[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2022":3,"related-2022":104},{"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":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":44,"search_phrases":68,"slug":71,"view_count":72,"doi":73,"paper":74,"created_at":103},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",null,"Agricultural Systems","2026-09-09T00:00:00Z","论文",10,false,76,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},15,21,17,14,9,1,"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。",[24],{"name":9,"url":6},[26,27,28,29,30],"生态经济","碳足迹","农业减排","菠萝","秸秆利用",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"B7","protected-horticulture","设施园艺与植物工厂","\u002Ftopic\u002Fhorticulture\u002Fprotected-horticulture","B",[38],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon","H",{"status":45,"locked":13,"version":46,"method":47,"evidence":48},"classified","2026-10-22.2","rules",{"candidates":49,"agricultural_evidence":52},[50,57,63],{"code":39,"score":51,"supported":52,"title":53,"abstract":55,"tags":56},13,true,[54],"carbon footprint",[54],[28,27],{"code":32,"score":58,"supported":52,"title":59,"abstract":61,"tags":62},11,[60],"greenhouse",[60],[],{"code":64,"score":21,"supported":13,"title":65,"abstract":66,"tags":67},"H5",[],[],[30],[69,70],"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":73,"openalex_id":75,"authors":76,"venue":9,"cited_by_count":101,"oa_url":8,"card":8,"direction":8,"ingested_from":102},"W7212051523",[77,80,83,85,87,90,91,94,97,98],{"name":78,"orcid":79},"Xin Jin","https:\u002F\u002Forcid.org\u002F0000-0002-7737-7506",{"name":81,"orcid":82},"Shoupeng Li","https:\u002F\u002Forcid.org\u002F0000-0002-5009-8013",{"name":84,"orcid":8},"Mingwan Chen",{"name":86,"orcid":8},"Chuangjun Wu",{"name":88,"orcid":89},"Changzhen Li","https:\u002F\u002Forcid.org\u002F0000-0002-8089-4838",{"name":88,"orcid":89},{"name":92,"orcid":93},"Huanyu Bao","https:\u002F\u002Forcid.org\u002F0009-0004-8127-1888",{"name":95,"orcid":96},"Changjiang Li","https:\u002F\u002Forcid.org\u002F0000-0002-5545-9690",{"name":95,"orcid":96},{"name":99,"orcid":100},"Yunze Ruan","https:\u002F\u002Forcid.org\u002F0000-0003-0079-9353",0,"openalex","2026-09-10T23:30:04.465334Z",{"total":105,"page":21,"page_size":105,"items":106},6,[107,204,265,337,412,530],{"id":108,"title":109,"url":110,"summary":111,"summary_zh":112,"content":8,"source_name":113,"source_url":110,"published_at":114,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":115,"score_detail":116,"sources":121,"tags":123,"primary_topic":128,"secondary_topics":129,"classification":135,"search_phrases":154,"slug":157,"view_count":101,"doi":158,"paper":159,"created_at":203},5467,"Temperature-directed valorisation of coconut frond through pyrolysis for carbon sequestration and sustainable agricultural residue management","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1966170","Coconut frond, an abundantly generated yet underutilized agricultural residue, was pyrolysed at 350 °C, 450 °C, and 550 °C alongside traditionally produced biochar (BC Trad) to evaluate the effects of pyrolysis temperature on physicochemical characteristics, fuel properties, carbon stability, and residue-valorisation potential. Comprehensive characterization using proximate and ultimate analyses, BET\u002FBJH, FTIR, XRD, Raman spectroscopy, SEM-EDS, total pyrogenic carbon (TPC), estimated CO 2 -equivalent stable-carbon retention potential, fuel and energy indices, and 