[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3526":3,"related-3526":97},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":65,"slug":68,"view_count":20,"doi":69,"paper":70,"created_at":96},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",null,"Agricultural Systems","2026-09-25T00:00:00Z","论文",10,false,80,{"impact":16,"substance":17,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":21},18,21,14,9,1,"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。",[23],{"name":9,"url":6},[25,26,27,28,29],"畜牧业","温室气体","农户生计","农牧交错带","减排路径",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"B7","protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[],{"status":38,"locked":13,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45},[43,50,55,60],{"code":31,"score":44,"supported":45,"title":46,"abstract":48,"tags":49},11,true,[47],"greenhouse",[47],[],{"code":51,"score":20,"supported":13,"title":52,"abstract":53,"tags":54},"C",[],[],[25],{"code":56,"score":20,"supported":13,"title":57,"abstract":58,"tags":59},"G6",[],[],[27],{"code":61,"score":20,"supported":13,"title":62,"abstract":63,"tags":64},"H4",[],[],[26],[66,67],"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":69,"openalex_id":71,"authors":72,"venue":9,"cited_by_count":94,"oa_url":6,"card":8,"direction":8,"ingested_from":95},"W7214275467",[73,76,78,80,82,84,86,89,92],{"name":74,"orcid":75},"Lulu Wang","https:\u002F\u002Forcid.org\u002F0000-0002-6901-8765",{"name":77,"orcid":8},"Jingfeng Xiao",{"name":79,"orcid":8},"Xinchao Liu",{"name":81,"orcid":8},"Haoqiang Xu",{"name":83,"orcid":8},"Zhuwen Xu",{"name":85,"orcid":8},"Susie Ruqun Wu",{"name":87,"orcid":88},"Yaoqi Zhang","https:\u002F\u002Forcid.org\u002F0009-0005-4435-4868",{"name":90,"orcid":91},"Raffaele Lafortezza","https:\u002F\u002Forcid.org\u002F0000-0003-4642-8435",{"name":93,"orcid":8},"Changliang Shao",0,"openalex","2026-09-26T23:30:05.031703Z",{"total":98,"page":20,"page_size":98,"items":99},6,[100,182,253,390,477,546],{"id":101,"title":102,"url":103,"summary":104,"summary_zh":105,"content":8,"source_name":106,"source_url":103,"published_at":107,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":108,"score_detail":109,"sources":114,"tags":116,"primary_topic":121,"secondary_topics":122,"classification":123,"search_phrases":157,"slug":160,"view_count":161,"doi":162,"paper":163,"created_at":181},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":110,"substance":16,"depth":111,"authority":112,"freshness":98,"relevant":20,"comment":113},8,16,13,"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。",[115],{"name":106,"url":103},[117,118,26,119,120],"智慧农业","设施农业","水产养殖","系统思维",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":124},{"candidates":125,"agricultural_evidence":45},[126,133,141,148,152],{"code":31,"score":127,"supported":45,"title":128,"abstract":129,"tags":132},17,[47],[130,131,47],"温室","无土栽培",[],{"code":134,"score":135,"supported":45,"title":136,"abstract":137,"tags":140},"D",7,[],[138,139],"水产","aquaculture",[119],{"code":142,"score":143,"supported":45,"title":144,"abstract":145,"tags":147},"H2",3,[],[146],"soil",[],{"code":61,"score":20,"supported":13,"title":149,"abstract":150,"tags":151},[],[],[26],{"code":153,"score":20,"supported":13,"title":154,"abstract":155,"tags":156},"I1",[],[],[117],[158,159],"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":162,"openalex_id":164,"authors":165,"venue":106,"cited_by_count":94,"oa_url":103,"card":175,"direction":179,"ingested_from":95},"W7214975686",[166,169,171,173],{"name":167,"orcid":168},"Marissa