[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5181":3,"related-5181":118},{"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":18,"tags":20,"primary_topic":9,"secondary_topics":25,"classification":26,"search_phrases":42,"slug":45,"view_count":15,"doi":46,"paper":47,"created_at":117},5181,"Satellite Remote Sensing of Methane Point Sources: A Review of Capabilities and Applications","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fegusphere-2026-6060","Abstract. The ability to remotely sense methane point sources continues to grow, driven by new satellite launches, newly discovered detection capabilities in satellites not originally intended for methane observation, and increasingly mature data processing and delivery pipelines. We review current and anticipated satellite remote sensing capabilities, including a description of instrument specifications, sampling strategies, and data availability. We detail algorithms that drive general methane plume processing pipelines and associated validation experiments across multiple product levels. We describe categories of stakeholder and science driven use cases that use satellite point source datasets. In particular, we detail several mitigation programs that use satellite point source detections to inform leak detection and verification (e.g., IMEO Methane Alert and Response System; California Satellite Methane Project). We also summarize research to date that incorporates point source datasets to inform practices to reduce emissions and aid aggregate accounting of emissions from facilities to regional scales. Continued work to establish common validation standards and reference sites to make detection and quantification performance comparable across instruments is recommended for building increased confidence in plume datasets. However, the successful integration of satellite point source imager observations into stakeholder workstreams demonstrates that these datasets are equipped today to support climate policy, operator response, and emissions accounting.","摘要：遥感甲烷点源的能力持续增强，这得益于新卫星的发射、原本并非用于甲烷观测的卫星上新发现的探测能力，以及日益成熟的数据处理与分发流程。本文综述了当前及预期的卫星遥感能力，包括仪器规格、采样策略和数据可获取性的描述。我们详细介绍了驱动通用甲烷羽流处理流程的算法，以及跨多个产品层级的相关验证实验。我们描述了利用卫星点源数据集的相关方和科学驱动用例的类别。特别是，我们详述了几个利用卫星点源探测为泄漏检测与核证提供信息的减排项目（例如，IMEO甲烷警报与响应系统；加州卫星甲烷项目）。我们还总结了迄今为止将点源数据集纳入研究以指导减排实践、并辅助从设施到区域尺度的排放总量核算的工作。建议继续努力建立统一的验证标准和参考站点，使不同仪器间的探测与量化性能具有可比性，从而增强对羽流数据集的信心。然而，卫星点源成像仪观测成功融入相关方工作流程表明，这些数据集目前已具备支持气候政策、运营者响应和排放核算的能力。",null,"OpenAlex","2026-10-15T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该文为卫星遥感甲烷点源综述，属环境与气候监测领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23,24],"温室气体","卫星遥感","甲烷监测","排放核算",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":30},"needs_review","2026-10-22.2","rules",{"candidates":31,"agricultural_evidence":14,"reason":41},[32],{"code":33,"score":34,"supported":35,"title":36,"abstract":38,"tags":40},"I3",15,true,[37],"remote sensing",[39,37],"遥感",[22],"农业相关性需要复核",[43,44],"卫星遥感 甲烷点源","甲烷泄漏 检测 卫星","卫星遥感甲烷点源-5181","10.5194\u002Fegusphere-2026-6060",{"doi":46,"openalex_id":48,"authors":49,"venue":9,"cited_by_count":15,"oa_url":108,"card":109,"direction":115,"ingested_from":116},"W7222319315",[50,53,56,59,61,64,67,70,73,76,79,82,85,88,91,94,97,100,102,105],{"name":51,"orcid":52},"Daniel Cusworth","https:\u002F\u002Forcid.org\u002F0000-0003-0158-977X",{"name":54,"orcid":55},"Daniel