90-day carbon mineralization incubation revealed pronounced temperature-dependent transformations. Biochar carbon recovery was highest at 350 °C (78.91%), demonstrating greater retention of feedstock carbon at lower pyrolysis temperature, whereas increasing temperature progressively enhanced carbon concentration, fixed carbon, thermostable carbon fraction, porosity, and surface area. BET surface area increased from 4.45 m 2 g −1 in BC Trad to 16.67 m 2 g −1 in BC550, accompanied by progressive pore refinement and depletion of oxygen-containing functional groups. Raman spectroscopy showed a decline in ID\u002FIG from 1.28 to 0.80, consistent with increasing structural ordering and aromatic condensation at higher temperatures. Fuel quality also improved with increasing temperature, with higher heating value increasing from 20.72 to 25.56 MJ kg −1 and fuel ratio from 1.49 to 4.26. TPC and estimated CO 2 -equivalent stable-carbon retention potential were highest at BC350 (0.29 kg C kg −1 feedstock and 0.86 kg CO 2 kg −1 feedstock, respectively), whereas BC550 exhibited the lowest apparent net soil-system carbon mineralization among the biochars during the 90-day incubation. Separately, its lower H\u002FC and O\u002FC ratios corresponded to a modelled BC +100 stability index of 0.720 and an estimated mean residence time of 347.61 years, providing model-derived indications of longer-term carbon persistence. Overall, the findings demonstrate a clear temperature-dependent trade-off between carbon recovery and carbon stability, with BC350 providing greater structural recalcitrance and apparent short-term mineralization resistance; the optimal pyrolysis temperature therefore depends on the intended end use rather than a single treatment being universally superior. Together, the short-term mineralization results and model-derived stability estimates indicate distinct dimensions of carbon persistence that should be considered when optimizing coconut-frond pyrolysis for sustainable agricultural-residue management, durable soil-carbon sequestration, and circular bioeconomy applications.","椰子叶是一种大量产生但未充分利用的农业废弃物，其在350 °C、450 °C和550 °C下热解，并与传统生产的生物炭（BC Trad）进行对比，以评估热解温度对理化特性、燃料性质、碳稳定性及残余物增值潜力的影响。采用工业分析和元素分析、BET\u002FBJH、FTIR、XRD、拉曼光谱、SEM-EDS、总热解碳（TPC）、估算CO₂当量稳定碳保留潜力、燃料与能量指标以及90天碳矿化培养进行综合表征，揭示了显著的温度依赖性变化。生物炭碳回收率在350 °C时最高（78.91%），表明较低热解温度下原料碳的保留更多，而升高温度则逐步提高碳浓度、固定碳、热稳定碳组分、孔隙率和比表面积。BET比表面积从BC Trad的4.45 m² g⁻¹增至BC550的16.67 m² g⁻¹，同时伴随孔隙细化和含氧官能团的消耗。拉曼光谱显示ID\u002FIG从1.28降至0.80，与较高温度下结构有序性和芳香缩合度增加相一致。燃料品质亦随温度升高而改善，高位热值从20.72增至25.56 MJ kg⁻¹，燃料比从1.49增至4.26。TPC和估算CO₂当量稳定碳保留潜力在BC350时最高（分别为0.29 kg C kg⁻¹原料和0.86 kg CO₂ kg⁻¹原料），而BC550在90天培养期间表现出生物炭中最低的表观净土壤系统碳矿化。此外，其较低的H\u002FC和O\u002FC比对应模拟BC +100稳定性指数为0.720，估算平均停留时间为347.61年，提供了模型推导的较长时期碳持久性指示。总体而言，研究结果揭示了碳回收与碳稳定性之间明显的温度依赖性权衡，BC350表现出更高的结构惰性和表观短期抗矿化性；因此，最佳热解温度取决于预期最终用途，而非单一处理普遍优越。短期矿化结果与模型推导的稳定性估算共同表明，碳持久性具有不同维度，应予考虑。","Frontiers in Sustainable Food Systems","2026-10-20T00:00:00Z",74,{"impact":117,"substance":118,"depth":119,"authority":51,"freshness":20,"relevant":21,"comment":120},12,22,18,"该研究系统考察了热解温度对椰叶生物炭碳回收与碳稳定性的权衡关系，数据翔实、结论可靠，对农业废弃物资源化与土壤固碳具有参考价值，但属于细分领域基础研究，公共影响有限。",[122],{"name":113,"url":110},[124,125,30,126,127],"生物炭","农业废弃物","土壤固碳","热解技术",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[130],{"code":131,"slug":132,"name":133,"path":134,"parent_code":43},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"status":45,"locked":13,"version":46,"method":47,"evidence":136},{"candidates":137,"agricultural_evidence":52},[138,143,149],{"code":39,"score":58,"supported":52,"title":139,"abstract":141,"tags":142},[140],"carbon