标题：Comparison of multivariate methods for estimating soil total nitrogen with visible/near-infrared spectroscopy作者：Shi, Tiezhu; Cui, Lijuan; Wang, Junjie; Fei, Teng; Chen, Yiyun; Wu,Guofeng

来源出版物：PLANT AND SOIL卷：366期：1-2页：363-375 DOI：10.1007/s11104-012-1436-8 出版年：MAY 2013

摘要：This study aimed to compare stepwise multiple linear regression (SMLR), partial least squares regression (PLSR) and support vector machine regression (SVMR) for estimating soil total nitrogen (TN) contents with laboratory visible/near-infrared reflectance (Vis/NIR) of selected coarse and heterogeneous soils. Moreover, the effects of the first (1st) vs. second (2nd) derivative of spectral reflectance and the importance wavelengths were explored.

The TN contents and the Vis/NIR were measured in the laboratory. Several methods were employed for Vis/NIR data pre-processing. The SMLR, PLSR and SVMR models were calibrated and validated using independent datasets.

Results showed that the SVMR and the PLSR models had similar performances, and better performances than the SMLR. The spectral bands near 1450, 1850, 2250, 2330 and 2430 nm in the PLSR model were important wavelengths. In addition, the 1st derivative was more appropriate than the 2nd derivative for spectral data pre-processing.

PLSR was the most suitable method for estimating TN contents in this study. SVMR may be a promising technique, and its potential needs to be further explored. Moreover, the future studies using outdoor and airborne/satellite hyperspectral data for estimating TN content are necessary for testing the findings.

入藏号：WOS:000317988600026

文献类型：Article

语种：English

作者关键词：Organic matter, Spectral pre-processing, Stepwise multiple linear regression, Partial least squares regression, Support vector machine, Heterogeneous soils

扩展关键词：DIFFUSE-REFLECTANCE SPECTROSCOPY; SUPPORT VECTOR MACHINES; ORGANIC-MATTER; NIR SPECTROSCOPY; HEAVY-METALS; CARBON; PREDICTION; REGRESSION; FRACTIONS; SPECTRA

通讯作者地址：Wu,Guofeng;Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址：guofeng.wu@whu.edu.cn

地址：

[Shi, Tiezhu; Wang, Junjie; Fei, Teng; Chen, Yiyun; Wu, Guofeng] WuhanUniv, Sch Resource & Environm Sci,Wuhan430079, Peoples RChina.

[Shi, Tiezhu; Wang, Junjie; Fei, Teng; Chen, Yiyun; Wu, Guofeng]WuhanUniv, Key Lab Geog Informat Syst, Minist Educ,Wuhan430079, Peoples RChina.

[Cui, Lijuan] Chinese Acad Forestry, Inst Wetland Res,Beijing100091, Peoples RChina.

研究方向：Agriculture; Plant Sciences

ISSN：0032-079X

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http://link.springer.com/journal/11104