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部署智慧农业与四季接续","https:\u002F\u002Fjx.ifeng.com\u002Fc\u002F8xPB4YCdgGF","《江西省「十五五」农业农村现代化规划》（赣府发〔2026〕16号）围绕32项重点任务展开，明确推进信息技术与农业深度融合，加快农业人工智能技术创新与场景拓展，建设农业农村大数据平台。规划还部署井冈山国家农业科技园区升建国家农高区，推广「村播」「田播」电商直播带货，并开展农产品碳足迹管理与农业碳交易。","（一）提升粮食等重要农产品供给保障水平。坚持产量产能、生产生态、增产增收一起抓，深入实施藏粮于地、藏粮于技战略，落实新一轮粮食产能提升行动，实施粮油作物大面积单产提升行动，建设吨粮片、高产片，促进良田良种良机良法集成增效。优化农产品种植结构，稳定水稻、油菜生产，大力发展油茶产业，提升大豆产能。优化生猪产能综合调控机制，推进牛羊产业扩量提质，促进畜禽养殖节本提质增效。推动农产品品种培优和品质提升，增加营养、健康、风味农产品供给。完善价格、补贴、保险“三位一体”的种粮农民收益保障机制，建立健全与周边省份粮食产销协作机制，强化粮食产购储加销协同保障。\n\n（二）构建多元化食物供给体系。践行大食物观，坚持农林牧渔并举，全方位、多用途开发食物资源。提升“菜篮子”产业质量和效益，推动蔬菜、水果、茶叶、中药材产业优质发展。丰富畜产品供给，发展蜂、兔、肉鸽、鹌鹑等特色养殖。积极发展大水面生态渔业，科学推进稻渔综合种养。发展林下经济，壮大林药和森林食品。发展富硒食品与功能食品，开发新型食品资源。\n\n（三）加强耕地保护与质量提升。严格落实耕地保护党政同责，严守耕地保护红线。统筹农用地布局优化，严格耕地占补平衡管理，规范补充耕地质量验收。科学开展红壤改良利用，推进酸化耕地治理，分阶段实施耕地有机质提升行动。分区分类高质量推进高标准农田建设，对新建和改造提升实行差异化投入，优先在鄱阳湖平原、赣抚平原、吉泰盆地等区域推进整区域建设，逐步把具备条件的永久基本农田建成高标准农田。完善高标准农田立项、建设、验收和管护机制，编制高标准农田建设全流程工作规范，统一建设标准、施工工艺、管理流程，压实管护责任。开展高标准农田整治提升行动，按照“集中修复一批、改造提升一批、疏通灌溉一批、置换退出一批”分类施策，逐步补齐设施短板、消除存量问题。健全完善问题发现响应处置机制。实施大中型灌区现代化建设与改造，推动井冈灌区、赣抚平原灌区等项目建设，强化高标准农田渠系与灌区骨干工程衔接。\n\n（四）提升农业防灾减灾救灾能力。发展韧性农业，完善农业气象、水文、地质灾害等监测预警机制。推进防洪排涝抗旱设施建设，持续开展农田沟渠修复整治、中小河流和平原涝区治理。完善农机应急救灾设施装备条件,健全和落实救灾机具配置、救灾备荒种子储备和应急调用机制，加快补齐烘干、仓储等设施装备短板。强化病虫疫情和重大动物疫病监测预警、联防联控和应急处置，建强县乡动植物疫病防控专业队伍。","凤凰网江西 2026-10-21","2026-10-21T00:00:00Z","政策",false,80,{"impact":321,"substance":584,"depth":361,"authority":173,"freshness":585,"relevant":455,"comment":586},23,9,"省级「十五五」农业农村现代化规划全文，条款与数字细节充实，涉及智慧农业、高标准农田、粮食产能等实质部署，值得进入每日精选。",[588],{"name":578,"url":575},[590,591,592,593,594],"智慧农业","高标准农田","十五五规划","大食物观","粮食产能",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":600},"classified","rules",{"candidates":601,"agricultural_evidence":603},[602,608,612,619,625,629,633,637],{"code":549,"score":524,"supported":603,"title":604,"abstract":606,"tags":607},true,[605],"农业农村现代化",[605],[],{"code":16,"score":585,"supported":603,"title":609,"abstract":610,"tags":611},[590],[],[590],{"code":160,"score":613,"supported":603,"title":614,"abstract":615,"tags":618},6,[],[616,617],"农业碳","碳足迹",[],{"code":24,"score":620,"supported":603,"title":621,"abstract":622,"tags":624},3,[],[623],"农业人工智能",[],{"code":263,"score":455,"supported":581,"title":626,"abstract":627,"tags":628},[],[],[594],{"code":450,"score":455,"supported":581,"title":630,"abstract":631,"tags":632},[],[],[593],{"code":136,"score":455,"supported":581,"title":634,"abstract":635,"tags":636},[],[],[591],{"code":542,"score":455,"supported":581,"title":638,"abstract":639,"tags":640},[],[],[592],[642,643],"江西 十五五 农业农村现代化规划","江西 高标准农田 鄱阳湖平原","江西十五五农业农村现代化规划-5498","2026-10-22T00:06:58.106992Z",{"id":647,"title":648,"url":649,"summary":650,"summary_zh":651,"content":11,"source_name":652,"source_url":649,"published_at":653,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":655,"score_detail":656,"sources":660,"tags":662,"primary_topic":668,"secondary_topics":669,"classification":672,"search_phrases":722,"slug":725,"view_count":424,"doi":726,"paper":727,"created_at":750},5472,"Turning dirt into gold: the business case of soil carbon for agrarian pathways in arid climate","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1966265","Introduction Agricultural carbon sequestration offers considerable potential for mitigating anthropogenic climate change, particularly in the low-organic-carbon soils of the Middle East. This study presents a foundational scenario-based assessment of soil carbon sequestration and economic feasibility. Materials and methods Crop production and market datasets from Jordanian statistics (1998–2023) were used to estimate potential soil carbon sequestration and economic performance. Using benchmarks from literature in comparable agroecological regions, four soil carbon management practices were evaluated across multiple crops for their carbon storage potential using Monte Carlo uncertainty and sensitivity analysis. Sensitivity of economic performance was assessed under optimistic\u002Fpessimistic scenarios. Results Among the evaluated practices, the highest carbon sequestration rate was achieved through increased Soil Organic Carbon (SOC), reaching a maximum of 27.44 metric tons of CO₂ per hectare per year (tCO₂\u002Fha\u002Fyear) under the high scenario for cucumbers. In contrast, barley showed the highest sequestration rate at 0.45 tCO₂\u002Fha\u002Fyear under increased SOC in the high scenario. Sensitivity analysis showed that ±20% uncertainty in the management coefficients resulted in practice-specific changes of 1.11 tCO₂\u002Fha\u002Fyear for increased SOC and 0.46 tCO₂\u002Fha\u002Fyear for improved cropland management. Horticultural crops, particularly cucumbers and lemons, exhibited the highest sequestration rates and strongest responses to management interventions. Field crops such as wheat, barley, and olives demonstrated lower, more stable sequestration rates. Economic analysis revealed that cucumbers, grapes, potatoes, and Open-field farming (OFF) tomatoes achieved the highest tri-pillar performance (net and adjusted profits and break-even cost) alongside effective carbon sequestration. These findings highlight that crop choice is a primary determinant of both crop profitability and sequestrated carbon potential and feasibility, with significant implications for climate-smart agriculture, carbon credit mechanisms, and intensification strategies in data-scarce regions. Study limitations While empirical field validation remains a future priority, this model-based study provides a screening-level theoretical baseline to guide targeted research and investment in arid agricultural systems.","引言 农业碳封存为缓解人为气候变化提供了可观潜力，尤其是在中东低有机碳土壤中。本研究提出了一项基于情景的土壤碳封存与经济学可行性基础评估。材料与方法 利用约旦统计数据（1998—2023年）中的作物生产和市场数据集，估算潜在的土壤碳封存及经济表现。参考可比农业生态区域文献中的基准值，采用蒙特卡洛不确定性分析和敏感性分析，评估了四种土壤碳管理措施在多种作物上的碳储存潜力。在乐观\u002F悲观情景下评估了经济表现的敏感性。结果 在评估的各项措施中，通过增加土壤有机碳（SOC）实现的碳封存速率最高，在黄瓜的高情景下达到最高27.44公吨二氧化碳\u002F公顷\u002F年（tCO₂\u002Fha\u002Fyear）。相比之下，大麦在增加SOC的高情景下表现出最高的封存速率，为0.45 tCO₂\u002Fha\u002Fyear。敏感性分析表明，管理系数±20%的不确定性导致增加SOC和改善农田管理分别产生1.11 tCO₂\u002Fha\u002Fyear和0.46 tCO₂\u002Fha\u002Fyear的措施特异性变化。园艺作物，尤其是黄瓜和柠檬，表现出最高的封存速率和对管理干预的最强响应。小麦、大麦和橄榄等大田作物表现出较低但更稳定的封存速率。经济分析显示，黄瓜、葡萄、马铃薯和露地栽培（OFF）番茄在有效碳封存的同时实现了最高的三支柱表现（净利润、调整后利润和盈亏平衡成本）。这些发现突出表明，作物选择是作物盈利能力和封存碳潜力及可行性的主要决定因素，对气候智慧型农业、碳信用机制和数据稀缺地区的集约化策略具有重要意义。研究局限性 尽管田间实证验证仍是未来的优先事项，但这项基于模型的研究提供了筛选层面的理论基线，以指导干旱农业系统中的针对性研究和投资。","Frontiers in Sustainable Food Systems","2026-10-20T00:00:00Z","论文",70,{"impact":416,"substance":508,"depth":657,"authority":658,"freshness":585,"relevant":455,"comment":659},16,13,"基于约旦1998–2023年统计数据的模型情景研究，量化了不同作物固碳速率与经济收益，对干旱区农业碳汇与碳信用机制有参考价值，但属区域性模拟研究，尚未经田间验证。",[661],{"name":652,"url":649},[663,664,665,666,667],"气候智慧农业","碳交易","干旱农业","土壤碳汇","作物选择",{"code":144,"slug":145,"name":146,"path":147,"parent_code":128},[670,671],{"code":184,"slug":185,"name":186,"path":187,"parent_code":128},{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":673},{"candidates":674,"agricultural_evidence":603},[675,680,687,692,696,702,707,712,717],{"code":144,"score":345,"supported":603,"title":676,"abstract":677,"tags":679},[145],[678,145],"土壤",[],{"code":184,"score":385,"supported":603,"title":681,"abstract":682,"tags":686},[],[683,684,685],"气候变化","干旱","climate change",[663],{"code":160,"score":173,"supported":603,"title":688,"abstract":689,"tags":691},[],[616,690],"carbon sequestration",[666,664],{"code":216,"score":613,"supported":603,"title":693,"abstract":694,"tags":695},[],[218,217],[],{"code":279,"score":613,"supported":603,"title":697,"abstract":698,"tags":701},[],[699,700],"番茄","黄瓜",[],{"code":240,"score":620,"supported":603,"title":703,"abstract":704,"tags":706},[],[705],"马铃薯",[],{"code":286,"score":620,"supported":603,"title":708,"abstract":709,"tags":711},[],[710],"葡萄",[],{"code":176,"score":620,"supported":603,"title":713,"abstract":714,"tags":716},[],[715],"农业生态",[],{"code":16,"score":620,"supported":603,"title":718,"abstract":719,"tags":721},[],[720],"smart agriculture",[],[723,724],"约旦 土壤碳汇 黄瓜","土壤固碳 经济可行性","约旦土壤碳汇黄瓜-5472","10.3389\u002Ffsufs.2026.1966265",{"doi":726,"openalex_id":728,"authors":729,"venue":652,"cited_by_count":424,"oa_url":649,"card":742,"direction":748,"ingested_from":749},"W7223064172",[730,732,734,737,739],{"name":731,"orcid":11},"Tasnim Althalaj",{"name":733,"orcid":11},"Ross. M. Thompson",{"name":735,"orcid":736},"Tala H. Qtaishat","https:\u002F\u002Forcid.org\u002F0000-0002-2700-6686",{"name":738,"orcid":11},"Dan Bumblauskas",{"name":740,"orcid":741},"Fayha Al-Shibli","https:\u002F\u002Forcid.org\u002F0000-0002-5628-0975",{"tldr":743,"method":744,"finding":745,"direction":746,"opportunity":747},"基于约旦1998–2023年数据，评估干旱区土壤固碳潜力与经济可行性。","用蒙特卡洛不确定性与敏感性分析，评估四种土壤碳管理措施在多作物下的表现。","黄瓜等园艺作物固碳率最高，作物选择是固碳与盈利的关键决定因素。","农业绿色发展与碳","数据稀缺干旱区可结合田间验证与碳信用机制，研究作物级固碳经济激励设计。","智慧农业 \u002F 农业物联网","openalex","2026-10-21T23:30:07.383006Z",{"id":752,"title":753,"url":754,"summary":755,"summary_zh":756,"content":11,"source_name":652,"source_url":754,"published_at":653,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":757,"score_detail":758,"sources":760,"tags":762,"primary_topic":768,"secondary_topics":769,"classification":771,"search_phrases":786,"slug":789,"view_count":424,"doi":790,"paper":791,"created_at":834},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。",74,{"impact":416,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":759},"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。",[761],{"name":652,"url":754},[763,764,765,766,767],"生物炭","农业废弃物","秸秆利用","土壤固碳","热解技术",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[770],{"code":144,"slug":145,"name":146,"path":147,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":772},{"candidates":773,"agricultural_evidence":603},[774,778,782],{"code":160,"score":524,"supported":603,"title":775,"abstract":776,"tags":777},[690],[690],[],{"code":144,"score":173,"supported":603,"title":779,"abstract":780,"tags":781},[],[678,145],[766,763],{"code":168,"score":408,"supported":603,"title":783,"abstract":784,"tags":785},[],[764],[764,765],[787,788],"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":790,"openalex_id":792,"authors":793,"venue":652,"cited_by_count":424,"oa_url":828,"card":829,"direction":746,"ingested_from":749},"W7223016223",[794,797,799,802,805,807,810,813,815,818,820,823,826],{"name":795,"orcid":796},"Morasanahalli Lokesha Sachin","https:\u002F\u002Forcid.org\u002F0009-0008-8615-0822",{"name":798,"orcid":11},"Yogananda Shivalli Boregowda",{"name":800,"orcid":801},"Matadadoddi Nanjundegowda Thimmegowda","https:\u002F\u002Forcid.org\u002F0000-0001-7632-1036",{"name":803,"orcid":804},"M. A. Ananthakumar","https:\u002F\u002Forcid.org\u002F0000-0003-4376-9541",{"name":806,"orcid":11},"Pudiyanda Shadali Fathima",{"name":808,"orcid":809},"C. M. Sunil","https:\u002F\u002Forcid.org\u002F0000-0002-9625-5686",{"name":811,"orcid":812},"K. M. Pravalika","https:\u002F\u002Forcid.org\u002F0009-0004-5258-392X",{"name":814,"orcid":11},"M.C. Anjali",{"name":816,"orcid":817},"Sathisha Govinakere Sambegowda","https:\u002F\u002Forcid.org\u002F0009-0000-8620-6461",{"name":819,"orcid":11},"B. Divya",{"name":821,"orcid":822},"M. K. Shruthi","https:\u002F\u002Forcid.org\u002F0000-0003-3703-9817",{"name":824,"orcid":825},"Santosh Onte","https:\u002F\u002Forcid.org\u002F0009-0002-8367-1303",{"name":827,"orcid":11},"Sanjeev Kumar","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1966170\u002Fpdf",{"tldr":830,"method":831,"finding":832,"direction":746,"opportunity":833},"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。","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":836,"title":837,"url":838,"summary":839,"summary_zh":11,"content":11,"source_name":840,"source_url":11,"published_at":11,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":841,"score_detail":842,"sources":844,"tags":846,"primary_topic":852,"secondary_topics":853,"classification":854,"search_phrases":871,"slug":874,"view_count":424,"doi":11,"paper":875,"created_at":883},5360,"国家农业绿色发展试点区对农业碳排放的影响:基于 284 城市 2013-2023 年面板数据","https:\u002F\u002Fm2.mtmt.hu\u002Fapi\u002Fpublication\u002F37540958","研究基于 284 个城市 2013—2023 年面板数据,以国家农业绿色发展试点区(NAGDPZ)为准自然实验,采用双重差分法(DID)系统评估政策对农业碳排放的影响。