J. Varon","https:\u002F\u002Forcid.org\u002F0000-0002-3207-5731",{"name":57,"orcid":58},"Dylan Jervis","https:\u002F\u002Forcid.org\u002F0009-0009-5387-635X",{"name":60,"orcid":9},"Jason McKeever",{"name":62,"orcid":63},"Alexander J. Turner","https:\u002F\u002Forcid.org\u002F0000-0003-1406-7372",{"name":65,"orcid":66},"Christian Frankenberg","https:\u002F\u002Forcid.org\u002F0000-0002-0546-5857",{"name":68,"orcid":69},"John R. Worden","https:\u002F\u002Forcid.org\u002F0000-0003-0257-9549",{"name":71,"orcid":72},"Andrew K. Thorpe","https:\u002F\u002Forcid.org\u002F0000-0001-7968-5433",{"name":74,"orcid":75},"Jay E. Fahlen","https:\u002F\u002Forcid.org\u002F0000-0002-1660-8104",{"name":77,"orcid":78},"Sudhanshu Pandey","https:\u002F\u002Forcid.org\u002F0000-0001-5938-385X",{"name":80,"orcid":81},"Joannes D. Maasakkers","https:\u002F\u002Forcid.org\u002F0000-0001-8118-0311",{"name":83,"orcid":84},"Ilse Aben","https:\u002F\u002Forcid.org\u002F0000-0003-2198-0768",{"name":86,"orcid":87},"A. Eldering","https:\u002F\u002Forcid.org\u002F0000-0003-1080-9922",{"name":89,"orcid":90},"Riley Duren","https:\u002F\u002Forcid.org\u002F0000-0003-4723-5280",{"name":92,"orcid":93},"Bradley Conrad","https:\u002F\u002Forcid.org\u002F0000-0003-3678-7434",{"name":95,"orcid":96},"Tia R. Scarpelli","https:\u002F\u002Forcid.org\u002F0000-0001-5544-8732",{"name":98,"orcid":99},"Daniel M. Bon","https:\u002F\u002Forcid.org\u002F0000-0002-0186-5087",{"name":101,"orcid":9},"Mackenzie Huffman",{"name":103,"orcid":104},"Itziar Irakulis‐Loitxate","https:\u002F\u002Forcid.org\u002F0000-0003-3646-4950",{"name":106,"orcid":107},"Luis Guanter","https:\u002F\u002Forcid.org\u002F0000-0002-8389-5764","https:\u002F\u002Fegusphere.copernicus.org\u002Fpreprints\u002F2026\u002Fegusphere-2026-6060\u002Fegusphere-2026-6060.pdf",{"tldr":110,"method":111,"finding":112,"direction":113,"opportunity":114},"综述卫星甲烷点源遥感能力、算法与利益相关方应用案例。","综述多卫星仪器规格、羽流处理算法、验证实验及泄漏检测项目。","卫星点源数据已可支撑气候政策、运营商响应与排放核算。","农业绿色发展与碳","农业甲烷（如稻田、畜禽）点源卫星监测与验证标准尚属空白，可切入。","农业遥感与作物表型","openalex","2026-10-17T23:30:31.714319Z",{"total":119,"page":120,"page_size":119,"items":121},6,1,[122,201,267,352,419,485],{"id":123,"title":124,"url":125,"summary":126,"summary_zh":127,"content":9,"source_name":128,"source_url":125,"published_at":129,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":130,"score_detail":131,"sources":137,"tags":139,"primary_topic":144,"secondary_topics":149,"classification":150,"search_phrases":164,"slug":167,"view_count":15,"doi":168,"paper":169,"created_at":200},5318,"Lagged Effects and Mechanisms of Central Environmental Inspection Policies on Agricultural Straw Burning: Evidence from Remote Sensing Data in China","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10668-026-08214-3","Lagged Effects and Mechanisms of Central Environmental Inspection Policies on Agricultural Straw Burning: Evidence from Remote Sensing Data in China。Environment Development and Sustainability","中央环保督察政策对农业秸秆焚烧的滞后效应与作用机制：来自中国遥感数据的证据。