[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2127":3,"related-2127":106},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":82,"slug":85,"view_count":86,"doi":87,"paper":88,"created_at":105},2127,"Beyond digital access: how does digital information complement agricultural production services to promote green technology adoption? Micro-evidence from Jiangxi Province, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1916148","In the context of agricultural green transformation, whether digital information can move beyond information provision and promote smallholders’ adoption of green technologies through complementarity with agricultural production services is an important theoretical and practical question. Using survey data from 1,040 rice-farming households in Jiangxi Province, China, this study constructs indicators of digital information, agricultural production services, and the number of core green technologies adopted. A Poisson pseudo-maximum likelihood (PPML) model is used to estimate their individual and interactive effects, supplemented by marginal-effect analysis, a supermodularity test, robustness checks, endogeneity analyses, mechanism tests, and heterogeneity analyses. The results show that (1) both digital information and agricultural production services significantly promote the adoption of core green technologies. In the full model, their coefficients are 0.329 and 0.330, respectively, while the interaction coefficient is 0.702 and significant at the 5% level. (2) Further tests confirm that the marginal effect of agricultural production services increases with the level of digital information, the average cross-partial effect is significantly positive, and the predicted adoption count is highest under the high-digital-information and high-production-services scenario. The supermodularity difference is 0.132, providing further evidence of complementarity. (3) The main findings remain robust to alternative dependent variables, model specifications, sample adjustments, and the use of double machine learning, instrumental variables, and entropy balancing. (4) Mechanism analyses suggest that complementarity promotes green technology adoption by easing labor constraints and improving farmers’ awareness of green policies. (5) Within-group estimates further indicate that the effect is more pronounced among farmers who own agricultural machinery, live in villages with better transportation conditions, and operate larger rice-farming areas. Overall, digital information does not simply substitute for agricultural production services; rather, it strengthens their conversion into actual green technology adoption. These findings support closer integration between digital information platforms and agricultural service systems.","在农业绿色转型背景下，数字信息能否超越信息供给功能，通过与农业生产性服务的互补性促进小农户采纳绿色技术，是一个重要的理论与实践问题。本研究基于中国江西省1040户水稻种植农户的调查数据，构建了数字信息、农业生产性服务与核心绿色技术采纳数量的指标，采用泊松伪最大似然（PPML）模型估计其个体效应与交互效应，并辅以边际效应分析、超模性检验、稳健性检验、内生性分析、机制检验和异质性分析。结果表明：（1）数字信息与农业生产性服务均显著促进核心绿色技术采纳，在全模型中二者系数分别为0.329和0.330，交互项系数为0.702，且在5%水平上显著。（2）进一步检验证实，农业生产性服务的边际效应随数字信息水平提高而增大，平均交叉偏效应显著为正，高数字信息与高生产性服务情景下预测采纳数量最高，超模性差异为0.132，进一步佐证了互补性。（3）主要结论在替换因变量、模型设定、样本调整以及使用双重机器学习、工具变量和熵平衡等方法后依然稳健。（4）机制分析表明，互补性通过缓解劳动力约束和提高农户对绿色政策的认知来促进绿色技术采纳。（5）分组估计进一步显示，该效应在拥有农业机械、所在村庄交通条件较好以及水稻种植面积较大的农户中更为明显。