Article(id=1302192629307957478, tenantId=1146029695717560320, journalId=1301850032934322245, issueId=1302192562882761358, articleNumber=null, orderNo=null, doi=10.3864/j.issn.0578-1752.2026.16.011, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1761321600000, receivedDateStr=2025-10-25, revisedDate=null, revisedDateStr=null, acceptedDate=1766073600000, acceptedDateStr=2025-12-19, onlineDate=1788396516396, onlineDateStr=2026-09-03, pubDate=1786809600000, pubDateStr=2026-08-16, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788396516396, onlineIssueDateStr=2026-09-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788396516396, creator=13701087609, updateTime=1788396516396, updator=13701087609, issue=Issue{id=1302192562882761358, tenantId=1146029695717560320, journalId=1301850032934322245, year='2026', volume='59', issue='16', pageStart='3465', pageEnd='3698', issueExtLink='null', onlineDate='null', pubDate='1786809600000', pubDateStr='2026-08-16', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1788396500558, creator='13701087609', updateTime=1788405251849, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1302229268860264480, tenantId=1146029695717560320, journalId=1301850032934322245, issueId=1302192562882761358, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1302229268860264481, tenantId=1146029695717560320, journalId=1301850032934322245, issueId=1302192562882761358, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3621, endPage=3639, ext={EN=ArticleExt(id=1302192629509284071, articleId=1302192629307957478, tenantId=1146029695717560320, journalId=1301850032934322245, language=EN, title=Effects of Reduced Nitrogen and Controlled Water Combined with Biochar and Nitrification Inhibitor on Nitrogen Losses in a Facility Soil-Tomato System, columnId=1302192608567120828, journalTitle=Scientia Agricultura Sinica, columnName=SOIL & FERTILIZER·WATER-SAVING IRRIGATION·AGROECOLOGY & ENVIRONMENT, runingTitle=null, highlight=null, articleAbstract=

【Objective】 This study aimed to clarify the regulatory effects of the reduced nitrogen combined with controlled water, biochar, and the nitrification inhibitor dicyandiamide (DCD) on nitrogen losses within a facility soil-tomato system, so as to provide a scientific basis for efficient nitrogen use and sustainable green development in facility vegetable production.【Method】 A field plot experiment was conducted using facility tomato as the research object, with two irrigation treatments including traditional drip irrigation (TD) and reduced drip irrigation (CD). Based on this, eight nitrogen treatments were designed, including no nitrogen (TDN0, and CDN0), traditional nitrogen (TDN1, and CDN1), reduced nitrogen (TDN2, and CDN2), and reduced nitrogen combined with biochar and dicyandiamide (DCD) (TDN2+BD, and CDN2+BD). During the topdressing period, soil N2O emission and NH3 volatilization, NO3--N accumulation in the 0-100 cm soil profile, and tomato nitrogen uptake, yield, and fruit quality indicators were systematically monitored to quantitatively evaluate the synergistic regulatory effects of biochar and DCD under reduced nitrogen and controlled water conditions. 【Result】 Nitrogen application significantly increased soil N2O emissions and NH3 volatilization, with peak fluxes occurring 2-3 days after topdressing. Nitrogen reduction effectively suppressed gaseous nitrogen losses, and the combined application of biochar and the nitrification inhibitor DCD further enhanced the mitigation effect on N2O emissions. Although biochar and DCD posed a potential risk of increasing NH3 volatilization, this adverse effect was substantially alleviated by reduced nitrogen and controlled water conditions. Compared with conventional nitrogen application, nitrogen reduction significantly decreased total gaseous nitrogen losses by 45.7%-56.6% and reduced NO3--N accumulation in the 0-100 cm soil profile by 13.7%-16.2%. When biochar and DCD were applied on the basis of nitrogen reduction, total gaseous nitrogen losses further declined by 49.4%-59.0%, while the reduction in NO3--N accumulation expanded to 27.4%-30.0%, with a clear suppression of deep leaching. Both irrigation methods enhanced the synergistic mitigation effects of water nitrogen regulation. However, controlled drip irrigation demonstrated superior performance compared with conventional drip irrigation. Under controlled irrigation, the CDN2+BD treatment reduced total nitrogen losses by 30.0% compared with CDN1, with decreasing the net nitrogen loss rate from 3.3% to 2.5%. This treatment also significantly inhibited deep NO3--N accumulation and increased NO3--N retention in the 20-40 cm soil layer by 27.1%. In addition, biochar and DCD increased the apparent nitrogen use efficiency under controlled irrigation to 28.9%; TDN2+BD and CDN2+BD improved nitrogen use efficiency by 53.0% and 30.2%, respectively, compared with their corresponding nitrogen-reduction treatments (TDN2 and CDN2) (P<0.05). Furthermore, the controlled irrigation with biochar and DCD (CDN2+BD) achieved the highest tomato yield (115.93 t·hm-2), while significantly enhancing fruit vitamin C content and improving soluble protein, soluble sugar, and total soluble solid levels.【Conclusion】 Reduced nitrogen application combined with controlled water, biochar, and the nitrification inhibitor dicyandiamide (DCD) significantly decreased gaseous and leaching nitrogen losses, optimized soil nitrogen distribution, and improved nitrogen use efficiency and tomato quality, representing an optimal technical approach for nitrogen reduction and efficiency enhancement in facility vegetable production.

, authors=JinJin LI1, 2, YuQing ZHAO1, 2, RuiYi LIU1, 2, YanZhi JI1, 2, 3, JianZhi XIE1, 2, YanJie GUO1, 2, 3, LiJuan ZHANG1, 2, 3, authorsList=JinJin LI, YuQing ZHAO, RuiYi LIU, YanZhi JI, JianZhi XIE, YanJie GUO, LiJuan ZHANG, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, 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=1302192631463829747, articleId=1302192629307957478, tenantId=1146029695717560320, journalId=1301850032934322245, language=CN, title=减氮控水配施生物炭与硝化抑制剂对设施土壤-番茄体系氮素损失的影响, columnId=1302192608739087294, journalTitle=中国农业科学, columnName=土壤肥料·节水灌溉·农业生态环境, runingTitle=null, highlight=null, articleAbstract=

【目的】 揭示减氮控水条件下配施生物炭与硝化抑制剂双氰胺(DCD)对设施土壤-番茄体系氮素损失的调控效应,为设施蔬菜氮肥高效利用与绿色发展提供依据。【方法】 以设施番茄为研究对象,设置常规滴灌(TD)与控水滴灌(CD)2种灌水方式,在此基础上设不施氮(TDN0、CDN0)、常规施氮(TDN1、CDN1)、减氮(TDN2、CDN2)及减氮配施生物炭与DCD(TDN2+BD、CDN2+BD)共8个处理。采用田间小区试验法,系统监测追肥期内土壤N2O排放与NH3挥发、剖面NO3--N累积分布及番茄氮素吸收利用、产量与品质指标,定量评估生物炭与双氰胺在减氮控水条件下的协同调控效应。【结果】 施氮显著提高了土壤N2O排放和NH3挥发,且排放高峰主要出现在追肥后2—3 d。减氮措施可有效抑制气态氮损失,在此基础上配施生物炭与DCD进一步强化了N2O的减排效应。在NH3挥发方面,生物炭和DCD施用存在一定升高风险,但控水滴灌能够显著缓解这一不利效应。与常规施氮相比,减氮措施可显著降低气态氮总损失量45.7%—56.6%,土壤0—100 cm剖面硝态氮累积减少13.7%—16.2%。在此基础上配施生物炭与硝化抑制剂DCD,气态氮总损失量进一步降低至49.4%—59.0%,硝态氮累积降幅则扩大至27.4%—30.0%,并有效抑制其深层淋溶。2种灌水方式均能增强水氮协同减损效应,但控水滴灌整体优于常规滴灌。CDN2+BD处理的N2O排放和NH3挥发总损失量较CDN1降低30.0%,净损失率由3.3%降至2.5%;同时显著减少硝态氮深层累积,并提高20—40 cm土层NO3--N保持能力(增加27.1%)。此外,生物炭与DCD能将控水滴灌下的氮肥表观利用率提升至28.9%,TDN2+BD和CDN2+BD处理较对应的单一减氮处理(TDN2和CDN2)分别显著提高53.0%和30.2%(P<0.05)。控水滴灌配施生物炭与DCD处理(CDN2+BD)在获得最高产量(115.93 t·hm-2)的同时,还显著提升了果实维生素C(Vc)含量,并促进了可溶性蛋白、可溶性糖及可溶性固形物的积累。【结论】 减氮控水配施生物炭与硝化抑制剂双氰胺可显著协同抑制氮素气态损失与淋溶,改善土壤氮分布,提高氮肥利用效率和番茄品质,是设施蔬菜氮素减量增效的优选技术模式。

