Article(id=1312073419135476671, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1312073311350256541, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2025.07.00077, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1752508800000, receivedDateStr=2025-07-15, revisedDate=1773936000000, revisedDateStr=2026-03-20, acceptedDate=null, acceptedDateStr=null, onlineDate=1790752280267, onlineDateStr=2026-09-30, pubDate=1787846400000, pubDateStr=2026-08-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790752280267, onlineIssueDateStr=2026-09-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790752280267, creator=13701087609, updateTime=1790752280267, updator=13701087609, issue=Issue{id=1312073311350256541, tenantId=1146029695717560320, journalId=1146031591421210625, year='2026', volume='44', issue='16', pageStart='1', pageEnd='180', issueExtLink='null', onlineDate='null', pubDate='1787846400000', pubDateStr='2026-08-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790752254569, creator='13701087609', updateTime=1790753187383, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1312077223981576789, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1312073311350256541, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1312077223981576790, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1312073311350256541, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=40, endPage=48, ext={EN=ArticleExt(id=1312073419361969088, articleId=1312073419135476671, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=From yield enhancement to carbon−nitrogen synergy: Evolution and future prospects of green manure research in rice agriculture, columnId=1150494644312879319, journalTitle=Science & Technology Review, columnName=Special to S & T Review, runingTitle=null, highlight=null, articleAbstract=

Rice green manure, as an agro−biological practice that simultaneously provides nutrient substitution and carbon sequestration/emission reduction benefits, holds strategic significance for concurrently safeguarding food security and advancing the green low−carbon transition in agriculture. Based on an "evolution–mechanism–pathway" framework, we systematically traces the paradigm shift from soil fertility enhancement and resource−use optimization toward ecological synergy in rice green manure research spanning 1928–2025. Critical knowledge gaps persist regarding synergistic multi−dimensional benefit quantification frameworks, micro−scale biogeochemical driving mechanisms, and digital integrated management technologies. Future priorities urgently call for: (1) a multi−dimensional evaluation framework for rice green manure cultivation grounded in water–carbon–nitrogen synergy; (2) the integration of multi−omics and isotope tracing approaches to elucidate key biogeochemical mechanisms; (3) the development of an integrated space–aerial–ground precision management system to overcome regional heterogeneity constraints; and (4) the refinement of measurement, reporting, and verification protocols to facilitate the inclusion of green manure carbon sinks into market−oriented ecological compensation mechanisms, thereby providing theoretical and technical support for the "emission reduction without yield reduction" strategy in agriculture.

, authors=Jiabei SUN1, 2, Shihang WANG1, Siyuan CAI2, 3, *, Xinyao PAN3, 4, Xu ZHAO2, 3, 4, *, authorsList=Jiabei SUN, Shihang WANG, Siyuan CAI, Xinyao PAN, Xu ZHAO, authorCompany=null, correspAuthors=Siyuan CAI, Xu ZHAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1312073420498625479, articleId=1312073419135476671, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=从增产肥田到碳氮协同:稻田绿肥研究演变与未来展望, columnId=1150494644438708440, journalTitle=科技导报, columnName=本刊专稿, runingTitle=null, highlight=null, articleAbstract=