总体而言，数字信息并非简单替代农业生产性服务，而是强化了其向实际绿色技术采纳的转化。上述发现支持数字信息平台与农业服务体系之间更紧密的融合。",null,"Frontiers in Sustainable Food Systems","2026-09-10T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,13,9,1,"基于江西1040户稻农微观调查，实证揭示数字信息与农业生产服务的互补效应，方法规范、结论可靠，对数字乡村与绿色转型政策有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"数字乡村","农业信息化","绿色技术采纳","农业社会化服务","水稻种植",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"A1","rice","水稻","\u002Ftopic\u002Ffield-crops\u002Frice","A",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,50,58,65,72,77],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":49},7,true,[],[34,33],[30],{"code":51,"score":52,"supported":46,"title":53,"abstract":54,"tags":57},"F5",6,[],[55,56],"农业机械","agricultural machinery",[],{"code":59,"score":52,"supported":46,"title":60,"abstract":61,"tags":64},"I2",[],[62,63],"机器学习","machine learning",[],{"code":66,"score":67,"supported":46,"title":68,"abstract":69,"tags":71},"G2",4,[],[70],"小农户",[29],{"code":73,"score":21,"supported":14,"title":74,"abstract":75,"tags":76},"I1",[],[],[27],{"code":78,"score":21,"supported":14,"title":79,"abstract":80,"tags":81},"I6",[],[],[26],[83,84],"农业社会化服务 绿色技术采纳 农业信息化 数字乡村","农业社会化服务 绿色技术采纳","农业社会化服务绿色技术采纳农业信息化数字乡村-2127",2,"10.3389\u002Ffsufs.2026.1916148",{"doi":87,"openalex_id":89,"authors":90,"venue":10,"cited_by_count":97,"oa_url":6,"card":98,"direction":102,"ingested_from":104},"W7212107776",[91,93,95],{"name":92,"orcid":9},"Yanqiu Tong",{"name":94,"orcid":9},"Zaiwei Yang",{"name":96,"orcid":9},"Zhaojiu Chen",0,{"tldr":99,"method":100,"finding":101,"direction":102,"opportunity":103},"基于江西1040户稻农数据，检验数字信息与农业生产服务对绿色技术采用的互补效应。","PPML模型、边际效应、超模性检验、工具变量与双重机器学习。","数字信息与生产服务显著互补，通过缓解劳动约束和提升政策认知促进绿色技术采用。","农业绿色发展与碳","可探究数字平台与服务系统协同的机制设计，及不同作物和区域的异质性推广路径。","openalex","2026-09-11T23:30:07.699262Z",{"total":52,"page":21,"page_size":52,"items":107},[108,166,241,313,378,450],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":9,"content":9,"source_name":113,"source_url":111,"published_at":114,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":115,"score_detail":116,"sources":120,"tags":122,"primary_topic":126,"secondary_topics":127,"classification":133,"search_phrases":150,"slug":153,"view_count":86,"doi":154,"paper":155,"created_at":165},3879,"Utilization and Effects of Farm Management Data and Smart Agricultural Machinery on Labor Time in Large-Scale Paddy Farming","https:\u002F\u002Fdoi.org\u002F10.3173\u002Fair.35.123","Utilization and Effects of Farm Management Data and Smart Agricultural Machinery on Labor Time in Large-Scale Paddy Farming。Agricultural Information Research","Agricultural Information Research","2026-09-30T00:00:00Z",68,{"impact":117,"substance":17,"depth":118,"authority":19,"freshness":20,"relevant":21,"comment":119},12,16,"核心期刊论文，聚焦大规模水稻种植中农场管理数据与智能农机对劳动时间的影响，方法数据扎实但属细分领域研究，公共影响有限。",[121],{"name":113,"url":111},[123,27,30,124,125],"智慧农业","农机作业","农场管理数据",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[128],{"code":51,"slug":129,"name":130,"path":131,"parent_code":132},"machinery","农机装备与机械化","\u002Ftopic\u002Finputs-equipment\u002Fmachinery","F",{"status":39,"locked":14,"version":40,"method":41,"evidence":134},{"candidates":135,"agricultural_evidence":46},[136,141,146],{"code":32,"score":117,"supported":46,"title":137,"abstract":139,"tags":140},[138],"paddy",[138],[30],{"code":51,"score":142,"supported":46,"title":143,"abstract":144,"tags":145},11,[56],[56],[],{"code":73,"score":86,"supported":14,"title":147,"abstract":148,"tags":149},[],[],[27,123],[151,152],"Agricultural