Breitenstein","https:\u002F\u002Forcid.org\u002F0009-0005-2148-8812",{"name":170,"orcid":8},"Elisabeth Bautista",{"name":172,"orcid":8},"Alexis Daniels",{"name":174,"orcid":8},"Andrea Hicks",{"tldr":176,"method":177,"finding":178,"direction":179,"opportunity":180},"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。","农业绿色发展与碳","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":183,"title":184,"url":185,"summary":186,"summary_zh":187,"content":8,"source_name":188,"source_url":185,"published_at":189,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":190,"score_detail":191,"sources":195,"tags":197,"primary_topic":202,"secondary_topics":203,"classification":208,"search_phrases":234,"slug":237,"view_count":143,"doi":238,"paper":239,"created_at":252},2531,"Spatial Coupling of Greenhouse Gas Emissions, Vegetation Activity, Groundwater Nitrate Occurrence, and Soil Environments Across Denmark: A 5-km Spatial Association and Soil-Stratified Analysis","https:\u002F\u002Fdoi.org\u002F10.31223\u002Fx5rj7d","Integrated environmental assessment increasingly requires the joint analysis of atmospheric emissions, vegetation dynamics, groundwater quality, and soil context rather than isolated thematic mapping. We developed a Denmark-wide 5-km analytical grid in EPSG:25832 containing 1,803 cells and harmonized four continuous environmental indicators: CO2 and CH4 emissions from EDGAR, vegetation activity represented by 2024 MODIS NDVI, and groundwater nitrate occurrence derived from national GEUS observations. Soil information from the GEUS Digital Soil Map was used to stratify environmental associations into five broad environmental groups. Global Pearson, Spearman, and Kendall associations were complemented by global Moran’s I, directional bivariate Moran’s I, local bivariate spatial association, an upper-1% CO2 sensitivity analysis, and soil-stratified statistics. CO2 and NDVI showed the strongest national association (Pearson r = −0.2621), while CH4 was positively associated with CO2 (r = 0.0898) and nitrate occurrence (r = 0.0792). All four continuous variables exhibited significant positive spatial autocorrelation under both Queen and Rook contiguity, with the strongest structure for CH4 and CO2 and the weakest for nitrate. Bivariate Moran analysis supported a negative CO2–NDVI cross-association and positive CH4–CO2 and CH4–nitrate cross-associations. Soil-stratified results showed substantial heterogeneity; the strongest Pearson CO2–NDVI association occurred in Human-affected & Technological environments (r = −0.6208), whereas Sandy & Poor and Sedimentary & Clay-rich environments displayed the clearest positive CH4–CO2 associations. The study is explicitly associative rather than causal. Its principal contribution is a spatially explicit national screening framework that reveals where environmental indicators co-occur, where relationships are spatially organized, and where targeted process-based investigation and monitoring may be most informative.","综合环境评估日益需要对大气排放、植被动态、地下水质量和土壤背景进行联合分析，而非孤立的专题制图。我们构建了一个覆盖丹麦全境、分辨率为5 km的EPSG:25832分析网格，包含1,803个单元，并统一整合了四项连续环境指标：来自EDGAR的CO2和CH4排放、以2024年MODIS NDVI表示的植被活动，以及源自GEUS国家观测数据的地下水硝酸盐赋存情况。来自GEUS数字土壤图的土壤信息被用于将环境关联分层为五个广泛的环境组。