研究发现:(1)NAGDPZ 政策显著降低农业碳排放,系数为 -0.008(10% 显著);(2)机制分析表明减排效应主要通过农业生产效率提升、数字普惠金融发展和农村创新创业推动;(3)异质性分析显示南方、非粮食主产区、农业金融支持水平较高地区的碳减排效应更显著,系数分别为 -0.008、-.016、-0.015。","《中国环境科学》46(1):555-567 2026",78,{"impact":321,"substance":321,"depth":361,"authority":345,"freshness":69,"relevant":455,"comment":843},"基于284城市十年面板数据的政策评估，方法规范、结论有新意，但发表时间较早、时效性弱，适合作为研究型精选而非快讯。",[845],{"name":840,"url":838},[847,848,849,850,851],"农业绿色发展","数字普惠金融","双重差分","农业碳排放","绿色试点区",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":855},{"candidates":856,"agricultural_evidence":603},[857,863,867],{"code":160,"score":858,"supported":603,"title":859,"abstract":861,"tags":862},24,[860,616],"碳排放",[860,616],[850,847],{"code":503,"score":455,"supported":581,"title":864,"abstract":865,"tags":866},[],[],[848],{"code":192,"score":455,"supported":581,"title":868,"abstract":869,"tags":870},[],[],[847],[872,873],"国家农业绿色发展试点区 农业碳排放","284城市 面板数据 碳减排","国家农业绿色发展试点区农业碳排放-5360",{"doi":11,"openalex_id":11,"authors":876,"venue":11,"cited_by_count":424,"oa_url":11,"card":877,"direction":746,"ingested_from":882},[],{"tldr":878,"method":879,"finding":880,"direction":746,"opportunity":881},"基于284城市面板数据，用DID评估国家农业绿色发展试点区对农业碳排放的影响。","284城市2013-2023年面板数据，双重差分法（DID）准自然实验。","试点区政策显著降低农业碳排放，主要通过生产效率、数字普惠金融和农村创新创业实现。","可探究数字普惠金融与绿色试点政策的协同减排机制，及非粮食主产区的差异化政策设计。","agent","2026-10-20T02:47:54.150914Z",{"id":885,"title":886,"url":887,"summary":888,"summary_zh":11,"content":11,"source_name":889,"source_url":11,"published_at":890,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":891,"score_detail":892,"sources":894,"tags":896,"primary_topic":900,"secondary_topics":901,"classification":902,"search_phrases":921,"slug":924,"view_count":455,"doi":11,"paper":925,"created_at":932},5227,"China's farm digitization reduces agricultural carbon emissions but the relationship is nonlinear (U-shaped)","https:\u002F\u002Fcommonplace.workforcefutures.net\u002Fpaper\u002Fopenalex:W7221809067","Gao、Feng、Yuan、Sun 在 OpenAlex 2026-10-16 索引的最新研究,基于中国31个省份2010—2023年平衡面板数据,采用双向固定效应面板与SEM中介模型,发现农业数字技术通过精准管理与间接融资\u002F绿色创新两条路径降低碳排放,但呈U型非线性,转折点为数字化指数0.540,劳动生产率提升可推迟转折点,数字化在区域、规模、排放来源维度呈现异质性。","OpenAlex W7221809067(2026-10-16)","2026-10-16T00:00:00Z",84,{"impact":321,"substance":584,"depth":361,"authority":658,"freshness":173,"relevant":455,"comment":893},"基于31省2010—2023年面板数据的全国性实证研究，揭示数字化与农业碳排放的U型关系及0.540转折点，结论新颖且具政策参考价值，值得进入每日精选。",[895],{"name":889,"url":887},[897,590,898,850,899],"数字乡村","农业数字化","绿色创新",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":903},{"candidates":904,"agricultural_evidence":603},[905,909,913,917],{"code":160,"score":400,"supported":603,"title":906,"abstract":907,"tags":908},[],[860],[850],{"code":16,"score":69,"supported":581,"title":910,"abstract":911,"tags":912},[],[],[898,590],{"code":7,"score":455,"supported":581,"title":914,"abstract":915,"tags":916},[],[],[898],{"code":56,"score":455,"supported":581,"title":918,"abstract":919,"tags":920},[],[],[897],[922,923],"农业数字化 碳排放 U型","数字技术 农业碳减排","农业数字化碳排放U型-5227",{"doi":11,"openalex_id":11,"authors":926,"venue":11,"cited_by_count":424,"oa_url":11,"card":927,"direction":746,"ingested_from":882},[],{"tldr":928,"method":929,"finding":930,"direction":746,"opportunity":931},"基于中国31省2010—2023年面板数据，发现农业数字化与碳排放呈U型非线性关系。","双向固定效应面板模型与SEM中介模型，31省平衡面板数据。","数字化通过精准管理和绿色创新降碳，但存在0.540的U型转折点。","可探究转折点后数字化增碳的机制，及劳动生产率等调节因素如何推迟拐点。","2026-10-18T00:05:30.735414Z",{"id":934,"title":935,"url":936,"summary":937,"summary_zh":938,"content":11,"source_name":652,"source_url":936,"published_at":939,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":841,"score_detail":940,"sources":942,"tags":944,"primary_topic":949,"secondary_topics":950,"classification":951,"search_phrases":966,"slug":969,"view_count":455,"doi":970,"paper":971,"created_at":1010},4871,"Integrated treatment strategies for olive mill wastewater: bridging conventional processes with biochar-enhanced nature-based solutions","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1941820","Olive mill wastewater (OMW) is one of the most challenging agro-industrial effluents, characterized by extremely high organic load (COD: 50–150 g\u002FL), total phenol concentrations exceeding 10 g\u002FL, high salinity (EC: 2–30 mS\u002Fcm), and a dark, phytotoxic composition that severely limits the performance of biological treatment systems. Developing effective, sustainable, and scalable treatment strategies has become a critical environmental and socio-economic priority for Mediterranean olive-producing regions. This review critically assesses existing OMW treatment technologies, evaluating their mechanisms, performance ranges, failure modes, and integration potential. Conventional physicochemical methods, such as sedimentation, filtration, coagulation-flocculation, membrane processes, and adsorption, are effective for particular pollutant fractions but individually insufficient for complete treatment (respectively achieving 20–30%, 30–40%, ~50% COD reduction with 60–70% phenolic removal, 60–95% COD rejection, and 70–90% phenolic removal). Chemical oxidation and advanced oxidation processes (AOPs) can degrade recalcitrant phenolic structures (75–90% removal of phenolics) but are constrained by energy demand and sludge management. Biological processes offer COD reductions of 60–90% but are frequently inhibited by OMW’s phenolic toxicity. Integrated natural treatment systems that combine sequential physicochemical pretreatment, oxidative degradation, and biological processing emerge as the most technically viable approach. Within this framework, this review gives particular and sustained attention to biochar-enhanced constructed wetlands (BCW) as a low-energy tertiary polishing stage. Critically, BCW systems are not suited for raw or minimally pre-treated OMW, as total phenol concentrations above 400–500 mg\u002FL inhibit nitrifying bacteria and electrical conductivity above 6–10 mS\u002Fcm impairs macrophyte survival. Applied to pre-treated effluents, conventional CW systems have achieved 74–87% phenolic removal and 83–98% COD reduction, while biochar-specific validation on OMW matrices remains an identified gap; BCW systems are expected to provide additional benefits for nutrient removal and carbon sequestration based on evidence from non-OMW wastewater matrices. Biochar derived from olive mill by-products themselves offers a particularly attractive circular economy pathway. This work highlights the need to move beyond single-process optimization toward integrated, scalable frameworks that combine high removal efficiency with sustainability and circular-economy principles and identifies the key scientific and engineering gaps that remain to be resolved.","橄榄磨废水（OMW）是最具挑战性的农业工业废水之一，其特点是有机负荷极高（COD：50–150 g\u002FL）、总酚浓度超过10 g\u002FL、盐度高（EC：2–30 mS\u002Fcm），且呈深色、具有植物毒性，严重限制了生物处理系统的性能。开发有效、可持续且可规模化的处理策略已成为地中海橄榄产区紧迫的环境和社会经济优先事项。本综述批判性地评估了现有OMW处理技术，考察其机理、性能范围、失效模式及整合潜力。常规物理化学方法，如沉淀、过滤、混凝-絮凝、膜过程和吸附，对特定污染物组分有效，但单独使用不足以实现完全处理（分别实现20–30%、30–40%、约50%的COD去除及60–70%的酚类去除、60–95%的COD截留和70–90%的酚类去除）。化学氧化和高级氧化工艺（AOPs）可降解难降解的酚类结构（酚类去除率75–90%），但受限于能耗和污泥管理。生物处理可实现60–90%的COD去除，但常因OMW的酚类毒性而受到抑制。将序批式物理化学预处理、氧化降解和生物处理相结合的综合自然处理系统，成为技术上最可行的方案。在此框架下，本综述特别并持续关注生物炭强化人工湿地（BCW）作为低能耗三级深度处理阶段。关键在于，BCW系统不适用于原水或仅经最低限度预处理的OMW，因为总酚浓度高于400–500 mg\u002FL会抑制硝化细菌，电导率高于6–10 mS\u002Fcm会损害大型水生植物存活。应用于预处理出水时，常规人工湿地系统已实现74–87%的酚类去除和83–98%的COD削减，而针对OMW基质的生物炭专项验证仍属空白；基于非OMW废水基质的证据，BCW系统有望在营养盐去除和碳封存方面提供额外效益。由橄榄磨副产物本身制备的生物炭提供了一条特别有吸引力的循环经济路径。本研究强调，需要超越单一工艺优化，转向集成化、可规模化的","2026-10-13T00:00:00Z",{"impact":657,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":941},"地中海橄榄油废水处理综述，数据翔实、方法新颖，对农产品加工废弃物资源化与循环农业有参考价值，但地域性强、与国内三农信息化关联偏弱。",[943],{"name":652,"url":936},[763,945,946,947,948],"循环农业","橄榄油加工","废水处理","人工湿地",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":952},{"candidates":953,"agricultural_evidence":603},[954,958,962],{"code":160,"score":620,"supported":603,"title":955,"abstract":956,"tags":957},[],[690],[],{"code":144,"score":455,"supported":581,"title":959,"abstract":960,"tags":961},[],[],[763],{"code":192,"score":455,"supported":581,"title":963,"abstract":964,"tags":965},[],[],[945],[967,968],"橄榄油厂废水 生物炭 人工湿地","橄榄油加工 人工湿地 废水处理 循环农业","橄榄油厂废水生物炭人工湿地-4871","10.3389\u002Ffsufs.2026.1941820",{"doi":970,"openalex_id":972,"authors":973,"venue":652,"cited_by_count":424,"oa_url":936,"card":1005,"direction":746,"ingested_from":749},"W7221620782",[974,976,979,982,984,986,988,991,993,996,999,1002],{"name":975,"orcid":11},"Chaimae Maldou",{"name":977,"orcid":978},"Konstantinos Tsamoutsoglou","https:\u002F\u002Forcid.org\u002F0009-0003-5980-9584",{"name":980,"orcid":981},"Ayoub El Ghadraoui","https:\u002F\u002Forcid.org\u002F0000-0002-5494-036X",{"name":983,"orcid":11},"Tonni Agustiono Kurniawan",{"name":985,"orcid":11},"Nacer Badi",{"name":987,"orcid":11},"Saleh A. Alghamdi",{"name":989,"orcid":990},"Abdulrhman M. Alsharari","https:\u002F\u002Forcid.org\u002F0000-0002-6993-1597",{"name":992,"orcid":11},"Adnan Sulaiman Almasoudi",{"name":994,"orcid":995},"F. M. Aldosari","https:\u002F\u002Forcid.org\u002F0000-0002-0854-9335",{"name":997,"orcid":998},"Theodore Azemtsop Manfo","https:\u002F\u002Forcid.org\u002F0000-0002-9043-3111",{"name":1000,"orcid":1001},"Anas Tallou","https:\u002F\u002Forcid.org\u002F0000-0002-1540-3561",{"name":1003,"orcid":1004},"Faissal Aziz","https:\u002F\u002Forcid.org\u002F0000-0001-9144-6400",{"tldr":1006,"method":1007,"finding":1008,"direction":746,"opportunity":1009},"综述橄榄油厂废水处理技术，重点评估生物炭强化人工湿地作为三级深度处理。","文献综述，比较物化、氧化、生物及集成工艺，分析生物炭人工湿地数据。","集成预处理+生物处理最可行，但生物炭人工湿地处理原废水受酚和盐度限制，需验证。","生物炭人工湿地处理橄榄油厂废水的实证研究空白，可结合橄榄副产物生物炭与碳封存。","2026-10-14T23:30:07.013601Z",{"id":1012,"title":1013,"url":1014,"summary":1015,"summary_zh":1016,"content":11,"source_name":652,"source_url":1014,"published_at":939,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":1017,"score_detail":1018,"sources":1022,"tags":1024,"primary_topic":1029,"secondary_topics":1030,"classification":1031,"search_phrases":1038,"slug":1041,"view_count":424,"doi":1042,"paper":1043,"created_at":1066},4870,"Association