[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3451":3,"related-3451":108},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":45,"search_phrases":78,"slug":81,"view_count":82,"doi":83,"paper":84,"created_at":107},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。",null,"Agricultural Systems","2026-09-24T00:00:00Z","论文",10,false,69,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,21,17,14,9,1,"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。",[25],{"name":10,"url":6},[27,28,29,30,31],"温室气体","碳足迹","生命周期评价","山羊养殖","秘鲁农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"C2","ruminants","草食牲畜","\u002Ftopic\u002Flivestock\u002Fruminants","C",[39],{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"status":46,"locked":14,"version":47,"method":48,"evidence":49},"classified","2026-10-22.2","rules",{"candidates":50,"agricultural_evidence":52},[51,57,63,71],{"code":40,"score":19,"supported":52,"title":53,"abstract":55,"tags":56},true,[54],"carbon footprint",[28,54],[27,29,28],{"code":33,"score":20,"supported":52,"title":58,"abstract":60,"tags":62},[59],"goat",[61,59],"山羊",[],{"code":64,"score":65,"supported":52,"title":66,"abstract":67,"tags":70},"A8",6,[],[68,69],"粮食安全","food security",[],{"code":72,"score":65,"supported":52,"title":73,"abstract":74,"tags":77},"B7",[],[75,76],"温室","greenhouse",[],[79,80],"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":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":99,"oa_url":6,"card":100,"direction":104,"ingested_from":106},"W7214193981",[87,89,91,93,95,97],{"name":88,"orcid":9},"Richard Ayala Roldan",{"name":90,"orcid":9},"Miguel Paredes-Chocce",{"name":92,"orcid":9},"Hugo Castillo Doloriert",{"name":94,"orcid":9},"David Godoy-Padilla",{"name":96,"orcid":9},"Juancarlos Alejandro Cruz-Luis",{"name":98,"orcid":9},"José Antonio Haro-Reyes",0,{"tldr":101,"method":102,"finding":103,"direction":104,"opportunity":105},"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","农业绿色发展与碳","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。","openalex","2026-09-25T23:30:04.201454Z",{"total":65,"page":22,"page_size":65,"items":109},[110,184,280,355,431,481],{"id":111,"title":112,"url":113,"summary":114,"summary_zh":115,"content":9,"source_name":116,"source_url":113,"published_at":117,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":118,"score_detail":119,"sources":125,"tags":127,"primary_topic":131,"secondary_topics":132,"classification":133,"search_phrases":162,"slug":165,"view_count":82,"doi":166,"paper":167,"created_at":183},2634,"Exploring the carbon footprint of Chinese beef systems – a life‑cycle assessment, decoupling analysis and spatial effects","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1849066","Introduction China’s beef cattle industry is currently in a phase of expansion, while its greenhouse gas (GHG) emission characteristics remain insufficiently elucidated. To fill this research gap, this study employed Life Cycle Assessment (LCA) to quantify the carbon footprint of beef cattle production across provinces in mainland China during the period 2002–2022. Methods The analysis encompassed total GHG emissions across three farming scales—small-scale (1–49 heads), medium-scale (50–500 heads), and large-scale (>500 heads)—classified by annual slaughter volume, and divided the entire production system into four stages: feed cultivation, enteric fermentation, manure management, and processing and transportation. Results Large-scale operations exhibited relatively lower carbon intensity, with an average of 23.71 kg CO 2 e per kilogram of beef, whereas all three scales demonstrated