sequestration",[140],[],{"code":131,"score":144,"supported":52,"title":145,"abstract":146,"tags":148},8,[],[147,132],"土壤",[126,124],{"code":64,"score":150,"supported":52,"title":151,"abstract":152,"tags":153},5,[],[125],[125,30],[155,156],"椰叶 热解 生物炭","生物炭 碳封存 农业废弃物","椰叶热解生物炭-5467","10.3389\u002Ffsufs.2026.1966170",{"doi":158,"openalex_id":160,"authors":161,"venue":113,"cited_by_count":101,"oa_url":196,"card":197,"direction":201,"ingested_from":102},"W7223016223",[162,165,167,170,173,175,178,181,183,186,188,191,194],{"name":163,"orcid":164},"Morasanahalli Lokesha Sachin","https:\u002F\u002Forcid.org\u002F0009-0008-8615-0822",{"name":166,"orcid":8},"Yogananda Shivalli Boregowda",{"name":168,"orcid":169},"Matadadoddi Nanjundegowda Thimmegowda","https:\u002F\u002Forcid.org\u002F0000-0001-7632-1036",{"name":171,"orcid":172},"M. A. Ananthakumar","https:\u002F\u002Forcid.org\u002F0000-0003-4376-9541",{"name":174,"orcid":8},"Pudiyanda Shadali Fathima",{"name":176,"orcid":177},"C. M. Sunil","https:\u002F\u002Forcid.org\u002F0000-0002-9625-5686",{"name":179,"orcid":180},"K. M. Pravalika","https:\u002F\u002Forcid.org\u002F0009-0004-5258-392X",{"name":182,"orcid":8},"M.C. Anjali",{"name":184,"orcid":185},"Sathisha Govinakere Sambegowda","https:\u002F\u002Forcid.org\u002F0009-0000-8620-6461",{"name":187,"orcid":8},"B. Divya",{"name":189,"orcid":190},"M. K. Shruthi","https:\u002F\u002Forcid.org\u002F0000-0003-3703-9817",{"name":192,"orcid":193},"Santosh Onte","https:\u002F\u002Forcid.org\u002F0009-0002-8367-1303",{"name":195,"orcid":8},"Sanjeev Kumar","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1966170\u002Fpdf",{"tldr":198,"method":199,"finding":200,"direction":201,"opportunity":202},"研究不同热解温度对椰叶生物炭碳固存与稳定性的影响。","350\u002F450\u002F550°C热解椰叶，多手段表征并做90天矿化培养。","碳回收率与碳稳定性随温度呈权衡，最佳温度取决于用途。","农业绿色发展与碳","可探索热解温度与还田情景耦合的长期碳固存模型及经济性评估。","2026-10-21T23:30:07.083785Z",{"id":205,"title":206,"url":207,"summary":208,"summary_zh":209,"content":8,"source_name":113,"source_url":207,"published_at":210,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":211,"score_detail":212,"sources":215,"tags":217,"primary_topic":221,"secondary_topics":222,"classification":223,"search_phrases":247,"slug":250,"view_count":21,"doi":251,"paper":252,"created_at":264},3991,"Long-term straw incorporation in farmland promotes carbon sequestration and mitigates emissions: a global meta-analysis","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1965841","Background Straw incorporation is an important agronomic practice for soil carbon seques-tration. However, the underlying processes of it remain unclear. Objective This study compared global carbon cycle processes under straw incorporation durations of ≤5 years and >5 years. Methods This study was based on a global meta-analysis. Results Straw incorporation improved soil physicochemical properties and increased soil organic carbon storage by 23.57% relative to no return. Long-term incorporation (>5 years) further increased SOC storage compared with ≤5 years. Microbial diversity and community structure were altered, with greater changes under longer durations. Straw incorporation enhanced genes involved in carbon degradation, fixation, and methane metabolism, and increased enzyme activities, soil respiration, and mineralization rate. Straw incorporation increased CH 4 , CO 2 , and N 2 O