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2 Key Laboratory for Farmland Eco-Environment of Hebei Province, Baoding 071001, Hebei
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HortScience, 2020, 55(11): 1744-1755., articleTitle=Tomato growth, yield, and root development, soil nitrogen and water distribution as affected by nitrogen and irrigation rates on a Florida sandy soil, refAbstract=null)], funds=[Fund(id=1302192639697248596, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, awardId=HBCT2018030206, language=CN, fundingSource=河北省现代农业产业技术体系蔬菜产业创新团队项目(HBCT2018030206), fundOrder=null, country=null), Fund(id=1302192639772746069, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, awardId=21326905D, language=CN, fundingSource=河北省重点研发计划项目(21326905D), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1302192631740653812, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, xref=1, ext=[AuthorCompanyExt(id=1302192631749042421, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192631740653812, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Resources and Environmental Sciences, Hebei Agricultural University, Baoding 071001, Hebei), AuthorCompanyExt(id=1302192631757431030, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192631740653812, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 河北农业大学资源与环境科学学院, 河北保定 071001)]), AuthorCompany(id=1302192632021672183, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, xref=2, ext=[AuthorCompanyExt(id=1302192632030060792, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192632021672183, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Key Laboratory for Farmland Eco-Environment of Hebei Province, Baoding 071001, Hebei), AuthorCompanyExt(id=1302192632042643705, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192632021672183, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 河北省农田生态环境重点实验室, 河北保定 071001)]), AuthorCompany(id=1302192632118141178, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, xref=3, ext=[AuthorCompanyExt(id=1302192632130724091, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192632118141178, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 Collaborative Innovation Center for Vegetable Industry of Hebei, Baoding 071001, Hebei), AuthorCompanyExt(id=1302192632139112700, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, companyId=1302192632118141178, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 河北省蔬菜产业协同创新中心, 河北保定 071001)])], figs=[ArticleFig(id=1302192637050642740, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Fig. 1, caption=Temporal dynamics of soil N2O emission fluxes under different treatments during the topdressing period, figureFileSmall=vdgVxNXZE0fQTDShT3FPLQ==, figureFileBig=UXXnNCYpVBJIVmXMjst40w==, tableContent=null), ArticleFig(id=1302192637109362997, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=图1, caption=追肥期间不同处理土壤N2O排放通量动态变化, figureFileSmall=vdgVxNXZE0fQTDShT3FPLQ==, figureFileBig=UXXnNCYpVBJIVmXMjst40w==, tableContent=null), ArticleFig(id=1302192637310689590, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Fig. 2, caption=Temporal dynamics of soil NH3 volatilization rate under different treatments during the topdressing period, figureFileSmall=ITfM1Gpyy5cBEeNLXdSI5Q==, figureFileBig=m1ynoBRSwxhd0xLh1xE+Tw==, tableContent=null), ArticleFig(id=1302192637470073143, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=图2, caption=追肥期间不同处理土壤NH3挥发速率动态变化, figureFileSmall=ITfM1Gpyy5cBEeNLXdSI5Q==, figureFileBig=m1ynoBRSwxhd0xLh1xE+Tw==, tableContent=null), ArticleFig(id=1302192637549764920, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Fig. 3, caption=Nitrate nitrogen accumulation in 0-100 cm soil profile after harvest

Different lowercase letters within the same soil layer of the figure indicate significant differences among treatments at the 0.05 level. The same as below

, figureFileSmall=AyWLtzkiEsuKXza5g/LEYA==, figureFileBig=TFO8AT6ecnrwyTRcdSk1bQ==, tableContent=null), ArticleFig(id=1302192637616873785, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=图3, caption=收获后不同处理土壤0—100 cm剖面硝态氮累积量

同一土层不同小写字母表示不同处理间在0.05水平上差异显著。下同

, figureFileSmall=AyWLtzkiEsuKXza5g/LEYA==, figureFileBig=TFO8AT6ecnrwyTRcdSk1bQ==, tableContent=null), ArticleFig(id=1302192637688176954, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Fig. 4, caption=Tomato yield and fruit quality indicators under different treatments, figureFileSmall=w6oF2m/G4hVheSBcVftlDA==, figureFileBig=tgusMjW45HfrfRO8RRyyxQ==, tableContent=null), ArticleFig(id=1302192637772063035, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=图4, caption=不同处理番茄产量与果实品质指标, figureFileSmall=w6oF2m/G4hVheSBcVftlDA==, figureFileBig=tgusMjW45HfrfRO8RRyyxQ==, tableContent=null), ArticleFig(id=1302192637843366204, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Fig. 5, caption=Nitrogen accumulation in tomato plant organs under different treatments, figureFileSmall=1s6VNAw8TftEcrWwWqYQOw==, figureFileBig=DBAv1TWn0L+VpG4vA74CtQ==, tableContent=null), ArticleFig(id=1302192637918863677, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=图5, caption=不同处理下番茄植株各器官的氮素积累, figureFileSmall=1s6VNAw8TftEcrWwWqYQOw==, figureFileBig=DBAv1TWn0L+VpG4vA74CtQ==, tableContent=null), ArticleFig(id=1302192637985972542, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 1, caption=

Soil basic physical and chemical properties of experimental site

, figureFileSmall=null, figureFileBig=null, tableContent=
土壤层次
Soil layer
(cm)
全氮
Total N
(g·kg-1)
有机质
SOM
(g·kg-1)
硝态氮
NO3--N
(mg·kg-1)
铵态氮
NH4+-N
(mg·kg-1)
有效磷
Olsen-P
(mg·kg-1)
速效钾
NH4OAc-K
(mg·kg-1)
pH
(水:土=2.5:1)
粒径组成 Particle size composition (%) 容重
Bulk density
(g·cm-3)
砂粒
Sand
粉粒
Silt
黏粒
Clay
0-20 1.07 17.49 150.67 27.71 113.65 172.72 7.92 59.99 16.66 23.35 1.21
20-40 0.75 11.78 123.86 29.38 78.16 115.51 8.02 67.91 15.32 16.77 1.25
40-60 0.54 8.79 106.71 25.28 52.05 191.33 8.13 73.89 12.93 13.18 1.35
60-80 0.50 8.91 84.07 20.87 57.44 184.89 8.16 77.57 11.05 11.38 1.46
80-100 0.57 11.70 82.29 13.01 59.61 285.99 8.18 72.03 13.41 14.56 1.45
), ArticleFig(id=1302192638065664319, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表1, caption=

试验地土壤基本理化性质

, figureFileSmall=null, figureFileBig=null, tableContent=
土壤层次
Soil layer
(cm)
全氮
Total N
(g·kg-1)
有机质
SOM
(g·kg-1)
硝态氮
NO3--N
(mg·kg-1)
铵态氮
NH4+-N
(mg·kg-1)
有效磷
Olsen-P
(mg·kg-1)
速效钾
NH4OAc-K
(mg·kg-1)
pH
(水:土=2.5:1)
粒径组成 Particle size composition (%) 容重
Bulk density
(g·cm-3)
砂粒
Sand
粉粒
Silt
黏粒
Clay
0-20 1.07 17.49 150.67 27.71 113.65 172.72 7.92 59.99 16.66 23.35 1.21
20-40 0.75 11.78 123.86 29.38 78.16 115.51 8.02 67.91 15.32 16.77 1.25
40-60 0.54 8.79 106.71 25.28 52.05 191.33 8.13 73.89 12.93 13.18 1.35
60-80 0.50 8.91 84.07 20.87 57.44 184.89 8.16 77.57 11.05 11.38 1.46
80-100 0.57 11.70 82.29 13.01 59.61 285.99 8.18 72.03 13.41 14.56 1.45
), ArticleFig(id=1302192638136967488, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 2, caption=

Fertilization methods, application rates, and timing under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
处理
Treatment
基肥
(2022-10-5)
Basal fertilizer
(October 5, 2022)
追肥Topdressing 总计
Total
(kg·hm-2)
灌水 Irrigation 总计
Total (m3·hm-2)
第1次
(2023-1-16)
First
(January 16, 2023)
第2次
(2023-3-14)
Second
(March 14, 2023)
第3次
(2023-4-15)
Third
(April 15,
2023)
第1次
(2022-10-12)
First
(October 12, 2022)
第2次
(2022-10-17)
Second
(October 17, 2023)
第3次
(2023-1-16)
Third
(January 16, 2023)
第4次
(2023-3-14)
Forth
(March 14, 2023)
第5次
(2023-4-15)
Fifth
(April 15, 2023)
第6次
(2023-5-5)
Sixth
(May 5, 2023)
第7次
(2023-6-1)
Seventh
(June 1, 2023)
N P2O5 K2O N P2O5 K2O N P2O5 K2O N P2O5 K2O N P2O5 K2O
TDN0 0 194 205 0 30 32 0 52 70 0 52 70 0 328 377 225 360 540 810 900 990 675 4500
TDN1 207 194 205 45 30 32 100 52 70 100 52 70 452 328 377 225 360 540 810 900 990 675 4500
TDN2 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 225 360 540 810 900 990 675 4500
TDN2+BD 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 225 360 540 810 900 990 675 4500
CDN0 0 194 205 0 30 32 0 52 70 0 52 70 0 328 377 169 270 405 608 675 743 506 3375
CDN1 207 194 205 45 30 32 100 52 70 100 52 70 452 328 377 169 270 405 608 675 743 506 3375
CDN2 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 169 270 405 608 675 743 506 3375
CDN2+BD 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 169 270 405 608 675 743 506 3375
), ArticleFig(id=1302192638246019393, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表2, caption=

不同处理施肥方式、施肥量及施用时间

, figureFileSmall=null, figureFileBig=null, tableContent=
处理
Treatment
基肥
(2022-10-5)
Basal fertilizer
(October 5, 2022)
追肥Topdressing 总计
Total
(kg·hm-2)
灌水 Irrigation 总计
Total (m3·hm-2)
第1次
(2023-1-16)
First
(January 16, 2023)
第2次
(2023-3-14)
Second
(March 14, 2023)
第3次
(2023-4-15)
Third
(April 15,
2023)
第1次
(2022-10-12)
First
(October 12, 2022)
第2次
(2022-10-17)
Second
(October 17, 2023)
第3次
(2023-1-16)
Third
(January 16, 2023)
第4次
(2023-3-14)
Forth
(March 14, 2023)
第5次
(2023-4-15)
Fifth
(April 15, 2023)
第6次
(2023-5-5)
Sixth
(May 5, 2023)
第7次
(2023-6-1)
Seventh
(June 1, 2023)
N P2O5 K2O N P2O5 K2O N P2O5 K2O N P2O5 K2O N P2O5 K2O
TDN0 0 194 205 0 30 32 0 52 70 0 52 70 0 328 377 225 360 540 810 900 990 675 4500
TDN1 207 194 205 45 30 32 100 52 70 100 52 70 452 328 377 225 360 540 810 900 990 675 4500
TDN2 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 225 360 540 810 900 990 675 4500
TDN2+BD 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 225 360 540 810 900 990 675 4500
CDN0 0 194 205 0 30 32 0 52 70 0 52 70 0 328 377 169 270 405 608 675 743 506 3375
CDN1 207 194 205 45 30 32 100 52 70 100 52 70 452 328 377 169 270 405 608 675 743 506 3375
CDN2 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 169 270 405 608 675 743 506 3375
CDN2+BD 145 194 205 32 30 32 70 52 70 70 52 70 317 328 377 169 270 405 608 675 743 506 3375
), ArticleFig(id=1302192638325711170, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 3, caption=

Repeated measured analysis of variance (ANOVA) of soil N2O emission flux under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
N2O排放通量
N2O emission flux
处理 Treatment 7 28456.892 18.73 <0.001
时间 Time 24 8923.417 35.62 <0.001
处理×时间Treatment×Time 168 1876.539 7.49 <0.001
), ArticleFig(id=1302192638392820035, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表3, caption=

