Background correction in near-infrared spectra of plant extracts by orthogonal signal correction

In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constitutents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) me...

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Bibliographic Details
Published in:Journal of Zhejiang University (Science B) 2005-08, Vol.6 (8), p.838-843
Main Authors: Hai-bin, Qu, Dan-lin, Ou, Yi-yu, Cheng
Format: Article
Language:English
Subjects:
Datasets
Derivatives
Extraction plants
I.R. radiation
Infrared analysis
Infrared spectra
Methods
Near infrared radiation
Plant extracts
Scatter
Simulation
Spectra
Transformations
Wavelet
Wavelet analysis
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Summary:In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constitutents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.
ISSN:1673-1581
1009-3095
1862-1783
DOI:10.1007/BF02842446