[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3433":3,"related-3433":45},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":22,"tags":24,"search_phrases":30,"slug":33,"view_count":34,"doi":8,"paper":35,"created_at":44},3433,"《数字农业发展的信贷融资效应——来自江苏省家庭农场的证据》","http:\u002F\u002Fwww.qikanzj.com\u002Fhek\u002Fzgncgc\u002Fmulu\u002F647040.html","周月书、葛云杰使用江苏省家庭农场实地问卷调查数据考察数字农业发展的信贷融资效应及其作用机制。研究发现：数字农业发展显著提升了家庭农场的信贷可得性与信贷融资规模；机制上通过缓解信息不对称程度、降低信贷交易成本和提升风险抵御能力促进家庭农场融资；异质性分析发现数字农业发展对于所在地农业技术发展环境较好、农技人员服务水平较高的家庭农场，以及家庭农场主资本禀赋较低、金融认知能力较低以及种植粮食作物的家庭农场具有更显著的融资增进作用。",null,"《中国农村观察》\u002F南京农业大学","2026-09-20T00:00:00Z","论文",10,false,78,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,22,14,6,1,"基于江苏家庭农场实地调研的实证研究，机制与异质性分析扎实，对数字普惠金融与新型经营主体融资有参考价值。",[23],{"name":9,"url":6},[25,26,27,28,29],"数字农业","家庭农场","江苏","农村金融","信贷融资",[31,32],"江苏 家庭农场 数字农业 信贷","周月书 数字农业 融资","江苏家庭农场数字农业信贷-3433",0,{"doi":8,"openalex_id":8,"authors":36,"venue":8,"cited_by_count":34,"oa_url":8,"card":37,"direction":41,"ingested_from":43},[],{"tldr":38,"method":39,"finding":40,"direction":41,"opportunity":42},"基于江苏家庭农场调查，研究数字农业发展对信贷融资的影响及机制。","江苏省家庭农场实地问卷调查数据，实证分析信贷效应与机制。","数字农业显著提升信贷可得性与规模，通过缓解信息不对称、降成本、提风险抵御力实现。","数字乡村与农业信息化","可探究数字农业融资效应在不同区域和作物类型间的差异，及金融科技的中介作用。","agent","2026-09-25T00:09:33.572434Z",{"total":19,"page":20,"page_size":19,"items":46},[47,72,99,132,171,247],{"id":48,"title":49,"url":50,"summary":51,"summary_zh":8,"content":52,"source_name":53,"source_url":8,"published_at":54,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":55,"sources":60,"tags":62,"search_phrases":66,"slug":69,"view_count":70,"doi":8,"paper":8,"created_at":71},421,"Debt financing and agricultural income among large-scale grain producers: evidence from Jiangsu Province, China","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-8\u002F20260806165737778.htm","发表于《Frontiers in Sustainable Food Systems》。基于江苏省LSGPs(大规模粮食生产者)调查数据,构建债务融资—要素投入—农业收入理论框架,从融资规模与融资结构双视角展开实证。研究核心问题:大规模粮食生产者仍面临组织能力弱、生产成本上升与经营效率低等约束,其根源在于自有资本有限与规模经营资本需求之间的错配严重制约农业收入持续增长。高效农村金融市场通过改善投资能力、促进农业现代化与增强风险韧性缓解资本约束,但中国农村金融市场仍存在发展不均与服务供给不足。论文发表于Frontiers in Sustainable Food Systems。","《Frontiers in Sustainable Food Systems》：Debt financing and agricultural income among large-scale grain producers: evidence from Jiangsu Province, China\n\n**编辑推荐：**\n\n实现大规模粮食生产者（large-scale grain producers, LSGPs）农业收入增长对保障粮食安全与促进农业可持续发展至关重要。基于2022年江苏省645户LSGPs调查数据，研究人员采用普通最小二乘法（ordinary least squ\n\n实现大规模粮食生产者（large-scale grain producers, LSGPs）农业收入增长对保障粮食安全与促进农业可持续发展至关重要。基于2022年江苏省645户LSGPs调查数据，研究人员采用普通最小二乘法（ordinary least squares, OLS）、两阶段最小二乘法（two-stage least squares, 2SLS）与中介效应模型，考察债务融资对农业收入的影响、机制及规模边界。结果显示，总信贷、传统信贷、民间信贷与贸易信贷对农业收入呈倒U形影响，而数字信贷（digital credit）具有显著正向影响。机制分析表明，债务融资主要通过转入耕地规模、机械投资与基础设施投资提升农业收入；传统信贷与数字信贷经全部三条渠道起效，贸易信贷经转入耕地规模与机械投资起效，民间信贷主要经转入耕地规模起效。债务融资对农业收入的影响亦存在教育异质性：相较初中及以下学历农户，高中及以上学历农户的总信贷与贸易信贷拐点更高，且数字信贷的正向收入效应更显著。