稻田绿肥作为兼具养分替代与固碳减排双重功能的农业生物措施,在协同保障粮食安全与推动农业绿色低碳转型中具有重要战略意义。基于“演化—机制—路径”框架,系统回顾了1928—2025年间该领域从肥力提升、资源利用向生态协同阶段的范式转型。当前研究在多维效益协同量化框架、微观生物地球化学驱动机制及数字化集成管理技术等方面仍存在关键知识缺口。未来亟需构建基于“水−碳−氮”协同的稻田绿肥种植多维评价体系;整合多组学与示踪技术揭示关键生物地球化学机制;发展“天空地”一体化精准管理系统以克服区域异质性约束;完善测算—报告—核证体系并推动绿肥碳汇纳入市场化生态补偿机制,从而为农业“减排不减产”战略提供理论与技术支撑。

, authors=孙佳蓓1, 2, 王世航1, 蔡思源2, 3, *, 潘鑫瑶3, 4, 赵旭2, 3, 4, *, authorsList=孙佳蓓, 王世航, 蔡思源, 潘鑫瑶, 赵旭, authorCompany=null, correspAuthors=蔡思源, 赵旭, authorNote=

孙佳蓓,硕士研究生,研究方向为农业遥感与模型,电子信箱:

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蔡思源(通信作者),副研究员,研究方向为农业可持续发展,电子信箱:;
赵旭(共同通信作者),研究员,研究方向为农田氮素循环,电子邮箱:
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从增产肥田到碳氮协同:稻田绿肥研究演变与未来展望
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孙佳蓓 1, 2 , 王世航 1 , 蔡思源 2, 3, * , 潘鑫瑶 3, 4 , 赵旭 2, 3, 4, *
科技导报 | 本刊专稿 2026,44(16): 40-48
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科技导报 |本刊专稿 2026 , 44 (16) : 40 -48
从增产肥田到碳氮协同:稻田绿肥研究演变与未来展望
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孙佳蓓1, 2 , 王世航1, 蔡思源2, 3, * , 潘鑫瑶3, 4, 赵旭2, 3, 4, *
作者信息
  • 1安徽理工大学空间信息与测绘工程学院,淮南 232001
  • 2中国科学院南京土壤研究所,江苏常熟农田生态系统国家野外科学观测研究站,土壤与农业可持续发展全国重点实验室,南京 211135
  • 3中国科学院大学南京学院,南京 211135
  • 4中国科学院大学,北京 100049
通讯作者:
蔡思源(通信作者),副研究员,研究方向为农业可持续发展,电子信箱:;
赵旭(共同通信作者),研究员,研究方向为农田氮素循环,电子邮箱:
作者简介:

孙佳蓓,硕士研究生,研究方向为农业遥感与模型,电子信箱:

From yield enhancement to carbon−nitrogen synergy: Evolution and future prospects of green manure research in rice agriculture
Jiabei SUN1, 2 , Shihang WANG1, Siyuan CAI2, 3, * , Xinyao PAN3, 4, Xu ZHAO2, 3, 4, *
Affiliations
  • 1School of Spatial Informatics and Geomatics Engineering, Anhui University of Science and Technology, Huainan 232001, China
  • 2State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro−Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 211135, China
  • 3University of the Chinese Academy of Sciences, Nanjing, Nanjing 211135, China
  • 4University of the Chinese Academy of Sciences, Beijing 100049, China
出版时间: 2026-08-28 doi: 10.3981/j.issn.1000-7857.2025.07.00077
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稻田绿肥作为兼具养分替代与固碳减排双重功能的农业生物措施,在协同保障粮食安全与推动农业绿色低碳转型中具有重要战略意义。基于“演化—机制—路径”框架,系统回顾了1928—2025年间该领域从肥力提升、资源利用向生态协同阶段的范式转型。当前研究在多维效益协同量化框架、微观生物地球化学驱动机制及数字化集成管理技术等方面仍存在关键知识缺口。未来亟需构建基于“水−碳−氮”协同的稻田绿肥种植多维评价体系;整合多组学与示踪技术揭示关键生物地球化学机制;发展“天空地”一体化精准管理系统以克服区域异质性约束;完善测算—报告—核证体系并推动绿肥碳汇纳入市场化生态补偿机制,从而为农业“减排不减产”战略提供理论与技术支撑。

水稻  /  绿肥  /  粮食安全  /  可持续农业  /  氮肥利用率

Rice green manure, as an agro−biological practice that simultaneously provides nutrient substitution and carbon sequestration/emission reduction benefits, holds strategic significance for concurrently safeguarding food security and advancing the green low−carbon transition in agriculture. Based on an "evolution–mechanism–pathway" framework, we systematically traces the paradigm shift from soil fertility enhancement and resource−use optimization toward ecological synergy in rice green manure research spanning 1928–2025. Critical knowledge gaps persist regarding synergistic multi−dimensional benefit quantification frameworks, micro−scale biogeochemical driving mechanisms, and digital integrated management technologies. Future priorities urgently call for: (1) a multi−dimensional evaluation framework for rice green manure cultivation grounded in water–carbon–nitrogen synergy; (2) the integration of multi−omics and isotope tracing approaches to elucidate key biogeochemical mechanisms; (3) the development of an integrated space–aerial–ground precision management system to overcome regional heterogeneity constraints; and (4) the refinement of measurement, reporting, and verification protocols to facilitate the inclusion of green manure carbon sinks into market−oriented ecological compensation mechanisms, thereby providing theoretical and technical support for the "emission reduction without yield reduction" strategy in agriculture.