of energy poverty, import and export diversification with agricultural sector performance in South Asia","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1749155","This paper examines the association between energy poverty, import diversification, export diversification, and agricultural sector performance in South Asia, while controlling for carbon dioxide emissions from agriculture and employment in agriculture. Using panel data for eight South Asian countries—Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka—covering the period from 2000 to 2023, the study constructs an Energy Poverty Index through Principal Component Analysis based on six energy-related indicators. The Feasible Generalized Least Squares results show that better energy conditions and lower energy poverty are positively associated with agricultural sector performance. In contrast, import diversification and carbon dioxide emissions from agriculture are negatively associated with agricultural sector performance, while export diversification is positively associated with it. Employment in agriculture shows a positive but statistically insignificant association. These findings remain robust when Panel-Corrected Standard Errors and Driscoll–Kraay standard error estimators are applied. Overall, the results suggest that improved energy access, environmentally sustainable agricultural practices, and strategic trade diversification are closely linked to agricultural sector performance in South Asia.","本文考察了南亚地区能源贫困、进口多样化、出口多样化与农业部门绩效之间的关联，同时控制了农业二氧化碳排放和农业就业。研究使用八个南亚国家——阿富汗、孟加拉国、不丹、印度、马尔代夫、尼泊尔、巴基斯坦和斯里兰卡——2000年至2023年的面板数据，基于六项能源相关指标，通过主成分分析构建了能源贫困指数。可行广义最小二乘法（Feasible Generalized Least Squares）结果显示，更好的能源条件和更低的能源贫困与农业部门绩效呈正相关。相比之下，进口多样化和农业二氧化碳排放与农业部门绩效呈负相关，而出口多样化则与其呈正相关。农业就业显示出正相关，但在统计上不显著。在应用面板校正标准误（Panel-Corrected Standard Errors）和Driscoll–Kraay标准误估计量后，这些发现仍然稳健。总体而言，结果表明，改善能源获取、环境可持续的农业实践以及战略性贸易多样化与南亚农业部门绩效密切相关。",72,{"impact":416,"substance":1019,"depth":1020,"authority":658,"freshness":585,"relevant":455,"comment":1021},21,17,"基于南亚八国2000—2023年面板数据的实证研究，方法规范、结论有新意，但属区域学术成果，公共政策影响有限。",[1023],{"name":652,"url":1014},[850,1025,1026,1027,1028],"面板数据","南亚农业","能源贫困","农业贸易",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1032},{"candidates":1033,"agricultural_evidence":603},[1034],{"code":160,"score":400,"supported":603,"title":1035,"abstract":1036,"tags":1037},[],[860],[850],[1039,1040],"南亚 能源贫困","南亚 农产品 出口多元化","南亚能源贫困-4870","10.3389\u002Ffsufs.2026.1749155",{"doi":1042,"openalex_id":1044,"authors":1045,"venue":652,"cited_by_count":424,"oa_url":1014,"card":1061,"direction":746,"ingested_from":749},"W7221619650",[1046,1049,1051,1053,1055,1057,1059],{"name":1047,"orcid":1048},"Abdullah‐Al Mamun","https:\u002F\u002Forcid.org\u002F0000-0002-3251-4271",{"name":1050,"orcid":11},"Md. Golam Kibria",{"name":1052,"orcid":11},"Farian Tahrim",{"name":1054,"orcid":11},"Jeremy Ko",{"name":1056,"orcid":11},"Chun Kai Leung",{"name":1058,"orcid":11},"Mohammad Ridwan",{"name":1060,"orcid":11},"Wai-kit Ming",{"tldr":1062,"method":1063,"finding":1064,"direction":746,"opportunity":1065},"研究南亚八国能源贫困、进出口多样化与农业表现的关系。","2000-2023年面板数据，主成分分析构建能源贫困指数，FGLS回归。","能源改善和出口多样化正向关联农业表现，进口多样化和农业碳排放负向关联。","可深入探究能源贫困缓解与农业碳减排的协同机制及南亚区域异质性。","2026-10-14T23:30:06.945702Z",{"id":1068,"title":1069,"url":1070,"summary":1071,"summary_zh":1072,"content":11,"source_name":1073,"source_url":1070,"published_at":1074,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":841,"score_detail":1075,"sources":1077,"tags":1079,"primary_topic":1085,"secondary_topics":1086,"classification":1087,"search_phrases":1108,"slug":1111,"view_count":424,"doi":1112,"paper":1113,"created_at":1131},4835,"Spatiotemporal Patterns of Carbon Storage and Their Driving Mechanisms Under Multiple Land-Use Scenarios: A Case Study of the Henan Section of the South-to-North Water Diversion Project","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101928","The water source area of the Henan Reach for the South-to-North Water Diversion Project is an important ecological protection zone, where variations in land-use patterns can adversely affect the region’s carbon sink capacity and long-term ecological stability. To examine the spatiotemporal distribution of carbon sinks and clarify the underlying factors driving their changes, an analytical framework combining PLUS, InVEST, and GeoDetector was applied. Xichuan County, Xixia County, Neixiang County, and Dengzhou City—four administrative units in Nanyang City that together form the Henan water source zone of the Middle Route—were selected as the research areas. Land-use records from 2002 to 2023 were analyzed to identify changes in the production–living–ecological (PLE) land-use structure and carbon storage dynamics through 2030 under four development scenarios: natural development, ecological protection, cultivated land protection, and engineering safety. The results indicated a gradual expansion of ecological land, while cultivated land and general ecological land exhibited distinct development trajectories. Spatially, carbon storage showed a pronounced west–high\u002Feast–low pattern, with high-density zones concentrated in the northwestern mountainous and hilly terrain under key ecological land and low-density zones prevailing in the eastern plains, urban built-up areas, and the Danjiangkou Reservoir surface. During the observation period, carbon gain patches proliferated across the northwestern mountains and reservoir-adjacent ecological restoration belts, whereas carbon loss areas gradually expanded from scattered hotspots toward the eastern plains and river valleys. Regional carbon sink initially decreased slightly but subsequently showed a gradual increase. Ecological land functioned as the primary carbon sink, whereas cultivated land contributed the largest share of carbon emissions. Across the simulated trajectories, the ecological conservation scenario resulted in the highest carbon sequestration, followed by the cultivated land protection scenario, while the natural development and engineering safety scenarios showed relatively limited carbon sequestration effects. Under the four scenarios, the projected 2030 spatial layout preserved the prevailing west–high\u002Feast–low configuration but diverged notably in the distribution of gains and losses: the ecological protection scenario generated connected carbon gain patches over the northwestern mountains and reservoir restoration belts, the cropland protection scenario triggered dispersed carbon loss zones around urban peripheries and river valley agricultural belts, and the engineering safety scenario maintained the most stable spatial pattern. GeoDetector analysis identified slope, elevation, and NDVI as the principal factors associated with spatial variations in carbon sink. Furthermore, the interaction between slope and NDVI produced the highest explanatory power, indicating that their combined influence on the phenomenon was significantly stronger than the effect of either factor alone. Based on these findings, adjustments to the land-use plan are proposed to enhance carbon sequestration and strengthen ecological security in the Henan section of the South-to-North Water Diversion Project.","南水北调工程河南段水源区是重要的生态保护区域，土地利用格局的变化会对区域碳汇能力和长期生态稳定性产生不利影响。为探究碳汇的时空分布特征并厘清其变化的驱动因素，本研究构建了PLUS、InVEST与GeoDetector相结合的分析框架。选取南阳市西川县、西峡县、内乡县和邓州市四个行政区作为研究区，四者共同构成中线工程河南水源区。基于2002—2023年土地利用记录，分析了生产—生活—生态（PLE）土地利用结构的变化，并在自然发展、生态保护、耕地保护和工程安全四种发展情景下模拟了至2030年的碳储量动态。结果表明，生态用地逐步扩张，而耕地和一般生态用地呈现出不同的发展轨迹。空间上，碳储量表现出显著的西高东低格局，高密度区集中于西北部山地丘陵地带的重点生态用地，低密度区则主要分布在东部平原、城市建成区和丹江口水库水面。观测期内，碳增益斑块在西北部山区和水库周边生态修复带不断扩展，而碳损失区域则从零星热点逐步向东部平原和河谷蔓延。区域碳汇初期略有下降，随后呈逐步增加趋势。生态用地是主要的碳汇来源，而耕地贡献了最大的碳排放份额。在各模拟情景中，生态保护情景的碳固持效果最佳，其次是耕地保护情景，而自然发展和工程安全情景的碳固持效果相对有限。四种情景下，2030年预测空间布局均保持了西高东低的基本格局，但在增益与损失的分布上存在显著差异：生态保护情景在西北部山区形成了连片的碳增益斑块，并","Land","2026-10-10T00:00:00Z",{"impact":657,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":1076},"核心期刊论文，方法组合新颖、情景模拟数据扎实，对水源区生态保护与土地利用规划有参考价值，但属区域案例研究，公共影响层级有限。",[1078],{"name":1073,"url":1070},[1080,1081,1082,1083,1084],"生态保护","遥感监测","土地利用","碳储量","南水北调",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1088},{"candidates":1089,"agricultural_evidence":603},[1090,1095,1100,1104],{"code":160,"score":385,"supported":603,"title":1091,"abstract":1092,"tags":1094},[],[860,1093,690],"碳汇",[1083],{"code":136,"score":620,"supported":603,"title":1096,"abstract":1097,"tags":1099},[],[1098],"耕地保护",[],{"code":176,"score":69,"supported":581,"title":1101,"abstract":1102,"tags":1103},[],[],[1082,1080],{"code":32,"score":455,"supported":581,"title":1105,"abstract":1106,"tags":1107},[],[],[1081],[1109,1110],"南水北调 河南水源区 碳储量","PLUS InVEST GeoDetector 土地利用","南水北调河南水源区碳储量-4835","10.3390\u002Fland15101928",{"doi":1112,"openalex_id":1114,"authors":1115,"venue":1073,"cited_by_count":424,"oa_url":1070,"card":1126,"direction":746,"ingested_from":749},"W7221508293",[1116,1118,1121,1123],{"name":1117,"orcid":11},"Xiaoyang Li",{"name":1119,"orcid":1120},"Wei Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-6322-2597",{"name":1122,"orcid":11},"Qi Jia",{"name":1124,"orcid":1125},"Lei Liu","https:\u002F\u002Forcid.org\u002F0000-0002-4966-5914",{"tldr":1127,"method":1128,"finding":1129,"direction":746,"opportunity":1130},"结合PLUS、InVEST与地理探测器，模拟南水北调河南水源区多情景土地利用与碳储时空演变及驱动机制","PLUS-InVEST-GeoDetector耦合框架，2002-2023年土地","碳储呈西高东低格局，生态保护情景固碳最优，生态用地为主要碳汇、耕地为主要排放源。","可引入多目标优化与政策成本约束，量化水源区生态保护与耕地保护的碳汇权衡协同路径。","2026-10-13T23:30:53.020186Z",{"id":1133,"title":1134,"url":1135,"summary":1136,"summary_zh":1137,"content":11,"source_name":1138,"source_url":1135,"published_at":1139,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":582,"score_detail":1140,"sources":1142,"tags":1144,"primary_topic":1147,"secondary_topics":1148,"classification":1149,"search_phrases":1167,"slug":1170,"view_count":400,"doi":1171,"paper":1172,"created_at":1187},4520,"Agricultural Industry Agglomeration and Carbon Emission Intensity: A Systems Perspective on Resilience and Digital Development","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsystems14101263","Decarbonizing agriculture depends not only on the efficiency of individual production activities but also on coordination among production, processing, and service activities. From a systems perspective, this study treats provincial agriculture as an interconnected industrial system and examines the relationship between agricultural industry agglomeration and agricultural carbon emission intensity. Moving beyond conventional measures of production concentration, agricultural industry agglomeration is measured as coordination between horizontal agglomeration in agricultural production and vertical agglomeration across production, processing, and agricultural services. Based on a balanced panel of 390 observations across 30 Chinese provinces from 2011 to 2023, the study uses province and year fixed effects, mediation and moderation analyses, robustness checks, and an endogeneity check. Results show that agricultural industry agglomeration is significantly associated with lower agricultural carbon emission intensity. The mediation results are consistent with a partial intermediary role for agricultural industry resilience in this relationship. The interaction and simple slope results show that the positive association between agricultural industry agglomeration and agricultural industry resilience is larger at higher levels of digital village development. These findings connect subsystem coordination, adaptive capacity, digital conditions, and carbon performance, thereby extending research on agricultural transformation toward lower carbon intensity from a systems perspective.","农业脱碳不仅取决于单个生产活动的效率，还取决于生产、加工和服务活动之间的协调。