研究发现，金融政策应有序推进数字信贷发展、将债务融资控制在适度区间、强化对生产性投资的支持，并按农户受教育程度提供差异化金融服务。\n\n研究背景方面，增加农业收入是现代农业发展核心目标，对保障粮食安全与推进乡村振兴具有根本意义。规模化经营成为农业现代化关键路径，但大规模粮食生产者（LSGPs）仍面临组织能力弱、生产成本上升与经营效率低等约束，其根源在于自有资本有限与规模经营资本需求之间的错配严重制约农业收入持续增长。高效农村金融市场通过改善投资能力、促进农业现代化与增强风险韧性缓解资本约束，但中国农村金融市场仍存在发展不均与服务供给不足，LSGPs融资需求未根本解决。既有文献沿农户债务融资行为、债务融资对要素投入决策影响、债务融资对农业收入影响三条线索展开，但对规模经营下债务融资是否存在适度边界、不同渠道异质效应及作用机制缺乏系统检验。为此，研究人员利用江苏省LSGPs调查数据构建债务融资—要素投入—农业收入理论框架，从融资规模与融资结构双视角展开实证，论文发表于《Frontiers in Sustainable Food Systems》。\n\n关键技术方法上，研究人员基于2022年江苏省常州、无锡、南通、泰州、淮安、徐州、宿迁七市分层随机抽取645户有效LSGPs样本（以50亩为大规模经营阈值），以农业净收入对数为主被解释变量，以总信贷及传统信贷、数字信贷、民间信贷、贸易信贷四类渠道为解释变量，以转入耕地规模、机械投资、基础设施投资为中介变量，控制户主年龄、教育年限、健康、家庭人口、非农收入、技术示范户、自有耕地、地权稳定性等变量并加入城市固定效应。估计策略依次采用OLS基准回归（含融资一次项与平方项捕捉倒U形）、以前期信贷及其平方项为工具变量的2SLS处理双向因果与遗漏变量偏误、utest与边际效应分析严格检验倒U形、逐步回归结合bootstrap（500次）的中介效应模型，以及按户主受教育年限以9年为切分的异质性分组回归。\n\n研究结果部分，第4.1节基准回归表明，总信贷对农业收入呈倒U形，拐点约121万元，94.88%样本低于拐点；传统信贷、民间信贷、贸易信贷同样倒U形，拐点分别约65万、52万、53万元；数字信贷线性显著为正。第4.2节内生性与稳健性检验中，2SLS以去年信贷及其平方项为工具变量，Hausman与DWH检验确认内生性，一阶段F均超10，结论与OLS一致；utest显示区间内斜率由正转负且极值落Fieller置信区间；边际效应在P25—P90为正、样本最大值转负；对农业收入1%缩尾及控制其他信贷渠道后结果稳健。第4.3节机制分析显示，转入耕地规模对全部四类渠道均具中介效应；机械投资中介传统、贸易、数字信贷，不中介民间信贷；基础设施投资仅中介传统与数字信贷。第4.4节教育异质性表明，总信贷倒U形在两组的拐点分别为117.57万与122.44万元；贸易信贷拐点由49.54万升至60.34万；数字信贷在初中及以下组不显著，在高中及以上组线性显著为正。\n\n讨论与结论翻译部分，研究人员基于江苏省645户LSGPs田野调查数据，使用OLS、2SLS与中介效应模型考察债务融资对农业收入的影响，发现总信贷呈倒U形，数字信贷正向，传统、民间、贸易信贷倒U形，超90%样本低于拐点。机制上转入耕地规模中介全部渠道，机械投资中介传统、贸易、数字信贷，基础设施投资仅中介传统与数字信贷。教育异质性显示高中及以上组总信贷与贸易信贷拐点更高，数字信贷正效应集中于该组。政策含义包括：信贷供给应控于适度区间；有序推进数字信贷并提升LSGPs使用能力；规范民间与贸易信贷互补作用；优化对转入耕地、机械与基础设施的生产性信贷支持；按教育程度提供差异化金融服务。研究局限为截面数据难以捕捉动态长期效应、工具变量排除限制未完全验证、样本仅限江苏需谨慎外推。","Frontiers in Sustainable Food Systems 2026-08-06","2026-08-06T00:00:00Z",{"impact":16,"substance":56,"depth":57,"authority":18,"freshness":58,"relevant":20,"comment":59},24,20,2,"基于江苏645户数据，系统考察债务融资对农业收入的影响，方法严谨，结论具有政策参考价值，但时效性稍差。",[61],{"name":53,"url":50},[27,63,64,65,28],"债务融资","大规模粮食生产者","农业收入",[67,68],"大规模粮食生产者 债务融资 农业收入 农村金融","大规模粮食生产者 债务融资","大规模粮食生产者债务融资农业收入农村金融-421",3,"2026-08-11T23:57:03.342056Z",{"id":73,"title":74,"url":75,"summary":76,"summary_zh":8,"content":8,"source_name":77,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":78,"sources":80,"tags":82,"search_phrases":87,"slug":90,"view_count":34,"doi":8,"paper":91,"created_at":98},3446,"《数字技术赋能下银保互联提升农户家庭经营收入了吗——来自浙江省的微观证据》","http:\u002F\u002Fwww.qikanvip.com\u002Fqkml\u002F171577.html","张晋华、陈爽羽、谢文彬、贾伟基于浙江省辖内县（市）级的农户微观调研数据，系统评估数字技术赋能下银保互联对农户家庭经营收入的影响及其作用机制。