信度、数字能力和农户异质性在理解山区农业气候适应数字化路径中的相关性。研究结果为制定差异化数字策略以支持农户气候适应提供了实证依据。","Frontiers in Sustainable Food Systems","2026-10-16T00:00:00Z",76,{"impact":137,"substance":138,"depth":139,"authority":56,"freshness":140,"relevant":22,"comment":141},16,21,17,9,"基于846户贵州椒农调查的实证研究，揭示数字农技推广与气候适应技术采纳的关联机制，数据扎实、结论有政策参考价值，值得入选。",[143],{"name":133,"url":130},[145,30,146,147,148],"数字农业","气候适应","贵州农业","辣椒种植",{"code":150,"slug":151,"name":152,"path":153,"parent_code":154},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[],{"status":88,"locked":14,"version":36,"method":37,"evidence":157},{"candidates":158,"agricultural_evidence":50},[159,165,171,175,181,187],{"code":150,"score":60,"supported":50,"title":160,"abstract":161,"tags":164},[],[162,163],"水资源","water resource",[],{"code":166,"score":167,"supported":50,"title":168,"abstract":169,"tags":170},"H7",4,[],[146],[146],{"code":46,"score":167,"supported":50,"title":172,"abstract":173,"tags":174},[],[145],[145],{"code":176,"score":98,"supported":50,"title":177,"abstract":178,"tags":180},"B1",[],[179],"辣椒",[],{"code":182,"score":98,"supported":50,"title":183,"abstract":184,"tags":186},"F4",[],[185],"生物防治",[],{"code":41,"score":22,"supported":14,"title":188,"abstract":189,"tags":190},[],[],[30],[192,193],"贵州 辣椒 农户 数字农业","数字农业技术推广 气候适应","贵州辣椒农户数字农业-5139","10.3389\u002Ffsufs.2026.1914305",{"doi":195,"openalex_id":197,"authors":198,"venue":133,"cited_by_count":116,"oa_url":203,"card":204,"direction":123,"ingested_from":209},"W7222443624",[199,201],{"name":200,"orcid":8},"Hongjuan Gao",{"name":202,"orcid":8},"Han Huiqing","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1914305\u002Fpdf",{"tldr":205,"method":206,"finding":207,"direction":123,"opportunity":208},"基于贵州846户椒农调查，分析数字农业技术推广与农户极端气候适应技术采纳的关联。","贵州椒农问卷数据，基线回归、中介、调节与异质性分析。","数字推广显著正向关联采纳程度与持续意愿，信息获取、信任、应用能力为中介路径。","可延伸研究数字推广对不同作物、不同地形区农户气候适应行为的差异化机制与长期效果。","openalex","2026-10-17T23:30:06.590477Z",{"id":212,"title":213,"url":214,"summary":215,"summary_zh":216,"content":8,"source_name":133,"source_url":214,"published_at":217,"category":12,"cover_url":8,"hotness":68,"is_selected":14,"score":218,"score_detail":219,"sources":221,"tags":223,"primary_topic":228,"secondary_topics":234,"classification":235,"search_phrases":248,"slug":251,"view_count":21,"doi":252,"paper":253,"created_at":276},3996,"Growth, instability and adoption trends of natural farming in apple cultivation in Himachal Pradesh, India","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1950685","This study analyses the trends in area under conventional and Subhash Palekar Natural Farming (SPNF) in apple cultivation in Himachal Pradesh from 2011 to 2024. It uses secondary data from the Directorate of Horticulture and the State Project Implementation Unit (SPIU), focusing on 24,595 registered SPNF apple growers. The analysis employs Compound Annual Growth Rate (CAGR), Coefficient of Variation (CV) and the Cuddy-Della Valle Instability Index (CDVI) to compare the periods before (2011–2017) and after (2018–2024) the adoption of SPNF practices. The