rice  /  green manure  /  food security  /  sustainable agriculture  /  nitrogen use efficiency
孙佳蓓, 王世航, 蔡思源, 潘鑫瑶, 赵旭. 从增产肥田到碳氮协同:稻田绿肥研究演变与未来展望. 科技导报, 2026 , 44 (16) : 40 -48 . DOI: 10.3981/j.issn.1000-7857.2025.07.00077
Jiabei SUN, Shihang WANG, Siyuan CAI, Xinyao PAN, Xu ZHAO. From yield enhancement to carbon−nitrogen synergy: Evolution and future prospects of green manure research in rice agriculture[J]. Science & Technology Review, 2026 , 44 (16) : 40 -48 . DOI: 10.3981/j.issn.1000-7857.2025.07.00077
作为全球主要水稻生产国与消费国之一,中国以仅占世界7%的耕地养活了近20%的人口,其中水稻贡献了超过60%的主粮消费量。2024年中国稻谷产量达2.08亿t[1],占全球总产量的26%[2]。然而,在未来人口峰值逼近与消费升级的双重压力下,传统稻作模式正面临严峻挑战,过量氮肥投入导致气候变暖,加剧空气污染、水体富营养化、硝酸盐污染、土壤酸化等环境风险,造成生态系统服务价值与健康损害成本达水稻净收益的52%[3]。在“两山”理念统领下,国家通过建立生态产品价值实现机制,将生态效益系统性纳入经济核算与激励体系[4]。在农业领域,围绕绿色低碳转型目标,政策层面持续推动“化肥零增长行动”等措施应用,加速稻作系统向资源节约型与环境友好型方向转变[5]。在这一背景下,绿肥种植作为连接传统农艺与现代生态农业的重要纽带,兼具生态修复、肥力提升与减排增效等多重功能,成为破解生态保护与农业生产二元对立、推动生态价值转化的关键途径之一。
绿肥(green manure)是指以改良土壤、提供养分补充及调节生态系统服务为主要目的,通过轮作、间套、覆盖等方式种植并在特定生育期进行生物还田的作物。其核心机制不仅在于通过养分还田与生物固氮提升耕地质量,更在于其在减少农药化肥依赖、拦截径流养分、抑制病虫草害及提升农田生物多样性方面的系统功能[6]。绿肥作为一项历史悠久的农艺措施,在全球范围内被证实是减少化学氮肥依赖、提升耕地质量的关键农艺措施[7]。鉴于其在可持续土壤管理中的突出贡献,绿肥技术已被联合国粮农组织纳入《可持续土壤管理资源准则》的推荐技术清单[8]。在中国,绿肥应用历史可追溯至西周时期。20世纪70年代,中国绿肥种植进入鼎盛时期,其中水稻田绿肥面积约占全国1300万hm2绿肥总面积的80%[9]。这种“以田养田”模式,使中国在化肥工业尚不发达的年代仍能长期保持高水平土地生产力。然而,随着化学肥料的大规模普及与现代农业追求速效化的趋势,绿肥种植面积显著减少,农户更倾向于依赖化肥获得即时产量效应,削弱了绿肥在维护土壤健康与农业可持续发展中的核心作用。
近年来,全球气候变化与农业绿色转型的双重压力使得绿肥重新成为实现可持续稻作的关键措施之一。一方面,过度依赖化学氮肥不仅导致氮利用率不足35%[10],还造成稻田温室气体排放增加和水体富营养化等环境风险[11];另一方面,中国农业发展模式正从“化学依赖型”向“生态循环型”转变。与此同时,《全国农业绿色发展规划(2021—2030年)》等文件提出,要恢复冬闲田绿肥种植,实现土壤肥力提升与绿色增产目标。尽管绿肥在理论上已形成广泛共识,但其在稻田体系中的多维功能耦合尚缺乏系统量化与机制整合。现有研究多陷于碎片化范式,侧重于单一维度的局部验证,忽视了跨尺度、跨学科的系统综合。此外,绿肥品种适应性、碳氮耦合过程、微生物介导机制及生态经济效益在不同区域间存在显著异质性。上述认知断层不仅限制了绿肥效应预测精度,也削弱了现有技术体系的普适性,进而难以支撑其规模化推广应用。