在全局Pearson、Spearman和Kendall关联分析的基础上，辅以全局Moran's I、方向性双变量Moran's I、局部双变量空间关联、前1% CO2敏感性分析以及土壤分层统计。CO2与NDVI在全国尺度上表现出最强的关联（Pearson r = −0.2621），而CH4与CO2（r = 0.0898）及硝酸盐赋存（r = 0.0792）呈正相关。四个连续变量在Queen和Rook邻接下均表现出显著的正空间自相关，其中CH4和CO2的空间结构最强，硝酸盐最弱。双变量Moran分析支持CO2–NDVI的负向交叉关联以及CH4–CO2和CH4–硝酸盐的正向交叉关联。土壤分层结果显示出显著异质性；最强的Pearson CO2–NDVI关联出现在人类影响与技术环境中（r = −0.6208），而砂质贫瘠环境和沉积物–黏土丰富环境则表现出最明显的CH4–CO2正相关。本研究明确为关联性而非因果性研究。其主要贡献在于提供了一个空间显式的全国筛查框架，揭示环境指标在何处共现、关系在何处呈现空间组织，以及有针对性的过程性研究与监测在何处可能最具信息价值。","OpenAlex","2026-09-14T00:00:00Z",71,{"impact":192,"substance":193,"depth":127,"authority":112,"freshness":19,"relevant":20,"comment":194},12,20,"基于全国5公里网格整合温室气体、植被、地下水硝酸盐与土壤环境的空间关联研究，方法系统、数据规模大，对农业环境监测与空间筛查有参考价值，但属关联性分析而非因果结论。",[196],{"name":188,"url":185},[198,26,199,200,201],"农业遥感","空间分析","地下水质量","土壤环境",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[204],{"code":142,"slug":146,"name":205,"path":206,"parent_code":207},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"status":38,"locked":13,"version":39,"method":40,"evidence":209},{"candidates":210,"agricultural_evidence":45},[211,216,220,224,229],{"code":142,"score":18,"supported":45,"title":212,"abstract":213,"tags":215},[146],[214,146],"土壤",[],{"code":31,"score":110,"supported":45,"title":217,"abstract":218,"tags":219},[47],[],[],{"code":61,"score":20,"supported":13,"title":221,"abstract":222,"tags":223},[],[],[26],{"code":225,"score":20,"supported":13,"title":226,"abstract":227,"tags":228},"I3",[],[],[198],{"code":230,"score":20,"supported":13,"title":231,"abstract":232,"tags":233},"I4",[],[],[199],[235,236],"地下水质量 农业遥感 土壤环境 温室气体","地下水质量 农业遥感","地下水质量农业遥感土壤环境温室气体-2531","10.31223\u002Fx5rj7d",{"doi":238,"openalex_id":240,"authors":241,"venue":8,"cited_by_count":94,"oa_url":245,"card":246,"direction":251,"ingested_from":95},"W7213077215",[242],{"name":243,"orcid":244},"Avideh Asadollahi","https:\u002F\u002Forcid.org\u002F0009-0000-9847-2177","https:\u002F\u002Feartharxiv.org\u002Frepository\u002Fobject\u002F14981\u002Fdownload\u002F26031\u002F",{"tldr":247,"method":248,"finding":249,"direction":179,"opportunity":250},"构建丹麦5公里网格，分析温室气体、植被、地下水硝酸盐与土壤的空间耦合关系。","EDGAR排放、MODIS NDVI、GEUS硝酸盐与土壤图，用Moran's ","CO2与NDVI负相关最强，CH4与CO2、硝酸盐正相关，土壤类型显著调节这些关联。","可基于该空间筛查框架，在热点区域开展过程模型与监测，探究土壤调节机制及因果路径。","农业遥感与作物表型","2026-09-15T23:30:20.707747Z",{"id":254,"title":255,"url":256,"summary":257,"summary_zh":258,"content":8,"source_name":9,"source_url":256,"published_at":259,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":260,"score_detail":261,"sources":264,"tags":266,"primary_topic":271,"secondary_topics":272,"classification":284,"search_phrases":326,"slug":329,"view_count":20,"doi":330,"paper":331,"created_at":389},2021,"The mixed effects of conservation agriculture principles including fertilizer management on greenhouse gas emissions: A scoping review and multi-study synthesis","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104909","Context Conservation agriculture (CA) has gained attention over the last decade for its potential to mitigate climate change, among other benefits. However, no clear pattern of CA's effect on greenhouse gas emissions exist, due to complex and interactive processes from CA's three main principles including appropriate fertilizer use as the fourth proposed principle of CA. Objective A comprehensive literature search was conducted to review evidence on the effect of