JOURNAL ARTICLE

Measurement and analysis of soil nitrogen and organic matter content using near-infrared spectroscopy techniques

Yong HeHaiyan SongAnnia García PereiraAntihus Hernández Gómez

Year: 2005 Journal:   Journal of Zhejiang University SCIENCE B Vol: 6 (11)Pages: 1081-1086   Publisher: Springer Science+Business Media

Abstract

Near infrared reflectance (NIR) spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen (N) and organic matter (OM) content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP (standard error of prediction) were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.

Keywords:
Near-infrared spectroscopy Soil test Partial least squares regression Spectroscopy Calibration Nitrogen Soil organic matter Analytical Chemistry (journal) Diffuse reflectance infrared fourier transform Organic matter Coefficient of determination Environmental science Soil science Soil water Chemistry Environmental chemistry Mathematics Statistics Optics

Metrics

31
Cited By
1.37
FWCI (Field Weighted Citation Impact)
18
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Soil Geostatistics and Mapping
Physical Sciences →  Environmental Science →  Environmental Engineering
Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry
Geochemistry and Geologic Mapping
Physical Sciences →  Computer Science →  Artificial Intelligence
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