a fluctuating yet gradually increasing trend over the study period. Enteric fermentation emerged as the dominant emission source, with an annual average of 268.84 TgCO 2 e. Methane consistently accounted for the largest proportion of GHG emissions, averaging 73.59% of the annual total. Spatially, both total emissions and various carbon intensity indicators showed a westward shift, with western regions lagging behind eastern regions in emission reduction performance. Decoupling analysis revealed that for most provinces from 2002 to 2022, GHG emissions from beef cattle production grew in tandem with the output value of the cattle industry. Spatial regression further identified significant agglomeration effects, with carbon intensity being significantly influenced by the economic level of the beef cattle sector, rural per capita disposable income, the share of the cattle industry in the regional economy, and grain yield.","引言 中国肉牛产业目前正处于扩张阶段，而其温室气体（GHG）排放特征尚不明确。为填补这一研究空白，本研究采用生命周期评价（LCA）方法，对2002—2022年中国大陆各省肉牛生产的碳足迹进行了量化。方法 分析涵盖三种养殖规模——小规模（1—49头）、中规模（50—500头）和大规模（>500头）——按年出栏量划分，并将整个生产系统分为四个阶段：饲料种植、肠道发酵、粪便管理和加工运输。结果 大规模养殖的碳强度相对较低，平均为每千克牛肉23.71 kg CO₂e，但三种规模在研究期间均呈现波动上升趋势。肠道发酵是主要排放源，年均排放量为268.84 TgCO₂e。甲烷始终占温室气体排放的最大比例，年均占总量的73.59%。在空间分布上，总排放量和各项碳强度指标均呈现向西转移的趋势，西部地区的减排表现落后于东部地区。脱钩分析表明，2002—2022年大多数省份的肉牛生产温室气体排放与养牛业产值同步增长。空间回归进一步识别出显著的集聚效应，碳强度受肉牛产业经济水平、农村人均可支配收入、养牛业在区域经济中的占比以及粮食产量的显著影响。","Frontiers in Sustainable Food Systems","2026-09-15T00:00:00Z",84,{"impact":120,"substance":121,"depth":122,"authority":123,"freshness":17,"relevant":22,"comment":124},22,23,18,13,"基于2002—2022年全国省级面板数据的肉牛全生命周期碳足迹核算，方法规范、数据规模大，揭示规模效应与排放西移趋势，对畜牧业绿色低碳转型有参考价值。",[126],{"name":116,"url":113},[128,28,29,129,130],"农业绿色发展","肉牛产业","畜牧业减排",{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},[],{"status":46,"locked":14,"version":47,"method":48,"evidence":134},{"candidates":135,"agricultural_evidence":52},[136,140,144,150,157],{"code":40,"score":19,"supported":52,"title":137,"abstract":138,"tags":139},[54],[28,54],[128,29,28],{"code":72,"score":65,"supported":52,"title":141,"abstract":142,"tags":143},[],[75,76],[],{"code":33,"score":65,"supported":52,"title":145,"abstract":146,"tags":149},[],[147,148],"肉牛","cattle",[],{"code":151,"score":152,"supported":52,"title":153,"abstract":154,"tags":156},"C4",3,[],[155],"饲料",[],{"code":158,"score":22,"supported":14,"title":159,"abstract":160,"tags":161},"H8",[],[],[128],[163,164],"农业绿色发展 生命周期评价 畜牧业减排 肉牛产业","农业绿色发展 生命周期评价","农业绿色发展生命周期评价畜牧业减排肉牛产业-2634","10.3389\u002Ffsufs.2026.1849066",{"doi":166,"openalex_id":168,"authors":169,"venue":116,"cited_by_count":99,"oa_url":113,"card":178,"direction":104,"ingested_from":106},"W7213306361",[170,172,174,176],{"name":171,"orcid":9},"Xianghui Yin",{"name":173,"orcid":9},"Shiqin Sun",{"name":175,"orcid":9},"Jiangge Wang",{"name":177,"orcid":9},"Tengyun Gao",{"tldr":179,"method":180,"finding":181,"direction":104,"opportunity":182},"用生命周期评估量化2002–2022年中国各省肉牛碳足迹，并分析脱钩与空间效应。","生命周期评估、脱钩分析、空间回归，覆盖三种养殖规模与四个生产阶段。","大规模养殖碳强度较低，肠道发酵为主排放源，排放呈西移趋势且多省未脱钩。","可探究西部减排滞后地区的规模优化与甲烷减排技术，及空间溢出机制。","2026-09-16T23:30:08.249805Z",{"id":185,"title":186,"url":187,"summary":188,"summary_zh":189,"content":9,"source_name":190,"source_url":187,"published_at":191,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":192,"score_detail":193,"sources":196,"tags":198,"primary_topic":203,"secondary_topics":204,"classification":205,"search_phrases":262,"slug":265,"view_count":99,"doi":266,"paper":267,"created_at":279},4879,"Smart and Mechanized Feeding Systems for Goat Farming: Integrating Agricultural Engineering, Precision Livestock Management, and