emissions, but the emission increment was lower in the >5 years group than in the ≤5 years group. Global warming potential showed a similar trend. Random forest analysis indicated that soil carbon storage was mainly driven by mineralization rate and microbial necromass carbon, while GWP was primarily regulated by available nitrogen and microbial necromass carbon. Conclusion These findings demonstrate that long-term straw incorporation can effectively enhance carbon sequestration and reduce the global warming potential in farmland.","背景 秸秆还田是促进土壤碳固存的重要农艺措施，但其内在过程仍不明确。目的 本研究比较了秸秆还田年限≤5年和>5年条件下的全球碳循环过程。方法 本研究基于全球荟萃分析。结果 与不还田相比，秸秆还田改善了土壤理化性质，使土壤有机碳储量提高了23.57%。与≤5年相比，长期还田（>5年）进一步提高了土壤有机碳储量。微生物多样性和群落结构发生改变，且还田年限越长变化越大。秸秆还田增强了参与碳降解、碳固定和甲烷代谢的基因，并提高了酶活性、土壤呼吸和矿化速率。秸秆还田增加了CH₄、CO₂和N₂O排放，但>5年组的排放增量低于≤5年组。全球增温潜势也表现出相似趋势。随机森林分析表明，土壤碳储量主要受矿化速率和微生物残体碳驱动，而全球增温潜势主要受有效氮和微生物残体碳调控。结论 这些发现表明，长期秸秆还田能够有效增强农田碳固存并降低全球增温潜势。","2026-10-01T00:00:00Z",80,{"impact":119,"substance":213,"depth":119,"authority":51,"freshness":144,"relevant":21,"comment":214},23,"全球尺度meta分析，量化长期秸秆还田的固碳与减排效应，数据扎实、结论明确，对农田碳汇与绿色农业有参考价值。",[216],{"name":113,"url":207},[218,219,28,126,220],"秸秆还田","碳循环","农田碳汇",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":45,"locked":13,"version":46,"method":47,"evidence":224},{"candidates":225,"agricultural_evidence":52},[226,230,235,240],{"code":39,"score":117,"supported":52,"title":227,"abstract":228,"tags":229},[140],[140],[28],{"code":131,"score":231,"supported":52,"title":232,"abstract":233,"tags":234},7,[],[147,132],[126],{"code":64,"score":236,"supported":52,"title":237,"abstract":238,"tags":239},4,[],[218],[218],{"code":241,"score":242,"supported":52,"title":243,"abstract":244,"tags":246},"H6",3,[],[245],"生物多样性",[],[248,249],"秸秆还田 土壤固碳 全球meta分析","长期秸秆还田 温室气体排放","秸秆还田土壤固碳全球meta分析-3991","10.3389\u002Ffsufs.2026.1965841",{"doi":251,"openalex_id":253,"authors":254,"venue":113,"cited_by_count":101,"oa_url":207,"card":259,"direction":201,"ingested_from":102},"W7215031184",[255,257],{"name":256,"orcid":8},"Xiaoyan Wang",{"name":258,"orcid":8},"Feng Luo",{"tldr":260,"method":261,"finding":262,"direction":201,"opportunity":263},"全球荟萃分析表明长期秸秆还田（>5年）比短期更能固碳并降低全球增温潜势。","全球荟萃分析，比较≤5年与>5年秸秆还田下碳循环过程与微生物机制。","长期还田进一步提升有机碳储量，温室气体排放增量更小，GWP更低。","可探究不同气候与土壤条件下长期还田的固碳减排阈值及微生物调控机制。","2026-10-02T23:30:09.544882Z",{"id":266,"title":267,"url":268,"summary":269,"summary_zh":270,"content":8,"source_name":113,"source_url":268,"published_at":271,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":211,"score_detail":272,"sources":274,"tags":276,"primary_topic":281,"secondary_topics":282,"classification":289,"search_phrases":318,"slug":321,"view_count":21,"doi":322,"paper":323,"created_at":336},3762,"Nitrogen-centered nutrient innovation for decoupling agricultural productivity from greenhouse-gas intensity: evidence, limits, and implementation pathways","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1934315","Increasing agricultural production while lowering greenhouse-gas (GHG) intensity is a defining challenge for climate-smart agrifood systems. This critical review evaluates nitrogen-centered nutrient innovations through a boundary-explicit, two-axis framework: evidence confidence for a stated productivity-GHG decoupling outcome and implementation readiness in a specified context. The synthesis covers enhanced-efficiency fertilizers (EEFs), biological nitrogen fixation (BNF), biological nitrification inhibition (BNI), site-specific nutrient management (SSNM), 4R stewardship, precision placement, digital decision support, circular nitrogen recovery, and integrated nutrient management (INM). Direct evidence requires paired crop-output and GHG data; nitrogen-use efficiency, fertilizer savings, nutrient-loss reduction, or soil-quality responses alone are classified as partial or supporting evidence. Evidence confidence is highest for locally calibrated SSNM, 4R rate-timing-placement practices, and selected EEFs in high-surplus or high-loss systems, although performance varies with crop, soil, climate, baseline nitrogen rate, and the measured boundary. Implementation readiness is high for established stewardship practices, moderate and context-dependent for EEFs, digital tools, recovered products, and BNI, and low for many nanofertilizers and non-legume microbial inoculants. Circular products may provide life-cycle benefits, but results depend on allocation, substitution, transport, energy, indirect N 2 O, and avoided-waste assumptions. Short-term biogenic soil CO 2 flux is not treated as fossil climate forcing; soil-carbon benefits require stock-change measurements with defined depth, baseline, duration, and permanence. Evidence is concentrated in cereal and high-input systems, and publication, language, citation-selection, and outcome-reporting biases limit generalization. Reliable decoupling therefore requires integrated portfolios, transparent accounting, independent field validation, and performance-oriented policy rather than claims based on input reduction alone.","在降低温室气体（GHG）强度的同时提高农业生产，是气候智慧型农食系统面临的一项决定性挑战。本批判性综述通过一个边界明确的双轴框架，评估以氮为中心的养分创新：针对特定生产力—温室气体脱钩结果的证据置信度，以及在特定情境下的实施就绪度。综述涵盖增效肥料（EEFs）、生物固氮（BNF）、生物硝化抑制（BNI）、位点特异性养分管理（SSNM）、4R管理、精准施肥、数字决策支持、循环氮回收和综合养分管理（INM）。直接证据要求配对的作物产量与温室气体数据；仅凭氮利用效率、肥料节约、养分损失减少或土壤质量响应，被归类为部分证据或支持性证据。对于经本地校准的SSNM、4R用量—时间—位置实践，以及在高盈余或高损失系统中选用的增效肥料，证据置信度最高，但其表现因作物、土壤、气候、基线氮用量和所测边界而异。实施就绪度对于成熟的管理实践较高，对于增效肥料、数字工具、回收产品和生物硝化抑制为中等且依赖情境，对于许多纳米肥料和非豆科微生物接种剂则较低。循环产品可能提供生命周期效益，但结果取决于分配、替代、运输、能源、间接N₂O和避免废弃物等假设。短期生物源土壤CO₂通量不被视为化石气候强迫；土壤碳效益需要具有明确深度、基线、持续时间和永久性的碳储量变化测量。证据集中于谷类作物和高投入系统，发表、语言、引用选择和结果报告偏倚限制了外推。因此，可靠的脱钩需要综合方案组合、透明核算、独立田间验证和以绩效为导向的政策，而非仅基于投入减少的宣称。","2026-09-28T00:00:00Z",{"impact":119,"substance":118,"depth":119,"authority":51,"freshness":20,"relevant":21,"comment":273},"系统综述氮素创新对农业生产与温室气体强度脱钩的证据与落地路径，方法框架清晰、结论审慎，对农业绿色低碳与智慧养分管理有参考价值。",[275],{"name":113,"url":268},[277,28,278,279,280],"养分管理","农业绿色低碳","氮肥增效","数字决策支持",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[283],{"code":284,"slug":285,"name":286,"path":287,"parent_code":288},"F3","fertilizers","肥料与水肥一体化","\u002Ftopic\u002Finputs-equipment\u002Ffertilizers","F",{"status":45,"locked":13,"version":46,"method":47,"evidence":290},{"candidates":291,"agricultural_evidence":52},[292,297,304,308,314],{"code":32,"score":19,"supported":52,"title":293,"abstract":294,"tags":296},[60],[295,60],"温室",[],{"code":284,"score":12,"supported":52,"title":298,"abstract":299,"tags":303},[],[300,301,277,302],"施肥","肥料","fertilizer",[277],{"code":131,"score":105,"supported":52,"title":305,"abstract":306,"tags":307},[],[147,132],[],{"code":309,"score":242,"supported":52,"title":310,"abstract":311,"tags":313},"I2",[],[312],"decision support",[],{"code":39,"score":21,"supported":13,"title":315,"abstract":316,"tags":317},[],[],[28],[319,320],"氮肥增效 温室气体 减排","4R养分管理 精准施肥","氮肥增效温室气体减排-3762","10.3389\u002Ffsufs.2026.1934315",{"doi":322,"openalex_id":324,"authors":325,"venue":113,"cited_by_count":101,"oa_url":329,"card":330,"direction":335,"ingested_from":102},"W7214627055",[326],{"name":327,"orcid":328},"Bonface