Information Research 水稻 智能农机","农场管理数据 农业信息化 农机作业 智慧农业","AgriculturalInformationResearch水稻智能农机-3879","10.3173\u002Fair.35.123",{"doi":154,"openalex_id":156,"authors":157,"venue":113,"cited_by_count":97,"oa_url":111,"card":9,"direction":164,"ingested_from":104},"W7214913919",[158,160,162],{"name":159,"orcid":9},"Yukari SHIMIZU",{"name":161,"orcid":9},"Tetsuya Ishikawa",{"name":163,"orcid":9},"Satoshi Yoshinaga","智慧农业 \u002F 农业物联网","2026-10-01T23:30:09.347033Z",{"id":167,"title":168,"url":169,"summary":170,"summary_zh":9,"content":9,"source_name":171,"source_url":169,"published_at":172,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":173,"score_detail":174,"sources":177,"tags":179,"primary_topic":182,"secondary_topics":183,"classification":196,"search_phrases":217,"slug":220,"view_count":86,"doi":221,"paper":222,"created_at":240},3500,"Remote sensing-driven soil fertility modelling and summer rice suitability mapping in a floodplain agroecosystem of Assam","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10333-026-01102-6","Remote sensing-driven soil fertility modelling and summer rice suitability mapping in a floodplain agroecosystem of Assam。Paddy and Water Environment","Paddy and Water Environment","2026-09-24T00:00:00Z",67,{"impact":117,"substance":17,"depth":118,"authority":19,"freshness":175,"relevant":21,"comment":176},8,"核心期刊论文，遥感驱动土壤肥力建模与水稻适宜性制图，方法有参考价值但属区域案例，未达每日精选门槛。",[178],{"name":171,"url":169},[123,27,180,181,30],"遥感","土壤肥力",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[184,190],{"code":185,"slug":186,"name":187,"path":188,"parent_code":189},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"code":191,"slug":192,"name":193,"path":194,"parent_code":195},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",{"status":39,"locked":14,"version":40,"method":41,"evidence":197},{"candidates":198,"agricultural_evidence":46},[199,204,208,213],{"code":32,"score":200,"supported":46,"title":201,"abstract":202,"tags":203},15,[33],[33,138],[30],{"code":185,"score":117,"supported":46,"title":205,"abstract":206,"tags":207},[186],[186],[181],{"code":191,"score":117,"supported":46,"title":209,"abstract":211,"tags":212},[210],"remote sensing",[210],[180],{"code":73,"score":86,"supported":14,"title":214,"abstract":215,"tags":216},[],[],[27,123],[218,219],"Assam 洪泛平原 水稻 遥感","土壤肥力 遥感 建模","Assam洪泛平原水稻遥感-3500","10.1007\u002Fs10333-026-01102-6",{"doi":221,"openalex_id":223,"authors":224,"venue":171,"cited_by_count":97,"oa_url":9,"card":9,"direction":239,"ingested_from":104},"W7214202229",[225,227,230,232,235,237],{"name":226,"orcid":9},"Pompy Deka",{"name":228,"orcid":229},"Jwngsar Moshahary","https:\u002F\u002Forcid.org\u002F0000-0002-3409-6691",{"name":231,"orcid":9},"Mrinal Choudhury",{"name":233,"orcid":234},"Perves Ahmed","https:\u002F\u002Forcid.org\u002F0000-0002-2114-1043",{"name":236,"orcid":9},"Britan Rahman",{"name":238,"orcid":9},"Ranjit