[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2032":3,"related-2032":88},{"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":65,"slug":68,"view_count":61,"doi":69,"paper":70,"created_at":87},2032,"Enhancing access and mitigating challenges of agricultural extension services among small-scale farmers in Asa local government area, Kwara state, Nigeria","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1829015","Agricultural extension services are essential for helping small-scale farmers in Nigeria increase productivity and promote sustainable farming; yet structural and institutional barriers limit their utilization. This study examined how small-scale farmers in Asa Local Government Area (LGA), Kwara State access agricultural extension services and the specific challenges they face. A mixed-methods design was employed, combining structured questionnaires administered to 120 randomly selected farmers with qualitative semi-structured interviews analyzed through thematic analysis. Descriptive statistics addressed the study objectives while a regression model tested the hypothesis on socioeconomic determinants of access. Utilization of extension services remains low despite their availability. Farmers rely predominantly on radio, television, and cooperatives for agricultural information. Advisory services and market information were most accessed, while training programs and workshops were least utilized. All reported outcomes, including improved market access and higher productivity, are farmer self-reports and represent perceived rather than objectively measured benefits. Inadequate funding, poor infrastructure, and limited training are the dominant barriers. Educational level and farm size significantly and positively predict access to extension services. Strengthening financial support, improving rural infrastructure, tailoring training programs, and reinforcing cooperative networks are critical for advancing sustainable agricultural development in rural Nigeria.","农业推广服务对于帮助尼日利亚小规模农户提高生产力、促进可持续农业至关重要，然而结构和制度性障碍限制了其利用。本研究考察了夸拉州阿萨地方政府区（LGA）小规模农户如何获取农业推广服务及其面临的具体挑战。研究采用混合方法设计，结合对120名随机抽取农户的结构化问卷调查，以及通过主题分析处理的定性半结构化访谈。描述性统计用于回应研究目标，回归模型用于检验关于获取服务的社会经济决定因素的假设。尽管推广服务存在，其利用率仍然较低。农户主要依赖广播、电视和合作社获取农业信息。咨询服务 and 市场信息获取最多，而培训项目和研讨会利用最少。所有报告的结果，包括市场准入改善和生产力提高，均为农户自我报告，代表感知而非客观测量的收益。资金不足、基础设施薄弱和培训有限是主要障碍。教育水平和农场规模显著且正向预测推广服务的获取。加强财政支持、改善农村基础设施、量身定制培训项目以及强化合作社网络，对于推进尼日利亚农村可持续农业发展至关重要。",null,"Frontiers in Sustainable Food Systems","2026-09-09T00:00:00Z","论文",10,false,62,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,18,14,13,9,1,"基于尼日利亚小农户调研的实证研究，揭示推广服务利用率低及教育水平、农场规模等影响因素，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，公共影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"合作社","小农户","农业推广","尼日利亚","农村信息化",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"G1","extension-transfer","农技推广与成果转化","\u002Ftopic\u002Frural-services\u002Fextension-transfer","G",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,59],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},15,true,[49],"agricultural extension",[29,49],[29],{"code":53,"score":54,"supported":47,"title":55,"abstract":56,"tags":58},"H8",3,[],[57],"可持续农业",[],{"code":60,"score":61,"supported":14,"title":62,"abstract":63,"tags":64},"G2",2,[],[],[27,28],[66,67],"农村信息化 农业推广 尼日利亚 合作社","农村信息化 农业推广","农村信息化农业推广尼日利亚合作社-2032","10.3389\u002Ffsufs.2026.1829015",{"doi":69,"openalex_id":71,"authors":72,"venue":10,"cited_by_count":79,"oa_url":6,"card":80,"direction":84,"ingested_from":86},"W7212064262",[73,75,77],{"name":74,"orcid":9},"Dolapo Tawakalitu",{"name":76,"orcid":9},"Egbewole Halimah",{"name":78,"orcid":9},"Adesokan Jamiu",0,{"tldr":81,"method":82,"finding":83,"direction":84,"opportunity":85},"研究尼日利亚小农户获取农业推广服务的现状、障碍及社会经济影响因素。","混合方法：120份问卷+半结构化访谈，描述统计与回归分析。","推广服务利用率低，主要靠广播和合作社；教育程度和农场规模显著正向预测获取。","数字乡村与农业信息化","可探索数字渠道（如手机、广播）替代传统推广，并针对低教育小农户设计适配服务。","openalex","2026-09-10T23:30:07.595776Z",{"total":89,"page":22,"page_size":89,"items":90},6,[91,169,227,282,335,425],{"id":92,"title":93,"url":94,"summary":95,"summary_zh":96,"content":9,"source_name":97,"source_url":94,"published_at":98,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":99,"score_detail":100,"sources":104,"tags":106,"primary_topic":109,"secondary_topics":110,"classification":115,"search_phrases":144,"slug":147,"view_count":54,"doi":148,"paper":149,"created_at":168},3154,"The