CA's three main principles (reduced tillage, mulching, crop diversification) including appropriate fertilizer management on greenhouse gas (nitrous oxide–N 2 O, carbon dioxide–CO 2 , methane–CH 4 ) emissions. Methods We reviewed 422 out of 3452 publications to assess the relative strength of evidence on effects of reduced tillage, mulching and fertilizer management on greenhouse gas emissions, with an in-depth multi-study synthesis on crop rotation and experimental characteristics. Control treatments included conventional tillage, zero mulch, monocropping and standard mineral nitrogen (N) fertilizer application. Results and conclusions There was good (73%) and some (46%) evidence that reduced tillage practices reduce CO 2 and N 2 O emissions, respectively. There was some evidence that mulching increases N 2 O (46%) and CO 2 (55%) emissions while the effects of different fertilizer management strategies on greenhouse gas emissions were mixed. The multi-study analysis showed an association of nitrogen fertilizer category, N fertilizer rate and overall rotation type with CH 4 emission. However, the CH 4 distribution was highly inconsistent. Overall, continuous legume-legume rotation was associated with decreases in CO 2 compared to continuous cereal-cereal rotations. The cereal-cereal rotation up to and including the current crop was associated with an increase in CO 2 emission relative to a monocrop. Nitrous oxide was associated with the N fertilizer application rate with the medium N fertilizer rate (102–175 kg N ha −1 ) associated with increases in N 2 O compared to the zero N control. Significance Our study highlights the effect of CA's three main principles and appropriate fertilizer use on greenhouse gas emissions under different cropping systems and agroecological regions, and the need for standardised reporting to ensure continued importance of field experiments, particularly long-term experiments, in providing empirical evidence on impacts of agronomic practices on global environmental change.","背景 保护性农业（CA）因其在减缓气候变化等方面的潜在效益，在过去十年中受到关注。然而，由于保护性农业三项主要原则及其作为第四项拟议原则的合理施肥之间复杂的交互过程，保护性农业对温室气体排放的影响尚无明确规律。目的 本研究进行了全面的文献检索，以综述保护性农业三项主要原则（减少耕作、覆盖、作物多样化）及合理施肥管理对温室气体（一氧化二氮–N₂O、二氧化碳–CO₂、甲烷–CH₄）排放影响的证据。方法 我们从3452篇文献中筛选出422篇进行综述，以评估减少耕作、覆盖和施肥管理对温室气体排放影响的证据相对强度，并对作物轮作和试验特征进行了深入的多研究综合分析。对照处理包括常规耕作、无覆盖、单作和标准矿质氮（N）肥施用。结果与结论 有良好证据（73%）和一些证据（46%）表明，减少耕作措施分别降低CO₂和N₂O排放。有一些证据表明，覆盖增加了N₂O（46%）和CO₂（55%）排放，而不同施肥管理策略对温室气体排放的影响则好坏参半。多研究分析显示，氮肥类别、氮肥施用量和总体轮作类型与CH₄排放存在关联。然而，CH₄分布高度不一致。总体而言，与连续谷类-谷类轮作相比，连续豆类-豆类轮作与CO₂排放减少相关。与单作相比，截至并包括当前作物的谷类-谷类轮作与CO₂排放增加相关。一氧化二氮与氮肥施用量相关，中等氮肥施用量（102–175 kg N ha⁻¹）与零氮对照相比增加了N₂O排放。意义 本研究强调了保护性农业三项主要原则及合理施肥在不同种植制度和农业生态区域下对温室气体排放的影响，并指出需要标准化报告，以确保田间试验，特别是长期试验，在提供农艺措施对全球环境变化影响的实证证据方面持续发挥重要作用。","2026-09-09T00:00:00Z",81,{"impact":16,"substance":262,"depth":16,"authority":18,"freshness":19,"relevant":20,"comment":263},22,"基于3452篇文献筛选422篇的保护性农业温室气体效应综述，方法扎实、结论具参考价值，但属学术综述而非产业级突破，适合作为专业精选。",[265],{"name":9,"url":256},[26,267,268,269,270],"保护性农业","农业减排","施肥管理","免耕覆盖",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[273,279],{"code":274,"slug":275,"name":276,"path":277,"parent_code":278},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",{"code":280,"slug":281,"name":282,"path":283,"parent_code":207},"H8","sustainable-agriculture","可持续与保护性农业","\u002Ftopic\u002Fenvironment\u002Fsustainable-agriculture",{"status":38,"locked":13,"version":39,"method":40,"evidence":285},{"candidates":286,"agricultural_evidence":45},[287,291,297,302,309,316,322],{"code":31,"score":18,"supported":45,"title":288,"abstract":289,"tags":290},[47],[130,47],[],{"code":274,"score":18,"supported":45,"title":292,"abstract":294,"tags":296},[293],"fertilizer",[295,293],"施肥",[],{"code":280,"score":192,"supported":45,"title":298,"abstract":300,"tags":301},[299],"conservation