Sustainable Rural Development","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23344398","2. Alternative Research Titles 1. Design and Development of an Automated Goat Feeding System for Improved Farm Productivity and Labour Efficiency 2. Mechanization of Goat Feeding Operations: Engineering Innovations for Sustainable Livestock Production 3. Smart Livestock Feeding Technologies: A Framework for Automated Feed Distribution and Precision Goat Farming 4. Low-Cost Automated Feeding Systems for Smallholder Goat Farms: Design Considerations, Operational Efficiency, and Economic Feasibility 5. Application of Sensor-Based Automation in Goat Farming: Advancing Feed Management and Rural Agricultural Productivity 6. Intelligent Feeding Mechanisms for Small Ruminants: Integrating Mechanical Design, Automation, and Digital Monitoring 7. Sustainable Goat Farming Through Feeding Automation: Opportunities, Challenges, and Technological Perspectives 8. Engineering Approaches to Livestock Feed Management: Development of Mechanized Feeding Systems for Small and Medium-Scale Goat Farms 9. Precision Feeding in Goat Production: Integrating Smart Sensors, Automated Dispensing, and Sustainable Farm Management 10. From Traditional Feeding to Smart Livestock Farming: A Technology-Driven Approach to Goat Feed Distribution 3. Suggested Subtitle An Engineering-Based Framework for Automated Feed Distribution, Labour Reduction, Feed-Waste Management, and Affordable Precision Livestock Production in India. 4. Detailed Research Description Research Description Research Description The proposed research investigates the design principles, operational requirements, and potential agricultural applications of smart and mechanized feeding systems for goat farming. Inspired by a Telugu newspaper article depicting a mechanized feeding arrangement, the study explores how engineering innovations can improve the efficiency, consistency, and sustainability of livestock feeding operations. Traditional goat-feeding practices frequently involve manual feed preparation, transportation, and distribution. These activities can require substantial labour and may result in inconsistent feed allocation, spillage, and limited documentation of feed consumption. The proposed research addresses these challenges through a conceptual framework that combines mechanical feed handling, controlled dispensing, suitable distribution mechanisms, and optional sensor-assisted monitoring. The study will examine the integration of feed-storage hoppers, metering devices, motor-driven mechanisms, weighing sensors, microcontrollers, and monitoring interfaces. Particular attention will be given to the suitability of these components for different feed materials, including chopped fodder, forage mixtures, and concentrated feed. The system will be designed around the operational requirements of small and medium-scale goat farms, with emphasis on affordability, reliability, ease of maintenance, and adaptability to Indian agricultural conditions. A central component of the research is the development of a quantitative evaluation framework for comparing mechanized and conventional feeding practices. Relevant performance indicators include labour time per feeding cycle, feed-distribution uniformity, feed wastage, energy consumption, equipment reliability, maintenance requirements, and overall operating cost. If a prototype is constructed, controlled testing and farm-based trials can be used to determine whether the proposed design provides measurable improvements under realistic operating conditions. The research will also consider