Sarma","农业遥感与作物表型","2026-09-25T23:30:30.923946Z",{"id":242,"title":243,"url":244,"summary":245,"summary_zh":9,"content":246,"source_name":247,"source_url":9,"published_at":248,"category":249,"cover_url":9,"hotness":13,"is_selected":14,"score":250,"score_detail":251,"sources":254,"tags":256,"primary_topic":259,"secondary_topics":264,"classification":266,"search_phrases":307,"slug":310,"view_count":311,"doi":9,"paper":9,"created_at":312},3221,"湖南杂交水稻研究中心授予屈原管理区\"全域水稻单产提升合作示范单位\"——科技兴农 数智赋能单产提升 2025年双季稻亩产提升40.9%","https:\u002F\u002Fyy.rednet.cn\u002Fcontent\u002F646043\u002F65\u002F16299864.html","9-21 红网岳阳站报道：9-21 屈原管理区2026年\"科技兴农提单产 和美屈原庆丰年\"中国农民丰收节在凤凰乡河泊潭村启幕。湖南省农业科学院党委委员、湖南杂交水稻研究中心党委书记许靖波授予屈原管理区\"全域水稻单产提升合作示范单位\"。湖南杂交水稻研究中心副研究员魏中伟向大户们讲解自序机抛秧的门道；区农业农村局农艺师王有成讲起秋粮\"一喷多促\"。现场播放的《数智农业赋能单产提升》短片将数字农田、智慧管护的鲜活现场直观呈现眼前。朝阳农机专业合作社负责人曹勇表示，\"以前种田靠经验、靠天吃饭，现在靠数据、靠科技。十个人，能管上千亩地。\" 2025年双季稻平均亩产1104.7公斤，较行动前的2022年亩产提升320.7公斤、增长40.9%，2026年早稻单产562.9公斤，较行动前提升44.7%。今年来，全区农户金融授信额度近9亿元，覆盖农户90%以上。","**红网时刻新闻9月21日岳阳讯**（记者 赵曼 通讯员 姜瑶 周洋 何宇）9月21日，岳阳市屈原管理区凤凰乡河泊潭村的田埂上，植保无人机腾空而起，掠过稻浪均匀播撒；一旁的水稻自序机抛秧展示基地前，种粮大户们俯身细看稻穗，听得仔细。当天，屈原管理区2026年“科技兴农提单产、和美屈原庆丰年”中国农民丰收节在此启幕——比起庆典，田里“晒”出的种田新变化，更抢眼。\n\n![Image 1](https:\u002F\u002Fpic-public.rednet.cn\u002Fbucketmam-1254231242\u002F6ab0d97fe4b062ff7a3eeaec.png)\n\n9月21日，屈原管理区2026年“科技兴农提单产、和美屈原庆丰年”中国农民丰收节现场。\n\n这场“变化”，有了省级支撑。活动现场，湖南省农业科学院授予屈原管理区“全域水稻单产提升合作示范单位”，屈原的水稻单产提升，从此将有省级科研力量持续加持；金融护航同步到位，今年来，全区农户金融授信额度近9亿元，覆盖农户90%以上。\n\n![Image 2](https:\u002F\u002Fpic-public.rednet.cn\u002Fbucketmam-1254231242\u002F6ab0da3be4b01c9c05d1361c.png)\n\n授牌仪式上，湖南省农业科学院党委委员、湖南杂交水稻研究中心党委书记许靖波湖授予屈原管理区“全域水稻单产提升合作示范单位”。\n\n田垄，是这堂“科技课”的第一教室。“这秧抛下去，根系扎得深、分蘖快，比传统机插省时又省工。”湖南杂交水稻研究中心副研究员魏中伟站在田埂边，向大户们讲解自序机抛秧的门道。区农业农村局农艺师王有成接过话头，讲起秋粮“一喷多促”：一次喷施，促壮苗、促灌浆、促成熟，还能防病虫害——一次下地，多重效果。\n\n成果展示区里，手摇风车、老式谷耙与插秧机、植保无人机同台陈列，不禁引人发问，数智农业，究竟给田埂一线带来了什么？\n\n朝阳农机专业合作社曹勇的账本最直观：“以前种田靠经验、靠天吃饭，现在靠数据、靠科技。”从播种到田管、从植保到收割，全程有数字化、机械化的“帮手”——十个人，能管上千亩地。用工省了，成本降了，稻谷的产量和品质反而上去了。\n\n![Image 3](https:\u002F\u002Fpic-public.rednet.cn\u002Fbucketmam-1254231242\u002F6ab0d98ae4b00ae231e4a5b0.png)\n\n9月21日丰收节现场，植保无人机在稻田上空喷洒农药。\n\n更深的变化，藏在数据里：2025年双季稻平均亩产1104.7公斤，较行动前的2022年亩产提升320.7公斤、增长40.9%，2026年早稻单产562.9公斤，较行动前提升44.7%。\n\n丰收的“后勤”也在场：屈原农文旅精品线路现场发布；政策咨询台前，粮食生产补贴、农机购置补贴、农业保险等惠农政策，被宣讲团“翻译”成大白话，宣传手册发了一摞又一摞；电商专区里，群众扫码下单，丰收的果实从田头“飞”进千家万户。","湖南红网","2026-09-21T00:00:00Z","报道",72,{"impact":17,"substance":252,"depth":200,"authority":13,"freshness":20,"relevant":21,"comment":253},20,"省级科研机构授牌叠加双季稻亩产提升40.9%的实测数据，属智慧农业与单产提升的实质性进展，具备精选价值。",[255],{"name":247,"url":244},[26,123,257,258,29],"种业振兴","水稻单产提升",{"code":260,"slug":261,"name":262,"path":263,"parent_code":36},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security",[265],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":267},{"candidates":268,"agricultural_evidence":46},[269,274,278,284,290,295,299,303],{"code":260,"score":117,"supported":46,"title":270,"abstract":272,"tags":273},[271],"单产提升",[271],[258],{"code":32,"score":142,"supported":46,"title":275,"abstract":276,"tags":277},[34],[34],[],{"code":51,"score":279,"supported":46,"title":280,"abstract":281,"tags":283},3,[],[282],"农机",[],{"code":285,"score":279,"supported":46,"title":286,"abstract":287,"tags":289},"J4",[],[288],"丰收节",[],{"code":291,"score":21,"supported":14,"title":292,"abstract":293,"tags":294},"F1",[],[],[257],{"code":66,"score":21,"supported":14,"title":296,"abstract":297,"tags":298},[],[],[29],{"code":73,"score":21,"supported":14,"title":300,"abstract":301,"tags":302},[],[],[123],{"code":78,"score":21,"supported":14,"title":304,"abstract":305,"tags":306},[],[],[26],[308,309],"屈原管理区 