太阳成8722(中国)有限公司-GREEN NO.1

标题：Prediction of total nitrogen in cropland soil at different levels of soil moisture with Vis/NIR spectroscopy作者：Liu, Yaolin; Jiang, Qinghu; Shi, Tiezhu; Fei, Teng; Wang, Junjie; Liu,Guilin; Chen, Yiyun

来源出版物：ACTA AGRICULTURAE SCANDINAVICA SECTION B-SOIL AND PLANT SCIENCE 卷：64期：3 页：267-281 DOI：10.1080/09064710.2014.906644 出版年：APR 3 2014

摘要：Visible/near-infrared (Vis/NIR) spectroscopy has been proven to be an effective technique for soil total nitrogen (TN) content estimation in the laboratory conditions. However, the transferability of this technique from laboratory study to field application is complicated by soil moisture effects. This study aims to compare the performance of four spectral transformation strategies, namely, Savitzky-Golay (SG) smoothing, SG smoothing followed by first derivative (FD), orthogonal signal correction (OSC), and generalized least squares weighting (GLSW), in the removal of soil moisture effects on TN estimation. The spectral transformations were applied on 8 sets of spectral reflectance measured from 62 soil samples at 8 moisture levels. The air-dried set was used for partial least squares regression (PLSR) calibration, whereas the other seven sets with moisture gradients were used for external validations. Results show that the SG-PLSR model cannot be transferred from the air-dried samples to the samples with moisture gradients. The FD-PLSR model showed fair TN prediction performance, with five out of seven residual prediction deviations (RPD) that are greater than 1.4. Both OSC-PLSR and GLSW-PLSR had good transferability to the moist samples. More specifically, the GLSW-PLSR model (mean of R-pre(2) = 0.718, root mean square error for prediction [RMSEP] = 0.262, and RPD = 1.885) outperformed the OSC-PLSR model (mean of R-pre(2) = 0.695, RMSEP = 0.277, and RPD = 1.780). The results demonstrate the value of OSC and GLSW in eliminating the effects of moisture on TN estimation, and the GLSW-PLSR is recommended for a better Vis/NIR estimation of TN content under different soil moisture conditions.

入藏号：WOS:000335848700009

文献类型：Article

语种：English

作者关键词：cropland soil, total nitrogen, visible, near-infrared spectroscopy, orthogonal signal correction, generalized least squares weighting, soil moisture effects

扩展关键词：DIFFUSE-REFLECTANCE SPECTROSCOPY; NEAR-INFRARED SPECTROSCOPY; ORGANIC-MATTER; ORTHOGONAL PROJECTION; NIR SPECTROSCOPY; CENTRAL YANGTZE; LEAST-SQUARES; SPECTRA; CARBON; QUANTIFICATION

通讯作者地址：Chen, Yiyun; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

电子邮件地址：kellypcyy@126.com

地址：

[Liu, Yaolin; Jiang, Qinghu; Shi, Tiezhu; Fei, Teng; Wang, Junjie; Chen, Yiyun]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

[Liu, Guilin] Univ Trier, Dept Environm Remote Sensing & Geoinformat, Trier, Germany.

研究方向：Agriculture

ISSN：0906-4710