area under conventional farming grew from 103,644 hectares in 2011 to 116,338 hectares in 2024, with a Compound Annual Growth Rate (CAGR) of 0.89 per cent. However, the expansion rate decreased from 1.40 per cent in 2011–2017 to 0.46 per cent in 2018–2024. In contrast, the area registered under SPNF increased rapidly during the initial adoption phase, from 224.35 ha in 2018 to 14,223.85 ha in 2022, before declining to 4,354.04 ha in 2024. The Welch’s t -test revealed a significant difference in mean conventional apple area between the pre- and post-SPNF periods ( t = −4.734, df = 7.54, p = 0.002). However, this temporal difference does not establish a causal effect of SPNF on apple cultivation area. The observed fluctuations in registered natural-farming area highlight the dynamic nature of adoption and the need for continued institutional support, extension services and market linkages.","本研究分析了2011年至2024年喜马偕尔邦苹果种植中常规农业与苏巴什·帕莱卡自然农法（Subhash Palekar Natural Farming, SPNF）种植面积的趋势。研究使用来自园艺局和国家项目实施单位（SPIU）的二手数据，重点关注24,595名已注册的SPNF苹果种植者。分析采用复合年增长率（CAGR）、变异系数（CV）和Cuddy-Della Valle不稳定指数（CDVI），对采用SPNF实践之前（2011—2017年）和之后（2018—2024年）两个时期进行比较。常规农业种植面积从2011年的103,644公顷增长到2024年的116,338公顷，复合年增长率（CAGR）为0.89%。然而，扩张速度从2011—2017年的1.40%下降到2018—2024年的0.46%。相比之下，SPNF注册面积在初始采用阶段迅速增加，从2018年的224.35公顷增至2022年的14,223.85公顷，随后在2024年下降到4,354.04公顷。Welch t检验显示，SPNF实施前后常规苹果种植面积均值存在显著差异（t = −4.734，df = 7.54，p = 0.002）。然而，这一时间差异并不能确立SPNF对苹果种植面积的因果效应。注册自然农法面积的观察到的波动凸显了采用过程的动态性，以及持续的制度支持、推广服务和市场联结的必要性。","2026-10-01T00:00:00Z",73,{"impact":92,"substance":18,"depth":139,"authority":56,"freshness":140,"relevant":22,"comment":220},"基于2011—2024年官方数据的自然农业采纳趋势实证研究，方法规范、数据翔实，但属印度区域案例，对国内三农信息化参考价值有限。",[222],{"name":133,"url":214},[30,224,225,226,227],"自然农业","苹果种植","喜马偕尔邦","种植面积",{"code":229,"slug":230,"name":231,"path":232,"parent_code":233},"B2","fruit","果树","\u002Ftopic\u002Fhorticulture\u002Ffruit","B",[],{"status":88,"locked":14,"version":36,"method":37,"evidence":236},{"candidates":237,"agricultural_evidence":50},[238,244],{"code":229,"score":71,"supported":50,"title":239,"abstract":241,"tags":243},[240],"apple",[242,240],"苹果",[],{"code":41,"score":22,"supported":14,"title":245,"abstract":246,"tags":247},[],[],[30],[249,250],"喜马偕尔邦 苹果 自然农业","SPNF 苹果 种植面积","喜马偕尔邦苹果自然农业-3996","10.3389\u002Ffsufs.2026.1950685",{"doi":252,"openalex_id":254,"authors":255,"venue":133,"cited_by_count":116,"oa_url":214,"card":270,"direction":274,"ingested_from":209},"W7215070267",[256,259,261,263,265,268],{"name":257,"orcid":258},"Dinesh Kumar","https:\u002F\u002Forcid.org\u002F0000-0001-5762-551X",{"name":260,"orcid":8},"Kapil Kathuria",{"name":262,"orcid":8},"Tarjan Singh Thakur",{"name":264,"orcid":8},"Piyush Mehta",{"name":266,"orcid":267},"Rahul Dhiman","https:\u002F\u002Forcid.org\u002F0000-0002-0521-3342",{"name":269,"orcid":8},"Akanksha Klate",{"tldr":271,"method":272,"finding":273,"direction":274,"opportunity":275},"分析印度喜马偕尔邦苹果常规与自然 farming 的面积趋势、不稳定性及采用动态。","用CAGR、CV、CDVI及Welch t检验分析2011-2024年官方二级数","SPNF面积先激增后骤降，常规面积增速放缓，采用波动大需持续支持。","农业绿色发展与碳","可探究自然 