《环境、发展与可持续性》","Environment Development and Sustainability","2026-10-19T00:00:00Z",84,{"impact":132,"substance":133,"depth":134,"authority":135,"freshness":13,"relevant":120,"comment":136},22,20,18,14,"基于全国遥感数据评估中央环保督察对秸秆焚烧的滞后效应，数据规模大、方法新颖，对农业环境政策有参考价值，值得进入每日精选。",[138],{"name":128,"url":125},[140,141,22,142,143],"农业政策","遥感监测","秸秆焚烧","环保督察",{"code":33,"slug":145,"name":146,"path":147,"parent_code":148},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":151,"locked":14,"version":28,"method":29,"evidence":152},"classified",{"candidates":153,"agricultural_evidence":35},[154,159],{"code":33,"score":155,"supported":35,"title":156,"abstract":157,"tags":158},16,[37],[39,37],[22,141],{"code":160,"score":120,"supported":14,"title":161,"abstract":162,"tags":163},"H5",[],[],[142],[165,166],"中央环保督察 秸秆焚烧","遥感数据 秸秆焚烧","中央环保督察秸秆焚烧-5318","10.1007\u002Fs10668-026-08214-3",{"doi":168,"openalex_id":170,"authors":171,"venue":128,"cited_by_count":15,"oa_url":9,"card":195,"direction":115,"ingested_from":116},"W7222877438",[172,174,176,178,180,182,184,187,189,191,193],{"name":173,"orcid":9},"Lu Dong",{"name":175,"orcid":9},"Linru Zhang",{"name":177,"orcid":9},"Na Liu",{"name":179,"orcid":9},"Xin Long",{"name":181,"orcid":9},"Ziyi Wang",{"name":183,"orcid":9},"Siyue Yang",{"name":185,"orcid":186},"Jie Tian","https:\u002F\u002Forcid.org\u002F0000-0001-6585-3643",{"name":188,"orcid":9},"Qiyuan Wang",{"name":190,"orcid":9},"Zhanfeng Dong",{"name":192,"orcid":9},"Long Wu",{"name":194,"orcid":9},"Yichen Wang",{"tldr":196,"method":197,"finding":198,"direction":113,"opportunity":199},"利用遥感数据评估中央环保督察政策对秸秆焚烧的滞后效应与作用机制。","基于中国遥感火点数据构建面板，采用滞后效应模型识别政策影响机制。","中央环保督察对秸秆焚烧具有显著但滞后的抑制效应，并存在区域异质性。","可结合地块级遥感与农户调查，量化督察滞后期内秸秆离田利用与替代处置的路径。","2026-10-19T23:30:22.693590Z",{"id":202,"title":203,"url":204,"summary":205,"summary_zh":206,"content":9,"source_name":207,"source_url":204,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":208,"score_detail":209,"sources":216,"tags":218,"primary_topic":9,"secondary_topics":222,"classification":223,"search_phrases":232,"slug":235,"view_count":15,"doi":236,"paper":237,"created_at":266},5171,"Fuel load and potential fire behavior vary seasonally and across grassland plant communities","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs42408-026-00593-2","Abstract Grassland fuels can be patchy across space and time, especially on landscapes where multiple grassland plant communities co-occur. However, the standard fuel models inadequately capture the spatiotemporal variability in grassland fuels for local, strategic planning of fuel treatments. We aimed to better understand the seasonal variation in grassland fuels and fire behavior across grassland types. Here, we developed remote sensing-based grassland fuel maps using multispectral satellite data (10-m resolution) from Sentinel-2, compared seasonal fire behavior across grassland types, and performed a sensitivity analysis of fire behavior models to changes in litter, dead 1 h, and live herbaceous loads, and fuelbed depth estimates. We were able to best predict live herbaceous load (R2 = 0.85), followed by fuelbed depth (R2 = 0.81), dead 1 h fuel load (R2 = 0.76), and litter load (R2 = 0.67) based on remotely sensed predictors. Our spatially predicted grassland fuel maps showed seasonal variability in fuel loads in different places, reflecting the varying timing of curing by grassland types. In particular, we observed more accumulation of dead 1 h load between August and October in early senescing mixedgrass prairies than later senescing tallgrass prairies. We found an overall faster modeled rate of spread in smooth brome-dominated, invasive grasslands and native tallgrass prairies compared to mixedgrass and prairie dog-dominated