研究发现：数字技术赋能下的银保互联显著提升了农户家庭经营收入；机制上通过'数据增信'缓解信贷配给和通过'数据风控'优化风险配给两条路径起作用；异质性检验发现农户的数字素养可显著强化增收效应，揭示数字红利存在'能力门槛'，在小规模、低资本投入农户群体中表现出更强的'补短板'特征。","《金融监管研究》2026年第3期",{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":79},"基于浙江农户微观调研的实证研究，揭示数字技术赋能银保互联通过数据增信与数据风控促进农户增收的机制，对农村数字普惠金融有参考价值。",[81],{"name":77,"url":75},[83,84,28,85,86],"数字乡村","数字素养","银保互联","农户增收",[88,89],"浙江 银保互联 农户收入","数字技术赋能 农村金融","浙江银保互联农户收入-3446",{"doi":8,"openalex_id":8,"authors":92,"venue":8,"cited_by_count":34,"oa_url":8,"card":93,"direction":41,"ingested_from":43},[],{"tldr":94,"method":95,"finding":96,"direction":41,"opportunity":97},"基于浙江农户调研数据，评估数字技术赋能下银保互联对农户家庭经营收入的增收效应。","浙江县市级农户微观调研数据，实证评估银保互联的收入效应与机制。","银保互联显著增收，通过数据增信与数据风控起作用，数字素养存在能力门槛。","可探究数字素养门槛的干预机制及银保互联在欠发达地区的适配性与长期效果。","2026-09-25T00:09:34.575538Z",{"id":100,"title":101,"url":102,"summary":103,"summary_zh":8,"content":8,"source_name":104,"source_url":8,"published_at":105,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":106,"score_detail":107,"sources":112,"tags":114,"search_phrases":119,"slug":122,"view_count":34,"doi":8,"paper":123,"created_at":131},3439,"《Agentic Artificial Intelligence in Agriculture: A Systematic Mapping Review of Reported Architectures, Applications, Challenges, and Future Directions》","https:\u002F\u002Fwww.mdpi.com\u002F2227-7080\u002F14\u002F9\u002F591","作者按PRISMA 2020方案从4111项记录筛选至181项研究，对2020—2026年农业代理式人工智能文献做系统映射综述：领域跨度30多年但LLM子集非常年轻（2024年才出现、46\u002F47项发表于2025—2026年）；82%研究报告合作能力，计划和推理分别仅31%、记忆6%、反思4%；只有33项研究报告现场或实际部署，68项仍停留在概念性阶段，仅11项报告了一个季度以上的评估。","《Technologies》2026, 14(9), 591 \u002F MDPI","2026-09-22T00:00:00Z",80,{"impact":16,"substance":108,"depth":16,"authority":109,"freshness":110,"relevant":20,"comment":111},23,13,8,"基于PRISMA的农业代理式AI系统映射综述，量化揭示LLM应用年轻化与落地不足，信息增量与专业深度突出，值得进入每日精选。",[113],{"name":104,"url":102},[25,115,116,117,118],"智慧农业","农业人工智能","农业大模型","智能体",[120,121],"农业代理式人工智能 系统映射综述","农业人工智能 农业大模型 数字农业 智慧农业","农业代理式人工智能系统映射综述-3439",{"doi":8,"openalex_id":8,"authors":124,"venue":8,"cited_by_count":34,"oa_url":8,"card":125,"direction":129,"ingested_from":43},[],{"tldr":126,"method":127,"finding":128,"direction":129,"opportunity":130},"系统映射181项研究，梳理农业代理式AI的架构、应用、挑战与未来方向。","按PRISMA 2020筛选4111项记录至181项，做系统映射综述。","LLM代理2024年才出现，多具合作能力但规划、记忆、反思薄弱，实际部署少。","农业人工智能与决策模型","农业LLM代理的长期田间部署、记忆与反思机制及跨季度评估仍是明显空白。","2026-09-25T00:09:33.995675Z",{"id":133,"title":134,"url":135,"summary":136,"summary_zh":137,"content":8,"source_name":138,"source_url":135,"published_at":105,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":139,"score_detail":140,"sources":144,"tags":146,"search_phrases":149,"slug":152,"view_count":34,"doi":153,"paper":154,"created_at":170},3367,"Digital Technology Adoption Conditioning Analysis Model in Agriculture","https:\u002F\u002Fdoi.org\u002F10.20944\u002Fpreprints202609.1880.v1","Technological advancements have been responsible for a significant part of the growth in agricultural productivity in recent years. Digital technologies have a high potential to enable the development of the agricultural sector, reshape value chains, and significantly contribute to more productive, resilient, and transparent food systems; however, their adoption in Brazil remains uneven due to regional disparities and structural bottlenecks. The research