farming 采用后回落的社会经济驱动因素及市场联结对持续性的影响。","2026-10-02T23:30:09.880266Z",{"id":278,"title":279,"url":280,"summary":281,"summary_zh":282,"content":8,"source_name":283,"source_url":280,"published_at":284,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":285,"score_detail":286,"sources":289,"tags":293,"primary_topic":298,"secondary_topics":302,"classification":303,"search_phrases":334,"slug":337,"view_count":21,"doi":338,"paper":339,"created_at":357},3880,"DETERMINANTS DE L'ADOPTION DES PRATIQUES ENDOGENES CLIMATO-INTELLIGENTES PAR LES MENAGES AGRICOLES A DJIDJA, AU SUD-BENIN","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23066853","Résumé Le secteur agricole béninois, bien que moteur de l'économie, est fragilisé par une forte variabilité climatique perçue par 97,6 % des producteurs de la commune de Djidja. Dans ce contexte, l’adoption des Pratiques Endogènes Climato-Intelligentes (PECI) apparaît comme une solution de résilience incontournable. Cette recherche vise à identifier les facteurs socio-économiques et institutionnels qui conditionnent l'adoption de ces pratiques. Dans cette étude, une approche mixte qui combine des variables qualitatives et quantitatives a été adoptée pour évaluer les effets des PECI sur la capacité d'adaptation et la sécurité alimentaire des ménages agricoles. Les collectes ont été faites dans quatre arrondissements de la commune de Djidja. Il s’agit de Setto, Mougnon, Djidja-centre et Monsourou. Prenant en compte les facteurs tels que la géographie et le nombre élevé de ménage agricole dans ces villages. L'étude s'appuie sur un échantillon de 123 ménages, obtenu grâce à la formule de Schwartz. La population est majoritairement sans instruction formelle (58,5 %) et disposant de revenus modestes (52,8 % gagnent moins de 500 000 FCFA\u002Fan). Un modèle de régression linéaire multiple a été utilisé pour tester l'influence de six variables clés sur le score d'adoption des PECI. Les résultats du modèle (R²=0,112 ; F=2,446 ; p=0,029) indiquent que l’adoption ne dépend pas des caractéristiques sociodémographiques classiques : le sexe (p=0,794), le niveau d’éducation (p=0,679), l’âge (p=0,110) et la superficie exploitée (p=0,419) n'ont aucun effet significatif. En revanche, l’expérience agricole (B=0,690 ; p=0,007) et l’accès à l’encadrement et à l’information agricole et météorologique (B=1,104 ; p=0,014) sont les déterminants majeurs et positifs. Cela démontre que l’appropriation des PECI à Djidja repose sur l’apprentissage empirique et la qualité du conseil agricole de proximité plutôt que sur le capital foncier ou l'instruction scolaire. L'étude conclut sur la nécessité de renforcer les dispositifs de vulgarisation et de favoriser les groupements d’agriculteurs (13 %) pour massifier la transition vers une agriculture climato-intelligente. Mots-clés : Changement climatique, PECI, Déterminants de l’adoption des PECI, Djidja, Bénin Abstract Benin’s agricultural sector, although a driving force of the economy, is weakened by significant climate