grasslands. From the sensitivity analysis, we found that modeled fire behavior model is most sensitive to dead 1 h fuel load and least sensitive to litter load in this grassland system. At a time when grassland fires are increasing and resources for fuel management are limited, remote sensing approach to grassland fuel modeling may help land managers make decisions about where and when to prioritize fuel treatments to mitigate the risk of catastrophic wildfires.","摘要 草地可燃物在空间和时间上往往呈斑块状分布，在多种草地植物群落共存的景观中尤为如此。然而，标准可燃物模型难以充分刻画草地可燃物的时空变异性，无法满足局部可燃物处理策略性规划的需求。本研究旨在更好地理解不同草地类型间可燃物和火行为的季节性变化。为此，我们利用Sentinel-2多光谱卫星数据（10 m分辨率）构建了基于遥感的草地可燃物图，比较了不同草地类型间的季节性火行为，并对火行为模型进行了敏感性分析，考察凋落物、1小时时滞死可燃物、活草本可燃物载量及可燃物床深度估算值变化的影响。基于遥感预测因子，我们对活草本可燃物载量的预测效果最佳（R² = 0.85），其次为可燃物床深度（R² = 0.81）、1小时时滞死可燃物载量（R² = 0.76）和凋落物载量（R² = 0.67）。空间预测的草地可燃物图显示，不同地点的可燃物载量存在季节性变异，反映了不同草地类型枯萎时序的差异。特别是，我们观察到早枯的混合草草原在8月至10月间1小时时滞死可燃物载量的累积多于晚枯的高草草原。我们发现，与混合草草原和草原犬鼠主导的草地相比，无芒雀麦主导的入侵草地和原生高草草原的模拟蔓延速率总体更快。敏感性分析表明，在该草地系统中，火行为模型对1小时时滞死可燃物载量最为敏感，对凋落物载量最不敏感。在草地火灾日益增多且可燃物管理资源有限的背景下，基于遥感的草地可燃物建模方法可帮助土地管理者决策在何处、何时优先开展可燃物处理，以降低灾难性野火风险。","Fire Ecology",72,{"impact":210,"substance":211,"depth":212,"authority":213,"freshness":214,"relevant":120,"comment":215},12,21,17,13,9,"基于 Sentinel-2 的草地可燃物遥感制图与火行为敏感性分析，方法新颖、结论可靠，对草原火险管理有实用价值，但属细分领域研究，公共影响有限。",[217],{"name":207,"url":204},[141,22,219,220,221],"草原火险","可燃物模型","草地管理",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":224},{"candidates":225,"agricultural_evidence":14,"reason":41},[226],{"code":33,"score":227,"supported":35,"title":228,"abstract":229,"tags":231},11,[],[39,37,230],"multispectral",[22,141],[233,234],"Sentinel-2 草地可燃物","草原火行为 遥感制图","Sentinel-2草地可燃物-5171","10.1186\u002Fs42408-026-00593-2",{"doi":236,"openalex_id":238,"authors":239,"venue":207,"cited_by_count":15,"oa_url":260,"card":261,"direction":115,"ingested_from":116},"W7221860401",[240,243,246,249,252,254,257],{"name":241,"orcid":242},"Lina Aoyama","https:\u002F\u002Forcid.org\u002F0000-0001-9677-7268",{"name":244,"orcid":245},"Katharine N. Suding","https:\u002F\u002Forcid.org\u002F0000-0002-5357-0176",{"name":247,"orcid":248},"Advyth Ramachandran","https:\u002F\u002Forcid.org\u002F0009-0005-1440-2726",{"name":250,"orcid":251},"Jordan T. Lee","https:\u002F\u002Forcid.org\u002F0000-0002-3188-9792",{"name":253,"orcid":9},"Paul Dennison",{"name":255,"orcid":256},"Thomas K. Merchant","https:\u002F\u002Forcid.org\u002F0000-0002-6905-0255",{"name":258,"orcid":259},"Jonathan J. Henn","https:\u002F\u002Forcid.org\u002F0000-0003-1551-9238","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1186\u002Fs42408-026-00593-2.pdf",{"tldr":262,"method":263,"finding":264,"direction":115,"opportunity":265},"用Sentinel-2遥感构建草地可燃物载量季节图谱并模拟火行为差异。","Sentinel-2多光谱数据回归预测可燃物载量，结合火行为模型敏感性分析。","早枯混草草原死1小时载量积累更多，入侵与高草草原蔓延速率更快。","可将遥感可燃物制图与火险预警、放牧管理结合，拓展到多草地类型时空动态监测。","2026-10-17T23:30:28.706068Z",{"id":268,"title":269,"url":270,"summary":271,"summary_zh":272,"content":9,"source_name":273,"source_url":270,"published_at":274,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":275,"score_detail":276,"sources":279,"tags":281,"primary_topic":286,"secondary_topics":292,"classification":293,"search_phrases":328,"slug":331,"view_count":332,"doi":333,"paper":334,"created_at":351},3874,"Exploring aquaponics systems and greenhouse gas emissions: an agent-based model case