鉴于此,本研究立足于农业绿色转型国家战略需求,针对上述系统认知缺失与机制整合瓶颈,系统梳理全球视野下绿肥在水稻可持续生产体系中的多维价值。本文基于“历史演化—作用机制—技术路径”分析框架(图1),从历史发展脉络、关键机制与未来技术路径3个层面系统解析绿肥在稻田生态系统中的功能演化,揭示其在土壤肥力维持、减排固碳、生态系统服务与农业绿色转型中的综合作用机制。研究旨在为构建高效、低碳、可持续的稻作绿肥模式提供科学支撑与政策参考。
本研究采用跨库检索策略,数据来源于Web of Science (WoS)和中国知网(CNKI)2大核心数据库,通过布尔逻辑检索式TS=(“Green manure” AND “Rice”)与主题=(“绿肥” AND “水稻”)进行跨库检索,检索时限截至2025年4月1日,共获取自1928—2025年原始文献2439篇(WoS为960篇,CNKI为1479篇)。为提升数据质量,执行同义词归并与停用词过滤的标准化预处理,建立基于专家校验的中英双语受控词表。为避免同义或异写形式造成的主题分散,利用语义归并技术[12],将物理属性相近或等义的术语统一化。在保留核心专业词汇的前提下,构建了包含地理通用词、作物背景词及泛化描述词的停用词库。引入Dimensions数据库检索并提取了2000年至今全球引文数据。基于此数据的年度发文量与被引频次分析,揭示该领域随时间推移的产出规模与学术关注度的演进特征。
1950—1980年绿肥种植面积数据引自《中国绿肥》官方统计资料[13]。针对1980年后绿肥播种面积历史数据缺失问题,根据《中国绿肥》中绿肥作物分类标准,杂豆与青饲料占绿肥品种总数比例超70%,其加和值可作为绿肥面积的代理变量,由此构建间接数据集,提取《中国农业统计年鉴》中“杂豆类”与“青饲料”播种面积(1990—2022年)[14]。
稻田绿肥是中国绿肥应用的主要形式,其种植规模与政策导向、农业生产需求紧密相关。新中国成立后,绿肥生产快速扩张,从1950年的52.5万hm2增至1975年的1366.1万hm2(图2(a)),成为当时保障粮食安全的重要有机养分来源[15]。这一阶段是绿肥在稻田中应用的重要历史时期,绿肥在提高土壤肥力、促进粮食生产、改良土壤结构等方面发挥了重要作用。自20世纪80年代至21世纪初的20多年间,受化肥工业迅速发展、农村劳动力转移以及传统品种更新滞后等因素影响,全国绿肥面积明显回落,从1980年的1103万hm2降至2000年的549万hm2(图2(a)),降幅约50.2%。
2000—2010年是中国绿肥种植的政策与科技转型萌芽期。从绿肥种植规模来看,2000—2005年间全国绿肥种植面积得到缓慢回升,年均增幅约2%(图2(a))。这一恢复性增长与国家农业政策导向密切相关,如2006年农业部启动“土壤有机质提升工程”,带动全国绿肥种植面积恢复到4000万亩(1亩=666.67 m2)左右。2008年南方稻区通过利用冬闲田和推广轻简化技术实现规模化复苏,4年间累计示范稻田绿肥24.7万hm2[16]。在科技转型层面,针对劳动力短缺与生产成本高的问题,研发了紫云英轻简高效播种机等设备;针对传统紫云英品种退化问题,湖南省农业科学院通过种质资源提纯复壮,适配了南方双季稻茬口需求[17]。
