Determination of organic matter in soils by FTIR/diffuse reflectance and multivariate calibration
β Scribed by I. Masserschmidt; C. J. Cuelbas; R. J. Poppi; J. C. de Andrade; C. A. de Abreu; C. U. Davanzo
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 70 KB
- Volume
- 13
- Category
- Article
- ISSN
- 0886-9383
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β¦ Synopsis
A non-destructive method avoiding the utilization of toxic and corrosive reagents is presented as an alternative for the determination of organic matter (OM) in soils. This method is based on a multivariate calibration procedure using partial least squares (PLS) regression to establish the relationship between the organic matter content in soils determined by conventional chemical measurements and by diffuse reflectance spectra in the mid-infrared region. The spectra are presented as reflectance (R) or log(1/R) and in Kubelka-Munk (K/S) units. Several data pretreatments such as multiplicative scatter correction (MSC), smoothing, derivation and normalization of the spectral data were employed to improve the performance of the method. The PLS analysis on the data expressed as R and log(1/R) after smoothing, differentiation and normalization showed better results, with RMSEPs equal to 0β 63% (for R) and 0β 69% (for log(1/R)) and linear correlation coefficients between reference and predicted OM values equal to 0β 981 (for R) and 0β 972 (for log(1/R)).
π SIMILAR VOLUMES
Diffuse reflectance FTIR spectroscopy (DRIFTS) coupled with modern multivariate calibration methods, namely artificial neural networks (ANNs) in two versions (ANN-raw and ANN-pca), support vector machines (SVMs), lazy learning (LL) and partial least squares (PLS) regression, is used in this study fo