[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3455":3,"related-3455":62},{"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,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":61},3455,"Model-based optimization of agricultural drainage design: comparing orthogonal design, range analysis, and surrogate-assisted evolutionary optimization","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1942112","Artificial drainage is essential for agricultural productivity, but current design methods struggle to incorporate changing climate conditions and evolving policies and economic constraints. We propose a model-based optimization framework employing orthogonal design, range analysis, numerical simulations, and economic cost assessment. To benchmark the simplified approach, a Gaussian Process surrogate model (trained on the 16 orthogonal treatments) coupled with NSGA-II multi-objective evolutionary optimization was implemented to search for Pareto-optimal designs in continuous space. The framework was evaluated through a case study in Eastern China. The orthogonal design reduced the required simulations by 75% (64 to 16). The identified optimum (12 m spacing, 140 cm depth, 3 cm surface roughness) was corroborated through a continuous-space NSGA-II search, where the Pareto front knee point achieved a model-validated water table depth of 86.82 cm vs. 87.93 cm for the orthogonal optimum. The GP surrogate predictions agreed well with the numerical model (mean absolute error 4.5 cm, 4.4%). Global sensitivity analysis identified the drainage efficiency weight (67%) as the most influential factor. Systematic optimization methods, from orthogonal designs to surrogate-assisted evolutionary algorithms, can effectively identify optimal drainage designs while substantially reducing simulation effort, bridging the gap between optimization theory and practical drainage engineering.","人工排水对农业生产至关重要，但当前的设计方法难以纳入变化的气候条件以及不断演变的政策和经济约束。我们提出了一种基于模型的优化框架，采用正交设计、极差分析、数值模拟和经济成本评估。为对简化方法进行基准测试，我们实现了一种高斯过程代理模型（基于16个正交处理训练）与NSGA-II多目标进化优化相结合的方法，以在连续空间中搜索帕累托最优设计。该框架通过中国东部的一个案例研究进行了评估。正交设计将所需模拟次数减少了75%（从64次降至16次）。所确定的最优方案（间距12 m、埋深140 cm、地表粗糙度3 cm）通过连续空间NSGA-II搜索得到了验证，其中帕累托前沿拐点实现了模型验证的地下水位埋深86.82 cm，而正交最优方案为87.93 cm。高斯过程代理模型预测与数值模型吻合良好（平均绝对误差4.5 cm，4.4%）。全局敏感性分析表明，排水效率权重（67%）是最具影响力的因素。从正交设计到代理辅助进化算法的系统优化方法，能够有效识别最优排水设计，同时大幅减少模拟工作量，弥合了优化理论与实际排水工程之间的差距。",null,"Frontiers in Sustainable Food Systems","2026-09-24T00:00:00Z","论文",10,false,74,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,22,18,13,9,1,"方法学扎实、数据可信的农业排水优化研究，但属细分领域技术论文，公共影响有限，适合主题聚合而非每日精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字农业","智慧农业","多目标优化","农业排水","农业模型优化",[33,34],"农业排水设计 正交试验 NSGA-II","GP代理模型 排水工程 优化","农业排水设计正交试验NSGA-II-3455",0,"10.3389\u002Ffsufs.2026.1942112",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":6,"card":54,"direction":58,"ingested_from":60},"W7214176721",[41,44,46,48,50,52],{"name":42,"orcid":43},"Yi Gong","https:\u002F\u002Forcid.org\u002F0000-0002-6768-5417",{"name":45,"orcid":9},"Yuehua Ma",{"name":47,"orcid":9},"Lidong Chen",{"name":49,"orcid":9},"Ruinan Li",{"name":51,"orcid":9},"Jingsen Liu",{"name":53,"orcid":9},"Hao Liu",{"tldr":55,"method":56,"finding":57,"direction":58,"opportunity":59},"提出基于模型的农田排水设计优化框架，比较正交设计与代理辅助进化优化。","正交设计、极差分析、数值模拟、高斯过程代理模型与NSGA-II多目标优化。","正交设计减少75%模拟，最优设计经连续空间搜索验证，排水效率权重影响最大。","农业人工智能与决策模型","可探索代理模型与进化算法在多变气候和政策约束下的动态排水设计优化。","openalex","2026-09-25T23:30:06.531154Z",{"total":63,"page":22,"page_size":63,"items":64},6,[65,104,134,171,246,297],{"id":66,"title":67,"url":68,"summary":69,"summary_zh":70,"content":9,"source_name":71,"source_url":68,"published_at":11,"category":12,"cover_url":9,"hotness":72,"is_selected":14,"score":73,"score_detail":74,"sources":78,"tags":82,"search_phrases":86,"slug":89,"view_count":36,"doi":90,"paper":91,"created_at":103},3482,"Digital Transformation and the Reconfiguration of Farming Systems: Understanding How Tech-nological Adoption and Institutional Conditions Shape Sustainable and Inclusive Agriculture","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22932900","Digital agriculture is progressively reshaping farming through the integration of sensors, artificial intelligence, Internet of Things technologies, digital platforms, data