2010年以来,绿肥种植面积从2015年的323万hm2恢复至2020年的428万hm2(图2(a))。区域层面,以吴中区为例,稻田轮作休耕面积由2017年的1332 hm2增至2019年的1933 hm2,稻田轮作休耕比例由2017年的70.4%增至2019年的85.3%[18]。从政策框架上看,2015年“化肥零增长行动”与2017年《耕地质量保护与提升行动方案》[19]都在政策层面有序推进绿肥应用规模。在绿肥遗传资源保护层面,依托国家作物种质资源库南方绿肥分库等16个专业化保存设施,构建了覆盖全国主要农业生态区的绿肥种质资源保护网络,成为世界最大的绿肥种质保存体系之一[20];在生产技术层面,集成了无人机精准飞播、开沟播种一体化等轻简智能化装备,初步建立绿肥智慧生产技术示范体系[21],为大面积推广绿肥种植提供了装备支撑。
绿肥通过生物固氮、活化土壤养分及提升土壤酶活性与微生物功能等途径,增加稻田有效养分供给并改善根际环境,在稳增产的同时提高氮素利用效率。在化肥减量管理下,绿肥还田通常能够维持甚至提高水稻产量,主要归因于绿肥对土壤氮素缓释效应及根系促进作用[22]。全球豆科轮作模式分析表明,稻豆轮作对水稻的平均增产效益达18.8%,且在中低产田尤为显著(图2(b))[23],说明绿肥轮作对水稻主要贡献在于生物固氮与缓释机制以提升底肥效益。在品质方面,绿肥通过改善氮素同化与碳氮分配,可促进籽粒营养品质的形成,并在品质上带来附加收益[24]。此外,近期研究显示,绿肥还田有助于降低稻米中镉(Cd)累积[25],其机制包括Cd形态转变、诱导铁膜形成与提升腐殖质组分比例等,从而减弱Cd的生物有效性与根系吸收风险。
绿肥效益同时涵盖物理结构优化、养分库容提升、生物活性增强及土壤障碍消减等多维度协同机制。首先,绿肥通过根系与腐解产物胶结作用,显著改善土壤三相结构,其根系分泌物通过螯合作用促进土壤团聚体形成,提升水稳性团聚体比例[26]。其次,绿肥腐解释放活性碳源及代谢产物,增强土壤有机碳库容量,激发矿物结合态养分释放,增强养分活化与供给能力[27]。值得注意的是,其对不同组分有机碳均有促进作用,显著提升土壤活性和惰性碳组分含量,提高土壤微生物量碳和可溶性有机碳含量[28]。此外,绿肥输入还可调整氮转化过程,如减少氨氧化菌株数、抑制氨氧化古菌丰度、降低羟胺还原酶活性[29],从而减缓硝化与脱氮过程,提升铵态氮供给,抑制氨挥发,减少氮淋失和N2O排放风险。在盐碱障碍消减方面,绿肥通过有机−无机复合机制调控离子平衡、降低盐分含量[30]。
绿肥对农业碳中和的贡献表现在温室气体减排与碳汇增强2大方面。稻田系统是CH4主要排放源,翻压绿肥会增加短期底物供给,理论上可能促进CH4排放;但通过绿肥与水分管理耦合时,可显著降低CH4排放通量,且随其施用年限增加而减少[31]。对N2O而言,绿肥与减氮管理配套,可减少硝化/反硝化底物供应、降低N2O产生[32]。同时,绿肥能通过优化氮循环路径抑制N2O生成,翻压绿肥可为反硝化细菌提供易分解有机碳源,促进nosZ型反硝化类群定向组装与代谢活性,从而提高N2O向N2的还原程度,降低N2O排放[29]。部分绿肥根系分泌的黄酮类化合物是天然的生物硝化抑制剂,能够显著降低N2O排放[33]。在间接减排方面,绿肥替代部分化肥氮可降低其生产—运输环节的CO2排放,并降低温室气体排放强度[34]。碳汇增强方面,绿肥通过“根系分泌物—残体分解—腐殖质形成”三重途径提升土壤固碳效率。原位13C标记试验表明,绿肥根系碳多以闭蓄态颗粒有机碳形式存在,并与黏粒和粉粒组分结合,延长了碳平均驻留时间[35]。