水稻单产提升","湖南杂交水稻研究中心 示范单位","屈原管理区水稻单产提升-3221",5,"2026-09-23T00:04:29.645046Z",{"id":314,"title":315,"url":316,"summary":317,"summary_zh":318,"content":9,"source_name":319,"source_url":316,"published_at":320,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":321,"score_detail":322,"sources":324,"tags":326,"primary_topic":329,"secondary_topics":330,"classification":331,"search_phrases":360,"slug":363,"view_count":86,"doi":364,"paper":365,"created_at":377},1538,"Determinants of Farm Record Keeping Among Rice Farmers in Northern Ghana","https:\u002F\u002Fdoi.org\u002F10.14738\u002Fassrj.1308.12006","Farm record keeping is essential for agricultural business success, yet adoption remains low in many developing countries. This study investigates the determinants of farm record keeping among rice farmers in Northern Ghana, a region that contributes significantly to national rice production. Using a mixed-methods approach, data were collected from 245 rice farmers across three districts (Tolon, Kumbungu, and Savelugu) through questionnaires and focus group discussions. The study employed a binary probit model to identify factors influencing farmers’ decisions to keep records. Results revealed that only 11% of respondents maintained farm records. Educational level, household size, and knowledge of farm accounting records significantly influenced record keeping decisions. Farmers cited lack of knowledge on how to keep records and uncertainty about their usefulness as major barriers. Most records maintained by farmers were rudimentary and insufficient for generating meaningful financial statements. The study recommends targeted educational interventions and simplified record-keeping systems tailored to farmers’ literacy levels. Government agencies and agricultural extension services should incorporate basic farm accounting training in their support programmes to enhance record-keeping practices among rice farmers, thereby improving farm management and profitability.","农场记录对于农业经营的成功至关重要，然而在许多发展中国家，其采用率仍然较低。本研究探讨了加纳北部水稻种植户农场记录行为的影响因素，该地区对全国水稻生产贡献显著。采用混合研究方法，通过问卷调查和焦点小组讨论，从三个地区（托隆、昆本古和萨韦卢古）的245名水稻种植户中收集了数据。研究运用二元Probit模型识别影响农户记录决策的因素。结果显示，仅有11%的受访者保持农场记录。教育水平、家庭规模和农场会计记录知识显著影响记录决策。农户将缺乏记录知识及对其用途的不确定性列为主要障碍。农户所保存的大多数记录较为简陋，不足以生成有意义的财务报表。研究建议开展有针对性的教育干预，并简化记录系统以适应农户的文化水平。政府机构和农业推广服务应在其支持计划中纳入基础农场会计培训，以增强水稻种植户的记录实践，进而改善农场管理并提高盈利能力。","Advances in Social Sciences Research Journal","2026-09-02T00:00:00Z",53,{"impact":175,"substance":17,"depth":200,"authority":13,"freshness":86,"relevant":21,"comment":323},"研究加纳水稻农户记录行为，虽地域性强，但为农业信息化推广提供实证参考。",[325],{"name":319,"url":316},[27,327,328,30],"非洲农业","农场记录",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":332},{"candidates":333,"agricultural_evidence":46},[334,338,345,351,355],{"code":32,"score":200,"supported":46,"title":335,"abstract":336,"tags":337},[33],[34,33],[30],{"code":339,"score":52,"supported":46,"title":340,"abstract":341,"tags":344},"G1",[],[342,343],"农业推广","agricultural extension",[],{"code":346,"score":279,"supported":46,"title":347,"abstract":348,"tags":350},"I7",[],[349],"研究方法",[],{"code":73,"score":21,"supported":14,"title":352,"abstract":353,"tags":354},[],[],[27],{"code":356,"score":21,"supported":14,"title":357,"abstract":358,"tags":359},"J3",[],[],[327],[361,362],"农业信息化 