不同处理土壤N2O排放通量重复测量方差分析(ANOVA)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
N2O排放通量
N2O emission flux
处理 Treatment 7 28456.892 18.73 <0.001
时间 Time 24 8923.417 35.62 <0.001
处理×时间Treatment×Time 168 1876.539 7.49 <0.001
), ArticleFig(id=1302192638476706116, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 4, caption=

Two-way analysis of variance (ANOVA) of soil N2O emission flux under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test PP value
N2O排放通量
N2O emission flux
灌水 Irrigation 1 519.059 13.579 0.002
氮素调控Nitrogen regulation 3 7079.078 185.199 <0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 51.432 1.346 0.295
), ArticleFig(id=1302192638552203589, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表4, caption=

不同处理土壤N2O排放通量双因素方差分析(ANOVA)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test PP value
N2O排放通量
N2O emission flux
灌水 Irrigation 1 519.059 13.579 0.002
氮素调控Nitrogen regulation 3 7079.078 185.199 <0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 51.432 1.346 0.295
), ArticleFig(id=1302192638627701062, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 5, caption=

Repeated measured analysis of variance (ANOVA) of soil NH3 volatilization rate under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F F value P P value
NH3挥发速率
NH3 volatilization rate
处理 Treatment 7 45.327 22.156 <0.001
时间 Time 41 28.641 48.773 <0.001
处理×时间Treatment×Time 287 6.892 11.734 <0.001
), ArticleFig(id=1302192638707392839, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表5, caption=

不同处理土壤NH3挥发速率重复测量方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F F value P P value
NH3挥发速率
NH3 volatilization rate
处理 Treatment 7 45.327 22.156 <0.001
时间 Time 41 28.641 48.773 <0.001
处理×时间Treatment×Time 287 6.892 11.734 <0.001
), ArticleFig(id=1302192638766113096, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 6, caption=

Two-way analysis of variance (ANOVA) of soil NH3 volatilization rate under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test PP value
NH3挥发速率
NH3 volatilization rate
灌水 Irrigation 1 16.609 52.123 <0.001
氮素调控Nitrogen regulation 3 281.212 882.511 <0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1.687 5.295 0.010
), ArticleFig(id=1302192638833221961, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表6, caption=

不同处理土壤NH3挥发速率双因素方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test PP value
NH3挥发速率
NH3 volatilization rate
灌水 Irrigation 1 16.609 52.123 <0.001
氮素调控Nitrogen regulation 3 281.212 882.511 <0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1.687 5.295 0.010
), ArticleFig(id=1302192638896136522, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 7, caption=

Soil cumulative N2O emissions, NH3 cumulative volatilization, and net loss rate under different treatments during the topdressing period

, figureFileSmall=null, figureFileBig=null, tableContent=
处理
Treatment
N2O NH3 N2O+NH3
累积排放量
Accumulated emission amount (kg·hm-2)
损失率
Loss rate
(%)
累积排放量
Accumulated emission amount (kg·hm-2)
损失率
Loss rate
(%)
总损失量
Total losses
(kg·hm-2)
净损失率
Net loss rate
(%)
TDN0 0.25±0.05 e 4.47±0.47 d 4.72+0.53 e
TDN1 2.18±0.14 a 0.79±0.43 a 18.44±1.55 a 5.70±0.79 a 20.62±1.59 a 6.49±0.65 a
TDN2 1.30+0.18 b 0.61±0.33 b 9.90±0.79 b 3.16±0.33 b 11.20±0.63 b 3.77±0.16 b
TDN2+BD 0.96±0.10 c 0.41±0.22 c 9.47±0.33 bc 2.91±0.35b 10.43±0.31 bc 3.32±0.46 bc
CDN0 0.22+0.05 e 3.91±0.35 d 4.13+0.30 e
CDN1 0.97±0.11 c 0.31±0.17 c 11.12±1.57 b 2.94±0.57 b 12.09±1.68 b 3.25±0.73 bc
CDN2 0.80+0.08 c 0.33±0.18 c 8.15±0.73 c 2.46±0.73 b 8.95+0.66 cd 2.79±0.27 bc
CDN2+BD 0.51±0.03 d 0.17±0.09 d 7.95±0.62 c 2.35±0.62 b 8.46±0.65 d 2.52±0.55 d
), ArticleFig(id=1302192638971633995, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表7, caption=

追肥期间不同处理土壤N2O累积排放量与NH3累积挥发量及净损失率

, figureFileSmall=null, figureFileBig=null, tableContent=
处理
Treatment
N2O NH3 N2O+NH3
累积排放量
Accumulated emission amount (kg·hm-2)
损失率
Loss rate
(%)
累积排放量
Accumulated emission amount (kg·hm-2)
损失率
Loss rate
(%)
总损失量
Total losses
(kg·hm-2)
净损失率
Net loss rate
(%)
TDN0 0.25±0.05 e 4.47±0.47 d 4.72+0.53 e
TDN1 2.18±0.14 a 0.79±0.43 a 18.44±1.55 a 5.70±0.79 a 20.62±1.59 a 6.49±0.65 a
TDN2 1.30+0.18 b 0.61±0.33 b 9.90±0.79 b 3.16±0.33 b 11.20±0.63 b 3.77±0.16 b
TDN2+BD 0.96±0.10 c 0.41±0.22 c 9.47±0.33 bc 2.91±0.35b 10.43±0.31 bc 3.32±0.46 bc
CDN0 0.22+0.05 e 3.91±0.35 d 4.13+0.30 e
CDN1 0.97±0.11 c 0.31±0.17 c 11.12±1.57 b 2.94±0.57 b 12.09±1.68 b 3.25±0.73 bc
CDN2 0.80+0.08 c 0.33±0.18 c 8.15±0.73 c 2.46±0.73 b 8.95+0.66 cd 2.79±0.27 bc
CDN2+BD 0.51±0.03 d 0.17±0.09 d 7.95±0.62 c 2.35±0.62 b 8.46±0.65 d 2.52±0.55 d
), ArticleFig(id=1302192639047131468, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 8, caption=

Two-way analysis of variance (ANOVA) of NO3--N accumulation in the soil profile under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
0-20 cm土层硝态氮累积
Nitrate accumulation in 0-20 cm soil layer
灌水 Irrigation 1 4378.937 31.271 0.000
氮素调控Nitrogen regulation 3 6572.520 46.936 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1348.067 9.627 0.001
20-40 cm土层硝态氮累积
Nitrate accumulation in 20-40 cm soil layer
灌水 Irrigation 1 59.143 0.233 0.636
氮素调控Nitrogen regulation 3 10214.254 40.263 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 723.765 2.853 0.072
40-60 cm土层硝态氮累积
Nitrate accumulation in 40-60 cm soil layer
灌水 Irrigation 1 583.208 5.595 0.032
氮素调控Nitrogen regulation 3 6778.893 65.039 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 197.226 1.892 0.174
60-80 cm土层硝态氮累积
Nitrate accumulation in 60-80 cm soil layer
灌水 Irrigation 1 515.565 6.455 0.023
氮素调控Nitrogen regulation 3 3586.607 44.908 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 326.159 4.084 0.026
80-100 cm土层硝态氮累积
Nitrate accumulation in 80-100 cm soil layer
灌水 Irrigation 1 163.375 2.795 0.115
氮素调控Nitrogen regulation 3 4002.020 68.474 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 147.159 2.518 0.097
), ArticleFig(id=1302192639131017549, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表8, caption=

不同处理土壤剖面NO3--N累积双因素方差分析(ANOVA)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
0-20 cm土层硝态氮累积
Nitrate accumulation in 0-20 cm soil layer
灌水 Irrigation 1 4378.937 31.271 0.000
氮素调控Nitrogen regulation 3 6572.520 46.936 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1348.067 9.627 0.001
20-40 cm土层硝态氮累积
Nitrate accumulation in 20-40 cm soil layer
灌水 Irrigation 1 59.143 0.233 0.636
氮素调控Nitrogen regulation 3 10214.254 40.263 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 723.765 2.853 0.072
40-60 cm土层硝态氮累积
Nitrate accumulation in 40-60 cm soil layer
灌水 Irrigation 1 583.208 5.595 0.032
氮素调控Nitrogen regulation 3 6778.893 65.039 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 197.226 1.892 0.174
60-80 cm土层硝态氮累积
Nitrate accumulation in 60-80 cm soil layer
灌水 Irrigation 1 515.565 6.455 0.023
氮素调控Nitrogen regulation 3 3586.607 44.908 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 326.159 4.084 0.026
80-100 cm土层硝态氮累积
Nitrate accumulation in 80-100 cm soil layer
灌水 Irrigation 1 163.375 2.795 0.115
氮素调控Nitrogen regulation 3 4002.020 68.474 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 147.159 2.518 0.097
), ArticleFig(id=1302192639210709326, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 9, caption=

Two-way analysis of variance (ANOVA) of tomato yield and fruit quality in different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
番茄产量
Tomato yield
灌水 Irrigation 1 27.290 0.896 0.359
氮素调控Nitrogen regulation 3 354.798 11.644 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 55.133 1.809 0.189
维生素C含量
Vc content
灌水 Irrigation 1 12.627 1.128 0.305
氮素调控Nitrogen regulation 3 92.285 8.241 0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 6.027 0.538 0.663
可溶性糖含量
Soluble sugar content
灌水 Irrigation 1 0.127 0.077 0.785
氮素调控Nitrogen regulation 3 2.929 1.774 0.187
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.065 0.039 0.989
可溶性蛋白含量
Soluble protein content
灌水 Irrigation 1 28.769 0.016 0.902
氮素调控Nitrogen regulation 3 10434.447 5.710 0.005
灌水×氮素调控 Irrigation×Nitrogen regulation 3 350.094 0.192 0.900
可溶性固形物含量
Soluble solid content
灌水 Irrigation 1 0.025 0.015 0.905
氮素调控Nitrogen regulation 3 2.161 1.278 0.322
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.050 0.030 0.993
可滴定酸含量
Titratable acid content
灌水 Irrigation 1 1.734 1.306 0.271
氮素调控Nitrogen regulation 3 3.149 2.371 0.099
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.337 0.254 0.857
), ArticleFig(id=1302192639290401103, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表9, caption=