绿肥系统通过作物−土壤−微生物多界面耦合作用,构建了污染阻控、资源循环与生态服务的环境效益体系。在污染阻控层面,豆科绿肥通过生物固氮与还田措施,可部分替代化学氮肥、缓解面源污染与温室气体排放压力[34]。在时空匹配上,冬闲期绿肥对土壤硝态氮具有生态拦截作用,可将稻季残留硝态氮转化为绿肥生物量氮库,从而减少冬闲季土壤氮损失[36]。资源高效利用方面,冬季绿肥翻压后与水稻需氮高峰实现供需同步,使土壤供氮能力与氮素利用效率得到提升[37]。在生态服务维度,绿肥翻压能够重构土壤微域生态,形成腐殖质−黏粒复合体,促进蚯蚓数量增加,土壤结构改善,进而达到有机质−土壤动物−微生物协同优化效果[38]。同时,绿肥通过增加稻田生物多样性,起到生物资源保育库的作用[20]。绿肥种植与分解过程释放的化感物质能起到天然生物防御作用,从而减少除草剂用量[38]。
通过整合2000—2024年间文献数据库中与稻田绿肥研究相关文献数量与引用数量,揭示稻田绿肥研究发展趋势(图3(a))。结果显示,稻田绿肥研究的产出规模呈现出明显的阶段性特征。根据发文量增长率波动,可将研究进程划分为2个阶段:波动增长期(2000—2010年)与指数增长期(2011—2024年)。2010年前,绿肥相关文献数量总体呈波动上升趋势,2008年出现阶段性高点,并于2010年再次达到较高水平(3425篇)。2010—2024年,稻田绿肥研究进入快速增长阶段,年发文量与引用量总体均呈指数上升趋势,年均增长率最高达62.8%。到2019年,文献数量增至2174篇,较2000年增长约5.6倍。这一数据趋势符合普赖斯文献增长定律,表明该领域研究关注度和交叉学科融合度均显著提升。该阶段文献量的激增与全球“土壤健康”倡议及中国“双碳”目标下的农业绿色转型相契合[39],反映了绿肥在农业绿色转型与生态系统管理中的重要地位得到强化。
通过对2000—2024年间稻田绿肥关键词时序分析,揭示了稻田绿肥领域在过去近1个世纪中研究范式的显著转型与科学问题的演变趋势(图3(b))。在2000年之前的早期研究中,主要聚焦于绿肥固氮能力评价及耕作制度优化。这一时期核心绿肥品种以田菁为主。研究多属农艺评价,旨在通过引入特定绿肥品种以解决化肥供应不足问题。步入21世纪,研究视角开始向肥料响应、氮素平衡及氮素管理优化转移。这一时期确立了以长期定位监测为基础的科学范式,为后续解析土壤演变规律奠定了基础[40]。2010年以后,稻田绿肥研究内容发生了显著扩张。近年来甲烷与温室气体等相关研究数量显著增加,表明研究内容已从传统的肥力与增产主题逐步扩展至温室气体减排与环境效应综合评价。同时,微生物群落等分子生物学类关键词频率上升,推动该领域由宏观向微生物生态机制层面延伸,为解析绿肥驱动的土壤−作物−微生物互作网络提供了新的研究路径。值得注意的是,尽管研究维度不断拓宽,产量与化肥等关键词始终保持较高研究热度。
当前稻田绿肥研究正实现从单一增产目标向增产−培肥−减排−增效多目标协同的转型。然而,立足全球农业绿色转型战略需求,稻田绿肥研究体系在系统量化、动态过程调控及数字化集成方面仍存在显著短板。为破解上述瓶颈,未来研究不应仅停留在绿肥单一效应分析,而需构建协同增产、减排、培肥与增效的系统解决方案。基于此,本文提出以下5个核心维度,以期通过技术、机制与政策深度耦合,实现稻田绿肥系统的可持续升级。
首先,绿肥多维效益量化与权衡缺乏统一评估框架。绿肥措施对水稻产量、土壤健康以及温室气体排放的影响常呈非线性响应。当前评估多侧重单一效应,而稻田绿肥综合效益需兼顾环境、经济和社会维度。同时,现有研究具有明显的地域局限性,多集中于长江中下游或南方典型稻区,导致不同生态区间研究结果缺乏时空可比性,难以在更大尺度对绿肥系统集成效益进行综合评估。