农场记录 水稻种植 非洲农业","农业信息化 农场记录","农业信息化农场记录水稻种植非洲农业-1538","10.14738\u002Fassrj.1308.12006",{"doi":364,"openalex_id":366,"authors":367,"venue":319,"cited_by_count":97,"oa_url":316,"card":370,"direction":376,"ingested_from":104},"W7206159908",[368],{"name":369,"orcid":9},"Ibrahim Alhassan",{"tldr":371,"method":372,"finding":373,"direction":374,"opportunity":375},"研究加纳北部水稻农户记账行为的影响因素，发现仅11%农户记账，教育水平等是关键。","混合方法，对245名农户问卷和焦点小组，用二元Probit模型分析。","教育水平、家庭规模和会计知识显著影响记账，主要障碍是缺乏知识和觉得无用。","数字乡村与农业信息化","可开发针对低识字率农户的简化记账工具或培训，结合移动应用提升记账率，并探索其与农业决策支持系统的结合。","农业人工智能与决策模型","2026-09-03T23:30:56.224189Z",{"id":379,"title":380,"url":381,"summary":382,"summary_zh":383,"content":9,"source_name":384,"source_url":381,"published_at":385,"category":12,"cover_url":9,"hotness":386,"is_selected":14,"score":387,"score_detail":388,"sources":392,"tags":397,"primary_topic":401,"secondary_topics":402,"classification":403,"search_phrases":431,"slug":434,"view_count":97,"doi":435,"paper":436,"created_at":449},5247,"From transfers to transformation: mobile money and the modernization of rice farming in Côte d’Ivoire","https:\u002F\u002Fdoi.org\u002F10.6084\u002Fm9.figshare.34660410","In this study, we explore how Mobile Money (MM) adoption influences farm management choices of smallholder rice production in Côte d’Ivoire, a West African context characterised by rich agricultural potential and moderately low digital financial inclusion. Using an endogenous switching regression (ESR) framework to a sample of 1,370 smallholder producers from three rice-producing departments and complemented by an inverse probability weighted regression adjustment (IPWRA) estimator for robustness to estimate the impact of MM on both agricultural intensification (higher fertilizer use), extensification (greater expansion of cultivated areas for food and cash crops outside rice farming system), total rice productivity and better market participation. There is evidence to suggest that remittances may be a plausible channel through which these effects work, by alleviating liquidity constraints, thus allowing clients to invest seasonally in inputs and labor. Our findings extend the mobile money literature, which remains concentrated in East Africa, by providing new evidence from an under-explored West African context, and offers important implications for policies promoting digital financial inclusion as a means of rural transformation. This study looks at the role of mobile money in the modernization of smallholder rice farming in Côte d’Ivoire. Using survey data from rice farmers, we examine whether mobile money use is linked to changes in farm management, input use, productivity, and access to markets. The results provide evidence that mobile financial services can help farmers manage some of the financial and transaction constraints associated with agricultural production. The study adds to the limited empirical evidence on the productive use of mobile money in African agriculture and provides useful insights for policies aimed at expanding digital financial services among smallholder farmers.","本研究探讨移动货币（Mobile Money，MM）的采用如何影响科特迪瓦小农户水稻生产的农场管理选择，该西非背景以丰富的农业潜力和中等偏低的数字金融普惠水平为特征。