各处理番茄产量和果实品质双因素方差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
番茄产量
Tomato yield
灌水 Irrigation 1 27.290 0.896 0.359
氮素调控Nitrogen regulation 3 354.798 11.644 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 55.133 1.809 0.189
维生素C含量
Vc content
灌水 Irrigation 1 12.627 1.128 0.305
氮素调控Nitrogen regulation 3 92.285 8.241 0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 6.027 0.538 0.663
可溶性糖含量
Soluble sugar content
灌水 Irrigation 1 0.127 0.077 0.785
氮素调控Nitrogen regulation 3 2.929 1.774 0.187
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.065 0.039 0.989
可溶性蛋白含量
Soluble protein content
灌水 Irrigation 1 28.769 0.016 0.902
氮素调控Nitrogen regulation 3 10434.447 5.710 0.005
灌水×氮素调控 Irrigation×Nitrogen regulation 3 350.094 0.192 0.900
可溶性固形物含量
Soluble solid content
灌水 Irrigation 1 0.025 0.015 0.905
氮素调控Nitrogen regulation 3 2.161 1.278 0.322
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.050 0.030 0.993
可滴定酸含量
Titratable acid content
灌水 Irrigation 1 1.734 1.306 0.271
氮素调控Nitrogen regulation 3 3.149 2.371 0.099
灌水×氮素调控 Irrigation×Nitrogen regulation 3 0.337 0.254 0.857
), ArticleFig(id=1302192639365898576, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 10, caption=

Two-way analysis of variance (ANOVA) of nitrogen accumulation in tomato plant organs under different treatments

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
根氮素累积
Root N accumulation
灌水 Irrigation 1 0.235 0.162 0.693
氮素调控Nitrogen regulation 3 12.728 8.801 0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1.311 0.907 0.461
茎氮素累积
Stem N accumulation
灌水 Irrigation 1 15.079 0.533 0.477
氮素调控Nitrogen regulation 3 278.588 9.839 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 3.146 0.111 0.952
叶氮素累积
Leaf N accumulation
灌水 Irrigation 1 0.243 0.010 0.923
氮素调控Nitrogen regulation 3 521.503 20.897 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 7.411 0.297 0.827
果实氮素累积
Fruit N accumulation
灌水 Irrigation 1 0.086 0.000 0.989
氮素调控Nitrogen regulation 3 2567.785 5.393 0.007
灌水×氮素调控 Irrigation×Nitrogen regulation 3 375.604 0.789 0.519
), ArticleFig(id=1302192639445590353, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表10, caption=

不同处理番茄植株各器官氮素累积双因素方差分析(ANOVA)

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 Index 因素 Factor 自由度 df 标准差 MS F检验 F test P P value
根氮素累积
Root N accumulation
灌水 Irrigation 1 0.235 0.162 0.693
氮素调控Nitrogen regulation 3 12.728 8.801 0.001
灌水×氮素调控 Irrigation×Nitrogen regulation 3 1.311 0.907 0.461
茎氮素累积
Stem N accumulation
灌水 Irrigation 1 15.079 0.533 0.477
氮素调控Nitrogen regulation 3 278.588 9.839 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 3.146 0.111 0.952
叶氮素累积
Leaf N accumulation
灌水 Irrigation 1 0.243 0.010 0.923
氮素调控Nitrogen regulation 3 521.503 20.897 0.000
灌水×氮素调控 Irrigation×Nitrogen regulation 3 7.411 0.297 0.827
果实氮素累积
Fruit N accumulation
灌水 Irrigation 1 0.086 0.000 0.989
氮素调控Nitrogen regulation 3 2567.785 5.393 0.007
灌水×氮素调控 Irrigation×Nitrogen regulation 3 375.604 0.789 0.519
), ArticleFig(id=1302192639533670738, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=EN, label=Table 11, caption=

Total nitrogen uptake, apparent nitrogen use efficiency, and agronomic efficiency of nitrogen fertilizer in tomato plants under different treatments

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处理 Treatment 总吸收氮量 Total N uptake (kg·hm-2) 氮肥表观利用率 RE (%) 氮肥农学效率 AE (kg·kg-1)
TDN0 127.4±3.9c
TDN1 228.0±7.0a 23.1±1.6ab 33.5±7.8b
TDN2 182.1±4.4b 18.5±2.5b 37.0±8.3ab
TDN2+BD 213.2±9.5ab 28.3±2.5a 49.7±8.5ab
CDN0 121.1±6.3c
CDN1 209.7±5.8ab 19.6±3.3b 36.4±9.7ab
CDN2 191.6±8.1ab 22.2±4.6ab 43.3±7.1ab
CDN2+BD 212.9±10.1ab 28.9±3.7a 60.7±6.1a
), ArticleFig(id=1302192639609168211, tenantId=1146029695717560320, journalId=1301850032934322245, articleId=1302192629307957478, language=CN, label=表11, caption=

不同处理番茄植株总吸收氮量、氮肥表观利用率和氮肥农学效率

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处理 Treatment 总吸收氮量 Total N uptake (kg·hm-2) 氮肥表观利用率 RE (%) 氮肥农学效率 AE (kg·kg-1)
TDN0 127.4±3.9c
TDN1 228.0±7.0a 23.1±1.6ab 33.5±7.8b
TDN2 182.1±4.4b 18.5±2.5b 37.0±8.3ab
TDN2+BD 213.2±9.5ab 28.3±2.5a 49.7±8.5ab
CDN0 121.1±6.3c
CDN1 209.7±5.8ab 19.6±3.3b 36.4±9.7ab
CDN2 191.6±8.1ab 22.2±4.6ab 43.3±7.1ab
CDN2+BD 212.9±10.1ab 28.9±3.7a 60.7±6.1a
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减氮控水配施生物炭与硝化抑制剂对设施土壤-番茄体系氮素损失的影响
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李津津 1, 2 , 赵宇晴 1, 2 , 刘芮怡 1, 2 , 吉艳芝 1, 2, 3 , 谢建治 1, 2 , 郭艳杰 1, 2, 3 , 张丽娟 1, 2, 3
中国农业科学 | 土壤肥料·节水灌溉·农业生态环境 2026,59(16): 3621-3639
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中国农业科学 |土壤肥料·节水灌溉·农业生态环境 2026 , 59 (16) : 3621 -3639
减氮控水配施生物炭与硝化抑制剂对设施土壤-番茄体系氮素损失的影响
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2 河北省农田生态环境重点实验室, 河北保定 071001
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2 Key Laboratory for Farmland Eco-Environment of Hebei Province, Baoding 071001, Hebei
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2 河北省农田生态环境重点实验室, 河北保定 071001
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李津津1, 2 , 赵宇晴1, 2, 刘芮怡1, 2, 吉艳芝1, 2, 3, 谢建治1, 2, 郭艳杰1, 2, 3 , 张丽娟1, 2, 3
作者信息
  • 1 河北农业大学资源与环境科学学院, 河北保定 071001
  • 2 河北省农田生态环境重点实验室, 河北保定 071001
  • 3 河北省蔬菜产业协同创新中心, 河北保定 071001
通讯作者:
郭艳杰,E-mail:
张丽娟,E-mail:
作者简介:

李津津,E-mail:

Effects of Reduced Nitrogen and Controlled Water Combined with Biochar and Nitrification Inhibitor on Nitrogen Losses in a Facility Soil-Tomato System
JinJin LI1, 2 , YuQing ZHAO1, 2, RuiYi LIU1, 2, YanZhi JI1, 2, 3, JianZhi XIE1, 2, YanJie GUO1, 2, 3 , LiJuan ZHANG1, 2, 3
Affiliations
  • 1 College of Resources and Environmental Sciences, Hebei Agricultural University, Baoding 071001, Hebei
  • 2 Key Laboratory for Farmland Eco-Environment of Hebei Province, Baoding 071001, Hebei
  • 3 Collaborative Innovation Center for Vegetable Industry of Hebei, Baoding 071001, Hebei
出版时间: 2026-08-16 doi: 10.3864/j.issn.0578-1752.2026.16.011
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【目的】 揭示减氮控水条件下配施生物炭与硝化抑制剂双氰胺(DCD)对设施土壤-番茄体系氮素损失的调控效应,为设施蔬菜氮肥高效利用与绿色发展提供依据。【方法】 以设施番茄为研究对象,设置常规滴灌(TD)与控水滴灌(CD)2种灌水方式,在此基础上设不施氮(TDN0、CDN0)、常规施氮(TDN1、CDN1)、减氮(TDN2、CDN2)及减氮配施生物炭与DCD(TDN2+BD、CDN2+BD)共8个处理。采用田间小区试验法,系统监测追肥期内土壤N2O排放与NH3挥发、剖面NO3--N累积分布及番茄氮素吸收利用、产量与品质指标,定量评估生物炭与双氰胺在减氮控水条件下的协同调控效应。【结果】 施氮显著提高了土壤N2O排放和NH3挥发,且排放高峰主要出现在追肥后2—3 d。减氮措施可有效抑制气态氮损失,在此基础上配施生物炭与DCD进一步强化了N2O的减排效应。在NH3挥发方面,生物炭和DCD施用存在一定升高风险,但控水滴灌能够显著缓解这一不利效应。与常规施氮相比,减氮措施可显著降低气态氮总损失量45.7%—56.6%,土壤0—100 cm剖面硝态氮累积减少13.7%—16.2%。在此基础上配施生物炭与硝化抑制剂DCD,气态氮总损失量进一步降低至49.4%—59.0%,硝态氮累积降幅则扩大至27.4%—30.0%,并有效抑制其深层淋溶。2种灌水方式均能增强水氮协同减损效应,但控水滴灌整体优于常规滴灌。CDN2+BD处理的N2O排放和NH3挥发总损失量较CDN1降低30.0%,净损失率由3.3%降至2.5%;同时显著减少硝态氮深层累积,并提高20—40 cm土层NO3--N保持能力(增加27.1%)。此外,生物炭与DCD能将控水滴灌下的氮肥表观利用率提升至28.9%,TDN2+BD和CDN2+BD处理较对应的单一减氮处理(TDN2和CDN2)分别显著提高53.0%和30.2%(P<0.05)。控水滴灌配施生物炭与DCD处理(CDN2+BD)在获得最高产量(115.93 t·hm-2)的同时,还显著提升了果实维生素C(Vc)含量,并促进了可溶性蛋白、可溶性糖及可溶性固形物的积累。【结论】 减氮控水配施生物炭与硝化抑制剂双氰胺可显著协同抑制氮素气态损失与淋溶,改善土壤氮分布,提高氮肥利用效率和番茄品质,是设施蔬菜氮素减量增效的优选技术模式。