本研究从系统视角出发，将省级农业视为一个相互关联的产业系统，考察农业产业集聚与农业碳排放强度之间的关系。本研究超越传统的生产集中度衡量方式，将农业产业集聚界定为农业生产横向集聚与生产、加工及农业服务纵向集聚之间的协调。基于2011年至2023年中国30个省份390个观测值的平衡面板数据，本研究采用省份和年份固定效应、中介与调节分析、稳健性检验以及内生性检验。结果表明，农业产业集聚与较低的农业碳排放强度显著相关。中介结果表明，农业产业韧性在这一关系中发挥部分中介作用。交互效应和简单斜率结果表明，在数字乡村发展水平较高时，农业产业集聚与农业产业韧性之间的正向关联更强。这些发现将子系统协调、适应能力、数字条件与碳绩效联系起来，从而从系统视角拓展了农业向低碳强度转型的研究。","Systems","2026-10-08T00:00:00Z",{"impact":361,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":1141},"基于30省2011-2023年面板数据，从系统视角揭示农业产业集聚通过韧性降低碳排放强度，并受数字乡村发展调节，方法规范、结论有政策参考价值。",[1143],{"name":1138,"url":1135},[897,590,1145,850,1146],"农业韧性","农业产业集聚",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1150},{"candidates":1151,"agricultural_evidence":603},[1152,1157,1163],{"code":160,"score":361,"supported":603,"title":1153,"abstract":1155,"tags":1156},[1154],"carbon emission",[860,616,1154],[850],{"code":56,"score":1158,"supported":603,"title":1159,"abstract":1160,"tags":1162},7,[],[897,1161],"digital village",[897],{"code":16,"score":455,"supported":581,"title":1164,"abstract":1165,"tags":1166},[],[],[590],[1168,1169],"农业产业集聚 碳排放强度","数字乡村 农业韧性","农业产业集聚碳排放强度-4520","10.3390\u002Fsystems14101263",{"doi":1171,"openalex_id":1173,"authors":1174,"venue":1138,"cited_by_count":424,"oa_url":1135,"card":1181,"direction":1186,"ingested_from":749},"W7220924322",[1175,1177,1179],{"name":1176,"orcid":11},"Jinghui Hu",{"name":1178,"orcid":11},"Jun He",{"name":1180,"orcid":11},"Junzhong He",{"tldr":1182,"method":1183,"finding":1184,"direction":746,"opportunity":1185},"从系统视角研究中国省级农业产业集聚对农业碳排放强度的影响及韧性与数字化的作用。","30省2011-2023年面板数据，固定效应、中介与调节分析。","农业产业集聚显著降低碳排放强度，产业韧性部分中介，数字乡村发展正向调节。","可探究产业集聚不同模式与数字化协同对碳减排的非线性及空间溢出效应。","数字乡村与农业信息化","2026-10-09T23:30:32.435467Z",{"id":1189,"title":1190,"url":1191,"summary":1192,"summary_zh":1193,"content":11,"source_name":1194,"source_url":1191,"published_at":1195,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":1196,"score_detail":1197,"sources":1199,"tags":1201,"primary_topic":1206,"secondary_topics":1207,"classification":1208,"search_phrases":1235,"slug":1238,"view_count":424,"doi":1239,"paper":1240,"created_at":1266},4510,"Organic carbon sequestration potential in alluvial agricultural terraces: A case study of a lama-bordo system in Oaxaca, Mexico","https:\u002F\u002Fdoi.org\u002F10.4067\u002Fs0718-58392026000600930","Soil is the primary C reservoir in terrestrial ecosystems and provides a variety of ecosystem services.Therefore, quantifying soil organic C (SOC) storage is essential for conservation technologies that ensure the sustainability of this non-renewable resource.In this context, the objective of this study was to estimate the SOC content within a pre-Hispanic agricultural terrace system, known locally as lama-bordo, in the Mixteca Alta region of Oaxaca, Mexico, using soil sampling, remote sensing, and geographic information systems.Based on the organic matter content, the SOC was determined in each soil sample from the surface layer (0-30 cm).The total SOC content in the lama-bordo system (LBS) was estimated using the average depth of each section and a highresolution digital elevation model.The results indicate that the LBS is capable of storing between 254.88 and 449.68 Mg ha -1 SOC, which can prevent the emission of C into the atmosphere through its conservation.These findings highlight the need for further research to generate more comprehensive knowledge of the functions of alluvial agricultural terraces.","土壤是陆地生态系统中主要的碳库，并提供多种生态系统服务。因此，量化土壤有机碳（SOC）储量对于确保这一不可再生资源可持续性的保护技术至关重要。在此背景下，本研究旨在利用土壤采样、遥感（remote sensing）和地理信息系统（geographic information systems），估算墨西哥瓦哈卡州米斯特卡阿尔塔地区一处前西班牙时期的农业梯田系统（当地称为lama-bordo）中的SOC含量。基于有机质含量，测定了每个表层（0-30 cm）土壤样品的SOC。利用每个断面的平均深度和高分辨率数字高程模型（digital elevation model），估算了lama-bordo系统（LBS）的SOC总含量。结果表明，LBS能够储存254.88至449.68 Mg ha⁻¹的SOC，通过对其进行保护可防止碳释放到大气中。这些发现凸显了进一步研究的必要性，以更全面地认识冲积农业梯田的功能。","Chilean journal of agricultural research","2026-10-07T00:00:00Z",66,{"impact":173,"substance":508,"depth":1020,"authority":658,"freshness":173,"relevant":455,"comment":1198},"基于遥感与GIS量化前西班牙时期梯田系统固碳潜力，方法新颖数据扎实，但属区域案例研究，公共影响有限。",[1200],{"name":1194,"url":1191},[1202,766,1203,1204,1205],"遥感","地理信息系统","墨西哥","农业梯田",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1209},{"candidates":1210,"agricultural_evidence":603},[1211,1215,1219,1224,1230],{"code":160,"score":173,"supported":603,"title":1212,"abstract":1213,"tags":1214},[690],[],[],{"code":144,"score":1158,"supported":603,"title":1216,"abstract":1217,"tags":1218},[],[678,145],[766],{"code":32,"score":1158,"supported":603,"title":1220,"abstract":1221,"tags":1223},[],[1202,1222],"remote sensing",[1202],{"code":40,"score":1158,"supported":603,"title":1225,"abstract":1226,"tags":1229},[],[1227,1228],"地理信息","geographic information",[1203],{"code":176,"score":620,"supported":603,"title":1231,"abstract":1232,"tags":1234},[],[1233],"生态系统服务",[],[1236,1237],"Oaxaca lama-bordo 梯田 固碳","墨西哥 梯田 土壤有机碳","Oaxacalama-bordo梯田固碳-4510","10.4067\u002Fs0718-58392026000600930",{"doi":1239,"openalex_id":1241,"authors":1242,"venue":1194,"cited_by_count":424,"oa_url":1259,"card":1260,"direction":1265,"ingested_from":749},"W7220837836",[1243,1245,1248,1251,1253,1256],{"name":1244,"orcid":11},"B. Estela Santiago-Mejía",{"name":1246,"orcid":1247},"Demetrio S. Fernández-Reynoso","https:\u002F\u002Forcid.org\u002F0000-0002-1734-3152",{"name":1249,"orcid":1250},"Gerardo Colín-García","https:\u002F\u002Forcid.org\u002F0000-0002-3155-6699",{"name":1252,"orcid":11},"M. Magdalena Nevárez-Favela",{"name":1254,"orcid":1255},"Moisés Márquez-Velázquez","https:\u002F\u002Forcid.org\u002F0009-0004-9341-628X",{"name":1257,"orcid":1258},"Madai Sánchez-Galindo","https:\u002F\u002Forcid.org\u002F0000-0002-4371-0817","http:\u002F\u002Fwww.scielo.cl\u002Fpdf\u002Fchiljar\u002Fv86n6\u002F0718-5839-chiljar-86-06-930.pdf",{"tldr":1261,"method":1262,"finding":1263,"direction":746,"opportunity":1264},"估算墨西哥瓦哈卡前西班牙时期梯田系统的土壤有机碳储量。","土壤采样、遥感与GIS结合，基于DEM估算0-30cm SOC。","梯田系统可储存254.88-449.68 Mg\u002Fha SOC，保护可防止碳释放。","可延伸研究不同梯田类型或区域的碳汇潜力及保护措施的固碳效益。","农业遥感与作物表型","2026-10-09T23:30:26.302393Z",{"id":1268,"title":1269,"url":1270,"summary":1271,"summary_zh":1272,"content":11,"source_name":652,"source_url":1270,"published_at":1195,"category":654,"cover_url":11,"hotness":447,"is_selected":581,"score":582,"score_detail":1273,"sources":1275,"tags":1280,"primary_topic":1282,"secondary_topics":1283,"classification":1285,"search_phrases":1312,"slug":1315,"view_count":424,"doi":1316,"paper":1317,"created_at":1334},4416,"Agricultural blockchain readiness environment and carbon emission intensity in maize production: evidence from provincial panel data in major maize-producing areas of China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1942225","China’s major maize-producing regions face the joint challenge of sustaining food production and reducing agricultural emissions. Existing research on digital agriculture often uses broad digitalization measures and therefore does not distinguish the regional conditions that may enable information management, traceability, and verification applications associated with blockchain. This study constructs an Agricultural Blockchain Readiness Environment Index (ABRE Index, block_index) using entropy weighting across digital infrastructure, the agricultural industrial base, and policy support. The index measures regional readiness and enabling conditions rather than realized blockchain adoption. Using 180 province-year observations for 12 major maize-producing provinces from 2010 to 2024, we estimate two-way fixed-effects models with province-clustered inference and conduct supplementary robustness analyses. The ABRE Index is negatively associated with carbon emissions per unit of maize-sown area, with the baseline coefficient statistically significant at the 10% level under conventional clustered inference and supported by supplementary inference procedures. The coefficient remains negative in all 12 leave-one-out specifications, is statistically significant at the 10% level or better in 10 specifications, and the wild cluster bootstrap test yields p = 0.0415. The index is positively correlated with blockchain-related patent activity ( r = 0.1883, p = 0.0114), although this correlation does not establish that the index measures realized adoption. The mechanism analysis is consistent with an organizational pathway through agricultural socialized services: the ABRE Index is positively associated with service_ratio (0.1099, p \u003C 0.01), and agricultural socialized services are negatively associated with ce_area (−2.2765, p \u003C 0.05). The interaction with the high-development indicator is negative but does not reach the conventional 10% significance threshold (−0.1499, p = 0.103). Overall, the evidence supports an associational relationship between blockchain-readiness conditions and maize-production carbon-emission intensity; it does not establish a strictly causal effect of blockchain adoption.","中国主要玉米产区面临保障粮食生产与减少农业排放的双重挑战。现有数字农业研究多采用宽泛的数字化指标，因而未能区分可能支撑与区块链相关的信息管理、追溯和验证应用的区域条件。本研究基于数字基础设施、农业产业基础和政策支持三个维度，采用熵权法构建了农业区块链就绪环境指数（ABRE Index，block_index）。该指数衡量的是区域就绪程度和使能条件，而非已实现的区块链采用。利用2010年至2024年12个主要玉米生产省份的180个省份—年份观测值，我们估计了双向固定效应模型，采用省份聚类推断，并进行了补充稳健性分析。ABRE指数与单位玉米播种面积碳排放呈负相关，基准系数在常规聚类推断下于10%水平上统计显著，并得到补充推断程序的支持。在全部12个逐一剔除（leave-one-out）设定中，该系数均保持为负，其中10个设定在10%或更优水平上统计显著，野生聚类自举检验（wild cluster bootstrap test）得出p = 0.0415。该指数与区块链相关专利活动呈正相关（r = 0.1883，p = 0.0114），尽管这一相关性并不能证明该指数衡量的是已实现的采用。机制分析与通过农业社会化服务发挥作用的组织路径相一致：ABRE指数与service_ratio呈正相关（0.1099，p \u003C 0.01），农业社会化服务与ce_area呈负相关（−2.2765，p \u003C 0.05）。与高发展指标的交互项为负，但未达到常规10%显著性阈值（−0.1499，p = 0.103）。