study","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1862992","Aquaponics is the combination of aquaculture (i.e., propagation of aquatic species) and hydroponics (i.e., soil-less propagation of plants), which is being investigated as a method for more sustainable food production. Along with ensuring the continued improvement of the technology itself, educating the public about aquaponics using a systems-thinking approach is equally important. Agent-based modeling was used to develop an aquaponics model that will allow any student to have an active learning experience with a generalized operation of the system while also exploring systems-thinking principles. By developing a model, individuals interested in learning are not limited by what their educational institutions can provide, which is often restricted by a lack of resources. The aquaponics agent-based model presented in this study allows the user to change the fish and plant types, climate, and season and display the corresponding greenhouse gas emissions when the theoretical system is operating. The number of plants harvested and the total greenhouse gas emissions are the two stochastic outputs of the model, given potential variations in timelines, system efficiencies, and general human error. Greenhouse gas emissions were compared with those reported in the relevant literature to inform parameter selection. The overall goal of this model is to provide an interactive and broadly accessible educational opportunity.","鱼菜共生（Aquaponics）是水产养殖（即水生物种的繁殖）与水培（即无土栽培植物）的结合，目前正被研究作为一种更可持续的粮食生产方式。在确保该技术本身持续改进的同时，利用系统思维方法向公众普及鱼菜共生知识同样重要。本研究采用基于主体的建模（Agent-based modeling）方法开发了一个鱼菜共生模型，使任何学生都能通过该系统的广义操作获得主动学习体验，同时探索系统思维原则。通过开发这一模型，有兴趣的学习者不再受限于其教育机构所能提供的条件——这些条件往往因资源匮乏而受到制约。本研究提出的鱼菜共生基于主体的模型允许用户更改鱼类和植物类型、气候和季节，并展示理论系统运行时的相应温室气体排放量。考虑到时间线、系统效率和一般人为误差的潜在变化，收获植物数量和温室气体排放总量是该模型的两个随机输出。温室气体排放量已与相关文献中报告的数据进行比较，以指导参数选择。该模型的总体目标是提供一种具有交互性且可广泛获取的教育机会。","Frontiers in Sustainable Food Systems","2026-09-30T00:00:00Z",61,{"impact":277,"substance":134,"depth":155,"authority":213,"freshness":119,"relevant":120,"comment":278},8,"该论文提出基于智能体的鱼菜共生教学模型，可模拟鱼类、植物、气候与季节变化并输出温室气体排放，方法新颖且具教育推广价值，但属细分领域学术成果，公共影响有限。",[280],{"name":273,"url":270},[282,283,21,284,285],"智慧农业","设施农业","水产养殖","系统思维",{"code":287,"slug":288,"name":289,"path":290,"parent_code":291},"B7","protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[],{"status":151,"locked":14,"version":28,"method":29,"evidence":294},{"candidates":295,"agricultural_evidence":35},[296,303,311,318,323],{"code":287,"score":212,"supported":35,"title":297,"abstract":299,"tags":302},[298],"greenhouse",[300,301,298],"温室","无土栽培",[],{"code":304,"score":305,"supported":35,"title":306,"abstract":307,"tags":310},"D",7,[],[308,309],"水产","aquaculture",[284],{"code":312,"score":313,"supported":35,"title":314,"abstract":315,"tags":317},"H2",3,[],[316],"soil",[],{"code":319,"score":120,"supported":14,"title":320,"abstract":321,"tags":322},"H4",[],[],[21],{"code":324,"score":120,"supported":14,"title":325,"abstract":326,"tags":327},"I1",[],[],[282],[329,330],"鱼菜共生 温室气体 模型","智慧农业 水产养殖 温室气体 系统思维","鱼菜共生温室气体模型-3874",2,"10.3389\u002Ffsufs.2026.1862992",{"doi":333,"openalex_id":335,"authors":336,"venue":273,"cited_by_count":15,"oa_url":270,"card":346,"direction":113,"ingested_from":116},"W7214975686",[337,340,342,344],{"name":338,"orcid":339},"Marissa