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Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada

文献类型:期刊论文

作者Xie, H. T.2; Yang, X. M.1; Drury, C. F.1; Yang, J. Y.1; Zhang, X. D.2
刊名CANADIAN JOURNAL OF SOIL SCIENCE
出版日期2011-02-01
卷号91期号:1页码:53-63
ISSN号0008-4271
关键词Soil Organic Carbon Soil Total Nitrogen Mid-infrared Spectroscopy Near-infrared Spectroscopy Partial Least Squares Regression
DOI10.4141/CJSS10029
英文摘要Xie, H. T., Yang, X. M., Drury, C. F., Yang, J. Y. and Zhang, X. D. 2011. Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada. Can. J. Soil Sci. 91: 53-63. Mid-infrared (MIR) and near-infrared (NIR) spectroscopy of soils have been tested to estimate soil organic carbon (SOC) and total N (TN) concentrations at local, regional and national scales. However, these methods have rarely been used to assess SOC and TN concentrations of the same soil under different management practices. The objective of this study was to determine if models developed from infrared spectra of Brookston clay loam soils under different management practices could be used to estimate SOC, and TN concentrations and the C:N ratio. Soils used for model calibration included 217 samples from a long-term fertilization and crop rotation study and a long-term compost study, whereas 78 soil samples from a long-term tillage study on the same soil type were used for model validation. Soil organic carbon and TN concentrations of all samples were also analyzed using dry combustion techniques. Soil samples were scanned from 4000 to 400 cm(-1) (2500-25 000 nm) for MIR spectra and from 8000 to 4000 cm(-1) (1250-2500 nm) for NI R spectra. Partial least squares regression (PLSR) analysis was used for the calibration dataset to build prediction models for SOC:, TN and C:N ratio. The SOC and TN concentrations determined using dry combustion techniques were compared with the prediction from the models using the calibration datasets. The predictions of SOC and TN concentrations by the PLSR method using infrared spectra were statistically sound, with high coefficient of determination with the calibration dataset (R(cal)(2), SOC(MIR)=0.99 and SOC(NIR)=0.97, TN(MIR)=0.98 and TN(NIR)=0.97) and the validation dataset (R(val)(2), SOC(MIR)=0.96 and SOC(NIR)=0.95, TN(MIR)=0.96 and TN(NIR)=0.95) and low root mean square error (RMSEP(cal), SOC(MIR)=0.93 and SOC(NIR)=1.60, TN(MIR)=0.08 and TN(NIR)=0.12; RMSEP(val) SOC(MIR)=1.40 and SOC(NIR)=1.75, TN(MIR)=0.11 and TN(NIR)=0.12). The predictions of SOC and TN concentrations in the 5 to 30 cm depth were better than the predictions for either the surface (0 to 5 cm) soils or for soils from lower depths (> 30 cm). The models could be used as an alternative method for determining SOC and TN concentrations of Brookston clay loam soils; however, larger sample populations and improved model algorithms could further improve predictions.
WOS研究方向Agriculture
语种英语
出版者AGRICULTURAL INST CANADA
WOS记录号WOS:000288567400005
源URL[http://210.72.129.5/handle/321005/121839]  
专题中国科学院沈阳应用生态研究所
通讯作者Yang, X. M.
作者单位1.Agr & Agri Food Canada, Greenhouse & Proc Crops Res Ctr, Harrow, ON N0R 1G0, Canada
2.Chinese Acad Sci, Key Lab Terr Ecol Proc, Inst Appl Ecol, Shenyang 110016, Peoples R China
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Xie, H. T.,Yang, X. M.,Drury, C. F.,et al. Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada[J]. CANADIAN JOURNAL OF SOIL SCIENCE,2011,91(1):53-63.
APA Xie, H. T.,Yang, X. M.,Drury, C. F.,Yang, J. Y.,&Zhang, X. D..(2011).Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada.CANADIAN JOURNAL OF SOIL SCIENCE,91(1),53-63.
MLA Xie, H. T.,et al."Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada".CANADIAN JOURNAL OF SOIL SCIENCE 91.1(2011):53-63.

入库方式: OAI收割

来源:沈阳应用生态研究所

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