Role of Agricultural Extension Services in Promoting Climate-Smart Agriculture Adoption among Smallholder Farmers in Mwingi West sub-county Kitui County, Kenya","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fajaees\u002F2026\u002Fv44i103022","Agricultural extension services provide smallholder farmers with knowledge, technical guidance, and advisory support that can facilitate the adoption of climate-smart agricultural (CSA) practices. This study examined the role of agricultural extension services in promoting CSA adoption among smallholder farmers in Mwingi West Sub-County, Kitui County, Kenya. A cross-sectional mixed-methods design was used. Quantitative data were collected from 200 randomly selected farmers through structured questionnaires, while qualitative evidence was obtained from 10 agricultural extension officers and 10 focus group discussions with farmer groups. Quantitative data were analysed using descriptive statistics and the chi-square test of independence. Significant associations were reported between CSA adoption and access to agricultural extension services, the source of extension information, type of extension support received, frequency of extension contact, perceived usefulness of extension services, CSA practices promoted through extension, and farmers’ perceived influence of extension services on adoption. Most respondents (82.0%) had access to extension services. Extension agents were the main information source (46.0%), and technical training was the most frequently reported support (38.0%). Conservation agriculture (30.0%), agroforestry (22.0%), and water harvesting (19.0%) were the leading practices promoted through extension activities. Nearly half of respondents (48.0%) reported that extension services had increased CSA adoption to a great extent. The findings indicate that accessible, practical, and regular extension support is closely associated with CSA adoption in the study area.","农业推广服务为小农户提供知识、技术指导和咨询服务，有助于促进气候智能型农业（CSA）实践的采纳。本研究考察了农业推广服务在促进肯尼亚基图伊县姆温吉西分区小农户采纳气候智能型农业实践中的作用。研究采用横断面混合方法设计。定量数据通过结构化问卷从200名随机抽取的农户中收集，定性证据则来自10名农业推广官员以及10次农户小组焦点小组讨论。定量数据采用描述性统计和卡方独立性检验进行分析。结果显示，气候智能型农业实践的采纳与以下因素存在显著关联：能否获得农业推广服务、推广信息来源、所获推广支持类型、推广接触频率、推广服务的感知有用性、通过推广所宣传的气候智能型农业实践，以及农户对推广服务在采纳过程中影响力的感知。大多数受访者（82.0%）能够获得推广服务。推广人员是主要的信息来源（46.0%），技术培训是最常报告的支持类型（38.0%）。通过推广活动宣传的主要实践包括保护性农业（30.0%）、农林业（22.0%）和雨水收集（19.0%）。近半数受访者（48.0%）表示推广服务在很大程度上提高了气候智能型农业实践的采纳率。研究结果表明，在研究区域内，可及、实用且定期的推广支持与气候智能型农业实践的采纳密切相关。","Asian Journal of Agricultural Extension Economics & Sociology","2026-09-22T00:00:00Z",65,{"impact":17,"substance":101,"depth":46,"authority":102,"freshness":13,"relevant":22,"comment":103},20,12,"基于肯尼亚小农户的实证研究，数据翔实但地域性强，对国内三农信息化参考价值有限，可作国际经验收录。",[105],{"name":97,"url":94},[107,28,108,29],"肯尼亚","气候智慧农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[111],{"code":60,"slug":112,"name":113,"path":114,"parent_code":37},"farm-services","社会化服务与规模经营","\u002Ftopic\u002Frural-services\u002Ffarm-services",{"status":40,"locked":14,"version":41,"method":42,"evidence":116},{"candidates":117,"agricultural_evidence":47},[118,123,128,134,139],{"code":33,"score":18,"supported":47,"title":119,"abstract":120,"tags":122},[49],[29,121,49],"技术培训",[29],{"code":60,"score":46,"supported":47,"title":124,"abstract":126,"tags":127},[125],"smallholder",[28,125],[28],{"code":129,"score":17,"supported":47,"title":130,"abstract":132,"tags":133},"I1",[131],"smart agriculture",[],[],{"code":53,"score":54,"supported":47,"title":135,"abstract":136,"tags":138},[],[137],"conservation agriculture",[],{"code":140,"score":22,"supported":14,"title":141,"abstract":142,"tags":143},"H7",[],[],[108],[145,146],"气候智慧农业 农业推广 小农户 肯尼亚","气候智慧农业 农业推广","气候智慧农业农业推广小农户肯尼亚-3154","10.9734\u002Fajaees\u002F2026\u002Fv44i103022",{"doi":148,"openalex_id":150,"authors":151,"venue":97,"cited_by_count":79,"oa_url":94,"card":162,"direction":167,"ingested_from":86},"W7213979623",[152,154,156,158,160],{"name":153,"orcid":9},"Simon Mbala",{"name":155,"orcid":9},"David Kawioo Mwanzia",{"name":157,"orcid":9},"Thomas