减氮控水  /  生物炭  /  硝化抑制剂  /  氮素损失调控  /  设施番茄

【Objective】 This study aimed to clarify the regulatory effects of the reduced nitrogen combined with controlled water, biochar, and the nitrification inhibitor dicyandiamide (DCD) on nitrogen losses within a facility soil-tomato system, so as to provide a scientific basis for efficient nitrogen use and sustainable green development in facility vegetable production.【Method】 A field plot experiment was conducted using facility tomato as the research object, with two irrigation treatments including traditional drip irrigation (TD) and reduced drip irrigation (CD). Based on this, eight nitrogen treatments were designed, including no nitrogen (TDN0, and CDN0), traditional nitrogen (TDN1, and CDN1), reduced nitrogen (TDN2, and CDN2), and reduced nitrogen combined with biochar and dicyandiamide (DCD) (TDN2+BD, and CDN2+BD). During the topdressing period, soil N2O emission and NH3 volatilization, NO3--N accumulation in the 0-100 cm soil profile, and tomato nitrogen uptake, yield, and fruit quality indicators were systematically monitored to quantitatively evaluate the synergistic regulatory effects of biochar and DCD under reduced nitrogen and controlled water conditions. 【Result】 Nitrogen application significantly increased soil N2O emissions and NH3 volatilization, with peak fluxes occurring 2-3 days after topdressing. Nitrogen reduction effectively suppressed gaseous nitrogen losses, and the combined application of biochar and the nitrification inhibitor DCD further enhanced the mitigation effect on N2O emissions. Although biochar and DCD posed a potential risk of increasing NH3 volatilization, this adverse effect was substantially alleviated by reduced nitrogen and controlled water conditions. Compared with conventional nitrogen application, nitrogen reduction significantly decreased total gaseous nitrogen losses by 45.7%-56.6% and reduced NO3--N accumulation in the 0-100 cm soil profile by 13.7%-16.2%. When biochar and DCD were applied on the basis of nitrogen reduction, total gaseous nitrogen losses further declined by 49.4%-59.0%, while the reduction in NO3--N accumulation expanded to 27.4%-30.0%, with a clear suppression of deep leaching. Both irrigation methods enhanced the synergistic mitigation effects of water nitrogen regulation. However, controlled drip irrigation demonstrated superior performance compared with conventional drip irrigation. Under controlled irrigation, the CDN2+BD treatment reduced total nitrogen losses by 30.0% compared with CDN1, with decreasing the net nitrogen loss rate from 3.3% to 2.5%. This treatment also significantly inhibited deep NO3--N accumulation and increased NO3--N retention in the 20-40 cm soil layer by 27.1%. In addition, biochar and DCD increased the apparent nitrogen use efficiency under controlled irrigation to 28.9%; TDN2+BD and CDN2+BD improved nitrogen use efficiency by 53.0% and 30.2%, respectively, compared with their corresponding nitrogen-reduction treatments (TDN2 and CDN2) (P<0.05). Furthermore, the controlled irrigation with biochar and DCD (CDN2+BD) achieved the highest tomato yield (115.93 t·hm-2), while significantly enhancing fruit vitamin C content and improving soluble protein, soluble sugar, and total soluble solid levels.【Conclusion】 Reduced nitrogen application combined with controlled water, biochar, and the nitrification inhibitor dicyandiamide (DCD) significantly decreased gaseous and leaching nitrogen losses, optimized soil nitrogen distribution, and improved nitrogen use efficiency and tomato quality, representing an optimal technical approach for nitrogen reduction and efficiency enhancement in facility vegetable production.

