Even though NIR spectroscopy is based on the Beer–Lambert law, which clearly relates the concentration of the absorbing elements with the absorbance, the measured spectra are subject to spurious signals, such as additive and multiplicative effects. The use of NIR spectra, therefore, requires a preprocessing step. This article reviews the main preprocessing methods in the light of aquaphotomics. Simple methods for visualizing the spectra are proposed in order to guide the user in the choice of the best preprocessing. The most common chemometrics preprocessing are presented and illustrated by three real datasets. Some preprocessing aims to produce a spectrum as close as possible to the absorbance that would have been measured under ideal conditions and is very useful for the establishment of an aquagram. Others, dedicated to the improvement of the resolution of the spectra, are very useful for the identification of the peaks. Finally, special attention is given to the problem of reducing multiplicative effects and to the potential pitfalls of some very popular methods in chemometrics. Alternatives proposed in recent papers are presented.
In
near-infrared spectroscopy (NIRS), the linear relationship between
absorbance and an absorbing compound concentration has been strictly
defined by the Bouguer–Beer–Lambert law only for the
case of transmission measurements of nonscattering media. However,
various quantitative calibrations have been successfully built both
on reflectance measurements and for scattering media. Although the
lack of linearity for scattering media has been observed experimentally,
the sound multivariate statistics and signal processing involved in
chemometrics have allowed us to overcome this problem in most cases.
However, in the case of samples with varying water content, important
modifications of scattering levels still make calibrations difficult
to build due to nonlinearities. Moreover, even when calibration procedures
are successfully developed, many preprocessing methods used do not
guarantee correct spectroscopic assignments (in the sense of a pure
chemical absorbance). In particular, this may prevent correct modeling
and interpretation of the structure of water. In this study, dynamic
near-infrared spectra acquired during a drying process allow the study
of the physical effects of water content variations, with a focus
on the first overtone OH absorbance region. A model sample consisting
of aluminum pellets mixed with water allowed us to study this specifically,
without any other absorbing interaction terms related to the dry mass-absorbing
constituents. A new formulation of the Bouguer–Beer–Lambert
law is proposed, by expressing path length as a power function of
water content. Through this new formulation, it is shown that a better
and simpler prediction model of water content may be developed, with
more precise and accurate identification of water absorbance bands.
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