总体而言，证据支持区块链就绪条件与玉米生产碳排放强度之间存在关联关系；但并未确立区块链采用的严格因果效应。",{"impact":361,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":1274},"基于12个玉米主产省2010—2024年面板数据构建农业区块链就绪环境指数，发现其与玉米碳排放强度负相关，方法规范、数据规模可观，但结论仅为关联性而非因果，属细分领域实证进展。",[1276,1277],{"name":652,"url":1270},{"name":1278,"url":1279},"Frontiers in Sustainable Food Systems 2026 年 10 月 07 日 Volume 10 Sec. Land, Livelihoods and Food Security","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1942225\u002Ffull",[897,590,226,850,1281],"区块链",{"code":224,"slug":225,"name":226,"path":227,"parent_code":200},[1284],{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":1286},{"candidates":1287,"agricultural_evidence":603},[1288,1293,1297,1303,1308],{"code":224,"score":1289,"supported":603,"title":1290,"abstract":1291,"tags":1292},15,[225],[226,225],[226],{"code":160,"score":416,"supported":603,"title":1294,"abstract":1295,"tags":1296},[1154],[860],[850],{"code":16,"score":1158,"supported":603,"title":1298,"abstract":1299,"tags":1302},[],[1300,1301],"数字农业","digital agriculture",[590],{"code":496,"score":620,"supported":603,"title":1304,"abstract":1305,"tags":1307},[],[1306],"社会化服务",[],{"code":56,"score":455,"supported":581,"title":1309,"abstract":1310,"tags":1311},[],[],[897],[1313,1314],"农业区块链 玉米 碳排放","玉米主产区 区块链 碳强度","农业区块链玉米碳排放-4416","10.3389\u002Ffsufs.2026.1942225",{"doi":1316,"openalex_id":1318,"authors":1319,"venue":652,"cited_by_count":424,"oa_url":1328,"card":1329,"direction":748,"ingested_from":749},"W7220869193",[1320,1323,1325],{"name":1321,"orcid":1322},"Pengfei Zhou","https:\u002F\u002Forcid.org\u002F0000-0003-2117-7967",{"name":1324,"orcid":11},"Zhiyi Hu",{"name":1326,"orcid":1327},"Yang Shen","https:\u002F\u002Forcid.org\u002F0000-0002-6781-6915","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1942225\u002Fpdf",{"tldr":1330,"method":1331,"finding":1332,"direction":746,"opportunity":1333},"构建农业区块链就绪环境指数，分析其与玉米生产碳排放强度的关联。","熵权法构建ABRE指数，用2010-2024年12省面板数据做双向固定效应模型。","ABRE指数与玉米单位播种面积碳排放负相关，机制可能通过农业社会化服务实现。","可探究区块链就绪环境通过社会化服务减碳的因果机制，并拓展到其他主粮作物或区域。","2026-10-08T23:30:07.668939Z",{"id":1336,"title":1337,"url":1338,"summary":1339,"summary_zh":1340,"content":11,"source_name":652,"source_url":1338,"published_at":1195,"category":654,"cover_url":11,"hotness":447,"is_selected":581,"score":1341,"score_detail":1342,"sources":1344,"tags":1349,"primary_topic":1355,"secondary_topics":1356,"classification":1357,"search_phrases":1377,"slug":1380,"view_count":455,"doi":1381,"paper":1382,"created_at":1396},4414,"Coupling coordination of digital finance, green fiscal support, and green technology adoption in China's agri-food systems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1947255","Whether agri-food systems can move toward lower emissions depends not just on how strong each enabling factor is, but on how well finance, public support, and production technology advance in step with one another. This study measures the coupling coordination degree among digital finance, green fiscal support, and agricultural green technology adoption across 30 Chinese provinces from 2011 to 2023, and traces its spatiotemporal patterns, regional disparities, convergence, and constraining factors. The entropy weight method and a three-system coupling coordination model are paired with Dagum Gini decomposition, convergence tests, and an obstacle-degree diagnosis. Coordination climbed from 0.37 to 0.71 across the period, shifting from mild imbalance toward intermediate coordination, yet an eastern–central–western gradient held throughout. Overall disparities narrowed, and gaps between regions made up close to 85% of the total. Coefficients of variation fell nationally and within each belt, both absolute and conditional convergence held, and the western region closed its gap fastest. Over time the binding constraint moved away from digital finance toward green fiscal support and fertilizer-use efficiency. Coordination and agricultural carbon intensity were negatively related, though the pattern reflects correlation rather than an identified causal effect. Together these results show where coordinated development falls short and what holds it back, giving some basis for regionally differentiated policy.","农业食物系统能否走向更低排放，不仅取决于各使能因素的强度，更取决于金融、公共支持与生产技术能否彼此同步推进。本研究测度了2011—2023年中国30个省份数字金融、绿色财政支持与农业绿色技术采纳之间的耦合协调度，并追踪其时空格局、区域差异、收敛性及制约因素。研究将熵权法与三系统耦合协调模型，同Dagum基尼分解、收敛检验及障碍度诊断相结合。协调度在此期间由0.37升至0.71，由轻度失衡转向中度协调，但东—中—西梯度始终存在。总体差异有所缩小，区域间差距约占总差异的85%。全国及各地带内变异系数均下降，绝对收敛与条件收敛均成立，西部地区追赶最快。随时间推移，主要约束已从数字金融转向绿色财政支持与化肥利用效率。协调度与农业碳排放强度呈负相关，但该格局反映的是相关关系，而非已识别的因果效应。上述结果共同揭示了协调发展不足所在及其制约因素，为区域差异化政策提供了一定依据。",79,{"impact":361,"substance":321,"depth":361,"authority":658,"freshness":173,"relevant":455,"comment":1343},"基于30省2011-2023年面板数据的耦合协调实证研究，方法规范、结论有政策参考价值，但属学术论文而非产业动态，时效性一般。",[1345,1346],{"name":652,"url":1338},{"name":1347,"url":1348},"Frontiers in Sustainable Food Systems 2026 年 10 月 07 日 Volume 10 Sec. Agricultural and Food Economics","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1947255\u002Ffull",[1350,1351,1352,1353,1354],"数字金融","区域协调","农业绿色技术","绿色财政","农业碳强度",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1358},{"candidates":1359,"agricultural_evidence":603},[1360,1364,1369,1373],{"code":160,"score":613,"supported":603,"title":1361,"abstract":1362,"tags":1363},[],[860,616],[],{"code":96,"score":620,"supported":603,"title":1365,"abstract":1366,"tags":1368},[],[1367],"fertilizer",[],{"code":503,"score":455,"supported":581,"title":1370,"abstract":1371,"tags":1372},[],[],[1350],{"code":192,"score":455,"supported":581,"title":1374,"abstract":1375,"tags":1376},[],[],[1352],[1378,1379],"数字金融 绿色财政 农业绿色技术","农业碳强度 耦合协调 省级","数字金融绿色财政农业绿色技术-4414","10.3389\u002Ffsufs.2026.1947255",{"doi":1381,"openalex_id":1383,"authors":1384,"venue":652,"cited_by_count":424,"oa_url":1390,"card":1391,"direction":746,"ingested_from":749},"W7220858039",[1385,1387],{"name":1386,"orcid":11},"Xiang Li",{"name":1388,"orcid":1389},"Jiarui Wu","https:\u002F\u002Forcid.org\u002F0000-0001-6305-1014","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1947255\u002Fpdf",{"tldr":1392,"method":1393,"finding":1394,"direction":746,"opportunity":1395},"测度中国30省2011-2023年数字金融、绿色财政与农业绿色技术采纳的耦合协调度及其时空演变。","熵权法、三系统耦合协调模型、Dagum基尼分解、收敛检验与障碍度诊断。","协调度由0.37升至0.71，呈东中西梯度，区域差距贡献约85%，约束由数字金融转向绿色财政与化肥效","可进一步识别耦合协调对农业碳排放的因果效应，并探究西部追赶的驱动机制与差异化政策路径。","2026-10-08T23:30:07.529115Z",{"id":1398,"title":1399,"url":1400,"summary":1401,"summary_zh":1402,"content":11,"source_name":1403,"source_url":1400,"published_at":1404,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":1405,"score_detail":1406,"sources":1408,"tags":1410,"primary_topic":1415,"secondary_topics":1416,"classification":1417,"search_phrases":1435,"slug":1438,"view_count":455,"doi":1439,"paper":1440,"created_at":1458},4243,"Digital corporate responsibility as an element of corporate social responsibility (a case study of Ukrainian agricultural enterprises)","https:\u002F\u002Fdoi.org\u002F10.36887\u002F2524-0455-2026-4-49","The article aims to substantiate the theoretical, methodological, and practical foundations of Digital Corporate Responsibility (DCR\u002FCDR) as a direction of Corporate Social Responsibility (CSR) amid the comprehensive digitalization of business processes, focusing on Ukraine’s agricultural sector. The study applies dialectical analysis and synthesis, grouping, structural-functional analysis, and case study methods. The results show that digitalization creates significant opportunities to improve the efficiency, productivity, and profitability of agribusiness while generating new ethical, social, and environmental risks, including cybersecurity threats, algorithmic bias, digital exclusion, the carbon footprint of IT infrastructure, and electronic waste. DCR is therefore considered an important mechanism for mitigating these risks and ensuring socially and environmentally responsible digital transformation. The scientific novelty lies in substantiating DCR within three interrelated ESG dimensions: digital environmental (E), digital social (S), and digital governance (G) responsibility. The study shows that implementing DCR can strengthen stakeholder relations, transparency, trust, and the sustainable development potential of agricultural companies. The experience of leading Ukrainian agricultural holdings, including Astarta and Kernel, illustrates practical approaches to combining digital technologies with responsible business practices. The research’s practical significance lies in the proposed use of corporate digital ethics codes to strengthen cybersecurity, protect digital rights, develop digital culture, and promote responsible digital behavior among employees and stakeholders. Further research should focus on developing a comprehensive system of indicators to assess the level of DCR, identifying relevant ESG criteria, and adapting international approaches and best practices to the institutional and socio-economic conditions of Ukrainian agribusiness. Keywords: Digital Corporate Responsibility, Corporate Social Responsibility, digitalization, digital transformation, ESG, agricultural sector, agribusiness, precision agriculture, digital ethics, sustainable development, cybersecurity, stakeholders.","本文旨在论证在企业流程全面数字化背景下，数字企业责任（Digital Corporate Responsibility, DCR\u002FCDR）作为企业社会责任（Corporate Social Responsibility, CSR）一个发展方向的理论、方法论与实践基础，并以乌克兰农业部门为聚焦对象。研究采用辩证分析与综合、分组法、结构功能分析以及案例研究等方法。结果表明，数字化为提升农业企业的效率、生产率和盈利能力创造了重要机遇，同时也带来了新的伦理、社会和环境风险，包括网络安全威胁、算法偏见、数字排斥、IT基础设施的碳足迹以及电子废弃物。因此，数字企业责任被视为缓解这些风险、确保社会与环境负责任的数字化转型的重要机制。本研究的科学新颖性在于从三个相互关联的ESG维度论证数字企业责任：数字环境（E）责任、数字社会（S）责任和数字治理（G）责任。研究表明，实施数字企业责任能够加强利益相关者关系、透明度、信任以及农业公司的可持续发展潜力。乌克兰领先农业控股公司，包括Astarta和Kernel的经验，展示了将数字技术与负责任商业实践相结合的实际路径。研究的实践意义在于提出利用企业数字伦理准则来加强网络安全、保护数字权利、发展数字文化，并促进员工和利益相关者负责任的数字行为。未来研究应着重开发评估数字企业责任水平的综合指标体系，确定相关ESG标准，并使国际方法和最佳实践适应乌克兰农业企业的制度与社会经济条件。