investigated this problem to build and validate the Digital Technology Adoption Conditioning Analysis Model (MAC-AgriTech), through a case study with Brazilian agricultural data, encompassing the identification of conditioning factors, their territorial evaluation, and the proposition of actions, while providing structured data collection and analysis instruments. The spatial analysis revealed deep territorial asymmetries, concentrating resources and infrastructure in the South and Southeast regions. Econometric modeling demonstrated that digital adoption is primarily driven by the producer’s digital familiarity, connectivity quality, and property scale, with 77% of producers identifying acquisition and maintenance costs as the primary barrier. The transition to digital agriculture in Brazil requires targeted, multidimensional public policies—such as expanded rural connectivity, technical training, and subsidized credit—to overcome regional gaps, and to increase agricultural competitiveness, efficiency, and sustainability.","近年来，技术进步对农业生产力增长贡献显著。数字技术具有巨大潜力，能够推动农业部门发展、重塑价值链，并为构建更高产、更具韧性且更透明的粮食体系作出重要贡献；然而，由于区域差异和结构性瓶颈，其在巴西的采用仍不均衡。本研究针对这一问题，通过一项基于巴西农业数据的案例研究，构建并验证了数字技术采用条件分析模型（MAC-AgriTech），涵盖条件因素的识别、其区域性评估以及行动建议的提出，同时提供了结构化的数据收集与分析工具。空间分析揭示了深刻的区域不对称性，资源和基础设施集中在南部和东南部地区。计量经济建模表明，数字采用主要受生产者数字熟悉度、连接质量和财产规模的驱动，其中77%的生产者将购置和维护成本视为主要障碍。巴西向数字农业的转型需要有针对性的、多维度的公共政策——如扩大农村连接、技术培训和补贴信贷——以克服区域差距，并提高农业竞争力、效率和可持续性。","Preprints.org",67,{"impact":141,"substance":57,"depth":142,"authority":19,"freshness":110,"relevant":20,"comment":143},16,17,"基于巴西农业数据的数字技术采纳条件分析模型研究，方法系统、结论有实证支撑，但属预印本且聚焦巴西，对国内参考价值有限。",[145],{"name":138,"url":135},[25,115,116,147,148],"巴西农业","农村数字化",[150,151],"巴西 数字农业 技术采纳","MAC-AgriTech 模型","巴西数字农业技术采纳-3367","10.20944\u002Fpreprints202609.1880.v1",{"doi":153,"openalex_id":155,"authors":156,"venue":138,"cited_by_count":34,"oa_url":135,"card":164,"direction":41,"ingested_from":169},"W7214109425",[157,160,162],{"name":158,"orcid":159},"Isabela Santos","https:\u002F\u002Forcid.org\u002F0009-0002-3659-2020",{"name":161,"orcid":8},"Eduardo Dias",{"name":163,"orcid":8},"Lidia Scoton",{"tldr":165,"method":166,"finding":167,"direction":41,"opportunity":168},"构建并验证MAC-AgriTech模型，分析巴西农业数字技术采纳的条件因素与区域差异。","巴西农业数据案例研究，空间分析与计量经济建模。","采纳主要由数字熟悉度、连接质量和农场规模驱动，77%生产者视成本为首要障碍。","可延伸至中国等发展中国家，探究数字素养、基础设施与政策组合对技术采纳的因果效应。","openalex","2026-09-24T23:30:27.046035Z",{"id":172,"title":173,"url":174,"summary":175,"summary_zh":176,"content":8,"source_name":177,"source_url":174,"published_at":178,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":179,"score_detail":180,"sources":183,"tags":185,"search_phrases":190,"slug":193,"view_count":34,"doi":194,"paper":195,"created_at":246},3351,"Integrated Land, Soil and Crop Information Systems in Ethiopia, Kenya, and Rwanda: Institutional Readiness and Implications for Climate-Smart