研究采用内生转换回归（Endogenous Switching Regression，ESR）框架，对来自三个水稻生产部门的1，370名小农户生产者样本进行分析，并辅以逆概率加权回归调整（Inverse Probability Weighted Regression Adjustment，IPWRA）估计量进行稳健性检验，以估计移动货币对农业集约化（提高化肥使用量）、外延化（在稻田系统之外扩大粮食作物和经济作物的种植面积）、水稻总生产率以及更好的市场参与的影响。有证据表明，汇款可能是一个可行的渠道，通过这些效应发挥作用，即缓解流动性约束，从而使客户能够按季节投资于投入品和劳动力。我们的研究拓展了移动货币文献——该文献仍集中于东非——通过提供来自一个尚未充分探索的西非背景的新证据，并为促进数字金融普惠作为农村转型手段的政策提供了重要启示。本研究考察移动货币在科特迪瓦小农户水稻种植现代化中的作用。利用水稻种植者的调查数据，我们检验移动货币的使用是否与农场管理、投入品使用、生产率和市场准入的变化相关联。结果提供证据表明，移动金融服务可以帮助农民应对与农业生产相关的一些财务和交易约束。本研究补充了关于移动货币在非洲农业中生产性用途的有限实证证据，并为旨在扩大数字金融服务在小农户中覆盖面的政策提供了有益见解。","Figshare","2026-10-17T00:00:00Z",25,64,{"impact":117,"substance":389,"depth":390,"authority":52,"freshness":175,"relevant":21,"comment":391},21,17,"该研究基于1370户样本，采用ESR与IPWRA方法，为西非移动支付促进水稻生产现代化提供了新证据，但属区域性学术成果，公共影响有限，未达每日精选门槛。",[393,394],{"name":384,"url":381},{"name":395,"url":396},"Cogent Economics & Finance","https:\u002F\u002Fdoi.org\u002F10.1080\u002F23322039.2026.2740883",[398,70,30,399,400],"数字普惠金融","移动支付","科特迪瓦",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":404},{"candidates":405,"agricultural_evidence":46},[406,411,416,422,426],{"code":32,"score":17,"supported":46,"title":407,"abstract":408,"tags":410},[33],[34,409,33],"稻田",[30],{"code":66,"score":45,"supported":46,"title":412,"abstract":413,"tags":415},[],[70,414],"smallholder",[70],{"code":417,"score":279,"supported":46,"title":418,"abstract":419,"tags":421},"F3",[],[420],"fertilizer",[],{"code":356,"score":279,"supported":46,"title":423,"abstract":424,"tags":425},[],[327],[],{"code":427,"score":21,"supported":14,"title":428,"abstract":429,"tags":430},"G3",[],[],[398],[432,433],"科特迪瓦 水稻 移动支付","mobile money 小农户 水稻","科特迪瓦水稻移动支付-5247","10.6084\u002Fm9.figshare.34660410",{"doi":435,"openalex_id":437,"authors":438,"venue":384,"cited_by_count":97,"oa_url":381,"card":444,"direction":374,"ingested_from":104},"W7222786991",[439,442],{"name":440,"orcid":441},"Innocent Daniel Gniza","https:\u002F\u002Forcid.org\u002F0000-0002-9617-1562",{"name":443,"orcid":9},"Grakolet Arnold Gourene",{"tldr":445,"method":446,"finding":447,"direction":374,"opportunity":448},"研究科特迪瓦移动支付对小农户水稻种植管理、生产力与市场参与的影响。","内生转换回归与IPWRA，基于三国1370户稻农调查数据。","移动支付通过缓解流动性约束促进施肥、扩种、提高水稻生产力与市场参与。","可延伸研究移动支付汇款渠道对西非小农户投入季节性与数字金融普惠政策的长期效应。","2026-10-18T23:30:39.982038Z",{"id":451,"title":452,"url":453,"summary":454,"summary_zh":455,"content":9,"source_name":456,"source_url":453,"published_at":457,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":458,"score_detail":459,"sources":461,"tags":463,"primary_topic":467,"secondary_topics":468,"classification":475,"search_phrases":499,"slug":502,"view_count":86,"doi":503,"paper":504,"created_at":524},4427,"Development of Internet of Things-Based Soil Sensors for pH and Phosphorus Monitoring in Paddy Fields: Development, Accuracy, and Implementation Challenges","https:\u002F\u002Fdoi.org\u002F10.56581\u002Fijrerd.11.05.01-08","The development of Internet of Things (IoT) technology provides opportunities for faster and continuous soil monitoring to support precision agriculture.Monitoring soil pH and phosphorus is important in rice cultivation because both parameters are associated with soil chemical conditions and nutrient availability.This review aimed to examine the development of IoT-based soil sensors for monitoring soil pH and phosphorus, including