reduced nitrogen and controlled water  /  biochar  /  nitrification inhibitor  /  nitrogen losses regulation  /  facility tomato
李津津, 赵宇晴, 刘芮怡, 吉艳芝, 谢建治, 郭艳杰, 张丽娟. 减氮控水配施生物炭与硝化抑制剂对设施土壤-番茄体系氮素损失的影响. 中国农业科学, 2026 , 59 (16) : 3621 -3639 . DOI: 10.3864/j.issn.0578-1752.2026.16.011
JinJin LI, YuQing ZHAO, RuiYi LIU, YanZhi JI, JianZhi XIE, YanJie GUO, LiJuan ZHANG. Effects of Reduced Nitrogen and Controlled Water Combined with Biochar and Nitrification Inhibitor on Nitrogen Losses in a Facility Soil-Tomato System[J]. Scientia Agricultura Sinica, 2026 , 59 (16) : 3621 -3639 . DOI: 10.3864/j.issn.0578-1752.2026.16.011
研究意义设施蔬菜生产作为现代农业的重要组成部分,在保障蔬菜供应、提高农民收入等方面发挥着关键作用[1]。尽管随着人们对于设施蔬菜产地生态环境的重视,以及化肥减量政策的实施,但设施蔬菜生产中过分依赖施用化学氮肥的现象依然较为普遍。调查显示,津冀两地设施蔬菜氮肥投入量在366.0—2 457.0 kg·hm-2[2],超出推荐量的1.3—5.8倍[3];2022—2023年山东沂南地区典型设施茄果类蔬菜施氮量仍为668.1—1 110.4 kg·hm-2,是其需求量的1.47—2.68倍[4]。高量氮肥投入不仅未带来预期的产量提升,反而导致氮肥利用率低下,仅为9.5%—33.3%[5],显著低于发达国家40%—60%的水平[6-7]。此外,蔬菜是鲜品,需水量大,不合理的灌溉管理导致灌溉水利用效率低。北京郊区设施果菜每年沟灌或漫灌的水量为7 500—10 500 m3·hm-2[8],天津市设施黄瓜每季灌溉量高达7 700 m3·hm-2[9],远超作物需求和土壤持水能力[10]。由此,大量未被作物吸收利用的氮肥通过氨(NH3)挥发、硝化-反硝化、淋溶等途径损失,造成了严重的资源浪费和环境污染[11-13]。因此,控制氮素损失、提升氮肥利用效率已成为当前设施蔬菜绿色高质量发展的关键科学问题。【前人研究进展】为应对上述挑战,研究者们主要从“水氮管理优化”与“添加外源调控剂”两个方向寻求解决方案。在水氮管理优化方面,通过减少施氮量和优化灌溉制度,从源头降低氮素供应过剩,改善土壤通气与水分环境,调节硝化-反硝化过程,从而减少气态排放和淋失损失。有研究表明,设施蔬菜氮肥用量减少40%,氮素淋失可减少39.6%[14]。张琳等[15]田间试验发现,温室黄瓜种植中,将氮肥施用量减少24.4%—28.2%,同时灌水量减少30%,NH3挥发量降低了44.7%—45.0%,N2O排放量减少了79.1%—83.7%,且黄瓜产量并未显著下降。薄录吉等[16]的设施番茄试验表明,减氮控水可使土壤氮素总淋失量降低25.6%。由此可见,减氮控水是一种切实可行的减少设施蔬菜生产中氮素损失的管理措施。在外源调控剂应用方面,施用硝化抑制剂(nitrification inhibitors,NIs)、生物炭(biochar)被认为是提高氮素利用率,减少氮素损失,提升作物产量与品质的有效途径,有着十分广阔的应用前景。NIs能够选择性地抑制氨氧化细菌(AOB)和氨氧化古菌(AOA)的活性,减缓铵态氮(NH4+-N)的硝化速率,使更多的氮素以铵态氮形式存在于土壤中,从而减少NO3--N的产生和累积,降低氮素淋溶和反硝化损失风险[17]。有研究表明,施用双氰胺(dicyandiamide,DCD)可减少土壤硝态氮累积62.9%—69.4%,可减少30.4%的N2O排放[18]。但NIs的施用会因为铵态氮的长期存留而增加NH3挥发风险。Wu等[19]通过Meta分析发现,NIs使NH3挥发增加了35.7%,并使NH3排放(以及随后的氮沉积)产生的间接N2O排放增加了2.9%—15.2%。此外,NIs作为一种非离子化合物,硝化抑制效果在很大程度上取决于其与土壤中NH4+-N接触的有效量。例如DCD易溶于水,在土壤中移动性较强,尤其是强灌水条件下,极易随水向下迁移,导致其与NH4+-N在土壤中空间分离,从而削弱其硝化抑制效果[20-21]。生物炭是生物质材料在缺氧或限氧条件下热解产生的一种稳定性强、含碳量高的固态产物。生物炭在土壤中的周转率相对较低,可存留超过100年[22]。已有研究广泛证实,生物炭在减少氮素损失方面具有重要作用。生物炭的添加可以调节土壤pH,使土壤环境不利于NH3挥发,从而降低NH3挥发损失高达70%以上[23]。此外,生物炭较大的比表面积和丰富的孔隙结构,能够吸附土壤中的NH4+-N和NO3--N,减少氮素的淋溶损失[24]。更为重要的是,生物炭还能增强NIs对NH4+-N的吸附,缓解NIs与NH4+-N之间的空间分离,从而增强NIs的抑制效果,有效减少NO3--N的形成与淋失[25-26]。既有研究推测生物炭与NIs联合施用对于减少氮素损失可能产生显著的协同效应,但相关定量证据仍有限。【本研究的切入点】设施番茄是华北地区最主要的设施作物,其氮肥投入和灌溉过量问题长期突出,围绕该种植体系的减氮控水、生物炭和硝化抑制剂等调控措施均已被证实能够不同程度降低氮素损失、提高氮肥利用率,然而关于三者的综合氮素调控效应仍鲜有报道,特别是在减氮控水背景下生物炭与NIs联合施用是否具有协同增效作用尚不明确。【拟解决的关键问题】本研究以设施番茄种植体系为研究对象,开展减氮控水配施生物炭与硝化抑制剂对土壤N2O排放与NH3挥发、剖面NO3--N累积分布及番茄氮素吸收利用的调控效应研究,并结合番茄产量与品质,旨在筛选出既能减少氮素损失又能实现番茄增产提质的水氮调控技术方案,为设施蔬菜生产的绿色高质量发展提供理论依据和技术参考。
试验布置在河北省石家庄市正定县塔元庄同福生态庄园区设施蔬菜生产基地的某一温室大棚(N38°9′39″,E114°32′15″)(棚龄10年,前茬作物为番茄)内。该地区属北温带半干旱、半湿润季风气候区,大陆性季风气候特征明显,四季气候特征差异显著。土壤养分条件优越,在全国范围内属中等水平,在河北省内位居上等水平,为作物生长提供了良好基础,非常适合蔬菜生长。试验地土壤基本理化性质见表1
供试蔬菜为番茄(Solanum lycopersicum L.),品种为普罗旺斯;供试氮肥为普通尿素(N,46%),磷钾肥分别为磷酸二氢钾(P2O5,52%;K2O,34%)和硫酸钾(K2O,52%);供试硝化抑制剂为双氰胺(N 66.7%,分析纯);供试生物炭为商品木炭,煅烧温度400—600 ℃,外表呈小块状和层状结构,圆形孔隙,基本理化性质为pH 10.0,有机碳125.4 g·kg-1,全氮1.8 g·kg-1,全磷1.5 g·kg-1,全钾4.6 g·kg-1,比表面积680 m2·g-1,总酸基0.5。
试验设2个灌水量水平,分别为农民常规滴灌和控水滴灌;每个灌水量水平下均设置4个氮素调控处理,分别为不施氮、农民常规施氮、推荐施氮(常规施氮基础上减30%)、推荐施氮+生物炭+硝化抑制剂,共8个处理:常规滴灌+不施氮(TDN0);常规滴灌+常规施氮(TDN1);常规滴灌+推荐施氮(TDN2);常规滴灌+推荐施氮+生物炭+硝化抑制剂(TDN2+BD);控水滴灌+不施氮(CDN0);控水滴灌+常规施氮(CDN1);控水滴灌+推荐施氮(CDN2);控水滴灌+推荐施氮+生物炭+硝化抑制剂(CDN2+BD)。随机区组设计,每处理3次重复,共24个小区,小区面积1.4 m×13 m。番茄采用传统垄栽法种植,株行距0.4 m×0.6 m,种植密度4.6万株/hm2。常规滴灌为农民习惯的滴灌水量,番茄整个生育期内灌水总量约为4 500 m3·hm-2,控水滴灌水量在常规滴灌基础上减量25%(3 375 m3·hm-2),整个生育期共灌水7次,其中3次随追施肥料及DCD灌溉,其余4次根据番茄生长发育情况而定,各处理详细灌水时间和灌水量见表2。各处理氮肥均以基肥和3次追肥形式施入,基肥为腐熟羊粪(N,1.26%),追肥为尿素氮肥,各处理氮肥基施46%,追施54%,施用方式、用量及施用时间详见表2;所有处理磷钾肥施用方式、用量及施用时间相同,磷肥总用量为134 kg·hm-2,钾肥总用量为172 kg·hm-2,追施时间和用量详见表2。DCD用量为纯氮量15%,生物炭用量为15 t·hm-2,均为课题组前期研究筛选的适宜用量。
试验开始前按照试验设计施入基肥,生物炭与有机肥基施后翻耕,一周后番茄定植(2022年10月12日)。定植后,供试化肥、DCD全部以追肥形式施入。每次追肥时,肥料与DCD随水滴灌,其中除施肥、灌溉外其他田间管理措施与当地常规管理方式一致,试验于2023年6月20日番茄全部收获后结束。
番茄收获后,统计各小区累计产量,并折合为单位面积产量(kg·hm-2);同时采集各小区长势均匀的完整植株3株,按照根、茎、叶、果实部分,在105 ℃下杀青30 min,65 ℃烘干至恒重。烘干粉碎后植物样品全氮含量采用浓H2SO4-H2O2消化-凯氏定氮法测定。盛果期取大小近似的商品果实,每小区3次重复,用于测定其营养品质。硝酸盐含量采用紫外分光光度法,维生素C(Vc)含量采用钼蓝比色法、可溶性糖含量采用蒽酮比色法,可溶性蛋白含量采用考马斯亮蓝G-250染色法,可滴定酸含量采用酸碱滴定法,可溶性固形物含量采用手持式折光仪测定[27]
采用静态箱-气相色谱法[28]测定。密闭式静态箱体由PVC材料制成,分为上部箱体和底座两部分。上部箱体为圆柱体(高15.5 cm、直径13.5 cm),箱体顶部设置一个气体取样口,内部装有风扇,底部开口可罩在底座上;底座是一个四周有水槽的圆柱体,测定N2O排放之前将底座插入土中至2.5 cm。每次施肥灌水后的第1、2、3、5、7、9天上午的 9:00—11:00采集气体样品。将已插入土中的底座水封槽内注满水,然后罩上密闭箱体,形成一个密闭性气体的空间,其后将箱体内风扇打开,使箱体内气体混合均匀后,从箱体顶端的气体取样口用50 mL注射器分别于0、15、30 min间隔采集气体样品,每次采集30 mL。采气时同步记录箱内温度。单独灌水后连续3 d采集,1次/天。按季节变化每隔10 d或1个月进行动态采气。采集到的N2O气体样品采用气相色谱仪(Agilent 7890A,美国)测定其浓度。土壤N2O排放通量计算公式为:
$ F=\frac{\rho \times \frac{V}{A} \times \frac{d c}{d \iota} \times 273}{273+T} \times 60 $
式中,F为N2O排放通量(μg·m-2·h-1);ρ为标准状态下N2O的密度(1.25 kg·m-3);A为箱内土面面积(m2);V为密闭箱内气体的有效体积(m3);T为采气时密闭箱内平均温度(℃);dc/dt为密闭箱内N2O浓度在单位时间的变化量(μL·L-1·min-1)。
通过内插法来计算未测定日的排放通量,之后将测定值和计算值逐日累加从而得出气体排放累积量。