agriculture",[299],[267],{"code":303,"score":98,"supported":45,"title":304,"abstract":305,"tags":308},"A7",[],[306,307],"轮作","crop rotation",[],{"code":310,"score":98,"supported":45,"title":311,"abstract":312,"tags":315},"H7",[],[313,314],"气候变化","climate change",[],{"code":317,"score":143,"supported":45,"title":318,"abstract":319,"tags":321},"H6",[],[320],"农业生态",[],{"code":61,"score":161,"supported":13,"title":323,"abstract":324,"tags":325},[],[],[268,26],[327,328],"保护性农业 免耕覆盖 农业减排 施肥管理","保护性农业 免耕覆盖","保护性农业免耕覆盖农业减排施肥管理-2021","10.1016\u002Fj.agsy.2026.104909",{"doi":330,"openalex_id":332,"authors":333,"venue":9,"cited_by_count":94,"oa_url":256,"card":384,"direction":179,"ingested_from":95},"W7212036648",[334,336,339,341,343,346,349,352,354,356,359,361,364,366,368,370,372,375,378,381],{"name":335,"orcid":8},"Muneta G. Manzeke-Kangara",{"name":337,"orcid":338},"Aranzazu Louro-Lopez","https:\u002F\u002Forcid.org\u002F0000-0002-1634-8664",{"name":340,"orcid":8},"Teri-Louise North",{"name":342,"orcid":8},"Clinton Fowler",{"name":344,"orcid":345},"Vengai Mbanyele","https:\u002F\u002Forcid.org\u002F0009-0008-2539-8795",{"name":347,"orcid":348},"Hannah V. Cooper","https:\u002F\u002Forcid.org\u002F0000-0003-2576-3429",{"name":350,"orcid":351},"Boitumelo Molise","https:\u002F\u002Forcid.org\u002F0000-0002-9700-0511",{"name":353,"orcid":8},"Tabisa Thandathu",{"name":355,"orcid":8},"Ivy S. Ligowe",{"name":357,"orcid":358},"Hatirarami Nezomba","https:\u002F\u002Forcid.org\u002F0000-0003-1370-1888",{"name":360,"orcid":8},"Jerry C. Dlamini",{"name":362,"orcid":363},"Elijah Phiri","https:\u002F\u002Forcid.org\u002F0000-0002-3637-3509",{"name":365,"orcid":8},"Patson C. Nalivata",{"name":367,"orcid":8},"A. Mead",{"name":369,"orcid":8},"Jess Hood",{"name":371,"orcid":8},"Andrew S. Gregory",{"name":373,"orcid":374},"Alice E. Milne","https:\u002F\u002Forcid.org\u002F0000-0002-4509-0578",{"name":376,"orcid":377},"Z. Sawińska","https:\u002F\u002Forcid.org\u002F0000-0002-7030-3221",{"name":379,"orcid":380},"Dominika Radzikowska","https:\u002F\u002Forcid.org\u002F0000-0001-6989-1348",{"name":382,"orcid":383},"Stanisław Świtek","https:\u002F\u002Forcid.org\u002F0000-0003-3794-5780",{"tldr":385,"method":386,"finding":387,"direction":179,"opportunity":388},"综述422篇文献，综合评估保护性农业三原则及合理施肥对温室气体排放的混合影响。","范围综述与多研究综合，分析3452篇中422篇，比较免耕、覆盖、轮作与施肥管理。","免耕减CO2和N2O，覆盖增N2O和CO2，施肥影响不一，豆科连作减CO2，中氮增N2O。","需标准化报告长期试验，探究保护性农业各原则与施肥对温室气体排放的交互及区域差异机制。","2026-09-10T23:30:04.405140Z",{"id":391,"title":392,"url":393,"summary":394,"summary_zh":395,"content":8,"source_name":396,"source_url":393,"published_at":397,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":398,"score_detail":399,"sources":401,"tags":403,"primary_topic":407,"secondary_topics":408,"classification":414,"search_phrases":445,"slug":448,"view_count":449,"doi":450,"paper":451,"created_at":476},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":16,"substance":262,"depth":16,"authority":112,"freshness":135