the role of digital technologies in precision livestock farming. Sensors and automated recordkeeping could support monitoring of delivered feed quantities, feed-bin levels, and equipment performance. Future extensions may incorporate Internet of Things connectivity and data analytics to support farm-management decisions. However, the system will be designed to retain essential operating and safety functions even when internet connectivity is unavailable. Animal welfare, nutritional suitability, and farm economics will remain central considerations. Mechanization must ensure appropriate feed access, hygienic feeding conditions, safe equipment operation, and compatibility with the nutritional requirements of goats. Economic analysis will examine initial investment, labour savings, potential reductions in feed losses, maintenance costs, energy requirements, and estimated payback period. The expected contribution is an engineering framework for developing and evaluating practical feeding automation technologies for goat farming. By connecting mechanical design with livestock-management requirements and rural economic considerations, the study seeks to establish a foundation for affordable, scalable, and sustainable agricultural mechanization. The proposed benefits will need to be established through prototype development and empirical validation rather than assumed in advance. 5. Research Objectives To develop a conceptual design for a mechanized goat-feeding system. To identify suitable feed-storage, metering, and distribution mechanisms. To evaluate the potential integration of sensors and automated control. To establish quantitative measures of feeding efficiency and feed wastage. To assess operational safety, animal welfare, and maintenance requirements. To formulate an economic evaluation framework for smallholder adoption. To propose future opportunities for IoT-enabled precision livestock management. 6. Proposed Research Novelty The potential novelty lies in integrating affordable mechanical feeding, quantity-controlled dispensing, and sensor-assisted monitoring into a modular system specifically evaluated for small and medium-scale goat farms. The novelty should be established through a systematic review of existing patents and research publications, followed by a clear comparison with previously developed livestock-feeding systems. The combination of existing components alone does not establish scientific novelty; the contribution should be demonstrated through a new design, validated performance improvement, or original experimental findings. 7. Recommended Keywords Goat farming; mechanized feeding; automated feed distribution; precision livestock farming; agricultural engineering; smart agriculture; feed management; Internet of Things; sustainable livestock production; rural mechanization; sensor-based automation; smallholder farming. 8. Author Details Geruganti Sudhakar Faculty Rajiv Gandhi University of Knowledge Technologies (RGUKT), IIIT Basar Telangana, India. My recommendation: Use the combined title in Section 1 for a broad, interdisciplinary review paper. If you plan to fabricate and experimentally test a feeder, Alternative Title 1 is more appropriate because it clearly communicates an engineering-development and validation study.","2. 备选研究标题 1. 用于提高农场生产力和劳动效率的自动化山羊饲喂系统的设计与开发 2. 山羊饲喂作业的机械化：可持续畜牧生产的工程创新 3. 智能畜牧饲喂技术：自动化饲料分配与精准山羊养殖框架 4. 面向小农户山羊养殖场的低成本自动化饲喂系统：设计考量、运行效率与经济可行性 5. 基于传感器的自动化技术在山羊养殖中的应用：推进饲料管理与农村农业生产力 6. 小型反刍动物的智能饲喂机制：机械设计、自动化与数字化监测的集成 7. 通过饲喂自动化实现可持续山羊养殖：机遇、挑战与技术展望 8. 畜牧饲料管理的工程方法：面向中小规模山羊养殖场的机械化饲喂系统开发 9. 山羊生产中的精准饲喂：智能传感器、自动化投喂与可持续农场管理的集成 10. 