Agriculture","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101776","Integrated land–soil–crop information systems are increasingly important for supporting climate-smart agricultural planning and implementation, yet their development in Eastern Africa is constrained by fragmented mandates, weak technical capacity, and limited data interoperability. This study assesses how institutional readiness, user demand, and technical and human-capacity conditions shape the integration of such systems into national Agricultural Knowledge and Innovation Systems (AKIS). A mixed-methods, multi-country assessment was conducted in Ethiopia, Kenya, and Rwanda (2022–2024), drawing on 145 semi-structured key-informant interviews, stakeholder mapping, national workshops, and a regional synthesis consultation. The analysis addressed three objectives: (i) diagnose institutional readiness and user demand; (ii) assess technical, infrastructural, and human-capacity requirements; and (iii) identify governance and design principles for embedding integrated information systems within AKIS and Climate-Smart Agriculture (CSA) strategies. The results show consistently high demand for spatially explicit soil and crop data but persistent fragmentation of mandates, uneven coordination, and substantial subnational capacity gaps. Despite these constraints, emerging digital-agriculture strategies, open-data policies, and regional soil-health initiatives provide potential entry points for integration. The study offers a comparative evidence base and design principles—covering governance, interoperability standards, co-production processes, and capacity strengthening—needed to transition from project-driven fragmentation toward interoperable and sustainable information systems. These findings provide diagnostic and design-oriented insights for national and regional efforts to strengthen agricultural information systems that support CSA implementation in Eastern Africa.","综合的土地—土壤—作物信息系统在支持气候智慧型农业规划与实施方面日益重要，但其在东非的发展受到职责分散、技术能力薄弱和数据互操作性有限的制约。本研究评估了制度准备度、用户需求以及技术和人力能力条件如何影响此类系统融入国家农业知识与创新系统（AKIS）。研究于2022—2024年在埃塞俄比亚、肯尼亚和卢旺达开展了混合方法、多国评估，基于145次半结构化关键知情人访谈、利益相关方映射、国家研讨会以及一次区域综合磋商。分析围绕三个目标展开：（i）诊断制度准备度和用户需求；（ii）评估技术、基础设施和人力能力需求；（iii）确定将综合信息系统嵌入AKIS和气候智慧型农业（CSA）战略的治理与设计原则。结果表明，对空间显式土壤和作物数据的需求持续较高，但职责分散、协调不均衡以及地方层面能力差距显著等问题长期存在。尽管存在这些制约，新兴的数字农业战略、开放数据政策和区域土壤健康倡议为整合提供了潜在切入点。本研究提供了比较性证据基础和设计原则——涵盖治理、互操作性标准、共同生产过程和能力建设——这些是从项目驱动的碎片化转向可互操作且可持续的信息系统所必需的。