Breitenstein","https:\u002F\u002Forcid.org\u002F0009-0005-2148-8812",{"name":341,"orcid":9},"Elisabeth Bautista",{"name":343,"orcid":9},"Alexis Daniels",{"name":345,"orcid":9},"Andrea Hicks",{"tldr":347,"method":348,"finding":349,"direction":113,"opportunity":350},"开发鱼菜共生系统智能体模型，模拟不同鱼、植物、气候和季节下的温室气体排放，用于教学。","基于智能体的建模（ABM），参数参考文献，输出随机性结果。","模型可交互展示鱼菜共生系统的温室气体排放，促进系统思维学习。","可扩展模型纳入更多环境与经济指标，或开发面向公众的在线交互平台。","2026-10-01T23:30:07.298849Z",{"id":353,"title":354,"url":355,"summary":356,"summary_zh":9,"content":9,"source_name":357,"source_url":355,"published_at":358,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":359,"score_detail":360,"sources":362,"tags":364,"primary_topic":9,"secondary_topics":369,"classification":370,"search_phrases":393,"slug":396,"view_count":397,"doi":398,"paper":399,"created_at":418},3527,"Greenhouse gas emissions assessment and mitigation potential in Pakistan's cattle and Buffalo sector: An IPCC tier 2 inventory method with probabilistic uncertainty modeling","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104994","Greenhouse gas emissions assessment and mitigation potential in Pakistan's cattle and Buffalo sector: An IPCC tier 2 inventory method with probabilistic uncertainty modeling。Agricultural Systems","Agricultural Systems","2026-09-25T00:00:00Z",81,{"impact":134,"substance":132,"depth":134,"authority":135,"freshness":214,"relevant":120,"comment":361},"该研究采用IPCC tier 2方法结合概率不确定性建模，评估巴基斯坦牛与水牛部门温室气体排放及减排潜力，方法新颖、数据扎实，对畜牧业绿色低碳发展有参考价值，但属区域性研究，影响范围有限。",[363],{"name":357,"url":355},[365,21,366,367,368],"畜牧业","减排","巴基斯坦","IPCC方法",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":371},{"candidates":372,"agricultural_evidence":35,"reason":392},[373,377,383,388],{"code":287,"score":227,"supported":35,"title":374,"abstract":375,"tags":376},[298],[298],[],{"code":378,"score":227,"supported":35,"title":379,"abstract":381,"tags":382},"C2",[380],"cattle",[380],[],{"code":384,"score":120,"supported":14,"title":385,"abstract":386,"tags":387},"C",[],[],[365],{"code":319,"score":120,"supported":14,"title":389,"abstract":390,"tags":391},[],[],[21],"多个产业证据相当，需要确认主归属",[394,395],"巴基斯坦 水牛 温室气体","IPCC tier 2 排放清单","巴基斯坦水牛温室气体-3527",5,"10.1016\u002Fj.agsy.2026.104994",{"doi":398,"openalex_id":400,"authors":401,"venue":357,"cited_by_count":15,"oa_url":355,"card":9,"direction":9,"ingested_from":116},"W7214389301",[402,404,407,409,412,415],{"name":403,"orcid":9},"Syed Agha Armaghan Asad Abbas Naqvi",{"name":405,"orcid":406},"Muhammad Waqas Alam Chattha","https:\u002F\u002Forcid.org\u002F0000-0003-1087-0854",{"name":408,"orcid":9},"Syed Akbar",{"name":410,"orcid":411},"Khurram Yousaf","https:\u002F\u002Forcid.org\u002F0000-0002-8897-3629",{"name":413,"orcid":414},"Almazea Fatima","https:\u002F\u002Forcid.org\u002F0009-0005-1654-2503",{"name":416,"orcid":417},"L. A. González","https:\u002F\u002Forcid.org\u002F0000-0002-6400-2588","2026-09-26T23:30:05.095606Z",{"id":420,"title":421,"url":422,"summary":423,"summary_zh":9,"content":9,"source_name":357,"source_url":422,"published_at":358,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":424,"score_detail":425,"sources":427,"tags":429,"primary_topic":433,"secondary_topics":434,"classification":435,"search_phrases":455,"slug":458,"view_count":120,"doi":459,"paper":460,"created_at":484},3526,"Household-level greenhouse gas emissions and economic performance on the Mongolia Plateau: Typology, trade-offs and scenario pathways","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104996","Household-level greenhouse gas emissions and economic performance on the Mongolia Plateau: Typology, trade-offs and scenario pathways。