Ekamais Akuja",{"name":159,"orcid":9},"Felix Ngunzo Kioli",{"name":161,"orcid":9},"Harrison Musyoka Maithya",{"tldr":163,"method":164,"finding":165,"direction":84,"opportunity":166},"研究肯尼亚小农户中农业推广服务对气候智慧型农业采纳的促进作用。","混合方法，200份农户问卷、10名推广员访谈和10组焦点小组，卡方检验。","推广服务可及性、信息源、支持类型和接触频率与CSA采纳显著相关，82%农户有推广服务。","可探索数字推广渠道（如手机短信、APP）如何替代或补充传统推广员，提升小农户CSA采纳率。","智慧农业 \u002F 农业物联网","2026-09-22T23:30:10.323072Z",{"id":170,"title":171,"url":172,"summary":173,"summary_zh":174,"content":9,"source_name":175,"source_url":172,"published_at":176,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":177,"sources":179,"tags":181,"primary_topic":186,"secondary_topics":187,"classification":194,"search_phrases":210,"slug":213,"view_count":79,"doi":214,"paper":215,"created_at":226},5078,"The Importance of Electronic Communication in the Use of Artificial Intelligence Programs and Applications in the Field of Smart Agriculture from the Point of View of Agricultural Extension Workers in Nineveh Governorate, Iraq","https:\u002F\u002Fdoi.org\u002F10.25125\u002Fijoear-oct-2026-3","The study aimed to identify the level of importance of electronic communication among agricultural extension workers in using artificial intelligence (AI) programs and applications in the field of smart agriculture. It also aimed to identify the most frequently used electronic communication means by extension workers in employing AI programs and applications and rank them according to their relative importance; measure the contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture; identify individual differences in the importance of electronic communication and the use of AI applications according to selected independent variables, namely gender, educational qualification, years of service, training courses, level of Internet use, and willingness to use social networking sites concerning smart-agriculture technologies; and identify the obstacles facing extension workers in using AI applications in smart agriculture. To obtain the study data, a questionnaire consisting of five parts was used. The first part concerned the respondents' personal and occupational information. The second part included a scale measuring the importance of electronic communication among extension workers in using AI programs and applications in smart agriculture. The third part measured the electronic communication means most frequently used by extension workers in employing AI programs and applications. The fourth part measured the contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture. The fifth part contained 15 items measuring the major obstacles facing extension workers in using AI applications in smart agriculture. After establishing the face validity of the questionnaire, reliability was assessed using Cronbach's alpha, which reached 0.95. The study population consisted of extension workers in the Nineveh Directorate of Agriculture and its 32 agricultural divisions, totaling 256 extension workers. A simple random sample of 128 extension workers, representing approximately 50% of the population, was selected. The data were coded, tabulated, and analyzed using SPSS. The results showed that the level of importance of electronic communication among extension workers in using AI programs and applications in smart agriculture was moderate and tended toward high, with a percentage of 48%. The item \"Using electronic platforms belonging to agricultural institutions to obtain information related to AI programs and applications\" ranked first, with a mean of 4.34. The contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture was high, with a percentage of 46%. No significant differences were found in the importance of electronic communication according to gender or training courses, whereas significant differences were reported according to educational qualification, years of occupational service, level of Internet use, and willingness to use social networking sites concerning smart-agriculture technologies. The item \"Poor compatibility of some AI applications with the nature and needs of agricultural extension work in Nineveh Governorate\" was identified as the most important obstacle. The major recommendation