针对上述局限,构建适用于稻田绿肥的多维效益综合评价体系成为领域内的迫切需求。针对绿肥在水稻产量、土壤健康提升与温室气体减排等方面的联合效应,应建立统一量化评估框架,集成多源数据,构建可比较、可推广的综合评价模型,为不同种植区绿肥措施的优化提供理论依据。目前初步形成的评价方法包括以下3种:层次分析法(analytic hierarchy process)被用于构建涵盖经济、生态与社会效益的多层次指标体系,通过定性与定量结合的权重赋值,实现对稻田绿肥综合效益的系统评估[41];生命周期评价(life cycle assessment)方法侧重于从资源消耗与污染减排的全过程视角,量化其环境足迹与可持续性水平,为评估绿肥的环境负荷提供了科学工具[34];综合指数法(comprehensive index method)通过建立多指标综合评价体系,实现不同种植模式综合效益的定量排序与比较[42]。通过上述方法的整合应用,可为实现绿肥种植模式的区域适配与可持续推广提供科学依据。
多种绿肥组合与精准施肥的配套机制尚不清晰。现有研究多集中于单一绿肥种类或短期试验,既忽略了混播绿肥对土壤碳氮比及微生物代谢网络演替的长期影响,也缺乏对不同绿肥组合养分释放规律与水稻氮素需求曲线同步性的系统量化。尽管长期定位试验已证实绿肥与化肥配施可显著提升土壤微生物量碳氮[43],但针对不同绿肥组合在长周期内驱动地力演变的异质性,以及由此造成的差异化化肥用量决策阈值,仍缺乏基于土壤−绿肥−作物三者耦合的系统对比与模型化表达。
针对上述研究空白,未来应致力于将微观互作解析与宏观精准调控相结合,构建区域适配的绿肥管理体系,深入研究不同绿肥作物与水稻互作机制,推动多种绿肥组合研究,优化绿肥组合与精准施肥技术。具体而言,重点筛选适用于不同生态区的绿肥品种及其组合方式[44],解析绿肥−水稻系统内养分释放与吸收利用的时空耦合规律[45],明确绿肥腐解特征及其对土壤氮磷转化的影响机制。在此基础上,建立以减肥增效、稳产减排为目标的精准施肥调控体系,依据绿肥养分释放规律与水稻需肥特性,制定分期、定量、定位的施肥策略,实现有机无机养分协同供应,提高肥料利用率,为绿肥稻田系统可持续发展提供理论与技术支撑。
在碳中和战略目标下,利用绿肥实现减排不减产技术路径的过程调控仍存在瓶颈。目前,对于水−碳−氮3因子耦合下,CH4氧化途径与氮素利用效率的协同机制仍缺乏深入理解。绿肥还田增加了土壤活性碳源,在传统淹水条件下会提高产甲烷菌活性,导致CH4排放增加[31]。而绿肥替代化学氮肥可通过优化土壤碳氮比、提高氮素利用效率,降低潜在N2O排放[32],由此形成CH4增加与N2O减排之间此消彼长的关系。同时,绿肥带来的高产效益往往伴随更高的根系分泌物与残体碳输入,进一步加剧CH4排放风险。目前,相关研究多处于单因素效应验证阶段,尚未形成过程调控策略,限制了减排不减产技术的推广应用。
针对上述机理与调控瓶颈,未来布局应致力于将水−碳−氮耦合逻辑转化为可落地的管理技术。采用间歇灌溉、控水增氧为核心的水肥联合调控管理策略[46],通过改善稻田氧化还原环境有效抑制绿肥还田后温室气体排放,实现温室气体减排与水稻高产协同。具体实施中,应依据绿肥类型、还田量及土壤特性,制定差异化的灌溉制度,例如在绿肥腐解关键期实施主动排水晒田,减少产甲烷菌的活性;在水稻需水关键期恢复灌溉,保障作物正常生长,实现温室气体减排与水稻高产的协同。
稻田绿肥在数字化管理与预测方面仍存在尺度断层与机理缺失。虽然以天空地一体化为代表的数字化技术已初步实现对水稻氮含量等关键生化参数的反演[47],但数字化监测手段与绿肥还田下田间高频变动数据尚未实现深度耦合。当前研究缺乏将多源遥感影像与田块尺度高精度实测数据进行同化的成熟范式,导致监测结果在区域宏观趋势与田块精准决策之间存在尺度断层。传统作物生长模型(如DSSAT、APSIM)高度依赖固定参数的输入,在处理绿肥还田诱导的稻田环境异质性方面表现出迟滞性。现有模型架构难以动态表征不同生态区下绿肥腐解规律与水稻养分需求的实时交互,无法精准模拟绿肥驱动的土壤地力提升对产量贡献的非线性过程[48]。