Agricultural Systems",80,{"impact":134,"substance":211,"depth":134,"authority":135,"freshness":214,"relevant":120,"comment":426},"核心期刊论文，基于农户尺度量化温室气体排放与经济绩效的权衡关系并提出情景路径，对牧区绿色低碳发展有参考价值。",[428],{"name":357,"url":422},[365,21,430,431,432],"农户生计","农牧交错带","减排路径",{"code":287,"slug":288,"name":289,"path":290,"parent_code":291},[],{"status":151,"locked":14,"version":28,"method":29,"evidence":436},{"candidates":437,"agricultural_evidence":35},[438,442,446,451],{"code":287,"score":227,"supported":35,"title":439,"abstract":440,"tags":441},[298],[298],[],{"code":384,"score":120,"supported":14,"title":443,"abstract":444,"tags":445},[],[],[365],{"code":447,"score":120,"supported":14,"title":448,"abstract":449,"tags":450},"G6",[],[],[430],{"code":319,"score":120,"supported":14,"title":452,"abstract":453,"tags":454},[],[],[21],[456,457],"蒙古高原 畜牧业 温室气体","农户 温室气体 经济绩效","蒙古高原畜牧业温室气体-3526","10.1016\u002Fj.agsy.2026.104996",{"doi":459,"openalex_id":461,"authors":462,"venue":357,"cited_by_count":15,"oa_url":422,"card":9,"direction":9,"ingested_from":116},"W7214275467",[463,466,468,470,472,474,476,479,482],{"name":464,"orcid":465},"Lulu Wang","https:\u002F\u002Forcid.org\u002F0000-0002-6901-8765",{"name":467,"orcid":9},"Jingfeng Xiao",{"name":469,"orcid":9},"Xinchao Liu",{"name":471,"orcid":9},"Haoqiang Xu",{"name":473,"orcid":9},"Zhuwen Xu",{"name":475,"orcid":9},"Susie Ruqun Wu",{"name":477,"orcid":478},"Yaoqi Zhang","https:\u002F\u002Forcid.org\u002F0009-0005-4435-4868",{"name":480,"orcid":481},"Raffaele Lafortezza","https:\u002F\u002Forcid.org\u002F0000-0003-4642-8435",{"name":483,"orcid":9},"Changliang Shao","2026-09-26T23:30:05.031703Z",{"id":486,"title":487,"url":488,"summary":489,"summary_zh":490,"content":9,"source_name":357,"source_url":488,"published_at":491,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":492,"score_detail":493,"sources":495,"tags":497,"primary_topic":502,"secondary_topics":506,"classification":512,"search_phrases":537,"slug":540,"view_count":541,"doi":542,"paper":543,"created_at":563},3451,"Carbon footprint of Creole goat milk production in Peru under crop-residue and Andean shrubland systems","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104993","CONTEXT Goat farming in Peru is economically marginal yet essential for rural livelihoods and food security. Creole goats are managed extensively on native rangelands or crop residues, but their greenhouse gas emissions remain poorly quantified. OBJECTIVE To assess the carbon footprint (CFP) of Creole goat milk production under two contrasting extensive systems in Lima (crop-residue based) and Ancash (shrubland-based), Peru. METHODS A cradle-to-farm-gate life cycle assessment was conducted on six farms per system during winter and summer. Emissions of CH₄, N₂O and CO₂ were estimated using IPCC methodologies and expressed per kilogram of fat- and protein-corrected milk (FPCM). CFP were analyzed using univariate and mixed-effects models. RESULTS AND CONCLUSIONS System differences in farm characteristics were more pronounced during summer, when Ancash system, compared to Lima system, showed higher dietary fiber