采用海绵通气法[28]测定。NH3挥发采集装置由上下开口的聚氯乙烯硬质塑料管(PVC管)制成,高14 cm,内径15 cm。测定时,先将PVC管插入土壤中约3 cm,将2块吸收了15 mL磷酸甘油溶液(40 mL丙三醇+50 mL磷酸,定容至1 000 mL)的海绵块(直径16 cm、厚度2 cm)置于PVC管中,2个海绵块之间间距2 cm,下层海绵距土面5 cm。每次施肥灌水后,安装NH3采集装置吸收24 h后更换新海绵块,连续10 d取样。取出采集后的海绵用300 mL的KCl溶液(1 mol·L-1)浸提,振荡过滤后,采用连续流动分析仪(Skarar SAN++,荷兰)测定滤液NH4+-N含量。土壤NH3挥发速率计算公式为:
FNH3-N=M/(A×D)
式中,FNH3-N为NH3挥发速率(mg·m-2·d-1);M为采用通气法单个装置平均每次测得的氨量(NH3-N,mg);D为每次连续捕获的时间(d);A为捕获装置的横截面积(m2)。
番茄收获后各小区分别采集0—100 cm剖面(每20 cm为一层)土壤,鲜土过5 mm筛后,采用KCl溶液(1.0 mol·L-1)浸提,振荡离心后,上清液经定量滤纸过滤,用连续流动分析仪(Skarar SAN++,荷兰)测定滤液中的NH4+-N和NO3--N。
(1)N2O净损失率(%)=(施氮处理N2O累积排放量-不施氮处理N2O累积排放量)/施氮量×100[15]
(2)NH3净损失率(%)=(施氮处理NH3累积挥发量-不施氮处理NH3累积挥发量)/施氮量×100[15]
(3)植株各器官吸氮量(kg·hm-2)=植株各器官生物量(kg·hm-2)×植株各器官含氮量(mg·kg-1)/106[29]
(4)土壤无机氮累积量(kg·hm-2)=土层厚度(cm)×土壤容重(g·cm-3)×土壤NO3--N(NH4+-N)含量(mg·kg-1)/10[30]
(5)氮肥表观利用率(RE,%)=(施氮区作物总吸氮量-不施氮区作物总吸氮量)/施氮量×100[6]
(6)氮肥农学效率(AE,kg·kg-1)=[施氮区作物产量(kg·hm-2)-不施氮区作物产量(kg·hm-2)]/施氮量(kg·hm-2[6]
文中所列数据均为3次重复的平均值±标准差。采用Microsoft Excel 2010进行数据处理与作图,SPSS 22.0软件进行数据统计分析,不同处理间差异采用单因素(One-way)方差分析,选用LSD(P<0.05)进行显著性检验;通过双因素(Two-way)方差分析法分析灌水、氮素调控及其二者交互作用对土壤N2O排放通量、NH3挥发速率、土壤硝态氮累积以及番茄产量和品质指标影响的显著性。
追肥期间,各处理土壤N2O排放通量动态变化如图1所示。对照处理(TDN0和CDN0)土壤N2O平均排放通量始终处于较低水平,施氮处理排放通量均在追肥后迅速升高,于2—3 d达到峰值后逐渐下降。常规滴灌下,TDN1处理土壤N2O排放通量范围为1.9—307.3 μg·m-2·h-1,均值为95.1 μg·m-2·h-1;TDN2和TDN2+BD处理均值分别为82.1和70.6 μg·m-2·h-1,较TDN1显著降低13.7%和25.8%(P<0.05)。控水滴灌下,CDN1、CDN2和CDN2+BD处理土壤N2O平均排放通量均值分别为84.2、71.8和55.7 μg·m-2·h-1,CDN2和CDN2+BD较CDN1处理分别显著降低14.7%和33.8%(P<0.05)。等氮条件下,在减氮控水基础上配施生物炭与DCD处理(TDN2+BD、CDN2+BD)的土壤N2O平均排放通量较相应单一减氮控水处理(TDN2和CDN2)分别显著降低14.0%和22.4%(P<0.05)。相同氮素调控水平下,控水滴灌处理土壤N2O平均排放通量普遍低于常规滴灌,其中CDN1和CDN2+BD 较TDN1和TDN2+BD分别降低11.5%和21.1%(P<0.05)。由表3可知,水氮调控处理、监测时间以及二者交互作用对设施蔬菜土壤N2O排放通量有极显著影响(P<0.01)。此外,灌水方式和氮素调控均对N2O排放通量产生极显著影响(P<0.01),但二者无交互作用(表4)。综上,常规滴灌条件下,减氮及其配施生物炭与硝化抑制剂均可有效降低N2O排放,而在控水滴灌条件下,减排效应进一步增强。
各处理土壤NH3挥发速率动态变化如图2所示。总体上,对照处理TDN0和CDN0的土壤NH3挥发速率始终保持最低且变幅较小(P>0.05),均值分别为6.4和5.9 mg·m-2·d-1。施氮处理均在追肥后第3天出现挥发峰值。在追肥期内还出现2次小幅波动,可能与温度或灌溉等条件变化有关。常规滴灌下,TDN1处理土壤NH3挥发速率均值为22.7 mg·m-2·d-1,TDN2和TDN2+BD处理均值较TDN1显著降低21.0%和9.8%。控水滴灌下,CDN2和CDN2+BD处理土壤NH3挥发速率均值分别为16.5和17.4 mg·m-2·d-1,较CDN1(20.9 mg·m-2·d-1)分别显著降低21.2%和16.7%。等氮条件下,TDN2+BD处理土壤NH3挥发平均速率较TDN2显著升高12.4%,而CDN2+BD较CDN2处理虽略有升高,但差异不显著(P>0.05)。相同氮素调控水平下,CDN1、CDN2和CDN2+BD的NH3平均挥发速率较常规滴灌的TDN1、TDN2和TDN2+BD分别降低7.7%、8.0%和14.8%(P<0.05)。方差分析显示,不同水氮调控处理、监测时间以及二者交互作用均显著影响NH3挥发(表5);灌水方式、氮素调控及其交互作用均显著影响土壤NH3挥发(表6)(P<0.05)。综上,常规滴灌条件下,减氮可有效降低NH3挥发,进一步控制灌水量可增强减排效果。但在等氮条件下,生物炭与硝化抑制剂配施存在增加NH3挥发的潜在风险。
表7可知,常规滴灌下,TDN1处理土壤N2O和NH3累积排放量最高,分别为2.2和18.4 kg·hm-2,总损失量达20.6 kg·hm-2,净损失率为6.5%。TDN2和TDN2+BD处理显著降低气态氮排放,其中TDN2处理N2O和NH3累积排放较TDN1分别下降40.4%和46.3%,总损失量减少45.7%,净损失率降至3.8%。TDN2+BD处理N2O和NH3累积排放分别较TDN1显著降低56.1%和48.6%,总损失量下降49.4%,净损失率降至3.3%。控水滴灌条件下,CDN1处理N2O和NH3累积排放量分别为1.0和11.1 kg·hm-2,总损失量12.1 kg·hm-2,净损失率3.3%。CDN2处理N2O排放、NH3挥发和气态总损失量较CDN1分别下降18.3%、26.7%和26.0%,净损失率降至2.8%;CDN2+BD处理N2O排放和NH3挥发较CDN1分别下降47.6%和28.5%,总损失量减少30.0%,净损失率降至2.5%。等氮条件下,TDN2+BD、CDN2+BD处理N2O排放分别较TDN2、CDN2显著降低26.2%、36.3%(P<0.05),但均对NH3挥发和总损失量影响不大。同一氮素调控水平下,控水滴灌处理的减排效果普遍优于常规滴灌。CDN1、CDN2和CDN2+BD总损失量分别较TDN1、TDN2和TDN2+BD显著下降41.4%、20.1%和18.9%(P<0.05)。总体来看,常规施氮显著促进了N2O与NH3损失,而减氮及其配施生物炭和硝化抑制剂显著抑制气态氮损失,其中CDN2+BD表现最优,在提高氮素利用效率和减排方面具有协同优势。
本研究分析了番茄收获后0—100 cm土壤剖面NO3--N的累积分布特征(图3)。与对照处理TDN0和CDN0相比,施氮各处理各土层的NO3--N累积量均较低,总累积量分别为347.6和318.9 kg·hm-2。2种灌水条件下,常规施氮TDN1和CDN1处理各土层NO3--N含量由于氮素的施入显著升高,总累积量分别为770.6和715.8 kg·hm-2。减氮处理显著降低了剖面NO3--N累积量。常规滴灌下,TDN2较TDN1各土层降低4.7%—25.0%,累积总量下降13.7%(P<0.05),TDN2+BD较TDN1处理各土层降低16.4%—37.6%,累积总量显著下降27.4%(P<0.05);控水滴灌下,CDN2较CDN1各层降低1.9%—46.4%,累积总量下降16.2%(P<0.05),CDN2+BD较CDN1各土层降低10.7%—49.7%,累积总量显著下降30.0%(P<0.05)。等氮条件下,TDN2+BD相较TDN2在各层减少0.5%—25.5%,累积总量显著下降15.9%(P<0.05);控水滴灌下,CDN2+BD处理0—20 cm表层土壤硝态氮含量较CDN2显著增加32.5%(P<0.05),其余土层则降低0.03%—48.8%,总量下降16.5%(P<0.05)。灌溉方式亦显著影响土壤NO3--N累积分布。相同氮素调控水平下,控水滴灌处理CDN1和CDN2在0—20和80—100 cm土层土壤NO3--N累积量显著低于常规滴灌下对应处理TDN1和TDN2;CDN2+BD与TDN2+BD在除60—80 cm外的各土层均表现为常规滴灌显著高于控水滴灌(P<0.05)。总体而言,控水滴灌不仅有效抑制了深层NO3--N累积,还显著增强了20—40 cm土层的养分保持能力,CDN2+BD较TDN2+BD提高27.1%(P<0.05)。进一步方差分析结果表明(表8),氮素调控对各土层NO3--N累积影响显著;灌水主要影响0—20、40—60和60—80 cm土层;二者交互作用则显著作用于0—20和60—80 cm土层。
不同处理对番茄产量与品质的影响结果如图4所示。在产量方面,2种灌水条件下,施氮处理番茄产量在109.9—112.9 t·hm-2(常规滴灌)和95.6—115.9 t·hm-2(控水滴灌),均显著高于不施氮对照处理,但各施氮处理间差异不显著(P>0.05)。在果实品质方面,减氮控水基础上配施生物炭和DCD能显著提升番茄果实Vc含量。常规滴灌下,TDN2和TDN2+BD处理较TDN1处理分别提高Vc含量4.7%和40.0%,其中TDN2+BD处理提升效果达显著水平,且较TDN2处理提高了33.8%。控水滴灌下,CDN2和CDN2+BD较CDN1分别提高Vc含量6.5%和65.9%,同样CDN2+BD处理的提升达显著水平,且较CDN2处理提高了55.8%(P<0.05)。2种灌水条件下,减氮及减氮基础上配施生物炭和DCD对番茄果实蛋白质含量影响不大,但在一定程度上促进了可溶性糖和可溶性固形物含量的增加(P>0.05)。相同氮素调控下,常规滴灌与控水滴灌的番茄产量和品质指标差异不显著(P>0.05)。表9方差分析结果表明,氮素调控措施对番茄产量、Vc和可溶性蛋白含量均具有显著影响,而灌水方式对这些指标的影响不显著。综合产量和品质指标来看,减氮配施生物炭与DCD的处理在保持番茄产量的同时,能够显著改善果实品质,特别是在提高Vc含量方面效果显著,其中以控水滴灌条件下的CDN2+BD处理表现最佳。
番茄植株各器官氮素累积量如图5所示。2种灌水条件下,番茄植株氮素主要分布于果实和叶片,其次为茎和根。可以看出,与对照相比,施氮促进了番茄根部和茎的氮素吸收,但施氮各处理间差异不显著(P>0.05)。施氮显著提高了番茄叶片和果实氮素吸收量(P<0.05),但与常规施氮(TDN1、CDN1)相比,减氮处理(TDN2、CDN2)及其配施生物炭和硝化抑制剂(TDN2+BD、CDN2+BD)均降低了叶片氮素吸收量,其中TDN2处理较TDN1显著降低了20.0%,CDN2较CDN1显著降低23.6%(P<0.05)。等氮条件下,生物炭与硝化抑制剂配施对叶和果实氮素吸收虽有一定促进作用,但差异不显著(P>0.05)。表10方差分析表明,氮素调控显著影响番茄根、茎、叶及果实氮素累积量(P<0.01或P<0.05),而灌水方式及其与氮素调控的交互作用对各器官氮素累积量的影响均未达到显著水平(P>0.05),表明氮素管理是影响番茄植株氮素吸收与分配的主导因素。
