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Two dimensional correlation spectroscopy applications in vibratioal and optical spectroscopy - Isao N.

Isao N. Two dimensional correlation spectroscopy applications in vibratioal and optical spectroscopy - Wiley publishing , 2004. - 312 p.
ISBN 0-471-62391-1
Download (direct link): twodimensionalcorrela2004.pdf
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4.2.2 BASELINE CORRECTION METHODS
Major causes for baseline fluctuations in transmittance spectra are light scattering and changes in density, while those in diffuse reflectance spectra are intensity changes in light scattering and normal reflection light induced by the variations in average particle size, distribution of particle shape, the density of packing of a sample in a cell, and so on. Baseline fluctuations are also induced by the effect of an optical fiber cable. The most popular baseline correction method is the use of derivative spectra. However, it is not a good idea to use derivative methods for the pretreatment of spectral data for 2D correlation spectroscopy, because ripples in derivative spectra may produce artificial peaks in 2D maps.
Multiplicative scatter (or signal) correction (MSC) is a very useful pretreatment method for eliminating the additive scatter factor (offset deviation) and the multiplicative scatter factor (amplification factor) in a spectrum.4 The idea of MSC lies in the fact that light scattering typically has a wavelength dependence different from that of chemically based light absorbance. Therefore, one can utilize data from many wavelengths to distinguish between light absorption and light scattering. MSC corrects spectra according to a simple linear univariate fit to a standard spectrum and is estimated by least squares regression using the standard spectrum. As the standard spectrum, a spectrum of a particular sample or an average spectrum is used. Let us give an example of effective pretreatments.
Figure 4.5 displays NIR spectra in the 1100-2500 nm region of 165 milk samples.5 It is noted that the signal-to-noise ratio of the spectra is not high in the 2000-2500 nm region, and the baseline changes from one spectrum to another. The spectra are very similar to that of water. A broad feature near 1450 nm is due to the combination of OH symmetric and antisymmetric stretching modes of water, while an intense band near 1930 nm is assigned to the combination of OH bending and symmetric stretching modes of water. It is difficult to extract useful information about milk components directly from the NIR spectra. Thus, 2D correlation analysis was applied to the 1100-1900 nm and 2000-2400 nm regions.
54
Generalized 2D Correlation Spectroscopy in Practice
1200 1400 1600 1800 2000 2200 2400
Wavelength/nm
Figure 4.5 NIR spectra in the 1100-2500 nm region of the milk samples. (Reproduced with permission from B. Czarnik-Matusewicz et al, Appl. Spectrosc., 53, 1582 (1999). Copyright (1999) Society for Applied Spectroscopy.)
Comparison of the two figures reveals that the baseline changes are much larger for the fat than for the protein concentration-dependent spectral variations. Milk contains light-scattering particles in the form of fat globules and protein micelles. The direct calculation of 2D correlation spectra from the raw spectra in Figures 4.6(Aa) and (Ba) yields a very strange looking synchronous spectrum and a very noisy asynchronous spectrum. The synchronous spectra showed only positive peaks probably because of the increasing baseline change. Thus, Czarnik-Matusewicz et al. applied MSC and smoothing as pretreatment procedures of the milk spectra selected for the calculation of 2D NIR correlation.5 Figures 4.6(Ab) and (Bb) depict, respectively, the spectra obtained after the applications MSC and smoothing to the spectra shown in Figures 4.6(Aa) and (Ba). The results in Figs. 4.6(Ab) and (Bb) demonstrate the usefulness of MSC and smoothing. More detailed discussion on the 2D correlation NIR study of milk based on protein and fat concentrations will be given in Chapter 13.
4.2.3 OTHER PRETREATMENT METHODS
Many other data pretreatment methods have been used in 2D correlation spectroscopy. While they are generally good techniques, care must always be exercised because the indiscriminate use of preprocessing methods may generate unwanted artifacts. For example, Fabian et al. used Fourier self-deconvolution
Pretreatment of Data
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2100
2200 2300
Wavelength/nm
2400
Wavelength/nm
Figure 4.6 (A) Fat concentration-dependent NIR spectral variations in the 2000-2400 nm
region of milk samples before (a) and after (b) pretreatments. (B) Protein concentration-dependent NIR spectral variations in the 2000-2400 nm region of milk samples before (a) and after (b) pretreatment. (Reproduced with permission from B. Czarnik-Matusewicz et al., Appl. Spectrosc., 53, 1582 (1999). Copyright (1999) Society for Applied Spectroscopy.)
A
(FSD) as a pretreatment for IR and NIR spectra of proteins to further enhance the spectral resolution of highly overlapped babds.6 Czarnik-Matusewicz et al. employed four kinds of pretreatment procedures to construct 2D correlation spectra from concentration-dependent attenuated total reflection (ATR) IR spectral changes of P-lactoglobulin (BLG) buffer solutions, including ATR correction, subtraction of the spectrum of buffer solution, smoothing, and normalization over the concentration.7
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