was for the Ministry of Agriculture to establish or develop official agricultural electronic platforms affiliated with agricultural and extension institutions and containing updated information on AI applications and their use in different agricultural fields. The main proposed future study was to investigate the obstacles to using AI applications in agricultural extension work in Nineveh Governorate from the perspective of extension workers.","本研究旨在确定农业推广人员在智慧农业领域使用人工智能（AI）程序和应用时电子沟通的重要程度，同时旨在确定推广人员在运用AI程序和应用时最常使用的电子沟通手段，并按其相对重要性进行排序；衡量电子沟通对提高推广人员在智慧农业中使用AI程序和应用效率的贡献；根据选定的自变量，即性别、学历、工龄、培训课程、互联网使用水平以及使用社交网站了解智慧农业技术的意愿，确定电子沟通重要性和AI应用使用方面的个体差异；并确定推广人员在智慧农业中使用AI应用所面临的障碍。为获取研究数据，使用了由五个部分组成的问卷。第一部分涉及受访者的个人和职业信息。第二部分包括一个测量推广人员在智慧农业中使用AI程序和应用时电子沟通重要性的量表。第三部分测量了推广人员在运用AI程序和应用时最常使用的电子沟通手段。第四部分测量了电子沟通对提高推广人员在智慧农业中使用AI程序和应用效率的贡献。第五部分包含15个题项，测量推广人员在智慧农业中使用AI应用面临的主要障碍。在确定问卷的表面效度后，使用克隆巴赫Alpha系数评估信度，达到0.95。研究总体为尼尼微农业局及其32个农业部门的推广人员，共计256名推广人员。采用简单随机抽样选取了128名推广人员，约占总体的50%。数据经编码、制表后使用SPSS进行分析。结果表明，推广人员在智慧农业中使用AI程序和应用时电子沟通的重要程度为中等且倾向于高，占比为48%。题项“使用电子","International Journal of Environmental and Agriculture Research","2026-10-15T00:00:00Z",{"impact":17,"substance":18,"depth":46,"authority":102,"freshness":21,"relevant":22,"comment":178},"伊拉克尼尼微省农业推广人员使用AI与电子通信的实证问卷研究，样本128人、信度0.95，结论与障碍分析具体，但属区域性研究，公共影响有限。",[180],{"name":175,"url":172},[182,183,29,184,185],"智慧农业","农业人工智能","伊拉克农业","电子通信",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[188],{"code":189,"slug":190,"name":191,"path":192,"parent_code":193},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":40,"locked":14,"version":41,"method":42,"evidence":195},{"candidates":196,"agricultural_evidence":47},[197,201,205],{"code":33,"score":46,"supported":47,"title":198,"abstract":199,"tags":200},[49],[29,49],[29],{"code":129,"score":46,"supported":47,"title":202,"abstract":203,"tags":204},[131],[182,131],[182],{"code":189,"score":102,"supported":47,"title":206,"abstract":208,"tags":209},[207],"artificial intelligence",[207],[183],[211,212],"尼尼微省 农业推广 人工智能","伊拉克 智慧农业 电子平台","尼尼微省农业推广人工智能-5078","10.25125\u002Fijoear-oct-2026-3",{"doi":214,"openalex_id":216,"authors":217,"venue":175,"cited_by_count":79,"oa_url":220,"card":221,"direction":167,"ingested_from":86},"W7222298248",[218],{"name":219,"orcid":9},"Luma Monther Adress","https:\u002F\u002Fijoear.com\u002Fassets\u002Farticles_menuscripts\u002Ffile\u002FIJOEAR-OCT-2026-3.pdf",{"tldr":222,"method":223,"finding":224,"direction":84,"opportunity":225},"调查伊拉克尼尼微省农业推广人员对电子通信在智慧农业AI应用中重要性的认知及障碍。","问卷量表+SPSS分析，128名推广人员样本，Cronbach's α=0.95","电子通信重要性处于中等偏高水平（48%），并识别出使用AI应用的主要障碍。","可延伸至发展中国家推广人员AI采纳行为与电子通信渠道的实证比较研究。","2026-10-16T23:30:08.170356Z",{"id":228,"title":229,"url":230,"summary":231,"summary_zh":9,"content":232,"source_name":233,"source_url":9,"published_at":234,"category":235,"cover_url":9,"hotness":13,"is_selected":14,"score":236,"score_detail":237,"sources":239,"tags":241,"primary_topic":246,"secondary_topics":252,"classification":254,"search_phrases":277,"slug":280,"view_count":22,"doi":9,"paper":9,"created_at":281},3585,"黑龙江省农业科学院、林业科学院组织科技特派员深入宾县永和乡鑫华泰蔬菜专业合作社——开展连续两日精准技术指导","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7689412538714292782\u002F","黑龙江省农业科学院浆果研究所专家率先进驻永和乡，围绕棚室科学通风调控、病虫害绿色防控、蜜蜂授粉技术引进应用等关键环节，结合当地种植实际开展细致讲解与现场示范。指导结束后，专家团队向合作社赠送果期叶面磷钾肥及辅助吸收药剂。黑龙江省林科院专家针对大棚作物栽培管理、良种选育、高效种植模式等内容实地察看作物生长态势。鑫华泰蔬菜专业合作社种植面积约1000亩，配套建成标准化冷棚种植区域，实现果蔬规模化、集约化、标准化种植，合作社以树莓规模化特色种植为主导，'合作社+农户'模式每月带动本地用工300人，人均日工资不低于150元。","## 宾县：科技下乡赋动能特色产业促振兴\n\n2026-09-25 18:08·[金台资讯](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAL8m7IqT5eR3-VgZjzlMhg66-z57FyRmydYIImMLAsQ4\u002F?source=tuwen_detail)\n\n宾县始终把科技助农作为推动农业提质增效、助力乡村振兴的重要抓手，持续对接优质科研资源，推动先进农业技术下沉基层。近日，黑龙江省农业科学院、黑龙江省林业科学院组织科技特派员深入永和乡鑫华泰蔬菜专业合作社，开展连续两日的精准技术指导服务，把科技良方送到田间地头，为当地特色农业发展注入强劲动力。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002Fa57bc233cdb34f5f87825084ea9f1c47~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1791072453&x-signature=prlpFcbKySZd4sl%2FR9ZnHt4EWIA%3D)\n永和乡依托本地土壤、气候资源优势，以特色种植为核心壮大乡村产业。鑫华泰蔬菜专业合作社种植面积约1000亩，配套建成标准化冷棚种植区域，实现果蔬规模化、集约化、标准化种植。合作社以树莓规模化特色种植为主导，因地制宜搭配种植毛豆、黏玉米、黑豆果等优质经济作物，构建起“主打特色、多元配套”的种植格局。通过推行“合作社+农户”的长效发展模式，合作社每月带动本地用工300人，人均日工资不低于150元，有效带动群众在家门口就业增收，让特色小浆果成长为富民兴村的重要产业。