Extracting Chemical Information from Spectral Data with Multiplicative Light Scattering Effects by Optical Path-Length Estimation and Correction

Abstract

When analyzing complex mixtures that exhibit sample-to-sample variability using spectroscopic instrumentation, the variation in the optical path length, resulting from the physical variations inherent within the individual samples, will result in significant multiplicative light scattering perturbations. Although a number of algorithms have been proposed to address the effect of multiplicative light scattering, each has associated with it a number of underlying assumptions, which necessitates additional information relating to the spectra being attained. This information is difficult to obtain in practice and frequently is not available. Thus, with a view to removing the need for the attainment of additional information, a new algorithm, optical path-length estimation and correction (OPLEC), is proposed. The methodology is applied to two near-infrared transmittance spectral data sets (powder mixture data and wheat kernel data), and the results are compared with the extended multiplicative signal correction (EMSC) and extended inverted signal correction (EISC) algorithms. Within the study, it is concluded that the EMSC algorithm cannot be applied to the wheat kernel data set due to core information for the implementation of the algorithm not being available, while the analysis of the powder mixture data using EISC resulted in incorrect conclusions being drawn and hence a calibration model whose performance was unacceptable. In contrast, OPLEC was observed to effectively mitigate the detrimental effects of physical light scattering and significantly improve the prediction accuracy of the calibration models for the two spectral data sets investigated without any additional information pertaining to the calibration samples being required.

FTIR Imaging of Tissues: Techniques and Methods of Analysis

“…In mSC, each spectrum is regressed in a set of related samples. In mSC a mean (or reference spectrum) is used to estimate the intercept and slope of an estimated regression equation [72]. Subtracting the intercept and dividing by the slope corrects each spectrum.…”

Application of Extended Multiplicative Signal Correction to Short-Wavelength near Infrared Spectra of Moisture in Marzipan

“…JDAIP been proposed to explicitly model the effect of multiplicative light scattering [15]. One of the most frequently reported techniques in the literature is that of multiplicative signal correction (MSC) [16].…”

“…Each individual spectrum is then corrected by subtracting the intercept and dividing by the slope. An alternative procedure proposed to correct for multiplicative light scattering, that is similar to MSC, is the inverted scatter correction (ISC), more recently is the Extended multiplicative signal correction (EMSC) is a modification of the standard MSC pre-processing method [4,5,[15][16][17][18] that allows the separation of physical light scattering effects from chemical (vibrational) light absorbance effects in spectra. It was developed by Martens and Stark [19,20] the methodology to identify and separate various effect in multi-chanel measurements making the measurements suitable lives it goes multivariate calibration, improving robustness and predictive ability [4,5,19].…”

Multivariate Calibration of Near Infrared Spectroscopy in the Presence of Light Scattering Effect: A Comparative Study

“…Optical path length estimation and correction (OPLEC) was devised using the same model as EMSC of ‫ܠ‬ = ܽ + ܾ ‫ܠ‬ , + ݀ ૃ + ݁ ૃ ଶ (Chen, Morris, and Martin 2006) …”