针对上述瓶颈,未来应致力于构建数据驱动与机理融合的数字化决策体系。综合运用遥感、物联网传感器网络和机器学习技术,建立从田块到区域尺度的绿肥/作物生长与生态环境效应一体化监测体系与决策支持系统[49]。重点开发高时空分辨率的绿肥识别与生物量反演算法,实现对其生长动态、还田时间及还田量的精准识别与定量评估。建立集成绿肥生长—腐解—养分释放全过程模型系统,集成环境驱动因子与田间管理措施,模拟不同情景下绿肥还田对土壤有机碳积累、温室气体排放及水稻产量的长期影响,为不同尺度绿肥种植规划与管理优化提供理论工具和量化依据。利用数字化工具为区域尺度绿肥种植规划提供量化依据,通过机理模型与实时数据的融合,克服传统模型的异质性适配难题,为稻田绿色发展提供智能化的理论工具。
碳汇交易市场政策激励与农户经济可接受度之间存在落差。当前,绿肥固碳与减排效益的测算—报告—核证链条尚未完善,限制了其进入碳交易市场。尽管现有监测方法已涵盖土壤结构与微生物等关键指标[50],但缺乏全国统一的核算标准,且现行农业碳汇方法学尚未实现对绿肥全生命周期碳排放边界的精准覆盖,导致不同生态区间数据可比性较差。同时,计量体系的缺失也导致相关政策激励机制难以有效传递至农户层面,制约了农户采纳绿肥技术的积极性,影响绿肥技术的推广与应用。
针对上述瓶颈,未来应致力于建立健全的测算、报告与核证体系,打通绿肥碳汇进入交易市场的“最后一公里”。应立足中国稻田绿肥种植特性,设计专属固碳减排量计量方法学,明确系统边界、关键参数及核算标准[51]。构建规范化数据采集与报告流程,整合田间实测、模型模拟与遥感估算数据,确保监测数据准确性、透明性与可追溯性。建立第三方核证机制,制定独立、公正的核证技术规范,保障碳汇量的真实性与额外性。在此基础上,积极探索绿肥碳汇纳入区域乃至全国碳交易市场的可行路径,通过设计合理的碳信用交易规则[52],形成基于市场机制的生态补偿措施,从而激励农业经营主体大规模推广绿肥种植,实现农田固碳减排与绿色发展的协同推进。
  • 国家自然科学基金青年科学基金C类(32402694)
  • 江苏省自然科学基金青年基金(BK20241700)
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2026年第44卷第16期
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doi: 10.3981/j.issn.1000-7857.2025.07.00077
  • 接收时间:2025-07-15
  • 首发时间:2026-09-30
  • 出版时间:2026-08-28
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  • 收稿日期:2025-07-15
  • 修回日期:2026-03-20
基金
国家自然科学基金青年科学基金C类(32402694)
江苏省自然科学基金青年基金(BK20241700)
作者信息
    1安徽理工大学空间信息与测绘工程学院,淮南 232001
    2中国科学院南京土壤研究所,江苏常熟农田生态系统国家野外科学观测研究站,土壤与农业可持续发展全国重点实验室,南京 211135
    3中国科学院大学南京学院,南京 211135
    4中国科学院大学,北京 100049

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蔡思源(通信作者),副研究员,研究方向为农业可持续发展,电子信箱:;
赵旭(共同通信作者),研究员,研究方向为农田氮素循环,电子邮箱:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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