\n\n为破解产业发展中的技术瓶颈，助力产业提档升级，此次省农科院、省林科院专家团队按需送技、精准服务。黑龙江省农科院浆果研究所专家率先进驻永和乡，围绕棚室科学通风调控、病虫害绿色防控、蜜蜂授粉技术引进应用等关键环节，结合当地种植实际开展细致讲解与现场示范，把专业技术转化为通俗易懂的实操方法，切实提升种植户科学管理能力。指导结束后，专家团队还向合作社赠送果期叶面磷钾肥及辅助吸收药剂，以实际物资支持助力农户稳产增收。黑龙江省林科院专家接续深入永和乡大棚园区，针对大棚作物栽培管理、良种选育、高效种植模式等内容，实地察看作物生长态势，手把手指导农户规范操作，逐一解答生产过程中遇到的难点问题，推动先进种植技术落地见效。\n\n此次科技下乡服务精准对接永和乡农业生产实际需求，有效提升当地特色作物的坐果率与果实品质，为产业高质量发展筑牢科技支撑。下一步，宾县将持续深化与科研院所的合作对接，常态化开展科技助农活动，推动更多农业新技术、新成果扎根田间地头，以科技赋能农业产业升级，壮大乡村特色产业，为全县乡村全面振兴夯实产业根基。(王若冰 卢蕾)\n\n来源：宾县委宣传部","金台资讯（今日头条转载）2026-09-25","2026-09-25T00:00:00Z","报道",44,{"impact":17,"substance":102,"depth":13,"authority":89,"freshness":17,"relevant":22,"comment":238},"地方科技下乡服务报道，有具体作物与帮扶细节，但属常规宣传通稿，公共价值有限。",[240],{"name":233,"url":230},[27,242,243,244,245],"科技特派员","科技下乡","特色种植","树莓",{"code":247,"slug":248,"name":249,"path":250,"parent_code":251},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[253],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":255},{"candidates":256,"agricultural_evidence":47},[257,262,267,273],{"code":247,"score":258,"supported":47,"title":259,"abstract":260,"tags":261},11,[249],[249],[],{"code":33,"score":13,"supported":47,"title":263,"abstract":265,"tags":266},[264],"科技特派",[],[243,242],{"code":268,"score":54,"supported":47,"title":269,"abstract":270,"tags":272},"F4",[],[271],"绿色防控",[],{"code":60,"score":22,"supported":14,"title":274,"abstract":275,"tags":276},[],[],[27],[278,279],"黑龙江农科院 宾县 树莓","科技特派员 永和乡 蔬菜合作社","黑龙江农科院宾县树莓-3585","2026-09-27T00:05:16.049506Z",{"id":283,"title":284,"url":285,"summary":286,"summary_zh":287,"content":9,"source_name":288,"source_url":285,"published_at":234,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":289,"score_detail":290,"sources":292,"tags":294,"primary_topic":297,"secondary_topics":298,"classification":299,"search_phrases":315,"slug":318,"view_count":61,"doi":319,"paper":320,"created_at":334},3539,"Event Satisfaction Influence on Adoption Intentions for Climate-Smart Agriculture and Sustainability Perception","https:\u002F\u002Fdoi.org\u002F10.54536\u002Fajet.v5i3.8433","Understanding why individuals decide to adopt climate-smart agricultural (CSA) practices is important in agricultural extension. While extension programs are designed to increase knowledge, research evidence suggests that knowledge gains alone may not fully explain adoption intentions. This study examines how knowledge gain, satisfaction, and demographic characteristics influence adoption intention and sustainability perceptions of CSA practices among CSA field days participants in Maryland (N = 79). Post-event survey data were analyzed using the Wilcoxon signed-rank test, Spearman’s rank correlation, and hierarchical regression. Wilcoxon signed-rank test results show that participants experienced a significant increase in knowledge following the field day event (V = 1933, p \u003C 0.001). Analysis revealed that knowledge gain is a significant predictor of adoption but not a significant predictor of sustainability perception. Demographic variables (age, gender, and education) were not significant predictors of adoption intention and sustainability perception. Once satisfaction was included in the model, it emerged as the only determinant of adoption intention (β = .31, p = .013) and sustainability perception (β = 0.34, p = .008), and knowledge gain was no longer a significant predictor of adoption intention. Overall, the findings highlight a divergence between knowledge gain and intention to adopt and sustainability beliefs of CSA practices, emphasizing that event quality and participant satisfaction play a more important role. These results indicate that outcomes of extension activities depend not only on knowledge delivery but also on the quality of the learning experience.","理解个人为何决定采用气候智慧型农业(CSA)实践在农业推广中具有重要意义。尽管推广项目旨在增加知识，但研究证据表明，仅靠知识增长可能无法完全解释采用意愿。本研究考察了知识增长、满意度和人口统计学特征如何影响马里兰州CSA田间日活动参与者(N = 79)对CSA实践的采用意愿和可持续性认知。活动后调查数据采用Wilcoxon符号秩检验、Spearman秩相关和分层回归进行分析。Wilcoxon符号秩检验结果表明，参与者在田间日活动后知识显著增加(V = 1933，p \u003C 0.001)。分析显示，知识增长是采用的显著预测因子，但不是可持续性认知的显著预测因子。人口统计学变量(年龄、性别和教育程度)不是采用意愿和可持续性认知的显著预测因子。一旦将满意度纳入模型，它成为采用意愿(β = .31，p = .013)和可持续性认知(β = 0.34，p = .008)的唯一决定因素，而知识增长不再是采用意愿的显著预测因子。总体而言，研究结果凸显了知识增长与CSA实践的采用意愿及可持续性信念之间的背离，强调活动质量和参与者满意度发挥着更为重要的作用。