从传统饲喂到智能畜牧养殖：一种技术驱动的山羊饲料分配方法 3. 建议副标题 一种基于工程的框架，用于印度自动化饲料分配、劳动力减少、饲料浪费管理及可负担的精准畜牧生产。 4. 详细研究描述 研究描述 研究描述 本研究拟探讨山羊养殖中智能化和机械化饲喂系统的设计原理、运行要求及潜在农业应用。受一篇描述机械化饲喂装置的泰卢固语报纸文章启发，本研究探索工程创新如何提升畜牧饲喂作业的效率、一致性和可持续性。传统的山羊饲喂方式通常涉及人工饲料制备、运输和分配。这些活动可能需要大量劳动力，并可能导致饲料分配不均、撒漏以及饲料消耗记录有限。本研究拟通过一个概念框架应对这些挑战，该框架结合机械饲料处理、受控投喂、适宜的分配机制以及可选的传感器辅助监测。研究将考察饲料储存料斗、计量装置、电机驱动机构、称重传感器、","Zenodo (CERN European Organization for Nuclear Research)","2026-10-13T00:00:00Z",45,{"impact":17,"substance":194,"depth":13,"authority":65,"freshness":21,"relevant":22,"comment":195},12,"概念性研究提案，聚焦小规模山羊养殖的机械化与精准饲喂框架，对智慧畜牧方向有参考价值但尚无实证数据。",[197],{"name":190,"url":187},[199,200,201,202,30],"智慧农业","农业物联网","农业机械化","精准畜牧",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":46,"locked":14,"version":47,"method":48,"evidence":206},{"candidates":207,"agricultural_evidence":52},[208,214,218,224,231,238,243,250,256],{"code":37,"score":20,"supported":52,"title":209,"abstract":211,"tags":213},[210],"livestock",[212,210],"畜牧",[],{"code":33,"score":20,"supported":52,"title":215,"abstract":216,"tags":217},[59],[61,59],[],{"code":219,"score":17,"supported":52,"title":220,"abstract":222,"tags":223},"G",[221],"rural development",[],[],{"code":225,"score":226,"supported":52,"title":227,"abstract":228,"tags":230},"C6",7,[],[202,229],"animal welfare",[202],{"code":232,"score":226,"supported":52,"title":233,"abstract":234,"tags":237},"I5",[],[235,236],"internet of things","IoT",[200],{"code":151,"score":65,"supported":52,"title":239,"abstract":240,"tags":242},[],[155,241],"forage",[],{"code":244,"score":65,"supported":52,"title":245,"abstract":246,"tags":249},"G2",[],[247,248],"小农户","smallholder",[],{"code":251,"score":82,"supported":52,"title":252,"abstract":253,"tags":255},"F5",[],[254],"机械化",[201],{"code":257,"score":82,"supported":52,"title":258,"abstract":259,"tags":261},"I1",[],[260],"smart agriculture",[199],[263,264],"山羊 机械化饲喂 系统","精准畜牧 自动投喂 印度","山羊机械化饲喂系统-4879","10.5281\u002Fzenodo.23344398",{"doi":266,"openalex_id":268,"authors":269,"venue":190,"cited_by_count":99,"oa_url":187,"card":273,"direction":277,"ingested_from":106},"W7221716542",[270],{"name":271,"orcid":272},"Sudhakar Geruganti","https:\u002F\u002Forcid.org\u002F0009-0000-0039-7536",{"tldr":274,"method":275,"finding":276,"direction":277,"opportunity":278},"提出山羊养殖智能机械化喂料系统的设计框架，整合工程、精准畜牧与农村可持续发展。","概念框架设计，结合料斗、计量装置、电机驱动、称重传感器等。","机械化喂料可减少劳动力、稳定投喂量、降低饲料浪费并提升记录能力。","智慧农业 \u002F 农业物联网","面向小农户的低成本自动化喂料系统缺乏实证，可研究其经济可行性与传感器集成效果。","2026-10-14T23:30:08.923193Z",{"id":281,"title":282,"url":283,"summary":284,"summary_zh":9,"content":9,"source_name":10,"source_url":283,"published_at":285,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":286,"score_detail":287,"sources":290,"tags":292,"primary_topic":297,"secondary_topics":302,"classification":304,"search_phrases":321,"slug":324,"view_count":325,"doi":326,"paper":327,"created_at":354},2022,"Greenhouse gas emissions, carbon footprint and ecosystem economic performance of tropical pineapple fields: responses to five practical pineapple straw management patterns","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104948","Greenhouse gas emissions, carbon footprint and ecosystem economic performance of tropical pineapple fields: responses to five practical pineapple straw management patterns。