Ombasa Manono","https:\u002F\u002Forcid.org\u002F0000-0001-9150-2126","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1934315\u002Fpdf",{"tldr":331,"method":332,"finding":333,"direction":201,"opportunity":334},"综述氮素创新技术能否在保障产量的同时降低农业温室气体强度，并评估证据与实施就绪度。","边界明确的双轴框架，综述EEFs、BNF、BNI、SSNM、4R、数字决策支持等","SSNM、4R和部分EEFs证据最强，但效果受作物、土壤、气候和基线氮量影响。","需在多样化作物与低投入系统中开展独立田间验证，并建立透明核算与政策评估体系。","智慧农业 \u002F 农业物联网","2026-09-29T23:30:07.225900Z",{"id":338,"title":339,"url":340,"summary":341,"summary_zh":342,"content":8,"source_name":9,"source_url":340,"published_at":343,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":344,"score_detail":345,"sources":347,"tags":349,"primary_topic":354,"secondary_topics":360,"classification":362,"search_phrases":386,"slug":389,"view_count":236,"doi":390,"paper":391,"created_at":411},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":144,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":346},"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。",[348],{"name":9,"url":340},[350,27,351,352,353],"温室气体","生命周期评价","山羊养殖","秘鲁农业",{"code":355,"slug":356,"name":357,"path":358,"parent_code":359},"C2","ruminants","草食牲畜","\u002Ftopic\u002Flivestock\u002Fruminants","C",[361],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":45,"locked":13,"version":46,"method":47,"evidence":363},{"candidates":364,"agricultural_evidence":52},[365,369,375,382],{"code":39,"score":18,"supported":52,"title":366,"abstract":367,"tags":368},[54],[27,54],[350,351,27],{"code":355,"score":19,"supported":52,"title":370,"abstract":372,"tags":374},[371],"goat",[373,371],"山羊",[],{"code":376,"score":105,"supported":52,"title":377,"abstract":378,"tags":381},"A8",[],[379,380],"粮食安全","food security",[],{"code":32,"score":105,"supported":52,"title":383,"abstract":384,"tags":385},[],[295,60],[],[387,388],"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","10.1016\u002Fj.agsy.2026.104993",{"doi":390,"openalex_id":392,"authors":393,"venue":9,"cited_by_count":101,"oa_url":340,"card":406,"direction":201,"ingested_from":102},"W7214193981",[394,396,398,400,402,404],{"name":395,"orcid":8},"Richard Ayala Roldan",{"name":397,"orcid":8},"Miguel Paredes-Chocce",{"name":399,"orcid":8},"Hugo Castillo Doloriert",{"name":401,"orcid":8},"David Godoy-Padilla",{"name":403,"orcid":8},"Juancarlos Alejandro Cruz-Luis",{"name":405,"orcid":8},"José Antonio Haro-Reyes",{"tldr":407,"method":408,"finding":409,"direction":201,"opportunity":410},"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",{"id":413,"title":414,"url":415,"summary":416,"summary_zh":417,"content":8,"source_name":9,"source_url":415,"published_at":418,"category":11,"cover_url":8,"hotness":12,"is_selected":52,"score":419,"score_detail":420,"sources":424,"tags":426,"primary_topic":431,"secondary_topics":436,"classification":443,"search_phrases":482,"slug":485,"view_count":236,"doi":486,"paper":487,"created_at":529},2912,"Spatial optimization of water-saving irrigation in Chinese rice paddies: Balancing yield, greenhouse gases, and cost using NSGA-II","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104976","CONTEXT Optimizing the spatial allocation of water-saving irrigation (WSI) promotion is critical for balancing rice production, greenhouse gas (GHG) mitigation, and economic costs, yet remains challenging at a national scale due to computational intractability. OBJECTIVE This study aims to develop