variability, as reported by 97.6% of farmers in the municipality of Djidja. In this context, the adoption of Climate-Smart Local Practices (CSLP) appears to be an essential solution for building resilience. This research aims to identify the socioeconomic and institutional factors that influence the adoption of these practices. In this study, a mixed-methods approach combining qualitative and quantitative variables was adopted to assess the effects of Endogenous Climate-Smart Practices (ECSPs) on the adaptive capacity and food security of farming households. Data were collected in four arrondissements of the commune of Djidja: Setto, Mougnon, Djidja-Centre, and Monsourou. These areas were selected based on geographical considerations and the high number of farming households in the selected villages. The study was conducted with a sample of 123 farming households, determined using the Schwartz formula. The majority of whom have no formal education (58.5%) and modest incomes (52.8% earn less than 500,000 CFA francs per year). A multiple linear regression model was used to test the influence of six key variables on the PECI adoption score. The model results (R² = 0.112; F = 2.446; p = 0.029) indicate that adoption does not depend on traditional sociodemographic characteristics: gender (p = 0.794), education level (p = 0.679), age (p = 0.110), and farm size (p = 0.419) have no significant effect. In contrast, agricultural experience (B=0.690; p=0.007) and access to technical guidance and agricultural information (B=1.104; p=0.014) are the major positive determinants. This demonstrates that the adoption of CSLPs in Djidja is based on empirical learning and the quality of local agricultural extension services rather than on land ownership or educational attainment. The study concludes that it is necessary to strengthen extension services and support farmers’ groups (13 %) to scale up the transition to climate-smart agriculture. Keywords: Climate change, CSLP, Determinants of CSLP adoption, Djidja, Benin","摘要 贝宁的农业部门虽然是经济的驱动力，却因97.6%的迪吉贾（Djidja）镇生产者所感受到的强烈气候变异性而变得脆弱。在此背景下，采用气候智能型本土实践（PECI）似乎成为不可或缺的韧性解决方案。本研究旨在识别制约这些实践采用的社会经济与制度因素。本研究采用定性与定量变量相结合的混合方法，评估PECI对农户适应能力和粮食安全的影响。数据采集在迪吉贾镇的四个区进行，即塞托（Setto）、穆尼翁（Mougnon）、迪吉贾中心（Djidja-centre）和蒙苏鲁（Monsourou），选取时考虑了地理因素以及这些村庄农户数量较多的情况。研究基于123户样本，通过Schwartz公式获得。该人群大多未接受正规教育（58.5%），收入微薄（52.8%年收入低于500 000非洲法郎）。采用多元线性回归模型检验六个关键变量对PECI采用得分的影响。模型结果（R²=0.112；F=2.446；p=0.029）表明，采用并不取决于传统的社会人口学特征：性别（p=0.794）、教育水平（p=0.679）、年龄（p=0.110）和经营面积（p=0.419）均无显著影响。相反，农业经验（B=0.690；p=0.007）以及获得农业与气象指导及信息的机会（B=1.104；p=0.014）是主要且正向的决定因素。这表明，迪吉贾对PECI的掌握依赖于经验学习和就近农业咨询的质量，而非土地资本或学校教育。研究结论指出，有必要加强推广机制并促进农民组织（13%），以大规模推进向气候智能型农业的转型。关键词：气候变化，PECI，PECI采用的决定因素，迪吉贾，贝宁 摘要 贝宁的农业部门虽然是经济的驱动力，却因迪吉贾镇97.6%的农民所报告的显著气候变异性而变得脆弱。