,"relevant":20,"comment":400},"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。",[402],{"name":396,"url":393},[117,26,404,405,406],"畜牧养殖","数据共享","碳排放核算",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[409],{"code":410,"slug":411,"name":412,"path":413,"parent_code":51},"C2","ruminants","草食牲畜","\u002Ftopic\u002Flivestock\u002Fruminants",{"status":38,"locked":13,"version":39,"method":40,"evidence":415},{"candidates":416,"agricultural_evidence":45},[417,421,431,437,441],{"code":31,"score":18,"supported":45,"title":418,"abstract":419,"tags":420},[47],[130,47],[],{"code":410,"score":19,"supported":45,"title":422,"abstract":423,"tags":430},[],[424,425,426,427,428,429],"奶牛","绵羊","山羊","cattle","sheep","goat",[],{"code":51,"score":98,"supported":45,"title":432,"abstract":433,"tags":436},[],[434,435],"畜牧","livestock",[],{"code":61,"score":20,"supported":13,"title":438,"abstract":439,"tags":440},[],[],[26],{"code":153,"score":20,"supported":13,"title":442,"abstract":443,"tags":444},[],[],[117],[446,447],"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",4,"10.1016\u002Fj.animal.2026.101946",{"doi":450,"openalex_id":452,"authors":453,"venue":396,"cited_by_count":94,"oa_url":469,"card":470,"direction":475,"ingested_from":95},"W7204954019",[454,457,460,462,464,466],{"name":455,"orcid":456},"Matti Pastell","https:\u002F\u002Forcid.org\u002F0000-0002-5810-4801",{"name":458,"orcid":459},"Vasileios Anestis","https:\u002F\u002Forcid.org\u002F0000-0003-4260-1763",{"name":461,"orcid":8},"A. Romera",{"name":463,"orcid":8},"A.M. Mazzetto",{"name":465,"orcid":8},"P. Ricci",{"name":467,"orcid":468},"Maguy Eugène","https:\u002F\u002Forcid.org\u002F0000-0002-2111-0597","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS175173112600193X\u002Fpdf",{"tldr":471,"method":472,"finding":473,"direction":179,"opportunity":474},"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。","智慧农业 \u002F 农业物联网","2026-09-02T23:30:13.638840Z",{"id":478,"title":479,"url":480,"summary":481,"summary_zh":8,"content":482,"source_name":483,"source_url":8,"published_at":484,"category":485,"cover_url":8,"hotness":12,"is_selected":13,"score":398,"score_detail":486,"sources":488,"tags":490,"primary_topic":494,"secondary_topics":500,"classification":506,"search_phrases":541,"slug":544,"view_count":143,"doi":8,"paper":8,"created_at":545},435,"三节点采样方案实现滴灌棉田温室气体精准采集——中国农科院西部中心与棉花所建立干旱区棉田碳监测技术体系","https:\u002F\u002Fcaas.cn\u002Fxwzx\u002Fkyhd\u002F7ef7293fed924affbc040b406faa3a4e.htm","中国农业科学院西部农业研究中心联合棉花研究所揭示了干旱区滴灌棉田温室气体排放变化规律,建立了三节点滴灌棉田温室气体精准采集技术体系。膜下滴灌水肥一体化技术为新疆棉花高产稳产提供了重要技术支撑,但灌溉施肥过程会引起土壤温室气体排放快速波动,传统采样方式难以实现农田温室气体的精准监测。研究发现,灌溉施肥后第1天是温室气体排放峰值形成的关键时期,据此提出了'灌溉前1天—灌溉后1天—灌溉后5天'三节点精准采样方案,相关研究成果发表在《农业水管理》(Agricultural Water Management)上。","近日，中国农业科学院西部农业研究中心联合棉花研究所揭示了干旱区滴灌棉田温室气体排放变化规律，建立了三节点滴灌棉田温室气体精准采集技术体系。相关研究成果发表在《农业水管理（Agricultural Water Management）》上。\n\n膜下滴灌水肥一体化技术为新疆棉花高产稳产提供了重要技术支撑，但灌溉施肥过程会引起土壤温室气体排放快速波动，传统采样方式难以实现农田温室气体的精准监测。\n\n该研究发现，灌溉施肥后第1天是温室气体排放峰值形成的关键时期，据此提出了“灌溉前1天—灌溉后1天—灌溉后5天”三节点精准采样方案。该方案能够在减少采样工作量的同时，保留温室气体排放关键动态信息，保持较高的排放估算精度。