表11可知,常规滴灌下,TDN1处理总吸氮量为228.0 kg·hm-2,氮肥表观利用率为23.1%;TDN2处理总吸氮量和氮肥表观利用率分别为182.1 kg·hm-2和18.5%;TDN2+BD处理总吸氮量为213.2 kg·hm-2,氮肥表观利用率为28.3%,较TDN2显著提高53.0%(P<0.05)。控水滴灌下,CDN1、CDN2和CDN2+BD处理总吸氮量分别为209.7、191.6和212.9 kg·hm-2,氮肥表观利用率分别为19.6%、22.2%和28.9%,CDN2+BD的氮肥表观利用率较CDN2处理提高30.2%(P>0.05)。氮肥农学效率在减氮配施处理中呈增加趋势,其中CDN2+BD处理最高(60.7 kg·kg-1)。
本研究结果表明,相较常规施氮滴灌,减氮控水滴灌可显著降低追肥后土壤N2O排放峰值,并缩短高排放持续时间,从而显著降低追肥期N2O损失(图1)。与常规水氮处理(TDN1)相比,单一减氮处理(TDN2)使N2O累积排放量降低40.4%,NH3累积挥发量降低46.3%,气态氮总损失量减少。当减氮与控水措施结合(CDN2),减排效果进一步增强,N2O和NH3总损失量较TDN1处理降低26.0%(表7)。这一结果与全球范围的meta分析结果相一致,即氮肥施用量与N2O排放呈非线性指数关系,施氮强度一旦超出作物需氮区间,单位增施带来的排放增量将显著放大,因此从源头实施“减氮”具备更高的边际减排效益[31]。同时,控水措施通过降低土壤水分含量,有效抑制了反硝化过程,这与Kuang等[32]关于滴灌减排效应的研究结果一致。在此基础上,配合施用生物炭与硝化抑制剂DCD(CDN2+BD)又能进一步强化减排效果。本研究发现,常规滴灌下,减氮配施生物炭与DCD的处理(TDN2+BD)相较于单一减氮处理(TDN2)土壤N2O排放通量降低14.0%,N2O累积排放量降低26.2%;控水滴灌下,CDN2+BD相较于单一减氮处理(CDN2)土壤N2O排放通量降低22.4%,N2O累积排放量降低36.3%(图1表7)。这一协同效应源于DCD对氨氧化细菌的特异性抑制[33-34],延缓了NH4+向NO3-的转化。而生物炭则通过其巨大的比表面积和丰富孔隙结构吸附氮素,调节土壤微环境[35-36]。二者联用形成了“抑制剂延缓转化、生物炭吸附固定”的协同机制,这与Deng等[37]和Chen等[38]在其他生态系统的研究结论相吻合。在稻田、旱地与设施体系中均观察到“生物炭+硝化抑制剂”较单施抑制剂进一步降低N2O的累积排放[39]。同时,在亏缺/滴灌背景下,生物炭与水分调控存在可叠加的“削峰”效应,进一步缩短>60% WFPS的暴露时间,从而放大季节减排幅度[40]
NH3挥发受土壤pH、温湿度和铵态氮浓度共同控制[41]。本研究发现,“减氮+控水滴灌”通过削减NH4+-N供给并缩短其在表层的停留时间,显著降低NH3挥发峰值与季节累积[42-43]。CDN2的NH3挥发平均速率较CDN1处理显著降低21.2%(图2)。在此基础上配施生物炭与硝化抑制剂,由于硝化抑制剂延缓硝化,维持NH4+形态,灌水后表层尿素水解导致pH短时上升,从而存在NH3挥发升高的潜在风险。本研究中,常规滴灌下,TDN2+BD处理的NH3挥发速率较TDN2显著增加12.4%,但在控水滴灌下,CDN2+BD与CDN2处理间差异不显著。说明控水措施有效缓解了配施带来的挥发风险。生物炭一方面因其较大比表面积以阳离子交换与微孔吸附固定NH4+、缓冲界面pH,降低NH3挥发[44-45];另一方面因自身或土壤呈碱性则可能提高NH3/NH4+比,表现出环境依赖的“双刃剑”效应[46-47]。本研究中,减氮控水条件下配施生物炭和DCD(CDN2+BD)NH3挥发得到了有效控制,说明在适宜水分条件下,生物炭的积极作用占主导地位。
减氮措施从源头减少了NO3⁻-N的输入总量,是降低其剖面累积的基础。本研究中,TDN2的剖面NO3--N总累积量较TDN1处理降低了13.7%,CDN2较CDN1处理显著降低16.2%(图3)。这一结果与Min等[14]的研究结论一致,表明通过减少氮肥用量可直接降低土壤中可迁移氮素总量。Zotarelli等[48]在番茄滴灌系统中的研究也证实,合理减氮能有效降低硝态氮淋失风险。生物炭与DCD的协同阻控效应进一步强化了减氮措施的效果。本研究中(图3),2种灌水条件下,与常规施氮相比,减氮及其配施生物炭和DCD处理显著降低了0—100 cm土壤剖面中NO3--N总累积量,TDN2+BD和CDN2+BD处理土壤剖面NO3--N总累积量较TDN1和CDN1分别显著下降27.4%和30.0%,在80—100 cm土层NO3--N的累积量最低。等氮条件下,TDN2+BD处理的剖面NO3--N总累积量较TDN2处理进一步降低(降低15.9%),特别是在20—60 cm土层达到显著水平。这一现象可通过二者的协同机制解释:DCD通过抑制氨氧化细菌活性,减缓NH4+-N向NO3--N的转化[49];而生物炭通过其巨大的比表面积和孔隙结构,增强了对氮素的吸附固持能力[50-51]。Li等[52]的研究也证实了这种协同效应,发现生物炭与硝化抑制剂配施可使土壤硝态氮含量降低25%—35%。
控水措施通过优化土壤水分在剖面中的分布,在降低硝态氮淋溶风险方面发挥关键作用。本研究结果显示,CDN2+BD处理在有效抑制80—100 cm土层NO3--N累积的同时,还显著提高了20—40 cm根层的氮素保持能力,较TDN2+BD处理提高27.1%(图3)。这一分布特征符合Cristóbal-Muñoz等[53]描述的滴灌水分运移规律,表明通过水分调控可以优化氮素在根层的分布,既保证作物养分需求,又降低深层淋溶风险。然而,在集约化高氮投入的设施蔬菜体系中,深层NO3--N积累与高淋失风险广为报道[54]。本研究结果表明,常规施氮在2种灌水条件下均显著抬升20—40 cm土层NO3--N峰值,并加大其在深层(≥60 cm)的累积,符合滴灌条件下“施灌同步”使溶质沿湿润锋下移,在根层下缘形成峰值带的典型模式[53]。相同灌水条件下,减氮显著降低了各土层与剖面NO3--N总量,表明源头削减直接缩小了可迁移NO3--N库。综合可知,“减氮控水配施生物炭与硝化抑制剂”处理在优化氮素垂向分布、降低环境风险方面具有显著协同效应。这可能是由于生物炭的吸附作用与微孔结构可延缓NO3-在土壤中的迁移速度[54-55],促使其更多停留于根系活跃层,而DCD的缓释效应使NH4+长期保留于表层,进一步减少硝态氮累积与淋失[55],再结合减氮控水,三者共同作用有效减少了氮素淋溶对地下水的污染风险。
本研究中,减氮配施生物炭与DCD能显著提高氮肥利用效率,其中TDN2+BD和CDN2+BD处理的氮肥表观利用率较相应减氮处理(TDN2,CDN2)分别显著提高52.9%和30.2%。在产量方面,各施氮处理间无显著差异,但减氮配施处理在保持产量稳定的同时,显著改善了果实品质(图5)。氮素吸收与利用的提升机制主要体现在两个方面。一方面,生物炭通过改善土壤结构,促进根系发育,本研究中TDN2+BD和CDN2+BD处理的根系氮素吸收量显著提高。另一方面,DCD通过延缓氮素转化,使养分供应更符合作物需求规律。这主要是生物炭通过改善土壤结构与保水性,促进根系生长和氮吸收[56];硝化抑制剂则减缓氮素转化,延长NH4+有效期,使作物吸氮与供氮更同步[35],使TDN2+BD处理的氮肥表观利用率达到28.3%,显著高于TDN2处理。
在产量与品质上,减氮控水及其配施生物炭与硝化抑制剂未致番茄减产,且等氮条件下产量有小幅上扬。在保证产量的同时,减氮及其配施生物炭和硝化抑制剂处理显著提高番茄果实Vc含量,并改善可溶性糖、固形物等品质指标,尤其是控水滴灌下减氮配施生物炭和硝化抑制剂提升最显著(较单一减氮提升65.9%)。这可能是由于控水强化了生物炭和硝化抑制剂对Vc合成的促进作用,如改善了氮素供应稳定性,减少了Vc降解[57-58]。由此可见,适度减氮并结合生物炭与硝化抑制剂可在不显著降低产量的情况下显著提高氮肥利用效率与果实品质,是实现设施番茄“提效稳产优质”的有效途径。水氮协同的品质调控作用值得特别关注。控水条件下配施处理(CDN2+BD)在Vc含量、可溶性糖含量等品质指标上的提升效果均优于常规灌水配施处理(TDN2+BD)。这可能是因为适度水分调控与优化的氮素供应共同促进了果实品质形成。Abdelghany等[56]的研究也表明,水分调控结合生物炭施用能显著改善番茄果实品质。本研究结果进一步证实了水氮协同对品质提升的积极作用。
综上所述,本研究中生物炭和硝化抑制剂在减少土壤活性氮损失、调控硝态氮累积以及提升番茄产量与品质方面具有显著协同作用,且与前人研究结果在趋势上基本相符,但在具体影响程度和机制上存在一定差异,这可能与生物炭自身性质、土壤类型、灌溉条件以及作物种类等多种因素有关,后续研究可进一步针对这些因素展开深入探讨。
常规与控水2种滴灌条件下,减氮及其配施生物炭和硝化抑制剂能有效降低设施土壤-番茄体系氮素损失。与常规施氮相比,减氮显著降低了N2O排放、NH3挥发及土壤0—100 cm剖面硝态氮累积,气态氮总损失量减少26.0%—45.7%,硝态氮累积量降低13.7%—16.2%,番茄产量保持稳定。进一步配施生物炭和硝化抑制剂后减排效果增强,在等氮条件下降低N₂O排放26.2%—36.3%,显著减少硝态氮下移,氮肥利用率提高30.2%—53.0%,且果实番茄Vc含量提高33.8%—55.8%。控水滴灌整体优于常规滴灌,有效减少了氮素气态损失,抑制了氮素的深层淋溶风险,并改善20—40 cm土层的养分保持能力。
总之,采用水肥一体化技术控水滴灌(3 375 m3·hm-2)结合“减氮30%(317 kg·hm-2)+生物炭(基施15 t·hm-2)+DCD(纯氮量15%)”的水氮调控方案可在保持番茄产量的前提下,最大程度降低气态氮的排放与硝态氮累积,并显著提高氮肥利用效率和果实品质,可作为华北地区设施番茄绿色生产的可行技术方案。
  • 河北省现代农业产业技术体系蔬菜产业创新团队项目(HBCT2018030206)
  • 河北省重点研发计划项目(21326905D)
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2026年第59卷第16期
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doi: 10.3864/j.issn.0578-1752.2026.16.011
  • 接收时间:2025-10-25
  • 首发时间:2026-09-03
  • 出版时间:2026-08-16
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  • 收稿日期:2025-10-25
  • 录用日期:2025-12-19
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河北省现代农业产业技术体系蔬菜产业创新团队项目(HBCT2018030206)
河北省重点研发计划项目(21326905D)
作者信息
    1 河北农业大学资源与环境科学学院, 河北保定 071001
    2 河北省农田生态环境重点实验室, 河北保定 071001
    3 河北省蔬菜产业协同创新中心, 河北保定 071001

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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