这些结果表明，推广活动的成效不仅取决于知识传递，还取决于学习体验的质量。","American Journal of Education and Technology",61,{"impact":17,"substance":18,"depth":46,"authority":102,"freshness":17,"relevant":22,"comment":291},"小样本（N=79）实证研究，结论有新意——满意度而非知识增益决定采纳意愿，对农业推广活动设计有参考价值，但影响范围限于学术与推广领域。",[293],{"name":288,"url":285},[108,295,29,296],"农业教育","农户采纳意愿",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":300},{"candidates":301,"agricultural_evidence":47},[302,306,311],{"code":129,"score":17,"supported":47,"title":303,"abstract":304,"tags":305},[131],[],[],{"code":33,"score":307,"supported":47,"title":308,"abstract":309,"tags":310},7,[],[29,49],[29],{"code":140,"score":22,"supported":14,"title":312,"abstract":313,"tags":314},[],[],[108],[316,317],"农户采纳意愿 气候智慧农业 农业推广 农业教育","农户采纳意愿 气候智慧农业","农户采纳意愿气候智慧农业农业推广农业教育-3539","10.54536\u002Fajet.v5i3.8433",{"doi":319,"openalex_id":321,"authors":322,"venue":288,"cited_by_count":79,"oa_url":285,"card":329,"direction":167,"ingested_from":86},"W7214349044",[323,325,327],{"name":324,"orcid":9},"S. S. Thagunna",{"name":326,"orcid":9},"L. B. Karki",{"name":328,"orcid":9},"M. L. Diack",{"tldr":330,"method":331,"finding":332,"direction":84,"opportunity":333},"研究马里兰CSA田间日活动参与者的满意度如何影响其采用意愿与可持续性认知。","对79名参与者进行活动后问卷调查，用Wilcoxon符号秩检验、Spearman","满意度是采用意愿和可持续性感知的唯一显著预测因子，知识增益不再显著。","可探索将参与者满意度与体验质量指标嵌入农业推广数字化平台，以预测和提升技术采用率。","2026-09-26T23:30:09.835141Z",{"id":336,"title":337,"url":338,"summary":339,"summary_zh":340,"content":9,"source_name":10,"source_url":338,"published_at":341,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":342,"score_detail":343,"sources":345,"tags":347,"primary_topic":352,"secondary_topics":353,"classification":354,"search_phrases":398,"slug":401,"view_count":402,"doi":403,"paper":404,"created_at":424},3337,"A study on entertainment farm education television programs in rainfed areas of the North-Western Himalayas, India","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1908513","Introduction Entertainment–education (E–E) integrates educational messages with engaging narrative and entertainment formats and can complement conventional agricultural extension by improving the accessibility and practical salience of technical information. Evidence on farmer preferences for agricultural E–E television in rainfed Himalayan farming systems remains limited. Methods This study assessed farmers’ preferred agricultural technology themes, ranked selected agricultural television programs, and identified priority program contents among 150 television owning farmers in Reasi district, Jammu and Kashmir, India. Four Community Development blocks were randomly selected from the district’s 12 blocks, followed by random selection of Gram Panchayats, villages, and respondents. We collected data using a structured interview schedule and analyzed them descriptively using frequencies, percentages, and preference rankings. Results and discussion Methods of using insecticides and pesticides were the most preferred technology theme for E–E presentation (56.66%), followed by dairy production (25.33%), poultry production (10.66%), and soil-improvement techniques (7.33%). Krishi Darshan was the most preferred agricultural television program (72.66%), followed by agricultural and allied-sector programs on DD Kisan (18.00%) and Sadi Dharti Sade Lok (9.33%). Among program contents, insecticide and pesticide-use information ranked first (87.00%), followed by dairy guidance (79.00%), animal husbandry (75.00%), and monthly crop-management schedules (69.00%). The findings indicate a strong demand for practical, problem-oriented agricultural information and support the potential of E–E television as a complementary extension channel. From a sustainable food-systems perspective, future E–E programming should integrate integrated pest management, pesticide safety, soil health, climate resilience, and crop–livestock integration. Future research should test effects on knowledge, adoption, farm economics, and environmental outcomes using larger samples and experimental or longitudinal designs.","引言 娱乐—教育（Entertainment–Education，E–E）将教育信息与引人入胜的叙事和娱乐形式相结合，能够通过提升技术信息的可及性和实际针对性来补充传统农业推广。在喜马拉雅雨养农业系统中，关于农民对农业E–E电视偏好的证据仍然有限。