Agricultural Systems","2026-09-09T00:00:00Z",76,{"impact":288,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":289},15,"热带菠萝园秸秆管理模式的温室气体与碳足迹研究，数据与结论具增量，但属细分作物领域，产业影响有限。",[291],{"name":10,"url":283},[293,28,294,295,296],"生态经济","农业减排","菠萝","秸秆利用",{"code":72,"slug":298,"name":299,"path":300,"parent_code":301},"protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[303],{"code":40,"slug":41,"name":42,"path":43,"parent_code":44},{"status":46,"locked":14,"version":47,"method":48,"evidence":305},{"candidates":306,"agricultural_evidence":52},[307,311,316],{"code":40,"score":123,"supported":52,"title":308,"abstract":309,"tags":310},[54],[54],[294,28],{"code":72,"score":312,"supported":52,"title":313,"abstract":314,"tags":315},11,[76],[76],[],{"code":317,"score":22,"supported":14,"title":318,"abstract":319,"tags":320},"H5",[],[],[296],[322,323],"农业减排 生态经济 秸秆利用 碳足迹","农业减排 生态经济","农业减排生态经济秸秆利用碳足迹-2022",2,"10.1016\u002Fj.agsy.2026.104948",{"doi":326,"openalex_id":328,"authors":329,"venue":10,"cited_by_count":99,"oa_url":9,"card":9,"direction":9,"ingested_from":106},"W7212051523",[330,333,336,338,340,343,344,347,350,351],{"name":331,"orcid":332},"Xin Jin","https:\u002F\u002Forcid.org\u002F0000-0002-7737-7506",{"name":334,"orcid":335},"Shoupeng Li","https:\u002F\u002Forcid.org\u002F0000-0002-5009-8013",{"name":337,"orcid":9},"Mingwan Chen",{"name":339,"orcid":9},"Chuangjun Wu",{"name":341,"orcid":342},"Changzhen Li","https:\u002F\u002Forcid.org\u002F0000-0002-8089-4838",{"name":341,"orcid":342},{"name":345,"orcid":346},"Huanyu Bao","https:\u002F\u002Forcid.org\u002F0009-0004-8127-1888",{"name":348,"orcid":349},"Changjiang Li","https:\u002F\u002Forcid.org\u002F0000-0002-5545-9690",{"name":348,"orcid":349},{"name":352,"orcid":353},"Yunze Ruan","https:\u002F\u002Forcid.org\u002F0000-0003-0079-9353","2026-09-10T23:30:04.465334Z",{"id":356,"title":357,"url":358,"summary":359,"summary_zh":360,"content":9,"source_name":361,"source_url":358,"published_at":362,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":363,"score_detail":364,"sources":366,"tags":368,"primary_topic":372,"secondary_topics":373,"classification":375,"search_phrases":401,"slug":404,"view_count":82,"doi":405,"paper":406,"created_at":430},1412,"Review: Opportunities for Data Based On-Farm Estimation of Greenhouse Gas Emissions from Ruminants Farming Systems","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.animal.2026.101946","Livestock farming has become increasingly digitalized in large parts of the world. Sensor technologies can be used to mitigate emissions from farming in several ways including improved efficiency of operations. The data that farmers collect to monitor and optimize their production offer a possibility to increase the accuracy of (GHG) emission estimation if utilized fully. However, technologies developed for farm management may not meet requirements for monitoring of GHG greenhouse gas emissions where high accuracy is required. The cost benefit and reliability of farm level data collection need to be considered before investing effort in their widespread adoption. The lack of access to data and poor interoperability of the data across different software systems also currently limits the use of data, however there are several data sharing initiatives, such as data spaces, that aim to develop the farmers right to data sovereignty and provide contractual and technical solutions for increasing data availability. This review assesses the state-of-the-art of the digital data collection and sharing usable for GHG accounting from ruminant farming systems perspective with focus on commercially available on-farm technology. A review of the accuracy of different methods and two case studies on the impact of the uncertainty of digital data sources on CH 4 emission prediction uncertainty quantified using Monte Carlo simulation are presented. In conclusion the greatest potential for automating the LCA process and