关键词：数字企业责任，企业社会责任，数字化，数字化转型，ESG，农业部门，农业企业，精准农业，数字伦理，可持续发展，网络安全，利益相关者。","Actual problems of innovative economy and law","2026-10-04T00:00:00Z",55,{"impact":173,"substance":361,"depth":1289,"authority":613,"freshness":173,"relevant":455,"comment":1407},"乌克兰农业企业数字企业责任的理论与案例研究，提出数字环境、数字社会、数字治理三维ESG框架，对农业数字化风险治理有参考价值，但属境外期刊论文、影响范围有限。",[1409],{"name":1403,"url":1400},[1300,1411,1412,1413,1414],"网络安全","乌克兰农业","农业ESG","数字伦理",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1418},{"candidates":1419,"agricultural_evidence":603},[1420,1426,1431],{"code":16,"score":1158,"supported":603,"title":1421,"abstract":1422,"tags":1425},[],[1423,1424],"精准农业","precision agriculture",[1300],{"code":160,"score":613,"supported":603,"title":1427,"abstract":1428,"tags":1430},[],[617,1429],"carbon footprint",[],{"code":56,"score":455,"supported":581,"title":1432,"abstract":1433,"tags":1434},[],[],[1411],[1436,1437],"Astarta Kernel 数字责任","乌克兰农业企业 数字化转型","AstartaKernel数字责任-4243","10.36887\u002F2524-0455-2026-4-49",{"doi":1439,"openalex_id":1441,"authors":1442,"venue":1403,"cited_by_count":424,"oa_url":1452,"card":1453,"direction":1186,"ingested_from":749},"W7219887548",[1443,1446,1449],{"name":1444,"orcid":1445},"Ірина Пасінович","https:\u002F\u002Forcid.org\u002F0000-0003-4899-7498",{"name":1447,"orcid":1448},"Olga Sych","https:\u002F\u002Forcid.org\u002F0000-0002-9322-8105",{"name":1450,"orcid":1451},"Orysia Vasylyna","https:\u002F\u002Forcid.org\u002F0000-0003-2124-3792","https:\u002F\u002Fapie.org.ua\u002Fwp-content\u002Fuploads\u002F2026\u002F10\u002Fapie_2026_r04_a49.pdf",{"tldr":1454,"method":1455,"finding":1456,"direction":746,"opportunity":1457},"研究乌克兰农业企业数字化中的数字企业责任，将其作为CSR新方向并构建ESG三维框架。","辩证分析、案例研究法，以Astarta和Kernel等乌克兰农业控股公司为例。","数字化带来效率提升的同时产生网络安全、算法偏见、数字排斥等新风险，需DCR机制应对。","可开发DCR评估指标体系，将数字伦理与ESG标准适配到不同国家农业情境中。","2026-10-05T23:30:31.062780Z",{"id":1460,"title":1461,"url":1462,"summary":1463,"summary_zh":1464,"content":11,"source_name":1465,"source_url":1462,"published_at":1466,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":1467,"score_detail":1468,"sources":1470,"tags":1472,"primary_topic":1476,"secondary_topics":1477,"classification":1478,"search_phrases":1499,"slug":1502,"view_count":620,"doi":1503,"paper":1504,"created_at":1525},4219,"Cognitive Causal Modeling of Blockchain Adoption in Agri-Food Supply Chains: A Fuzzy-DEMATEL Approach","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12559-026-10660-0","Background \u002F Introduction: Blockchain can improve agri-food supply-chain transparency, but adoption decisions are cognitively complex because managers judge interdependent criteria under uncertainty. This study frames adoption as cognitive causal decision modeling, aligning with cognitive computation through expert judgment, linguistic uncertainty, causal reasoning, and explainable decision support. Methods: We applied Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to judgments from 20 experts. Eight technology-adoption criteria were modeled using triangular fuzzy numbers, and an impact relationship map was used to classify criteria by outgoing influence (R), incoming influence (C), prominence (R + C), and net causality (R − C). Results: Smart Contracts showed the strongest net causal influence (R = 3.46; R − C = + 0.78). Food Traceability was the most prominent criterion (R + C = 6.40) and the most influenced by other criteria (C = 3.17). Smart Contracts, Payment Transactions, Food Traceability, Fraud Prevention, and Secure Storage were net causes, whereas Food Waste Prevention, Carbon Emission Detection, and Power Consumption were net effects. Sensitivity analysis confirmed a stable cause\u002Feffect partition across threshold and prominence-cutoff variation, with Fraud Prevention the only criterion whose sign reverses at the lower fuzzy bound. Payment Transactions and Secure Storage sit close to the core-driving boundary. Conclusions: The findings support an explainable prioritization logic: transactional and information-security capabilities should be addressed before downstream sustainability outcomes. Because the evidence is expert-elicited rather than longitudinal field performance data, the results should be interpreted as structured decision-support guidance.","背景\u002F引言：区块链可以提高农业食品供应链的透明度，但其采纳决策在认知上较为复杂，因为管理者需要在不确定性下判断相互依赖的标准。本研究将采纳行为界定为认知因果决策建模，通过专家判断、语言不确定性、因果推理和可解释决策支持与认知计算相契合。方法：我们采用模糊决策试验与评价实验室方法（Fuzzy Decision-Making Trial and Evaluation Laboratory，Fuzzy-DEMATEL）对20位专家的判断进行分析。使用三角模糊数对八项技术采纳标准进行建模，并利用影响关系图按输出影响（R）、输入影响（C）、中心度（R + C）和净因果性（R − C）对标准进行分类。结果：智能合约表现出最强的净因果影响（R = 3.46；R − C = + 0.78）。食品追溯是最突出的标准（R + C = 6.40），也是受其他标准影响最大的标准（C = 3.17）。智能合约、支付交易、食品追溯、欺诈预防和安全存储为净原因，而食品浪费预防、碳排放检测和电力消耗为净结果。敏感性分析证实，在阈值和中心度截断值变化下，原因\u002F结果划分保持稳定，欺诈预防是唯一在较低模糊边界下符号发生反转的标准。支付交易和安全存储接近核心驱动边界。结论：研究结果支持一种可解释的优先排序逻辑：交易和信息安全能力应先于下游可持续性结果加以处理。由于证据来自专家 elicitation 而非纵向实地绩效数据，结果应被解释为结构化的决策支持指导。","Cognitive Computation","2026-10-02T00:00:00Z",71,{"impact":416,"substance":508,"depth":1020,"authority":345,"freshness":173,"relevant":455,"comment":1469},"核心期刊论文，用模糊DEMATEL方法对20位专家判断建模，识别智能合约与食品溯源为区块链采纳的关键驱动因素，方法新颖、结论有决策参考价值，但属专家主观判断而非实地数据，产业影响偏细分领域。",[1471],{"name":1465,"url":1462},[590,1473,1474,1281,1475],"农业供应链","农产品溯源","决策支持",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1479},{"candidates":1480,"agricultural_evidence":603},[1481,1485,1490,1495],{"code":160,"score":613,"supported":603,"title":1482,"abstract":1483,"tags":1484},[],[860,1154],[],{"code":465,"score":400,"supported":603,"title":1486,"abstract":1487,"tags":1489},[],[1488],"food traceability",[1474],{"code":24,"score":400,"supported":603,"title":1491,"abstract":1492,"tags":1494},[],[1493],"decision support",[1475],{"code":16,"score":455,"supported":581,"title":1496,"abstract":1497,"tags":1498},[],[],[590],[1500,1501],"区块链 农产品供应链 溯源","Fuzzy-DEMATEL 区块链","区块链农产品供应链溯源-4219","10.1007\u002Fs12559-026-10660-0",{"doi":1503,"openalex_id":1505,"authors":1506,"venue":1465,"cited_by_count":424,"oa_url":1518,"card":1519,"direction":748,"ingested_from":749},"W7216251074",[1507,1510,1513,1516],{"name":1508,"orcid":1509},"Ali Ala","https:\u002F\u002Forcid.org\u002F0000-0003-4552-4732",{"name":1511,"orcid":1512},"Behnam Malmir","https:\u002F\u002Forcid.org\u002F0000-0003-1771-9751",{"name":1514,"orcid":1515},"Hamed Baziyad","https:\u002F\u002Forcid.org\u002F0000-0002-5770-7766",{"name":1517,"orcid":11},"Vladimir Simic","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs12559-026-10660-0.pdf",{"tldr":1520,"method":1521,"finding":1522,"direction":1523,"opportunity":1524},"用模糊DEMATEL对20位专家判断建模，分析农业食品供应链区块链采纳的因果优先级。","模糊DEMATEL、三角模糊数、20位专家判断、敏感性分析","智能合约净因果影响最强，食品溯源最突出；交易与信息安全能力应先于可持续性结果。","农业人工智能与决策模型","可结合纵向田间绩效数据验证专家因果结论，并研究交易安全能力向碳减排等可持续结果的传导机制。","2026-10-05T23:30:12.085269Z",{"id":1527,"title":1528,"url":1529,"summary":1530,"summary_zh":1531,"content":11,"source_name":1532,"source_url":1529,"published_at":1533,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":424,"score_detail":1534,"sources":1536,"tags":1538,"primary_topic":1544,"secondary_topics":1545,"classification":1546,"search_phrases":1576,"slug":1579,"view_count":424,"doi":1580,"paper":1581,"created_at":1593},4216,"The Evolution of Green Products: Anticipating 2025","https:\u002F\u002Fdoi.org\u002F10.69687\u002Fime.nseeepsd.2026.1.39","Introduction: 2025 is likely to be a critical year for environmentally friendly products as environmental issues keep attracting worldwide interest. Customers are more dedicated than ever to lower their carbon footprints, which forces companies to create new ideas and use sustainable methods. Driven by technology advancements, shifting customer preferences, and regulatory systems meant to lower carbon emissions and waste, the environmentally friendly product industry is predicted to see explosive expansion by 2025. Methodology: This study uses a qualitative research approach combining expert interviews with secondary data to investigate the direction of environmentally friendly products. Secondary research is an examination of the body of current material on the topic comprising market studies, industry reports and scholarly publications, which promotes a general awareness of the trends, developments and market changes of the environmentally friendly product spectrum. Apart from secondary research, expert interviews with business leaders in sustainable packaging, environmentally friendly fashion, plant-based food production and renewable energy give primary understanding of the possibilities and difficulties in the market. These interviews centre on knowledge of the technical developments, consumer behaviourand legal influences determining the futures of these items, and the information gathered is examined to spot new trends, possibilities and difficulties. Results & Discussion: Ten areas of development are documented. Packaging innovations include biodegradable and compostable materials from seaweed, mushrooms and cornstarch, returnable and refillable glass and stainless steel containers, and edible and dissolvable films. Fashion trends include circular fashion, vegan leather from pineapple fibres, cactus and mycelium, waterless dyeing and expanding resale, rental and upcycling markets. Plant-based alternatives include lab-grown meat, plant-based fish and shellfish, and fermentation technology. Clean beauty features waterless products, refillable packaging and zero-waste items such as toothpaste tablets and shampoo bars. Smart home and renewable energy developments cover solar-powered gadgets, energy-efficient smart devices, community renewable systems and advanced battery storage. Further areas cover eco-friendly cleaning agents, green transportation and electric vehicles including hydrogen fuel cell vehicles, zero-waste lifestyle products, eco-friendly devices, and smart agriculture including vertical and regenerative farming. Company examples include Lush, Evoware, Loop, Patagonia, Stella McCartney, Adidas, Impossible Foods, Beyond Meat, Good Catch Foods, SunPower, Nest, Sense, Tesla and Rivian. Conclusion: By 2025 consumer demand, legislative changes and technology innovation will propel demand for environmentally friendly products. Businesses who give sustainability top priority and provide useful, eco-friendly goods will keep growing. Adopting these trends as consumers means choosing more deliberately, which taken together lessens our environmental effect. The article underlines how consumer tastes, technology developments and legislative changes are coming together to build a sustainable future whereby environmentally friendly products solve problems and provide useful alternatives for customers. One item at a time, we may help to build a more sustainable earth.","引言：随着环境问题持续吸引全球关注，2025年很可能成为环保产品的关键一年。消费者比以往任何时候都更致力于降低碳足迹，这迫使企业创造新理念并采用可持续方法。在技术进步、消费者偏好转变以及旨在减少碳排放和废弃物的监管体系的推动下，预计到2025年，环保产品行业将迎来爆发式增长。方法：本研究采用定性研究方法，结合专家访谈与二手数据，探讨环保产品的发展方向。二手研究是对该主题现有资料的梳理分析，包括市场研究、行业报告和学术出版物，有助于总体了解环保产品领域趋势、发展和市场变化。除二手研究外，对可持续包装、环保时尚、植物基食品生产和可再生能源领域商业领袖的专家访谈，提供了对市场可能性和困难的第一手理解。这些访谈聚焦于对决定这些产品未来的技术发展、消费者行为和法律影响的认识，并对所收集的信息进行分析，以识别新趋势、可能性和困难。结果与讨论：记录了十个发展领域。包装创新包括由海藻、蘑菇和玉米淀粉制成的可生物降解和可堆肥材料，可回收和可再填充的玻璃及不锈钢容器，以及可食用和可溶解薄膜。时尚趋势包括循环时尚、由菠萝纤维、仙人掌和菌丝体制成的纯素皮革、无水染色，以及不断扩大的转售、租赁和升级再造市场。植物基替代品包括实验室培养肉、植物基鱼类和贝类，以及发酵技术。清洁美容包括无水产品、可再填充包装，以及牙膏片和洗发皂等零废弃产品。智能家居和可再生能源发展涵盖太阳能设备、节能智能设备、社区可再生能源系统和先进电池储能。