a spatially explicit optimization framework to identify WSI promotion pathways across China's rice paddies that simultaneously maximize yield gain, maximize GHG reduction, and minimize implementation cost. METHODS We coupled K-means clustering with a multi-objective evolutionary algorithm (NSGA-II). Based on machine-learning predicted yield and GHG emissions for 157,417 flooded irrigation grids, we first clustered these grids into 500 environmentally and agronomically homogeneous groups. We then formulated a continuous optimization problem with cluster-level conversion rates as decision variables, simultaneously maximizing national yield gain, maximizing GHG reduction, and minimizing implementation cost. RESULTS AND CONCLUSIONS The Pareto front comprised 100 non-dominated solutions spanning promotion rates from 61.8% to 80.3%. The optimal solution, selected by normalized scoring, achieved 6.47 Mt. yield gain and 63.5 Mt. CO 2 e GHG reduction at a cost of 10.14 billion CNY, corresponding to a national promotion rate of 80.3%. Cluster-scale conversion rates exhibited significant spatial heterogeneity and positive correlation with cluster size ( r = 0.23), revealing economies of scale in WSI promotion. Compared with a random promotion strategy at 90% adoption, our optimized solution delivered 74% higher yield gain with 9.7 percentage points lower promotion effort while achieving comparable GHG reduction. SIGNIFICANCE Our framework provides a spatially explicit decision-support tool for precision agricultural policy, demonstrating that smart spatial allocation can substantially enhance the efficiency of limited resources in scaling climate-smart agricultural practices.","背景 优化节水灌溉（WSI）推广的空间配置对于平衡水稻生产、温室气体（GHG）减排和经济成本至关重要，但由于计算上的不可处理性，在全国尺度上仍具挑战性。目的 本研究旨在开发一个空间显式优化框架，以识别中国稻田的WSI推广路径，同时最大化产量增益、最大化GHG减排并最小化实施成本。方法 我们将K-means聚类与多目标进化算法（NSGA-II）相结合。基于机器学习预测的157,417个淹水灌溉网格的产量和GHG排放，我们首先将这些网格聚类为500个在环境和农艺上同质的组。然后，我们构建了一个以组级转换率为决策变量的连续优化问题，同时最大化全国产量增益、最大化GHG减排并最小化实施成本。结果与结论 Pareto前沿包含100个非支配解，推广率从61.8%到80.3%不等。通过归一化评分选出的最优解实现了6.47 Mt的产量增益和63.5 Mt CO₂e的GHG减排，成本为101.4亿元人民币，对应全国推广率为80.3%。组尺度转换率表现出显著的空间异质性，并与组规模呈正相关（r = 0.23），揭示了WSI推广中的规模经济。与90%采纳率的随机推广策略相比，我们的优化方案在推广力度低9.7个百分点的情况下实现了高出74%的产量增益，同时实现了相当的GHG减排。意义 我们的框架为精准农业政策提供了一个空间显式的决策支持工具，表明智能空间配置可以显著提高有限资源在推广气候智慧型农业实践中的效率。","2026-09-18T00:00:00Z",89,{"impact":421,"substance":213,"depth":422,"authority":19,"freshness":20,"relevant":21,"comment":423},24,19,"基于NSGA-II的全国稻田节水灌溉空间优化框架，数据规模大、结论具体，对气候智慧型农业政策有决策参考价值。",[425],{"name":9,"url":415},[427,428,429,430,28],"智慧农业","水稻","空间优化","节水灌溉",{"code":432,"slug":433,"name":428,"path":434,"parent_code":435},"A1","rice","\u002Ftopic\u002Ffield-crops\u002Frice","A",[437,442],{"code":438,"slug":439,"name":440,"path":441,"parent_code":43},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":45,"locked":13,"version":46,"method":47,"evidence":444},{"candidates":445,"agricultural_evidence":52},[446,451,456,460,467,473,478],{"code":432,"score":119,"supported":52,"title":447,"abstract":448,"tags":450},[433],[428,449,433],"稻田",[428],{"code":438,"score":16,"supported":52,"title":452,"abstract":453,"tags":455},[439],[454,439],"灌溉",[430],{"code":32,"score":19,"supported":52,"title":457,"abstract":458,"tags":459},[60],[295,60],[],{"code":461,"score":105,"supported":52,"title":462,"abstract":463,"tags":466},"J1",[],[464,465],"农业政策","agricultural