研究构建的关键时期识别—精准采样优化—排放精准估算技术体系，为干旱区滴灌棉田温室气体监测提供了科学方案。","中国农业科学院 2026-08-08","2026-08-08T00:00:00Z","报道",{"impact":193,"substance":262,"depth":16,"authority":18,"freshness":449,"relevant":20,"comment":487},"国家级科研机构发布滴灌棉田温室气体监测技术体系，方法新颖、数据详实，对农业碳减排有实质贡献，但发布已过4天，时效性稍弱。",[489],{"name":483,"url":480},[491,492,26,493],"中国农科院","棉花","西部农业",{"code":495,"slug":496,"name":497,"path":498,"parent_code":499},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",[501,502],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"code":310,"slug":503,"name":504,"path":505,"parent_code":207},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"status":38,"locked":13,"version":39,"method":40,"evidence":507},{"candidates":508,"agricultural_evidence":45},[509,513,517,522,527,531,537],{"code":495,"score":192,"supported":45,"title":510,"abstract":511,"tags":512},[492],[492],[492],{"code":31,"score":44,"supported":45,"title":514,"abstract":515,"tags":516},[130],[130],[],{"code":310,"score":44,"supported":45,"title":518,"abstract":520,"tags":521},[519],"干旱",[519],[],{"code":274,"score":98,"supported":45,"title":523,"abstract":524,"tags":526},[],[295,525],"水肥一体化",[],{"code":142,"score":143,"supported":45,"title":528,"abstract":529,"tags":530},[],[214],[],{"code":532,"score":143,"supported":45,"title":533,"abstract":534,"tags":536},"H3",[],[535],"灌溉",[],{"code":61,"score":20,"supported":13,"title":538,"abstract":539,"tags":540},[],[],[26],[542,543],"中国农科院 温室气体 西部农业 棉花","中国农科院 温室气体","中国农科院温室气体西部农业棉花-435","2026-08-12T23:57:22.438495Z",{"id":547,"title":548,"url":549,"summary":550,"summary_zh":551,"content":8,"source_name":552,"source_url":549,"published_at":553,"category":11,"cover_url":8,"hotness":554,"is_selected":13,"score":190,"score_detail":555,"sources":557,"tags":561,"primary_topic":566,"secondary_topics":567,"classification":568,"search_phrases":603,"slug":606,"view_count":94,"doi":607,"paper":608,"created_at":619},5566,"Accelerated Precision Cultivation of Coffea arabica in a Vertical Hybrid Greenhouse Unit Integrated with Non-Thermal Dielectric Barrier Discharge Plasma Seed Priming","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23509132","Indoor controlled environment agriculture (CEA) offers substantial opportunities to insulate perennial crops from climate volatility and optimize resource efficiency, yet high-density cultivation of coffee (Coffea arabica) remains constrained by long ontogenetic establishment periods, slow seed germination, and physical root-zone limitations. In this work, we propose, model, and optimize a four-stage Vertical Hybrid Coffee Cultivation Unit (VH-CCU™) coupled with an upstream non-thermal dielectric barrier discharge (DBD) plasma seed conditioning skid. Pre-sowing treatment of Coffea arabica var. Kholani seeds using a 50 W, 10 kHz atmospheric helium DBD reactor induced sub-micron coat etching and accelerated imbibition by 10% to 12%, advancing emergence by approximately two weeks and boosting the Seedling Vigor Index from 475.9 to 766.6 (+61.1%) at 120 s exposure without generating toxic chemical effluents. Downstream cultivation integrates rooftop agrivoltaics (Stage 1), tiered pyramid micro-droplet fertigation (Stage 2), an engineered shallow volcanic-coir substrate bed (Stage 3), and an enclosed aeroponic sub-chamber (“basement”) for automated, non-destructive root phenotyping via multispectral computer vision (Stage 4). A 46-run Box–Behnken response surface Design of Experiments (DoE) evaluated five design factors across biological, hydraulic, and energetic responses. Multi-objective numerical optimization identified an optimal operating regime (X∗ 1 = 214 s plasma exposure, X∗ 2 = 1.21 L\u002Fplant\u002Fday drip volume, X∗ 3 = 25.5 cm bed