在此背景下，采用气候智能型本土","African Scientific Journal","2026-09-30T00:00:00Z",65,{"impact":287,"substance":17,"depth":137,"authority":92,"freshness":140,"relevant":22,"comment":288},8,"基于123户调查的实证研究，发现农业经验与推广信息服务而非教育程度决定气候智慧型本土实践的采纳，对发展中国家农业信息化推广有参考价值，但属区域性个案，影响力有限。",[290,291],{"name":283,"url":280},{"name":283,"url":292},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23066852",[30,294,295,296,297],"小农户","气候智慧型农业","农业推广","贝宁农业",{"code":166,"slug":299,"name":300,"path":301,"parent_code":154},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",[],{"status":88,"locked":14,"version":36,"method":37,"evidence":304},{"candidates":305,"agricultural_evidence":50},[306,313,320,325,330],{"code":166,"score":307,"supported":50,"title":308,"abstract":309,"tags":312},7,[],[310,311],"气候变化","climate change",[295],{"code":314,"score":60,"supported":50,"title":315,"abstract":316,"tags":319},"A8",[],[317,318],"粮食安全","food security",[],{"code":97,"score":167,"supported":50,"title":321,"abstract":322,"tags":324},[],[323],"agricultural extension",[296],{"code":46,"score":98,"supported":50,"title":326,"abstract":327,"tags":329},[],[328],"smart agriculture",[],{"code":41,"score":21,"supported":14,"title":331,"abstract":332,"tags":333},[],[],[30,294],[335,336],"Djidja 气候智慧型农业 农户采纳","贝宁 农业推广 气候适应","Djidja气候智慧型农业农户采纳-3880","10.5281\u002Fzenodo.23066853",{"doi":338,"openalex_id":340,"authors":341,"venue":283,"cited_by_count":116,"oa_url":280,"card":351,"direction":356,"ingested_from":209},"W7214914541",[342,344,346,348],{"name":343,"orcid":8},"Imelda DANNOU",{"name":345,"orcid":8},"Gervais ATCHADE",{"name":347,"orcid":8},"Océane GANSA",{"name":349,"orcid":350},"Ibouraïma Yabi","https:\u002F\u002Forcid.org\u002F0000-0002-8465-9405",{"tldr":352,"method":353,"finding":354,"direction":123,"opportunity":355},"分析贝宁Djidja农户采用本土气候智慧实践的社会经济与制度决定因素。","123户混合问卷+多元线性回归，检验六变量对采用得分影响。","农业经验与推广信息获取显著促进采用，性别、教育、年龄和土地面积无显著影响。","可研究数字气象与农技信息服务如何替代传统推广，提升小农户气候智慧实践采用率。","智慧农业 \u002F 农业物联网","2026-10-01T23:30:09.405648Z",{"id":359,"title":360,"url":361,"summary":362,"summary_zh":363,"content":8,"source_name":364,"source_url":361,"published_at":365,"category":12,"cover_url":8,"hotness":68,"is_selected":14,"score":366,"score_detail":367,"sources":369,"tags":371,"primary_topic":375,"secondary_topics":381,"classification":386,"search_phrases":419,"slug":422,"view_count":423,"doi":424,"paper":425,"created_at":449},3469,"ARTIFICIAL INTELLIGENCE FOR AGRICULTURE: A SYSTEMATIC REVIEW OF FARMERS' PERCEPTIONS, ACCEPTANCE, ADOPTION AND BARRIERS","https:\u002F\u002Fdoi.org\u002F10.64013\u002Fbbasrjlifess.v2026i1.70","Artificial intelligence (AI) is rapidly reshaping agriculture, enabling the application of data for efficient decision-making, precision farming, crop monitoring, pest management, disease detection, smart irrigation, yield prediction, and various aspects of farm automation. Yet, to successfully gain a foothold in farms, factors like farmers' perceptions, their acceptance, desire, and readiness to adopt, as well as the capability to surmount socioeconomic, technological, and institutional challenges, must also make a difference. This article systematically collates the available information on farmers' perspectives on, acceptance of, readiness to adopt, and the obstacles related to AI in the agricultural