coverage of production for national inventories exists for dairy cattle, sheep and goat farms with daily milk yield recording and high technology feeding systems and lowest for pasture based meat production systems. The use of on-farm data for GHG accounting provides an opportunity for more targeted mitigation and even differential product pricing favouring the lowest emitting farms within a region. The reliability as well as contribution to overall emissions of each additional data source collected from farms should be assessed before it is taken into use and calibration protocols for farmers to ensure accurate data should be developed and their application monitored.","畜牧业在全球大部分地区已日益数字化。传感器技术可通过多种方式减少农业排放，包括提高作业效率。农民为监测和优化生产所收集的数据，若得到充分利用，有望提高温室气体（GHG）排放估算的准确性。然而，为农场管理开发的技术可能无法满足对高精度要求的温室气体排放监测需求。在投入精力广泛采用这些技术之前，需权衡农场级数据收集的成本效益与可靠性。目前，数据获取渠道有限以及不同软件系统间数据互操作性差也制约了数据的使用，不过已有多个数据共享倡议（如数据空间）致力于发展农民的数据主权，并提供合同和技术解决方案以增强数据可用性。本综述从反刍动物养殖系统的视角，评估了可用于温室气体核算的数字数据收集与共享的现状，重点关注市售的农场技术。文中综述了不同方法的准确性，并展示了两项案例研究，利用蒙特卡洛模拟量化了数字数据源不确定性对甲烷（CH₄）排放预测不确定性的影响。结论表明，对于奶牛、绵羊和山羊养殖场，若具备每日产奶量记录和高度技术化的饲喂系统，其生命周期评估（LCA）流程自动化及生产覆盖国家清单的潜力最大；而对于基于放牧的肉类生产系统，这一潜力最低。将农场数据用于温室气体核算，为实现更有针对性的减排乃至差异化产品定价提供了机会，可惠及区域内排放最低的养殖场。在采用从农场收集的每一项额外数据源之前，应评估其可靠性及对整体排放的贡献，并应制定供农民使用的校准协议以确保数据准确性，同时对其应用进行监测。","animal","2026-09-01T00:00:00Z",78,{"impact":122,"substance":120,"depth":122,"authority":123,"freshness":226,"relevant":22,"comment":365},"综述评估了利用农场数字数据估算反刍动物温室气体排放的潜力与挑战，对农业碳核算和减排有重要参考价值。",[367],{"name":361,"url":358},[199,27,369,370,371],"畜牧养殖","数据共享","碳排放核算",{"code":72,"slug":298,"name":299,"path":300,"parent_code":301},[374],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":46,"locked":14,"version":47,"method":48,"evidence":376},{"candidates":377,"agricultural_evidence":52},[378,382,389,393,397],{"code":72,"score":20,"supported":52,"title":379,"abstract":380,"tags":381},[76],[75,76],[],{"code":33,"score":21,"supported":52,"title":383,"abstract":384,"tags":388},[],[385,386,61,148,387,59],"奶牛","绵羊","sheep",[],{"code":37,"score":65,"supported":52,"title":390,"abstract":391,"tags":392},[],[212,210],[],{"code":40,"score":22,"supported":14,"title":394,"abstract":395,"tags":396},[],[],[27],{"code":257,"score":22,"supported":14,"title":398,"abstract":399,"tags":400},[],[],[199],[402,403],"碳排放核算 数据共享 智慧农业 温室气体","碳排放核算 数据共享","碳排放核算数据共享智慧农业温室气体-1412","10.1016\u002Fj.animal.2026.101946",{"doi":405,"openalex_id":407,"authors":408,"venue":361,"cited_by_count":99,"oa_url":424,"card":425,"direction":277,"ingested_from":106},"W7204954019",[409,412,415,417,419,421],{"name":410,"orcid":411},"Matti Pastell","https:\u002F\u002Forcid.org\u002F0000-0002-5810-4801",{"name":413,"orcid":414},"Vasileios Anestis","https:\u002F\u002Forcid.org\u002F0000-0003-4260-1763",{"name":416,"orcid":9},"A. Romera",{"name":418,"orcid":9},"A.M. Mazzetto",{"name":420,"orcid":9},"P. Ricci",{"name":422,"orcid":423},"Maguy Eugène","https:\u002F\u002Forcid.org\u002F0000-0002-2111-0597","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS175173112600193X\u002Fpdf",{"tldr":426,"method":427,"finding":428,"direction":104,"opportunity":429},"综述利用农场数字数据估算反刍动物温室气体排放的机遇与挑战。","综述现有技术，结合蒙特卡洛模拟案例评估数据不确定性影响。","奶牛、绵羊、山羊场数据潜力大，肉牛放牧系统潜力低。","可研究农场数据用于碳核算的校准协议及数据共享机制，提升估算准确性。","2026-09-02T23:30:13.638840Z",{"id":432,"title":433,"url":434,"summary":435,"summary_zh":9,"content":9,"source_name":10,"source_url":434,"published_at":436,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":437,"score_detail":438,"sources":441,"tags":443,"primary_topic":447,"secondary_topics":448,"classification":449,"search_phrases":460,"slug":463,"view_count":99,"doi":464,"paper":465,"created_at":480},5542,"Beyond profitability: heterogeneous associations between ESG-related mechanisms and farm economic sustainability-evidence from Spanish sheep and goat farming","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.105022","Beyond profitability: heterogeneous associations between ESG-related mechanisms and farm economic sustainability-evidence from Spanish sheep and goat farming。