policy",[],{"code":468,"score":236,"supported":52,"title":469,"abstract":470,"tags":472},"I1",[],[471],"精准农业",[427],{"code":309,"score":242,"supported":52,"title":474,"abstract":475,"tags":477},[],[476],"机器学习",[],{"code":39,"score":21,"supported":13,"title":479,"abstract":480,"tags":481},[],[],[28],[483,484],"中国稻田 节水灌溉 空间优化","NSGA-II 水稻 温室气体 减排","中国稻田节水灌溉空间优化-2912","10.1016\u002Fj.agsy.2026.104976",{"doi":486,"openalex_id":488,"authors":489,"venue":9,"cited_by_count":101,"oa_url":415,"card":524,"direction":201,"ingested_from":102},"W7213551595",[490,492,495,498,500,502,504,506,509,511,514,517,520,522],{"name":491,"orcid":8},"Qiang Xu",{"name":493,"orcid":494},"Fan Yao","https:\u002F\u002Forcid.org\u002F0000-0002-4393-7296",{"name":496,"orcid":497},"Dan Wei","https:\u002F\u002Forcid.org\u002F0000-0003-4401-567X",{"name":499,"orcid":8},"Hui Gao",{"name":501,"orcid":8},"Min Jiang",{"name":503,"orcid":8},"Wenya Chen",{"name":505,"orcid":8},"Yourui Cao",{"name":507,"orcid":508},"Peng Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-3036-1507",{"name":510,"orcid":8},"A. I. Abdo",{"name":512,"orcid":513},"Liujun Xiao","https:\u002F\u002Forcid.org\u002F0000-0002-1900-1586",{"name":515,"orcid":516},"Hao Liang","https:\u002F\u002Forcid.org\u002F0000-0002-9955-6492",{"name":518,"orcid":519},"Xiaoqing Cui","https:\u002F\u002Forcid.org\u002F0000-0002-1970-5145",{"name":521,"orcid":8},"Xia Liang",{"name":523,"orcid":8},"Huiqing Bai",{"tldr":525,"method":526,"finding":527,"direction":201,"opportunity":528},"构建空间优化框架，为中国稻田节水灌溉推广寻找兼顾产量、温室气体与成本的路径。","耦合K-means聚类与NSGA-II多目标进化算法，基于15.7万网格的机器学","最优方案增产6.47 Mt、减排63.5 Mt CO2e，成本101.4亿元，推广率80.3%，存在","可将该空间优化框架扩展到其他气候智慧型农业技术，并耦合农户采纳行为与政策激励。","2026-09-19T23:30:05.508592Z",{"id":531,"title":532,"url":533,"summary":534,"summary_zh":535,"content":8,"source_name":113,"source_url":533,"published_at":536,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":537,"score_detail":538,"sources":540,"tags":542,"primary_topic":546,"secondary_topics":547,"classification":548,"search_phrases":576,"slug":579,"view_count":236,"doi":580,"paper":581,"created_at":597},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。","2026-09-15T00:00:00Z",84,{"impact":118,"substance":213,"depth":119,"authority":51,"freshness":144,"relevant":21,"comment":539},"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。",[541],{"name":113,"url":533},[543,27,351,544,545],"农业绿色发展","肉牛产业","畜牧业减排",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":45,"locked":13,"version":46,"method":47,"evidence":549},{"candidates":550,"agricultural_evidence":52},[551,555,559,565,571],{"code":39,"score":18,"supported":52,"title":552,"abstract":553,"tags":554},[54],[27,54],[543,351,27],{"code":32,"score":105,"supported":52,"title":556,"abstract":557,"tags":558},[],[295,60],[],{"code":355,"score":105,"supported":52,"title":560,"abstract":561,"tags":564},[],[562,563],"肉牛","cattle",[],{"code":566,"score":242,"supported":52,"title":567,"abstract":568,"tags":570},"C4",[],[569],"饲料",[],{"code":572,"score":21,"supported":13,"title":573,"abstract":574,"tags":575},"H8",[],[],[543],[577,578],"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":580,"openalex_id":582,"authors":583,"venue":113,"cited_by_count":101,"oa_url":533,"card":592,"direction":201,"ingested_from":102},"W7213306361",[584,586,588,590],{"name":585,"orcid":8},"Xianghui Yin",{"name":587,"orcid":8},"Shiqin Sun",{"name":589,"orcid":8},"Jiangge Wang",{"name":591,"orcid":8},"Tengyun Gao",{"tldr":593,"method":594,"finding":595,"direction":201,"opportunity":596},"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"]