context. The PRISMA 2020 guideline has been followed to select studies that are related, evaluated for inclusion, and finally, per the criteria, combined into a systematic synthesis. The review mainly discusses the aspects that influence the use of AI, like perceived usefulness, ease of use, trust, digital literacy, affordability, farm size, socioeconomic characteristics, availability of digital infrastructure, and access to agricultural technical advisory services. Main challenges identified involve the high cost of implementing AI, poor connectivity, weak rural infrastructure, low levels of technological knowledge, unavailability of support services, concerns about data privacy, distrust of algorithmic bias, language barriers, and inequalities impacting smallholder farmers. Besides barriers, the review indicates the potential of leveraging AI through extension services, agricultural mobile apps, precision farming, climate-smart agriculture, early-warning systems, and tailored farm advisories. By drawing out technical, behavioral, socioeconomic, and institutional perspectives, the review pinpoints important research questions and presents a farmholder-oriented setup to explain the process of taking up AI in farming. The outcomes can be used by scientific experts, policymakers, extension personnel, and software developers to create low-cost, reliable, and accessible AI systems aimed at promoting sustainable agricultural development.","人工智能（AI）正迅速重塑农业，使数据得以应用于高效决策、精准农业、作物监测、病虫害管理、病害检测、智能灌溉、产量预测以及农场自动化的各个方面。然而，要在农场中成功立足，农民的认知、接受度、采用意愿和准备程度，以及克服社会经济、技术和制度挑战的能力，同样至关重要。本文系统梳理了现有关于农民对农业领域人工智能的看法、接受度、采用准备程度及相关障碍的信息。研究遵循PRISMA 2020指南，筛选相关研究，评估其纳入资格，并最终依据标准进行系统性综合。综述主要探讨了影响人工智能使用的因素，包括感知有用性、易用性、信任、数字素养、可负担性、农场规模、社会经济特征、数字基础设施的可用性以及农业技术咨询服务的获取。识别出的主要挑战包括人工智能实施成本高昂、网络连接不佳、农村基础设施薄弱、技术水平低下、支持服务缺乏、数据隐私担忧、对算法偏见的疑虑、语言障碍以及影响小农户的不平等问题。除障碍外，综述还指出了通过推广服务、农业移动应用、精准农业、气候智慧型农业、预警系统和定制化农场咨询来利用人工智能的潜力。通过梳理技术、行为、社会经济和制度层面的视角，本综述指出了重要的研究问题，并提出了一个以农场主为导向的框架，以解释在农业中采用人工智能的过程。研究结果可供科学专家、政策制定者、推广人员和软件开发者用于创建低成本、可靠且可及的人工智能系统，以促进可持续农业发展。","Journal of Life and Social Sciences","2026-09-24T00:00:00Z",80,{"impact":19,"substance":18,"depth":19,"authority":56,"freshness":140,"relevant":22,"comment":368},"基于PRISMA的系统综述，系统梳理农户对AI的认知、接受度与采纳障碍，对智慧农业推广与政策设计有实质参考价值。",[370],{"name":364,"url":361},[372,373,374,30,294],"智慧农业","农业人工智能","数字素养",{"code":376,"slug":377,"name":378,"path":379,"parent_code":380},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[382],{"code":41,"slug":383,"name":384,"path":385,"parent_code":85},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",{"status":88,"locked":14,"version":36,"method":37,"evidence":387},{"candidates":388,"agricultural_evidence":50},[389,394,399,404,409,415],{"code":376,"score":92,"supported":50,"title":390,"abstract":392,"tags":393},[391],"artificial