其他领域涵盖环保清洁剂、绿色交通和电动汽车（包括氢燃料电池汽车）、零废弃生活方式产品、环保","IntelliMindEd","2026-10-03T00:00:00Z",{"impact":424,"substance":424,"depth":424,"authority":424,"freshness":424,"relevant":424,"comment":1535},"内容为泛绿色消费品趋势综述，与三农、农业信息化、智慧农业无直接关联，不达相关性门槛。",[1537],{"name":1532,"url":1529},[1539,1540,1541,1542,1543],"绿色产品","可持续消费","循环时尚","植物基食品","清洁能源",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1547},{"candidates":1548,"agricultural_evidence":603},[1549,1553,1557,1562,1567,1571],{"code":160,"score":613,"supported":603,"title":1550,"abstract":1551,"tags":1552},[],[860,617],[],{"code":224,"score":620,"supported":603,"title":1554,"abstract":1555,"tags":1556},[],[226],[],{"code":309,"score":620,"supported":603,"title":1558,"abstract":1559,"tags":1561},[],[1560],"蘑菇",[],{"code":388,"score":620,"supported":603,"title":1563,"abstract":1564,"tags":1566},[],[1565],"水产",[],{"code":16,"score":620,"supported":603,"title":1568,"abstract":1569,"tags":1570},[],[720],[],{"code":64,"score":620,"supported":603,"title":1572,"abstract":1573,"tags":1575},[],[1574],"研究方法",[],[1577,1578],"Lush Evoware Loop 绿色产品","Beyond Meat 植物基食品","LushEvowareLoop绿色产品-4216","10.69687\u002Fime.nseeepsd.2026.1.39",{"doi":1580,"openalex_id":1582,"authors":1583,"venue":1532,"cited_by_count":424,"oa_url":1529,"card":1588,"direction":748,"ingested_from":749},"W7219598566",[1584,1586],{"name":1585,"orcid":11},"Satish Kannuru",{"name":1587,"orcid":11},"Prof. P. Uma Maheswari Devi",{"tldr":1589,"method":1590,"finding":1591,"direction":746,"opportunity":1592},"通过专家访谈与二手资料，预测2025年绿色产品在包装、时尚、食品等十大领域的发展趋势。","定性研究，结合专家访谈与市场报告、行业报告等二手数据。","绿色产品将在包装、时尚、食品、清洁美容、智能家居等十大领域出现创新与市场扩张。","可延伸研究绿色产品在农业领域的应用，如可降解农膜、植物基投入品及碳足迹评估。","2026-10-05T23:30:10.436515Z",{"id":1595,"title":1596,"url":1597,"summary":1598,"summary_zh":11,"content":11,"source_name":1599,"source_url":11,"published_at":1600,"category":654,"cover_url":11,"hotness":385,"is_selected":603,"score":101,"score_detail":1601,"sources":1604,"tags":1606,"primary_topic":1610,"secondary_topics":1611,"classification":1614,"search_phrases":1634,"slug":1637,"view_count":400,"doi":11,"paper":1638,"created_at":1645},4194,"数字乡村建设的代价？数字乡村战略对粮食安全和农业碳循环的非对称影响——来自中国的证据","https:\u002F\u002Fideas.repec.org\u002Fa\u002Fspr\u002Fagfoec\u002Fv14y2026i1d10.1186_s40100-026-00503-9.html","Weilong Gao、Qian Zhang、Ying Peng（吉林大学国家发展与安全研究院、大连理工大学商学院、长春工业大学经济管理学院）。发表于Agricultural and Food Economics 2026, 14(1): 1-22。基于989个县和1835户农户的多层次数据，将县级数字乡村发展指数与家庭层面数字采纳指数链接，运用固定效应和两阶段最小二乘法模型。结果显示：农村数字化与粮食产量显著正相关，与农业碳排放显著负相关，但对作物生物量碳吸收或净碳足迹无显著改善。机制分析表明生产收益与土地利用集约化（特别是双季种植扩张）相关，减排与减少劳动力和农药使用一致。异质性分析显示数字基础设施驱动生产率增长，数字治理和数字生活与减排关联更密切。","Agricultural and Food Economics 2026, 14(1)","2026-10-01T00:00:00Z",{"impact":321,"substance":858,"depth":1602,"authority":345,"freshness":585,"relevant":455,"comment":1603},19,"基于989县1835户的全国性实证研究，揭示数字乡村对粮食安全与农业碳循环的非对称影响，数据规模大、结论有政策参考价值，值得进入每日精选。",[1605],{"name":1599,"url":1597},[897,1607,1608,850,1609],"数字基础设施","粮食安全","农户数字化",{"code":263,"slug":264,"name":265,"path":266,"parent_code":200},[1612,1613],{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"code":56,"slug":57,"name":58,"path":59,"parent_code":7},{"status":598,"locked":581,"version":4,"method":599,"evidence":1615},{"candidates":1616,"agricultural_evidence":603},[1617,1621,1625,1629],{"code":160,"score":361,"supported":603,"title":1618,"abstract":1619,"tags":1620},[616],[860,616,617],[850],{"code":56,"score":658,"supported":603,"title":1622,"abstract":1623,"tags":1624},[897],[897],[897,1607],{"code":263,"score":585,"supported":603,"title":1626,"abstract":1627,"tags":1628},[1608],[],[1608],{"code":104,"score":620,"supported":603,"title":1630,"abstract":1631,"tags":1633},[],[1632],"农药",[],[1635,1636],"数字乡村 粮食安全 农业碳循环","吉林大学 数字乡村 农户","数字乡村粮食安全农业碳循环-4194",{"doi":11,"openalex_id":11,"authors":1639,"venue":11,"cited_by_count":424,"oa_url":11,"card":1640,"direction":1186,"ingested_from":882},[],{"tldr":1641,"method":1642,"finding":1643,"direction":1186,"opportunity":1644},"基于中国县级与农户数据，评估数字乡村战略对粮食安全和农业碳循环的非对称影响。","989县与1835户多层次数据，固定效应和两阶段最小二乘法。","数字化提升粮食产量并减少碳排放，但未改善作物碳吸收或净碳足迹。","可探究数字乡村对碳吸收无显著影响的原因，并优化数字治理以协同减排与固碳。","2026-10-05T00:04:55.880239Z",{"id":1647,"title":1648,"url":1649,"summary":1650,"summary_zh":1651,"content":11,"source_name":652,"source_url":1649,"published_at":1600,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":582,"score_detail":1652,"sources":1654,"tags":1656,"primary_topic":1661,"secondary_topics":1662,"classification":1663,"search_phrases":1683,"slug":1686,"view_count":455,"doi":1687,"paper":1688,"created_at":1700},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。",{"impact":361,"substance":584,"depth":361,"authority":658,"freshness":173,"relevant":455,"comment":1653},"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。",[1655],{"name":652,"url":1649},[1657,1658,1659,766,1660],"秸秆还田","碳循环","农业减排","农田碳汇",{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},[],{"status":598,"locked":581,"version":4,"method":599,"evidence":1664},{"candidates":1665,"agricultural_evidence":603},[1666,1670,1674,1678],{"code":160,"score":416,"supported":603,"title":1667,"abstract":1668,"tags":1669},[690],[690],[1659],{"code":144,"score":1158,"supported":603,"title":1671,"abstract":1672,"tags":1673},[],[678,145],[766],{"code":168,"score":400,"supported":603,"title":1675,"abstract":1676,"tags":1677},[],[1657],[1657],{"code":176,"score":620,"supported":603,"title":1679,"abstract":1680,"tags":1682},[],[1681],"生物多样性",[],[1684,1685],"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":1687,"openalex_id":1689,"authors":1690,"venue":652,"cited_by_count":424,"oa_url":1649,"card":1695,"direction":746,"ingested_from":749},"W7215031184",[1691,1693],{"name":1692,"orcid":11},"Xiaoyan Wang",{"name":1694,"orcid":11},"Feng Luo",{"tldr":1696,"method":1697,"finding":1698,"direction":746,"opportunity":1699},"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":1702,"title":1703,"url":1704,"summary":1705,"summary_zh":1706,"content":11,"source_name":652,"source_url":1704,"published_at":1707,"category":654,"cover_url":11,"hotness":385,"is_selected":603,"score":1708,"score_detail":1709,"sources":1711,"tags":1713,"primary_topic":1719,"secondary_topics":1720,"classification":1723,"search_phrases":1743,"slug":1746,"view_count":69,"doi":1747,"paper":1748,"created_at":1771},3815,"Carbon labels and carbon trading as market-based incentives for conserving traditional upland rice: a case study from Hainan, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1969345","Introduction Traditional crop varieties that underpin agricultural biodiversity are rapidly disappearing as their cultivation becomes economically marginalized. Public ecological compensation has proven effective in incentivizing on-farm conservation, but it faces long-term fiscal sustainability constraints. Market-based carbon mechanisms including carbon labeling and carbon trading are increasingly proposed as complementary incentives, but real-world documented cases in smallholder traditional agroecosystems remain extremely limited. This study addresses this gap by analyzing an operational pilot practice launched for the globally important Shanlan upland rice system in Hainan, China. Methods Drawing on program documents, field interview records, and official verification data from the UNDP-GEF C-SAP3 2020–2025 project, this study systematically evaluates the full operational logic, implementation process and actual performance of the combined carbon label and carbon trading mechanism. A comparative analysis framework is constructed to compare the incentive strength, operation cost and institutional positioning of market-based carbon instruments and existing differentiated public ecological compensation schemes. Results The Shanlan rice conservation system has established a verified carbon sequestration rate of 2.1 t CO₂\u002Fha\u002Fyr, completed the first provincial carbon market transaction of RMB 530,000 in 2024, and officially released the dedicated Shanlan rice carbon label at the 2024 Hainan Winter Trade Fair. At the current carbon price of RMB 50\u002Ft, the annual carbon revenue per mu is only about RMB 7, accounting for roughly 3% of the existing public ecological compensation standard of RMB 200–220\u002Fmu. The carbon accounting parameter has already been embedded into the local ecological compensation calculation algorithm as an ecological service value component. Discussion The empirical results confirm that current carbon market instruments can only play a complementary rather than substitution role for public ecological compensation in traditional crop conservation scenarios, and their near-term value is more institutional than purely financial. The ambiguity between modeled sequestration parameters and actual measured conservation outcomes still limits the credibility of such market mechanisms. Three core propositions including incentive complementarity, measurement validation and long-term institutional stewardship are proposed to support future comparative research on similar agrobiodiversity conservation practices.","引言 支撑农业生物多样性的传统作物品种正因其种植在经济上被边缘化而迅速消失。公共生态补偿已被证明能有效激励农田就地保护，但面临长期财政可持续性约束。包括碳标签和碳交易在内的市场化碳机制日益被提议作为补充性激励手段，但在小农传统农业生态系统中，实际有据可查的案例仍然极为有限。本研究通过分析针对中国海南具有全球重要性的山栏稻旱作系统所开展的一项运行中的试点实践，来填补这一空白。方法 本研究依据联合国开发计划署—全球环境基金C-SAP3 2020—2025项目的项目文件、实地访谈记录和官方核证数据，系统评估碳标签与碳交易相结合机制的完整运行逻辑、实施过程和实际绩效。构建比较分析框架，对市场化碳工具与现有差异化公共生态补偿方案在激励强度、运行成本和制度定位方面进行比较。结果 山栏稻保护系统已确立经核证的碳汇速率为2.1吨二氧化碳\u002F公顷\u002F年，于2024年完成首笔省级碳市场交易53万元人民币，并在2024年海南冬交会上正式发布专用山栏稻碳标签。按当前碳价50元\u002F吨计算，每亩年度碳收益仅约7元人民币，约占现有公共生态补偿标准200—220元\u002F亩的3%。碳核算参数已作为生态服务价值组成部分嵌入地方生态补偿计算算法。讨论 实证结果证实，在当前传统作物保护情景下，碳市场工具只能对公共生态补偿发挥补充而非替代作用，其近期价值更多体现在制度层面而非纯粹财务层面。模型化碳汇参数与实际测得的保护成效之间的模糊性，仍限制此类市场机制的可信度。提出激励互补性、计量验证和长期制度管护三项核心命题，以支持未来比较研究。","2026-09-29T00:00:00Z",82,{"impact":361,"substance":584,"depth":361,"authority":345,"freshness":585,"relevant":455,"comment":1710},"以海南山栏稻为案例，首次量化碳标签与碳交易对传统作物保护的激励强度（约7元\u002F亩，仅为生态补偿3%），数据扎实、结论明确，对农业碳汇与生物多样性保护政策具参考价值。",[1712],{"name":652,"url":1704},[1714,664,1715,1716,1717,1718],"农业碳汇","生态补偿","碳标签","山栏稻","农业生物多样性",{"code":208,"slug":209,"name":210,"path":211,"parent_code":200},[1721,1722],{"code":176,"slug":177,"name":178,"path":179,"parent_code":128},{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":1724},{"candidates":1725,"agricultural_evidence":603},[1726,1730,1734,1738],{"code":208,"score":524,"supported":603,"title":1727,"abstract":1728,"tags":1729},[209],[209],[],{"code":176,"score":385,"supported":603,"title":1731,"abstract":1732,"tags":1733},[],[1681,715,177],[1715],{"code":160,"score":173,"supported":603,"title":1735,"abstract":1736,"tags":1737},[],[1093,690],[1714,664],{"code":496,"score":620,"supported":603,"title":1739,"abstract":1740,"tags":1742},[],[1741],"smallholder",[],[1744,1745],"海南 山栏稻 碳标签","山栏稻 碳交易 生态补偿","海南山栏稻碳标签-3815","10.3389\u002Ffsufs.2026.1969345",{"doi":1747,"openalex_id":1749,"authors":1750,"venue":652,"cited_by_count":424,"oa_url":1704,"card":1766,"direction":746,"ingested_from":749},"W7214741801",[1751,1753,1755,1758,1760,1762,1764],{"name":1752,"orcid":11},"Qimin Cao",{"name":1754,"orcid":11},"易伟鹏",{"name":1756,"orcid":1757},"Tao Guo","https:\u002F\u002Forcid.org\u002F0000-0003-0587-4762",{"name":1759,"orcid":11},"Chuanliang Fu",{"name":1761,"orcid":11},"Zhijun Zhang",{"name":1763,"orcid":11},"Wen Zhang",{"name":1765,"orcid":11},"Yujia Wu",{"tldr":1767,"method":1768,"finding":1769,"direction":746,"opportunity":1770},"分析海南山栏稻碳标签与碳交易试点，评估其作为传统作物保护市场激励的效果。","基于UNDP-GEF项目文件、访谈与核证数据，对比碳机制与公共生态补偿。","碳收益仅约7元\u002F亩，为公共补偿的3%，只能补充而非替代公共补偿。","小农户传统农业碳汇计量与碳市场激励的长期制度设计及实测验证研究。","2026-09-30T23:30:07.250289Z",{"id":1773,"title":1774,"url":1775,"summary":1776,"summary_zh":1777,"content":11,"source_name":1778,"source_url":1775,"published_at":1779,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":329,"score_detail":1780,"sources":1782,"tags":1784,"primary_topic":1788,"secondary_topics":1789,"classification":1791,"search_phrases":1821,"slug":1824,"view_count":400,"doi":1825,"paper":1826,"created_at":1843},3554,"Spatial