sensor performance, factors affecting measurement results, and potential applications.A literature review was conducted on research and review articles published between 2019 and 2026.The literature was descriptively analyzed and synthesized based on technological development, sensor performance, and environmental and soil characteristics.The results indicate that pH and phosphorus sensors have been developed using various sensing approaches and have demonstrated promising performance under certain conditions; however, measurement results vary across parameters and soil conditions.Sensor performance is influenced by the sensing principle, soil characteristics, environmental conditions, calibration, and validation.IoT-based sensors have the potential to support real-time soil monitoring, but their application as quantitative measurement tools still requires validation and calibration under diverse soil conditions.","物联网（IoT）技术的发展为实现更快、连续性的土壤监测以支持精准农业提供了机遇。监测土壤pH和磷在水稻种植中具有重要意义，因为这两个参数均与土壤化学状况和养分有效性相关。本综述旨在考察用于监测土壤pH和磷的基于物联网的土壤传感器的发展现状，包括传感器性能、影响测量结果的因素以及潜在应用。本文对2019年至2026年间发表的研究论文和综述文章进行了文献综述。基于技术发展、传感器性能以及环境和土壤特征，对文献进行了描述性分析和综合。结果表明，pH和磷传感器已采用多种传感方法进行开发，并在特定条件下展现出良好性能；然而，测量结果因参数和土壤条件的不同而存在差异。传感器性能受传感原理、土壤特性、环境条件、校准和验证的影响。基于物联网的传感器具有支持实时土壤监测的潜力，但其作为定量测量工具的应用仍需在不同土壤条件下进行验证和校准。","International journal of recent engineering research and development.","2026-10-06T00:00:00Z",62,{"impact":117,"substance":17,"depth":200,"authority":20,"freshness":175,"relevant":21,"comment":460},"综述性论文，系统梳理IoT土壤pH与磷传感器的发展、精度与落地挑战，对智慧农业土壤监测方向有参考价值，但非突破性成果。",[462],{"name":456,"url":453},[123,464,465,466,30],"物联网","精准农业","土壤监测",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[469,474],{"code":470,"slug":471,"name":472,"path":473,"parent_code":195},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot",{"code":185,"slug":186,"name":187,"path":188,"parent_code":189},{"status":39,"locked":14,"version":40,"method":41,"evidence":476},{"candidates":477,"agricultural_evidence":46},[478,484,488,494],{"code":470,"score":17,"supported":46,"title":479,"abstract":481,"tags":483},[480],"internet of things",[464,480,482],"IoT",[464],{"code":32,"score":200,"supported":46,"title":485,"abstract":486,"tags":487},[138],[34,33],[30],{"code":185,"score":489,"supported":46,"title":490,"abstract":491,"tags":493},14,[186],[492,186],"土壤",[],{"code":73,"score":175,"supported":46,"title":495,"abstract":496,"tags":498},[],[465,497],"precision agriculture",[123,465],[500,501],"物联网 土壤传感器 稻田","土壤pH 监测","物联网土壤传感器稻田-4427","10.56581\u002Fijrerd.11.05.01-08",{"doi":503,"openalex_id":505,"authors":506,"venue":456,"cited_by_count":97,"oa_url":453,"card":519,"direction":164,"ingested_from":104},"W7220841659",[507,509,512,514,517],{"name":508,"orcid":9},"Fariha Laqania",{"name":510,"orcid":511},"Oviyanti Mulyani","https:\u002F\u002Forcid.org\u002F0000-0003-3941-8896",{"name":513,"orcid":9},"Ade Setiawan",{"name":515,"orcid":516},"Pujawati Suryatmana","https:\u002F\u002Forcid.org\u002F0000-0002-4012-8645",{"name":518,"orcid":9},"Wahyu Daradjat",{"tldr":520,"method":521,"finding":522,"direction":164,"opportunity":523},"综述2019-2026年稻田pH与磷的物联网土壤传感器发展、精度及实施挑战。","文献综述，按技术发展、传感器性能与土壤环境特征归纳分析。","传感器在特定条件下表现良好，但精度受原理、土壤、环境与校准影响，定量应用仍需验证。","稻田复杂土壤条件下pH\u002F磷传感器的原位校准与多源数据融合验证是待突破的研究空白。","2026-10-08T23:30:13.316611Z"]