analytics, robotics and automated decision-support systems. This paper examines this transformation by connecting three complementary dimensions: the socio-technical development of digital agriculture, the determinants and processes of technological adoption, and the economic, organizational and inclusive consequences of digitalization for farming systems. The literature indicates that agricultural digitalization cannot be reduced to the availability of increasingly sophisticated technologies. Adoption and sustained use depend on farmers’ perceptions of usefulness and compatibility, farm resources, human capital, infrastructure, institutional support, advisory systems and the capacity to integrate technologies into established production routines. Digital technologies may improve resource efficiency, information management, productivity and sustainability, while also modifying labor organization, farmer autonomy, data governance and relationships among actors within agricultural value chains. These effects remain uneven across farms and territories, particularly where smallholders face financial, infrastructural and capability constraints. The paper therefore interprets digital agriculture as a multidimensional transformation whose outcomes depend on the interaction between technological capabilities, farmer behavior and institutional conditions. Inclusive and sustainable digitalization requires attention not only to innovation diffusion but also to governance, skills, accessibility and the distribution of technological benefits.","数字农业正通过传感器、人工智能、物联网技术、数字平台、数据分析、机器人技术和自动化决策支持系统的整合，逐步重塑农业生产方式。本文通过连接三个互补维度来考察这一转型：数字农业的社会技术发展、技术采纳的决定因素与过程，以及数字化对农业系统产生的经济、组织和包容性后果。文献表明，农业数字化不能简化为日益复杂的技术供给。采纳和持续使用取决于农民对有用性和兼容性的认知、农场资源、人力资本、基础设施、制度支持、咨询系统以及将技术整合到既定生产惯例中的能力。数字技术可能提高资源效率、信息管理、生产力和可持续性，同时也会改变劳动组织、农民自主性、数据治理以及农业价值链中参与者之间的关系。这些影响在农场和区域之间仍不均衡，尤其是小农户面临资金、基础设施和能力约束的地方。因此，本文将数字农业解释为一种多维转型，其结果取决于技术能力、农民行为和制度条件之间的相互作用。包容和可持续的数字化不仅需要关注创新扩散，还需要关注治理、技能、可及性和技术收益的分配。","Zenodo (CERN European Organization for Nuclear Research)",25,77,{"impact":19,"substance":75,"depth":76,"authority":20,"freshness":21,"relevant":22,"comment":77},20,17,"系统梳理数字农业技术采纳与制度条件的研究综述，对智慧农业政策与推广有参考价值，但属文献综述类，非重大突破。",[79,80],{"name":71,"url":68},{"name":71,"url":81},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22932899",[27,28,83,84,85],"农业人工智能","小农户","技术采纳",[87,88],"农业人工智能 技术采纳 数字农业 智慧农业","农业人工智能 技术采纳","农业人工智能技术采纳数字农业智慧农业-3482","10.5281\u002Fzenodo.22932900",{"doi":90,"openalex_id":92,"authors":93,"venue":71,"cited_by_count":36,"oa_url":68,"card":96,"direction":102,"ingested_from":60},"W7214187008",[94],{"name":95,"orcid":9},"Chilufya Banda",{"tldr":97,"method":98,"finding":99,"direction":100,"opportunity":101},"综述数字农业转型，分析技术采纳与制度条件如何共同塑造可持续包容性农业。","文献综述，整合社会技术、技术采纳与数字化经济组织后果三维度。","数字化成效取决于技术能力、农户行为与制度条件的交互，小农面临多重约束。","数字乡村与农业信息化","可实证检验制度支持与农户能力如何调节数字技术对包容性和可持续性的影响。","智慧农业 \u002F 农业物联网","2026-09-25T23:30:18.463733Z",{"id":105,"title":106,"url":107,"summary":108,"summary_zh":9,"content":9,"source_name":109,"source_url":9,"published_at":110,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":111,"score_detail":112,"sources":116,"tags":118,"search_phrases":121,"slug":124,"view_count":36,"doi":9,"paper":125,"created_at":133},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":19,"substance":113,"depth":19,"authority":20,"freshness":114,"relevant":22,"comment":115},23,8,"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。",[117],{"name":109,"url":107},[27,28,83,119,120],"农业大模型","智能体",[122,123],"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":9,"openalex_id":9,"authors":126,"venue":9,"cited_by_count":36,"oa_url":9,"card":127,"direction":58,"ingested_from":132},[],{"tldr":128,"method":129,"finding":130,"direction":58,"opportunity":131},"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。","agent","2026-09-25T00:09:33.995675Z",{"id":135,"title":136,"url":137,"summary":138,"summary_zh":139,"content":9,"source_name":140,"source_url":137,"published_at":110,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":141,"score_detail":142,"sources":145,"tags":147,"search_phrases":150,"slug":153,"view_count":36,"doi":154,"paper":155,"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":143,"substance":75,"depth":76,"authority":63,"freshness":114,"relevant":22,"comment":144},16,"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。",[146],{"name":140,"url":137},[27,28,83,148,149],"巴西农业","农村数字化",[151,152],"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":154,"openalex_id":156,"authors":157,"venue":140,"cited_by_count":36,"oa_url":137,"card":165,"direction":100,"ingested_from":60},"W7214109425",[158,161,163],{"name":159,"orcid":160},"Isabela