方法 本研究评估了印度查谟和克什米尔雷阿西县150名拥有电视的农民所偏好的农业技术主题，对选定的农业电视节目进行了排序，并确定了优先节目内容。从该县12个区块中随机选取了4个社区发展区块，随后随机选取了村委会、村庄和受访者。我们使用结构化访谈表收集数据，并通过频数、百分比和偏好排序进行描述性分析。结果与讨论 杀虫剂和农药使用方法是最受偏好的E–E呈现技术主题（56.66%），其次是乳制品生产（25.33%）、家禽生产（10.66%）和土壤改良技术（7.33%）。Krishi Darshan是最受偏好的农业电视节目（72.66%），其次是DD Kisan上的农业及相关产业节目（18.00%）和Sadi Dharti Sade Lok（9.33%）。在节目内容中，杀虫剂和农药使用信息排名第一（87.00%），其次是乳制品指导（79.00%）、畜牧业（75.00%）和月度作物管理日程（69.00%）。研究结果表明，农民对实用、以问题为导向的农业信息有强烈需求，并支持E–E电视作为补充推广渠道的潜力。从可持续食物系统角度看，未来的E–E节目应整合病虫害综合治理、农药安全、土壤健康、气候韧性和农牧结合。未来研究应使用更大样本和实验或纵向设计，检验其对知识、采用、农场经济和环境结果的影响。","2026-09-23T00:00:00Z",63,{"impact":17,"substance":18,"depth":46,"authority":20,"freshness":21,"relevant":22,"comment":344},"基于印度雨养山区150户调查的农业娱乐教育电视偏好研究，数据具体、结论明确，对农业信息化推广渠道建设有参考价值，但属区域性小样本调查，影响范围有限。",[346],{"name":10,"url":338},[29,348,349,350,351],"病虫害防治","农业电视节目","农户偏好","雨养农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":355},{"candidates":356,"agricultural_evidence":47},[357,361,368,375,381,388,393],{"code":33,"score":307,"supported":47,"title":358,"abstract":359,"tags":360},[],[29,49],[29],{"code":362,"score":89,"supported":47,"title":363,"abstract":364,"tags":367},"C",[],[365,366],"畜牧","livestock",[],{"code":369,"score":89,"supported":47,"title":370,"abstract":371,"tags":374},"C3",[],[372,373],"家禽","poultry",[],{"code":268,"score":89,"supported":47,"title":376,"abstract":377,"tags":380},[],[378,379],"农药","pesticide",[],{"code":382,"score":89,"supported":47,"title":383,"abstract":384,"tags":387},"H2",[],[385,386],"土壤","soil",[],{"code":140,"score":54,"supported":47,"title":389,"abstract":390,"tags":392},[],[391],"climate resilience",[],{"code":394,"score":22,"supported":14,"title":395,"abstract":396,"tags":397},"H3",[],[],[351],[399,400],"Reasi 农户 农业电视节目","Krishi Darshan 农业推广","Reasi农户农业电视节目-3337",4,"10.3389\u002Ffsufs.2026.1908513",{"doi":403,"openalex_id":405,"authors":406,"venue":10,"cited_by_count":79,"oa_url":338,"card":419,"direction":84,"ingested_from":86},"W7214095281",[407,409,412,414,417],{"name":408,"orcid":9},"Banarsi Lal",{"name":410,"orcid":411},"Parvender Sheoran","https:\u002F\u002Forcid.org\u002F0000-0002-0929-6261",{"name":413,"orcid":9},"Amit Singh Charak",{"name":415,"orcid":416},"Jasbir Singh Manhas","https:\u002F\u002Forcid.org\u002F0000-0002-6474-7176",{"name":418,"orcid":9},"Suja N. Qureshi",{"tldr":420,"method":421,"finding":422,"direction":84,"opportunity":423},"调查印度西北喜马拉雅雨养区农民对农业教育电视节目的偏好与内容需求。","对150户有电视农户结构化访谈，用频数、百分比和偏好排序描述分析。","农民最偏好农药使用主题和Krishi Darshan节目，需求偏向实用问题导向信息。","可实验检验教育娱乐电视对知识、采纳、农场经济与环境结果的影响，并拓展至IPM与气候韧性内容。","2026-09-24T23:30:07.503435Z",{"id":426,"title":427,"url":428,"summary":429,"summary_zh":430,"content":9,"source_name":431,"source_url":428,"published_at":432,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":433,"score_detail":434,"sources":438,"tags":440,"primary_topic":443,"secondary_topics":444,"classification":447,"search_phrases":465,"slug":468,"view_count":61,"doi":469,"paper":470,"created_at":486},1747,"Artificial Intelligence and Large Language Models in Agricultural Extension: Critical Synthesis of Adoption, Efficacy, and Equity in Smallholder Advisory Systems","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fair\u002F2026\u002Fv27i51723","Agricultural extension and advisory services are undergoing a rapid digital transformation driven by artificial intelligence (AI), machine learning, natural language processing, and, more recently, generative artificial intelligence and large language models (LLMs). These technologies have the potential to address persistent constraints in conventional agricultural extension, including limited adviser-to-farmer ratios, geographical isolation, inadequate localisation of information, and delays in the dissemination of climate, market, and agronomic information. LLM-based advisory systems are particularly significant because they can transform complex agricultural knowledge into conversational, multilingual, and potentially personalised guidance. However, their technical capability does not automatically translate into effective or equitable agricultural outcomes. This review synthesises emerging evidence on the adoption, efficacy, scalability, and equity implications of AI and LLM-based agricultural advisory