depth, X∗ 4 = 16.7 mol\u002Fm2\u002Fday DLI, and X∗ 5 = adaptive edge-vision mist control), which achieved an experimental water-use efficiency of 4.72 g dry biomass\u002FL, compressed time to first bearing from 36–48 months down to 17–18 months, and maintained active root health above 96%. Techno economic modeling reveals that while high specific energy requirements (∼241 kWh\u002Fkg of green coffee) preclude commodity grade scaling, targeted micro-lot specialty production (SCA score 88+) paired with rooftop solar offsets yields a simple payback of 5.1 years and a 10-year Net Present Value of +$169,400. This hybrid framework establishes an empirical basis for the rapid, resource-efficient indoor production of high-grade coffee.","室内受控环境农业（CEA）为多年生作物规避气候波动和优化资源效率提供了重要机遇，但咖啡（Coffea arabica）的高密度栽培仍受限于漫长的个体发育建成期、缓慢的种子萌发以及根区物理空间限制。本研究提出、建模并优化了一种四阶段垂直混合咖啡栽培单元（VH-CCU™），并耦合上游非热介质阻挡放电（DBD）等离子体种子调理装置。采用50 W、10 kHz大气氦气DBD反应器对Kholani品种咖啡种子进行播前处理，诱导了亚微米级种皮刻蚀，使吸胀速率提高10%至12%，出苗提前约两周，在120 s暴露条件下将幼苗活力指数从475.9提升至766.6（+61.1%），且不产生有毒化学废液。下游栽培集成了屋顶农业光伏（第1阶段）、分层金字塔微滴灌施肥（第2阶段）、工程化浅层火山椰糠基质床（第3阶段）以及封闭式气雾栽培地下子室（第4阶段），后者通过多光谱计算机视觉实现自动化非破坏性根系表型分析。通过46组Box–Behnken响应面试验设计（DoE），评估了五个设计因子在生物学、水力学和能量学响应方面的表现。多目标数值优化确定了最优运行方案（X∗1 = 214 s等离子体暴露时间，X∗2 = 1.21 L\u002F株\u002F天滴灌量，X∗3 = 25.5 cm基质床深度，X∗4 = 16.7 mol\u002Fm²\u002F天日光积分，X∗5 = 自适应边缘视觉喷雾控制），实现了4.72 g干生物量\u002FL的实验水分利用效率，将首次结果期从36–48个月缩短至17–18个月，并维持根系健康率在96%以上。技术经济建模表明，尽管高比能耗（约241 kWh\u002Fkg生咖啡）限制了商品级规模化生产，但面向微批次精品生产（SCA评分88+）并配合屋顶太阳能抵消，可实现5.1年简单投资回收期和+$169,400的10年净现值。该混合框架为高等级咖啡的快速、资源高效室内生产奠定了实证基础。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",25,{"impact":192,"substance":262,"depth":16,"authority":12,"freshness":19,"relevant":20,"comment":556},"方法新颖、数据扎实的室内咖啡栽培论文，但属细分作物与预印本平台，产业影响有限，可作主题聚合而非每日精选头条。",[558,559],{"name":552,"url":549},{"name":552,"url":560},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23527545",[117,562,563,564,565],"垂直农业","设施园艺","咖啡种植","等离子种子处理",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":13,"version":39,"method":40,"evidence":569},{"candidates":570,"agricultural_evidence":45},[571,575,582,587,594,599],{"code":31,"score":12,"supported":45,"title":572,"abstract":573,"tags":574},[47],[],[562,563],{"code":576,"score":135,"supported":45,"title":577,"abstract":578,"tags":581},"B3",[],[579,580],"咖啡","coffee",[564],{"code":274,"score":98,"supported":45,"title":583,"abstract":584,"tags":586},[],[295,585],"fertigation",[],{"code":588,"score":98,"supported":45,"title":589,"abstract":590,"tags":593},"I2",[],[591,592],"计算机视觉","computer vision",[],{"code":225,"score":143,"supported":45,"title":595,"abstract":596,"tags":598},[],[597],"multispectral",[],{"code":153,"score":20,"supported":13,"title":600,"abstract":601,"tags":602},[],[],[117],[604,605],"Coffea arabica 垂直温室 等离子种子处理","VH-CCU 咖啡 室内栽培","Coffeaarabica垂直温室等离子种子处理-5566","10.5281\u002Fzenodo.23509132",{"doi":607,"openalex_id":609,"authors":610,"venue":552,"cited_by_count":94,"oa_url":549,"card":614,"direction":251,"ingested_from":95},"W7223104009",[611],{"name":612,"orcid":613},"Ahmed Hala","https:\u002F\u002Forcid.org\u002F0000-0002-7749-2299",{"tldr":615,"method":616,"finding":617,"direction":475,"opportunity":618},"提出并优化等离子体种子预处理+四阶段垂直混合温室单元，加速咖啡室内栽培。","50W氦DBD等离子体处理种子，Box-Behnken响应面试验与多目标优化建模","出苗提前约两周，活力指数增61.1%，首果期缩至17-18个月，水分利用效率4.72g\u002FL。","等离子体种子预处理与室内垂直栽培耦合可拓展至其他多年生高值作物，并需验证规模化能耗经济性。","2026-10-22T11:20:31.314461Z"]