Estimation of Carbon Sequestration Using Remote Sensing and Its Application in Carbon-credit Assessment: A Comprehensive Review","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fjgeesi\u002F2026\u002Fv30i91125","Carbon sequestration is fundamental to climate-change mitigation because terrestrial and aquatic ecosystems store carbon in vegetation, biomass, soils, and the Earth’s crust. Reliable estimation of carbon stocks and their temporal and spatial changes is essential for the formulation of climate policy, ecosystem management, carbon accounting, and carbon-credit assessment. Conventional field measurements provide detailed information but are constrained by sampling requirements, cost, labour, spatial heterogeneity, and limitations in continuous monitoring. Remote sensing provides a complementary approach by enabling spatially continuous observations of vegetation characteristics, land-cover change, biomass, and other carbon-related variables across different spatial and temporal scales. Advances in multispectral, hyperspectral, synthetic aperture radar, LiDAR, thermal, and high-resolution satellite observations have extended the capability for carbon estimation. Their integration with geographic information systems, field observations, statistical techniques, and machine-learning algorithms enables precise spatial assessment of above-ground biomass, below-ground biomass, soil organic carbon, forest carbon, agricultural carbon, mangrove carbon, and blue-carbon resources. However, uncertainties associated with sensor characteristics, field-data quality, model selection, spatial variability, temporal dynamics, and scaling remain acknowledged limitations. Converting spatial carbon estimates into carbon credits requires consideration of baseline conditions, additionality, permanence, leakage, uncertainty, verification, and measurement, reporting, and verification requirements. This review critically examines remote sensing technologies, carbon-estimation models, spatial mapping approaches, machine-learning techniques, carbon-accounting frameworks, and their integration into carbon-credit assessment. It places particular emphasis on multisource data fusion, emerging Earth-observation technologies, artificial intelligence, uncertainty assessment, and digital MRV systems. Major methodological, technological, and policy gaps are identified, along with opportunities for developing transparent, spatially explicit, scientifically robust, and scalable carbon-credit assessment frameworks.","碳固存是减缓气候变化的基础，因为陆地和水生生态系统将碳储存在植被、生物量、土壤和地壳中。可靠估算碳储量及其时空变化，对于制定气候政策、生态系统管理、碳核算和碳信用评估至关重要。传统野外测量可提供详细信息，但受采样要求、成本、劳动力、空间异质性以及连续监测局限性等因素制约。遥感提供了一种互补方法，能够在不同时空尺度上对植被特征、土地覆盖变化、生物量及其他碳相关变量进行空间连续观测。多光谱、高光谱、合成孔径雷达、激光雷达、热红外和高分辨率卫星观测的进步，拓展了碳估算能力。这些技术与地理信息系统、野外观测、统计技术和机器学习算法的集成，使得对地上生物量、地下生物量、土壤有机碳、森林碳、农业碳、红树林碳和蓝碳资源进行精确空间评估成为可能。然而，与传感器特性、野外数据质量、模型选择、空间变异性、时间动态和尺度转换相关的不确定性仍是公认的局限。将空间碳估算转化为碳信用，需要考虑基线条件、额外性、永久性、泄漏、不确定性、核查以及测量、报告和核查要求。本综述批判性地审视了遥感技术、碳估算模型、空间制图方法、机器学习技术、碳核算框架及其在碳信用评估中的集成。特别强调了多源数据融合、新兴地球观测技术、人工智能、不确定性评估和数字化MRV系统。识别了主要的方法学、技术和政策差距，以及开发透明、空间明确、科学稳健且可扩展的碳信用评估框架的机遇。","Journal of Geography Environment and Earth Science International","2026-09-25T00:00:00Z",{"impact":416,"substance":361,"depth":657,"authority":416,"freshness":585,"relevant":455,"comment":1781},"系统综述遥感碳汇估算与碳信用评估的方法、不确定性与数字MRV进展，对农业碳汇与碳交易信息化有参考价值，但属综述类论文，公共影响有限。",[1783],{"name":1778,"url":1775},[1785,1202,1093,1786,1787],"机器学习","碳信用","数字MRV",{"code":32,"slug":33,"name":34,"path":35,"parent_code":7},[1790],{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":1792},{"candidates":1793,"agricultural_evidence":603},[1794,1800,1804,1809,1813,1817],{"code":32,"score":361,"supported":603,"title":1795,"abstract":1796,"tags":1799},[1222],[1202,1222,1797,1798],"multispectral","hyperspectral",[1202],{"code":160,"score":1289,"supported":603,"title":1801,"abstract":1802,"tags":1803},[690],[616,690],[1093],{"code":24,"score":1158,"supported":603,"title":1805,"abstract":1806,"tags":1808},[],[1785,1807],"artificial intelligence",[1785],{"code":144,"score":613,"supported":603,"title":1810,"abstract":1811,"tags":1812},[],[678,145],[],{"code":40,"score":613,"supported":603,"title":1814,"abstract":1815,"tags":1816},[],[1227,1228],[],{"code":184,"score":620,"supported":603,"title":1818,"abstract":1819,"tags":1820},[],[683],[],[1822,1823],"遥感 碳汇 估算","碳信用 评估 遥感","遥感碳汇估算-3554","10.9734\u002Fjgeesi\u002F2026\u002Fv30i91125",{"doi":1825,"openalex_id":1827,"authors":1828,"venue":1778,"cited_by_count":424,"oa_url":1775,"card":1838,"direction":1265,"ingested_from":749},"W7214392294",[1829,1831,1834,1836],{"name":1830,"orcid":11},"Aishwarya Desai",{"name":1832,"orcid":1833},"Himalaya Ganachari","https:\u002F\u002Forcid.org\u002F0000-0002-6157-9242",{"name":1835,"orcid":11},"Sangita Shinde",{"name":1837,"orcid":11},"Sachinkumar Nandgude",{"tldr":1839,"method":1840,"finding":1841,"direction":746,"opportunity":1842},"综述遥感碳储量估算技术及其在碳信用评估中的应用与挑战。","综述多光谱、高光谱、SAR、LiDAR等遥感与GIS、机器学习融合方法。","遥感可空间连续估算多类碳库，但不确定性及MRV要求制约碳信用转化。","可研究多源数据融合与AI驱动的数字MRV，降低碳信用评估不确定性。","2026-09-26T23:30:30.002197Z",{"id":1845,"title":1846,"url":1847,"summary":1848,"summary_zh":1849,"content":11,"source_name":652,"source_url":1847,"published_at":1779,"category":654,"cover_url":11,"hotness":385,"is_selected":581,"score":582,"score_detail":1850,"sources":1852,"tags":1854,"primary_topic":1857,"secondary_topics":1858,"classification":1860,"search_phrases":1887,"slug":1890,"view_count":455,"doi":1891,"paper":1892,"created_at":1908},3531,"Extreme climate shocks and agricultural net carbon sinks: the moderating role of supply chain resilience in China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1940685","Introduction Extreme climate shocks increasingly challenge the ability of agricultural systems to sustain crop carbon fixation while controlling production-related emissions. Methods Using panel data for 240 Chinese cities from 2002 to 2023, this study examines the relationships between four climate shocks—extreme high temperature (HTD), extreme low temperature (LTD), extreme rainfall (ERD), and extreme drought (EED)—and agricultural net carbon sinks (NCS), together with the moderating role of agricultural supply chain resilience. NCS is measured as annual crop-biomass carbon fixation net of selected agricultural production emissions, thereby providing an integrated, production-based indicator of agricultural carbon performance. Results Two-way fixed-effects estimates show that all four climate shocks are negatively associated with NCS, and the direction of these relationships remains stable across alternative accounting boundaries, sample adjustments, leave-one-province-out tests, and double machine learning specifications. Agricultural supply chain resilience significantly conditions the climate–carbon relationship. Its resistance, recovery, and reorientation capacities attenuate the adverse associations of high-temperature, extreme-rainfall, and drought shocks with NCS. The low-temperature result further indicates that the effectiveness of resilience depends on matching supply chain functions with the biological mechanisms and intervention windows of specific climate hazards. Heterogeneity analyses confirm that climate sensitivity and resilience requirements vary with regional location, agricultural productivity, modernization, and irrigation conditions. Complementary machine-learning analysis identifies nonlinear predictive patterns and reinforces the importance of differentiated adaptation. Discussion These findings extend agricultural climate research from production and emissions to an integrated carbon-balance perspective and demonstrate that hazard-specific supply chain resilience can support both climate adaptation and low-carbon agricultural development.","引言 极端气候冲击日益挑战农业系统在维持作物碳固定的同时控制生产相关排放的能力。方法 本研究利用2002年至2023年中国240个城市的面板数据，考察四种气候冲击——极端高温（HTD）、极端低温（LTD）、极端降雨（ERD）和极端干旱（EED）——与农业净碳汇（NCS）之间的关系，以及农业供应链韧性的调节作用。NCS以年度作物生物量碳固定量扣除部分农业生产排放量来衡量，从而提供一个基于生产的综合性农业碳绩效指标。结果 双向固定效应估计表明，四种气候冲击均与NCS呈负相关，且这些关系的方向在替代核算边界、样本调整、逐一剔除省份检验和双重机器学习设定下均保持稳定。农业供应链韧性显著调节气候—碳关系。其抵抗能力、恢复能力和重新定向能力减弱了高温、极端降雨和干旱冲击与NCS之间的不利关联。低温结果进一步表明，韧性的有效性取决于供应链功能与特定气候灾害的生物机制及干预窗口的匹配。异质性分析证实，气候敏感性和韧性需求因区域位置、农业生产率、现代化水平和灌溉条件而异。补充性机器学习分析识别出非线性预测模式，并强化了差异化适应的重要性。讨论 这些发现将农业气候研究从生产和排放拓展至综合碳平衡视角，并表明针对特定灾害的供应链韧性能够同时支持气候适应和农业低碳发展。",{"impact":361,"substance":321,"depth":361,"authority":658,"freshness":585,"relevant":455,"comment":1851},"基于240城22年面板数据的实证研究，方法扎实、结论稳健，对农业气候适应与低碳发展有参考价值，但属学术论文，公共传播性有限。",[1853],{"name":652,"url":1847},[590,1473,1855,1856,1714],"低碳农业","气候韧性",{"code":184,"slug":185,"name":186,"path":187,"parent_code":128},[1859],{"code":160,"slug":161,"name":162,"path":163,"parent_code":128},{"status":598,"locked":581,"version":4,"method":599,"evidence":1861},{"candidates":1862,"agricultural_evidence":603},[1863,1869,1873,1878,1883],{"code":184,"score":385,"supported":603,"title":1864,"abstract":1865,"tags":1868},[],[1866,684,1867],"气候适应","drought",[1856],{"code":160,"score":173,"supported":603,"title":1870,"abstract":1871,"tags":1872},[],[1093,616],[1855,1714],{"code":152,"score":613,"supported":603,"title":1874,"abstract":1875,"tags":1877},[],[1876,153],"灌溉",[],{"code":24,"score":613,"supported":603,"title":1879,"abstract":1880,"tags":1882},[],[1785,1881],"machine learning",[],{"code":16,"score":455,"supported":581,"title":1884,"abstract":1885,"tags":1886},[],[],[590],[1888,1889],"中国 农业净碳汇 极端气候","农业供应链韧性 气候适应","中国农业净碳汇极端气候-3531","10.3389\u002Ffsufs.2026.1940685",{"doi":1891,"openalex_id":1893,"authors":1894,"venue":652,"cited_by_count":424,"oa_url":1847,"card":1903,"direction":746,"ingested_from":749},"W7214310732",[1895,1897,1900],{"name":1896,"orcid":11},"Chunyan Zhao",{"name":1898,"orcid":1899},"Jiajie Xia","https:\u002F\u002Forcid.org\u002F0000-0003-3225-0154",{"name":1901,"orcid":1902},"Guoping Ding","https:\u002F\u002Forcid.org\u002F0000-0002-4865-5044",{"tldr":1904,"method":1905,"finding":1906,"direction":746,"opportunity":1907},"基于240个城市2002-2023年面板数据，检验四类极端气候冲击对农业净碳汇的影响及供应链韧性的调","双向固定效应模型、双重机器学习，240城市面板数据，农业净碳汇指标。","四类极端气候冲击均降低农业净碳汇，供应链韧性可显著缓解高温、暴雨和干旱的负面影响。","可探究不同气候灾害下供应链韧性功能与生物机制匹配的差异化适应策略及非线性预测。","2026-09-26T23:30:07.569768Z",{"technologies":1910,"keywords":1917},[1911,1912,1913,1914,1915,1916],{"name":1202,"count":620},{"name":1281,"count":69},{"name":1081,"count":69},{"name":1474,"count":455},{"name":1203,"count":455},{"name":1785,"count":455},[1918,1919,1920,1921,1922,1924,1925,1926,1927,1928,1929,1930],{"name":850,"count":345},{"name":897,"count":524},{"name":590,"count":385},{"name":1855,"count":1158},{"name":1923,"count":400},"农业碳减排",{"name":766,"count":400},{"name":1300,"count":400},{"name":898,"count":620},{"name":1714,"count":620},{"name":847,"count":620},{"name":664,"count":620},{"name":617,"count":620}]