Santos","https:\u002F\u002Forcid.org\u002F0009-0002-3659-2020",{"name":162,"orcid":9},"Eduardo Dias",{"name":164,"orcid":9},"Lidia Scoton",{"tldr":166,"method":167,"finding":168,"direction":100,"opportunity":169},"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。","2026-09-24T23:30:27.046035Z",{"id":172,"title":173,"url":174,"summary":175,"summary_zh":176,"content":9,"source_name":177,"source_url":174,"published_at":178,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":179,"score_detail":180,"sources":183,"tags":185,"search_phrases":190,"slug":193,"view_count":36,"doi":194,"paper":195,"created_at":245},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":19,"substance":18,"depth":19,"authority":181,"freshness":21,"relevant":22,"comment":182},14,"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},[27,28,186,187,188,189],"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":36,"oa_url":174,"card":240,"direction":102,"ingested_from":60},"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":9},"Thaïsa van der Woude",{"name":207,"orcid":9},"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":9},"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":100,"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。","2026-09-24T23:30:10.120978Z",{"id":247,"title":248,"url":249,"summary":250,"summary_zh":251,"content":9,"source_name":252,"source_url":249,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":253,"score_detail":254,"sources":256,"tags":258,"search_phrases":261,"slug":264,"view_count":36,"doi":265,"paper":266,"created_at":296},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",62,{"impact":114,"substance":19,"depth":143,"authority":13,"freshness":13,"relevant":22,"comment":255},"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。",[257],{"name":252,"url":249},[27,28,83,259,260],"农业物联网","畜牧养殖",[262,263],"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":265,"openalex_id":267,"authors":268,"venue":252,"cited_by_count":36,"oa_url":249,"card":291,"direction":102,"ingested_from":60},"W7214075234",[269,271,273,275,277,279,282,285,287,289],{"name":270,"orcid":9},"Nicholas Renaldo",{"name":272,"orcid":9},"Sulaiman Musa",{"name":274,"orcid":9},"Jaswar Koto",{"name":276,"orcid":9},"Kristy Veronica",{"name":278,"orcid":9},"Umar Faruq",{"name":280,"orcid":281},"Yulvia Nora Marlim","https:\u002F\u002Forcid.org\u002F0009-0007-8624-5023",{"name":283,"orcid":284},"Rangga Rahmadian Yuliendi","https:\u002F\u002Forcid.org\u002F0000-0003-2288-3580",{"name":286,"orcid":9},"Wilda Susanti",{"name":288,"orcid":9},"Achmad Tavip Junaedi",{"name":290,"orcid":9},"Nabila Wahid",{"tldr":292,"method":293,"finding":294,"direction":102,"opportunity":295},"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",{"id":298,"title":299,"url":300,"summary":301,"summary_zh":9,"content":9,"source_name":302,"source_url":9,"published_at":303,"category":304,"cover_url":9,"hotness":13,"is_selected":14,"score":305,"score_detail":306,"sources":308,"tags":310,"search_phrases":314,"slug":317,"view_count":36,"doi":9,"paper":9,"created_at":318},3301,"莲都区107个水稻新品种集中亮相——2026年第四届浙西南水稻新品种数字化展示现场观摩会","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7688050911050007074","9月21日，2026年第四届浙西南水稻新品种数字化展示现场观摩会在莲都区碧湖镇白口村举行。参会嘉宾实地查看107个水稻新品种的长势特点、田间管理和产量等情况。今年观摩会所在的国家级分子育种创新服务平台(长三角)分中心片区，由华智种谷智创科技(浙江)有限公司提供技术支撑，构建了BT生物技术+DT大数据技术的技术体系：运用水稻液相芯片对参试品种开展功能基因图谱鉴定，依托DT大数据技术搭建数字化品种展示评价系统。农业专家团队综合考量茎秆粗壮度、穗粒结构、综合抗性等多项指标，推介出春丰优7号、春优83、春诚优887等15个品种。","今日头条（莲都发布） 2026年09月22日","2026-09-21T18:04:00Z","报道",60,{"impact":181,"substance":19,"depth":181,"authority":63,"freshness":114,"relevant":22,"comment":307},"地市级观摩会，107个品种与BT+DT数字化评价体系有实质信息量，但影响层级与信源权威度有限，可作主题页聚合素材。",[309],{"name":302,"url":300},[27,28,311,312,313],"种业振兴","分子育种","水稻新品种",[315,316],"浙西南 水稻新品种 观摩会","莲都 水稻液相芯片 数字化展示","浙西南水稻新品种观摩会-3301","2026-09-24T00:03:59.270091Z"]