Agricultural Systems","2026-10-21T00:00:00Z",66,{"impact":17,"substance":122,"depth":439,"authority":20,"freshness":13,"relevant":22,"comment":440},16,"西班牙羊山羊养殖ESG与经济可持续性实证研究，方法有一定新意但属区域性细分议题，公共影响有限，不宜进入每日精选。",[442],{"name":10,"url":434},[444,369,445,446],"可持续农业","ESG","农场经济",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":46,"locked":14,"version":47,"method":48,"evidence":450},{"candidates":451,"agricultural_evidence":52},[452,456],{"code":33,"score":120,"supported":52,"title":453,"abstract":454,"tags":455},[387,59],[387,59],[],{"code":158,"score":22,"supported":14,"title":457,"abstract":458,"tags":459},[],[],[444],[461,462],"西班牙 养殖 ESG","可持续农业 农场经济 畜牧养殖 ESG","西班牙养殖ESG-5542","10.1016\u002Fj.agsy.2026.105022",{"doi":464,"openalex_id":466,"authors":467,"venue":10,"cited_by_count":99,"oa_url":434,"card":9,"direction":9,"ingested_from":106},"W7223120996",[468,471,474,477],{"name":469,"orcid":470},"Maria Llanos Soria-Oliver","https:\u002F\u002Forcid.org\u002F0009-0005-2631-1135",{"name":472,"orcid":473},"Carolina Pontones Rosa","https:\u002F\u002Forcid.org\u002F0000-0001-6989-7969",{"name":475,"orcid":476},"Inmaculada Alonso Carrillo","https:\u002F\u002Forcid.org\u002F0000-0002-0813-9934",{"name":478,"orcid":479},"Rosario Pérez Morote","https:\u002F\u002Forcid.org\u002F0000-0001-5502-3646","2026-10-22T11:20:12.622588Z",{"id":482,"title":483,"url":484,"summary":485,"summary_zh":9,"content":9,"source_name":486,"source_url":9,"published_at":487,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":488,"score_detail":489,"sources":491,"tags":493,"primary_topic":499,"secondary_topics":500,"classification":507,"search_phrases":519,"slug":522,"view_count":99,"doi":9,"paper":523,"created_at":531},5534,"DC-YOLO：应对遮挡与光照变化的湖羊行为检测模型","https:\u002F\u002Ffinance.sina.com.cn\u002Froll\u002F2026-10-19\u002Fdoc-inivumaf7730137.shtml","中国农业大学团队针对集约化养殖中多目标严重遮挡、光照多变与类别不均问题，引入自适应细节—上下文注意力机制构建模块，并采用边界框相似度软抑制防止误删遮挡目标，预训练光照编码器迁移参数应对光照变化。数据集来自湖羊养殖场全天候监控，含505张标注图像、5类行为。","智慧农业（中英文）2026-10-19","2026-10-19T00:00:00Z",75,{"impact":122,"substance":18,"depth":19,"authority":123,"freshness":65,"relevant":22,"comment":490},"论文提出面向湖羊行为检测的DC-YOLO模型，方法有新意、数据来自真实养殖场，属智慧养殖细分领域实质进展，值得精选。",[492],{"name":486,"url":484},[494,495,496,497,498],"农业人工智能","智慧养殖","目标检测","湖羊","动物行为检测",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[501],{"code":502,"slug":503,"name":504,"path":505,"parent_code":506},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":46,"locked":14,"version":47,"method":48,"evidence":508},{"candidates":509,"agricultural_evidence":52},[510,514],{"code":33,"score":194,"supported":52,"title":511,"abstract":512,"tags":513},[497],[497],[497],{"code":502,"score":13,"supported":52,"title":515,"abstract":517,"tags":518},[516],"YOLO",[],[494,496],[520,521],"中国农业大学 湖羊 行为检测","DC-YOLO 遮挡 光照","中国农业大学湖羊行为检测-5534",{"doi":9,"openalex_id":9,"authors":524,"venue":9,"cited_by_count":99,"oa_url":9,"card":525,"direction":277,"ingested_from":530},[],{"tldr":526,"method":527,"finding":528,"direction":277,"opportunity":529},"提出DC-YOLO模型，用于湖羊行为检测，解决遮挡与光照变化问题。","自适应细节-上下文注意力、边界框相似度软抑制、光照编码器迁移，505张标注图像。","模型在遮挡和光照变化下有效检测湖羊行为，减少误删。","可探索多模态融合与轻量化部署，提升复杂养殖场景下的实时行为监测能力。","agent","2026-10-22T00:07:09.998247Z"]