systems, with particular emphasis on smallholder farmers in low- and middle-income countries. The literature indicates that AI-enabled advisory systems can improve access to timely information, facilitate question-answering, support crop and pest management, and extend the reach of human extension personnel. Emerging platforms such as Farmer.Chat demonstrate the feasibility of large-scale generative AI-enabled advisory delivery, while recent experiments with retrieval-augmented generation indicate promising pathways for improving factual grounding and contextual relevance. Nevertheless, evidence of direct impacts on farm productivity, profitability, resilience, and sustained behavioural change remains considerably weaker than evidence of technological feasibility and user engagement. Major limitations include hallucination, outdated or geographically inappropriate information, language and dialect constraints, weak interoperability with local agricultural databases, limited transparency, data governance concerns, and overreliance on automated recommendations. Equity is an equally important concern because digital access, literacy, gender, income, connectivity, and social norms influence who can benefit from AI-enabled services. The review argues that LLMs should therefore be positioned as augmentation technologies within pluralistic extension systems rather than as substitutes for human advisers. Future agricultural AI systems should combine retrieval from authoritative local knowledge bases, multimodal and multilingual interfaces, human oversight, participatory design, continuous evaluation, responsible data governance, and explicit equity metrics. The future value of AI in agricultural extension will ultimately depend not on model sophistication alone but on the quality of the socio-technical systems in which these technologies are embedded.","农业推广与咨询服务正在经历一场由人工智能（AI）、机器学习、自然语言处理以及近年来兴起的生成式人工智能和大语言模型（LLMs）驱动的快速数字化转型。这些技术有望解决传统农业推广中长期存在的制约因素，包括推广人员与农民比例有限、地理隔离、信息本地化不足，以及气候、市场和农艺信息传播的延迟。基于大语言模型的咨询系统尤为重要，因为它们能够将复杂的农业知识转化为对话式、多语言且可能实现个性化的指导。然而，其技术能力并不会自动转化为有效或公平的农业成果。本综述综合了关于基于AI和大语言模型的农业咨询系统在采用、有效性、可扩展性和公平性影响方面的新兴证据，特别关注低收入和中等收入国家的小农户。文献表明，AI赋能的咨询系统能够改善及时信息的获取，促进问答交互，支持作物与病虫害管理，并扩展人工推广人员的服务范围。诸如Farmer.Chat等新兴平台展示了大规模生成式AI赋能咨询服务的可行性，而近期关于检索增强生成的实验则表明，在改善事实依据和情境相关性方面存在有前景的路径。尽管如此，关于对农业生产率、盈利能力、韧性及持续性行为改变产生直接影响的证据，仍明显弱于关于技术可行性和用户参与度的证据。主要局限包括幻觉现象、信息过时或地理上不适用、语言和方言限制、与当地农业数据库的互操作性薄弱、透明度有限、数据治理问题，以及对自动化建议的过度依赖。公平性同样是一个重要关切，因为数字接入、素养、性别、收入、连通性和社会规范都会影响谁能够从AI赋能的服务中受益。本综述认为，大语言模型应被定位为多元推广体系中的增强技术，而非人类推广人员的替代品。未来的农业AI系统应将检索增强生成与结构化农业知识图谱、","Advances in Research","2026-09-04T00:00:00Z",82,{"impact":435,"substance":435,"depth":101,"authority":20,"freshness":436,"relevant":22,"comment":437},22,5,"系统综述AI与LLM在农技推广中的应用、效能与公平性，对智慧农业实践有重要参考价值。",[439],{"name":431,"url":428},[183,441,28,442],"大语言模型","农技推广",{"code":189,"slug":190,"name":191,"path":192,"parent_code":193},[445,446],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"code":60,"slug":112,"name":113,"path":114,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":448},{"candidates":449,"agricultural_evidence":47},[450,457,461],{"code":189,"score":451,"supported":47,"title":452,"abstract":453,"tags":456},19,[207],[454,455,207],"机器学习","machine learning",[183,441],{"code":33,"score":46,"supported":47,"title":458,"abstract":459,"tags":460},[49],[29,49],[442],{"code":60,"score":46,"supported":47,"title":462,"abstract":463,"tags":464},[125],[28,125],[28],[466,467],"农业人工智能 大语言模型 农技推广 小农户","农业人工智能 大语言模型","农业人工智能大语言模型农技推广小农户-1747","10.9734\u002Fair\u002F2026\u002Fv27i51723",{"doi":469,"openalex_id":471,"authors":472,"venue":431,"cited_by_count":79,"oa_url":428,"card":480,"direction":84,"ingested_from":86},"W7208785535",[473,476,478],{"name":474,"orcid":475},"Swati Sucharita","https:\u002F\u002Forcid.org\u002F0000-0003-3409-3295",{"name":477,"orcid":9},"Pratima Sachan",{"name":479,"orcid":9},"T. Sravan Kumar",{"tldr":481,"method":482,"finding":483,"direction":484,"opportunity":485},"综述AI与LLM在农业推广中的应用，评估其采纳、效果与公平性，尤其关注小农户。","系统综述新兴证据，分析AI\u002FLLM咨询系统的采用、效能、可扩展性及公平性。","AI可提升信息获取，但生产力影响证据弱，存在幻觉、公平性等问题，应作为增强而非替代。","农业人工智能与决策模型","研究空白：LLM在农业推广中的实际生产力影响与公平性机制，以及如何结合本地数据与人类顾问实现增强。","2026-09-05T23:30:36.654266Z"]