这些发现为国家和区域层面加强支持东非CSA实施的农业信息系统提供了诊断性和设计导向的见解。","Land","2026-09-23T00:00:00Z",81,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":181,"relevant":20,"comment":182},9,"基于三国145位关键知情人访谈的混合方法研究，为东非农业信息系统整合与气候智慧农业提供治理与设计原则，方法扎实、结论可靠，具区域政策参考价值。",[184],{"name":177,"url":174},[25,115,186,187,188,189],"土壤健康","气候智慧农业","农业数据","数据互操作",[191,192],"埃塞俄比亚 肯尼亚 卢旺达 农业信息系统","气候智慧农业 土壤作物数据","埃塞俄比亚肯尼亚卢旺达农业信息系统-3351","10.3390\u002Fland15101776",{"doi":194,"openalex_id":196,"authors":197,"venue":177,"cited_by_count":34,"oa_url":174,"card":240,"direction":245,"ingested_from":169},"W7214079859",[198,201,204,206,208,211,214,217,219,222,225,228,231,234,237],{"name":199,"orcid":200},"John Walker Recha","https:\u002F\u002Forcid.org\u002F0000-0002-1146-7197",{"name":202,"orcid":203},"A. Kooiman","https:\u002F\u002Forcid.org\u002F0000-0001-8208-6781",{"name":205,"orcid":8},"Thaïsa van der Woude",{"name":207,"orcid":8},"Hanneke Heesmans",{"name":209,"orcid":210},"Ermias Aynekulu","https:\u002F\u002Forcid.org\u002F0000-0002-1955-6995",{"name":212,"orcid":213},"Angela Nduta Gitau","https:\u002F\u002Forcid.org\u002F0000-0002-8963-2375",{"name":215,"orcid":216},"Pascal Debons","https:\u002F\u002Forcid.org\u002F0000-0001-6314-9935",{"name":218,"orcid":8},"Frank van Weert",{"name":220,"orcid":221},"Michael Okoti","https:\u002F\u002Forcid.org\u002F0000-0002-9550-8258",{"name":223,"orcid":224},"Elizabeth A. Okwuosa","https:\u002F\u002Forcid.org\u002F0000-0001-5941-7423",{"name":226,"orcid":227},"Kennedy Were","https:\u002F\u002Forcid.org\u002F0000-0002-8012-6812",{"name":229,"orcid":230},"Girma Mamo Diga","https:\u002F\u002Forcid.org\u002F0000-0002-2593-3187",{"name":232,"orcid":233},"Dejene Abera","https:\u002F\u002Forcid.org\u002F0000-0003-3692-8620",{"name":235,"orcid":236},"Pierre Celestin Ndayisaba","https:\u002F\u002Forcid.org\u002F0000-0002-8400-9146",{"name":238,"orcid":239},"Jules Rutebuka","https:\u002F\u002Forcid.org\u002F0000-0002-5236-3503",{"tldr":241,"method":242,"finding":243,"direction":41,"opportunity":244},"评估埃塞俄比亚、肯尼亚和卢旺达三国土地-土壤-作物综合信息系统的机构准备度与整合路径。","2022-2024年三国混合方法评估，含145个关键知情人访谈、利益相关方映射与","三国对空间化土壤作物数据需求高，但机构职责碎片化、协调不均、地方能力缺口大。","可研究开放数据政策与区域土壤健康倡议如何作为切入点，推动跨部门互操作标准与联合生产能力建设。","智慧农业 \u002F 农业物联网","2026-09-24T23:30:10.120978Z",{"id":248,"title":249,"url":250,"summary":251,"summary_zh":252,"content":8,"source_name":253,"source_url":250,"published_at":254,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":255,"score_detail":256,"sources":258,"tags":260,"search_phrases":263,"slug":266,"view_count":34,"doi":267,"paper":268,"created_at":298},3347,"Integrating Material Flow Cost Accounting and IoT-Based Monitoring for Eco-Efficient Goat Farm Management","https:\u002F\u002Fdoi.org\u002F10.35145\u002F6e5wnv18","Goat farming plays an important role in supporting rural livelihoods, food production, and agricultural sustainability. However, conventional goat farm management often separates environmental monitoring, financial accounting, and livestock management, limiting the ability to identify resource inefficiencies and associated environmental impacts. This study aims to develop and implement GEMBALA (Green Eco-smart Management-Based Automation for Livestock and Accounting), an integrated digital platform that combines Internet of Things (IoT)-based