concentrations (42.65% vs 33.10%; p \u003C 0.001) and produced milk with greater total solids content (15.38% vs 13.70%; p \u003C 0.05). However, CFP did not differ significantly between systems, ranging from 0.681 to 1.672 kg CO₂-eq kg −1 FPCM, with enteric fermentation accounting for 74–79% of total emissions. Significant system × season interactions for fuel and electricity emissions revealed contrasting seasonal resource-use responses between systems. These findings indicate that seasonal dynamics are a major driver of emission variability, while overall CFP remained comparable between systems. SIGNIFICANCE This study provides the first CFP assessment of Creole goat milk production in Peru and highlights the importance of considering ecosystem and seasonal variability when assessing emissions from marginal goat systems.","背景 秘鲁的山羊养殖在经济上处于边缘地位，但对农村生计和粮食安全至关重要。克里奥尔山羊以粗放方式在天然牧场或作物残茬上饲养，但其温室气体排放量仍缺乏量化研究。目的 评估秘鲁利马（基于作物残茬）和安卡什（基于灌木地）两种对比鲜明的粗放养殖体系下克里奥尔山羊奶生产的碳足迹（CFP）。方法 在冬夏两季对每个体系的六个农场进行了从摇篮到农场门口的生命周期评估。采用IPCC方法估算CH₄、N₂O和CO₂排放量，并以每千克脂肪和蛋白质校正乳（FPCM）表示。采用单变量和混合效应模型分析CFP。结果与结论 农场特征的体系差异在夏季更为明显，此时安卡什体系与利马体系相比，日粮纤维浓度更高（42.65% vs 33.10%；p \u003C 0.001），所产羊奶总固形物含量也更高（15.38% vs 13.70%；p \u003C 0.05）。然而，CFP在体系间无显著差异，范围为0.681至1.672 kg CO₂-eq kg⁻¹ FPCM，其中肠道发酵占总排放的74–79%。燃料和电力排放在体系×季节间存在显著交互作用，揭示了两体系在季节性资源利用响应上的差异。这些发现表明，季节动态是排放变异的主要驱动因素，而总体CFP在体系间保持可比。意义 本研究首次对秘鲁克里奥尔山羊奶生产进行CFP评估，并强调了在评估边缘化山羊体系排放时考虑生态系统和季节变异性的重要性。","2026-09-24T00:00:00Z",69,{"impact":277,"substance":211,"depth":212,"authority":135,"freshness":214,"relevant":120,"comment":494},"首次量化秘鲁克里奥尔山羊奶碳足迹，方法规范数据扎实，但属区域性研究，对国内三农信息化参考价值有限。",[496],{"name":357,"url":488},[21,498,499,500,501],"碳足迹","生命周期评价","山羊养殖","秘鲁农业",{"code":378,"slug":503,"name":504,"path":505,"parent_code":384},"ruminants","草食牲畜","\u002Ftopic\u002Flivestock\u002Fruminants",[507],{"code":319,"slug":508,"name":509,"path":510,"parent_code":511},"carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"status":151,"locked":14,"version":28,"method":29,"evidence":513},{"candidates":514,"agricultural_evidence":35},[515,520,526,533],{"code":319,"score":212,"supported":35,"title":516,"abstract":518,"tags":519},[517],"carbon footprint",[498,517],[21,499,498],{"code":378,"score":135,"supported":35,"title":521,"abstract":523,"tags":525},[522],"goat",[524,522],"山羊",[],{"code":527,"score":119,"supported":35,"title":528,"abstract":529,"tags":532},"A8",[],[530,531],"粮食安全","food security",[],{"code":287,"score":119,"supported":35,"title":534,"abstract":535,"tags":536},[],[300,298],[],[538,539],"秘鲁 山羊 碳足迹","生命周期评价 山羊养殖 温室气体 秘鲁农业","秘鲁山羊碳足迹-3451",4,"10.1016\u002Fj.agsy.2026.104993",{"doi":542,"openalex_id":544,"authors":545,"venue":357,"cited_by_count":15,"oa_url":488,"card":558,"direction":113,"ingested_from":116},"W7214193981",[546,548,550,552,554,556],{"name":547,"orcid":9},"Richard Ayala Roldan",{"name":549,"orcid":9},"Miguel Paredes-Chocce",{"name":551,"orcid":9},"Hugo Castillo Doloriert",{"name":553,"orcid":9},"David Godoy-Padilla",{"name":555,"orcid":9},"Juancarlos Alejandro Cruz-Luis",{"name":557,"orcid":9},"José Antonio Haro-Reyes",{"tldr":559,"method":560,"finding":561,"direction":113,"opportunity":562},"首次评估秘鲁两种放牧系统下克里奥尔山羊奶的碳足迹，发现系统间无显著差异。","生命周期评价，IPCC方法估算CH₄、N₂O、CO₂，混合效应模型分析。","碳足迹为0.681-1.672 kg CO₂-eq\u002Fkg FPCM，肠道发酵占74-79%，季节影响","可探究季节调控放牧管理以减少肠道发酵排放，并拓展其他 marginal 畜牧系统的碳足迹研究。","2026-09-25T23:30:04.201454Z"]