intelligence",[391],[373],{"code":41,"score":287,"supported":50,"title":395,"abstract":396,"tags":398},[],[294,397],"smallholder",[30,294],{"code":46,"score":307,"supported":50,"title":400,"abstract":401,"tags":403},[],[402,328],"精准农业",[372],{"code":150,"score":60,"supported":50,"title":405,"abstract":406,"tags":408},[],[407,151],"灌溉",[],{"code":410,"score":98,"supported":50,"title":411,"abstract":412,"tags":414},"H8",[],[413],"可持续农业",[],{"code":108,"score":22,"supported":14,"title":416,"abstract":417,"tags":418},[],[],[374],[420,421],"农民 AI 采纳 障碍","农业人工智能 系统综述","农民AI采纳障碍-3469",5,"10.64013\u002Fbbasrjlifess.v2026i1.70",{"doi":424,"openalex_id":426,"authors":427,"venue":364,"cited_by_count":116,"oa_url":361,"card":444,"direction":356,"ingested_from":209},"W7214189410",[428,430,432,434,436,438,440,442],{"name":429,"orcid":8},"MM JAMEEL",{"name":431,"orcid":8},"M SAEED",{"name":433,"orcid":8},"SA SHER",{"name":435,"orcid":8},"Z ALI",{"name":437,"orcid":8},"Q HAYYAT",{"name":439,"orcid":8},"S KIRBAG",{"name":441,"orcid":8},"S KHAN",{"name":443,"orcid":8},"HN AHMAD",{"tldr":445,"method":446,"finding":447,"direction":123,"opportunity":448},"系统综述农民对农业AI的感知、接受度、采纳意愿及障碍。","遵循PRISMA 2020指南，系统筛选并综合相关文献。","成本、基础设施、数字素养与信任是主要障碍，小农户受影响最大。","可研究低成本、本地化AI采纳模型及小农户数字包容机制。","2026-09-25T23:30:09.670568Z",{"id":451,"title":452,"url":453,"summary":454,"summary_zh":8,"content":8,"source_name":455,"source_url":8,"published_at":456,"category":12,"cover_url":8,"hotness":68,"is_selected":14,"score":457,"score_detail":458,"sources":460,"tags":462,"primary_topic":465,"secondary_topics":471,"classification":472,"search_phrases":487,"slug":490,"view_count":21,"doi":8,"paper":491,"created_at":498},3450,"《数智技术赋能农业新质生产力：内在机理、驱动要素与实现进路》","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fjianghuailuntan\u002Fmulu\u002F678750.html","孙壮珍从数智技术赋能农业新质生产力内在机理入手，分析数智技术赋能农业新质生产力驱动要素，并从主体-组织-制度全域视角提出通过构建利益导向机制、培育新型载体平台、推进制度调适的实现进路。文章认为农业新质生产力有高度的渗透性与广泛的链接性，能够进一步拓展农业的生产空间与效率边界，变革农业生产的工艺、技术与流程，加速我国农业强国建设的进程。","《江淮论坛》\u002F西南科技大学","2026-09-20T00:00:00Z",75,{"impact":19,"substance":17,"depth":139,"authority":71,"freshness":60,"relevant":22,"comment":459},"核心期刊论文，从机理、要素到实现进路系统论述数智技术赋能农业新质生产力，理论增量明确，但属学术探讨而非政策落地，时效性一般。",[461],{"name":455,"url":453},[76,372,463,464,32],"农业新质生产力","农业强国",{"code":466,"slug":467,"name":468,"path":469,"parent_code":470},"J2","modernization","农业强国与现代化","\u002Ftopic\u002Fpolicy\u002Fmodernization","J",[],{"status":88,"locked":14,"version":36,"method":37,"evidence":473},{"candidates":474,"agricultural_evidence":50},[475,479,483],{"code":466,"score":423,"supported":50,"title":476,"abstract":477,"tags":478},[],[464],[464,463],{"code":46,"score":21,"supported":14,"title":480,"abstract":481,"tags":482},[],[],[32,372],{"code":108,"score":22,"supported":14,"title":484,"abstract":485,"tags":486},[],[],[76],[488,489],"数智技术 农业新质生产力","江淮论坛 农业新质生产力","数智技术农业新质生产力-3450",{"doi":8,"openalex_id":8,"authors":492,"venue":8,"cited_by_count":116,"oa_url":8,"card":493,"direction":123,"ingested_from":125},[],{"tldr":494,"method":495,"finding":496,"direction":123,"opportunity":497},"分析数智技术赋能农业新质生产力的内在机理、驱动要素与实现进路。","理论分析，从主体-组织-制度全域视角提出机制、平台与制度调适路径。","农业新质生产力具高渗透性与广链接性，可拓展生产空间与效率边界，加速农业强国建设。","可实证检验数智技术赋能农业新质生产力的机制与制度调适效果，弥补纯理论分析不足。","2026-09-25T00:09:34.845621Z"]