environmental monitoring, Material Flow Cost Accounting (MFCA), emission analysis, artificial intelligence-based livestock management, and analytical reporting. The research employed a research and development approach in collaboration with CV Cahaya Firdaus (Fathur Farm). An IoT sensor prototype was developed, installed, and tested in a real goat farming environment to monitor temperature, humidity, Heat Index (THI), ammonia gas, and dust density. The platform also incorporates MFCA, emission, AI Estrus, AI Health, and analytical reporting modules. The results demonstrate progress toward integrating environmental, economic, and livestock management information within a unified digital platform. However, further validation is required to improve sensor data transmission, synchronization, emission calculations, MFCA data consistency, and AI performance evaluation. The study provides a foundation for eco-economic decision support, sustainable livestock management, and future commercialization of digital livestock technologies.","山羊养殖在支撑农村生计、粮食生产和农业可持续性方面发挥着重要作用。然而，传统的山羊养殖场管理往往将环境监测、财务核算和畜牧管理相互分离，限制了识别资源低效利用及相关环境影响的能力。本研究旨在开发并实施GEMBALA（基于绿色生态智能管理的畜牧与会计自动化平台），这是一个集成了基于物联网（IoT）的环境监测、物料流成本会计（MFCA）、排放分析、基于人工智能的畜牧管理以及分析报告的综合数字平台。研究采用研发方法，与CV Cahaya Firdaus（Fathur Farm）合作开展。研究开发了物联网传感器原型，并在真实山羊养殖环境中进行安装和测试，用于监测温度、湿度、热指数（THI）、氨气和粉尘密度。该平台还整合了MFCA、排放、AI发情检测、AI健康和分析报告模块。结果表明，在将环境、经济和畜牧管理信息整合到统一数字平台方面取得了进展。然而，仍需进一步验证，以改进传感器数据传输、同步、排放计算、MFCA数据一致性以及AI性能评估。本研究为生态经济决策支持、可持续畜牧管理以及数字畜牧技术的未来商业化提供了基础。","Journal of Applied Business and Technology","2026-09-24T00:00:00Z",62,{"impact":110,"substance":16,"depth":141,"authority":12,"freshness":12,"relevant":20,"comment":257},"论文提出融合物联网监测与物料流成本核算的山羊养殖数字平台，方法有创新但尚处原型验证阶段，产业影响有限。",[259],{"name":253,"url":250},[25,115,116,261,262],"农业物联网","畜牧养殖",[264,265],"GEMBALA 山羊养殖 物联网","MFCA 畜牧 环境监测","GEMBALA山羊养殖物联网-3347","10.35145\u002F6e5wnv18",{"doi":267,"openalex_id":269,"authors":270,"venue":253,"cited_by_count":34,"oa_url":250,"card":293,"direction":245,"ingested_from":169},"W7214075234",[271,273,275,277,279,281,284,287,289,291],{"name":272,"orcid":8},"Nicholas Renaldo",{"name":274,"orcid":8},"Sulaiman Musa",{"name":276,"orcid":8},"Jaswar Koto",{"name":278,"orcid":8},"Kristy Veronica",{"name":280,"orcid":8},"Umar Faruq",{"name":282,"orcid":283},"Yulvia Nora Marlim","https:\u002F\u002Forcid.org\u002F0009-0007-8624-5023",{"name":285,"orcid":286},"Rangga Rahmadian Yuliendi","https:\u002F\u002Forcid.org\u002F0000-0003-2288-3580",{"name":288,"orcid":8},"Wilda Susanti",{"name":290,"orcid":8},"Achmad Tavip Junaedi",{"name":292,"orcid":8},"Nabila Wahid",{"tldr":294,"method":295,"finding":296,"direction":245,"opportunity":297},"开发集成物联网监测与物料流成本核算的山羊养殖数字平台GEMBALA。","研发方法，在真实羊场部署物联网传感器并集成MFCA、排放分析与AI模块。","平台初步实现环境、经济与养殖信息整合，但传感器传输与数据一致性仍需验证。","可延伸研究物联网数据与MFCA实时耦合的算法优化及AI模块的长期性能验证。","2026-09-24T23:30:09.863218Z"]