SVD‐based method for intensity normalization, background correction and solvent subtraction in Raman spectroscopy exploiting the properties of water stretching vibrations

Abstract

A semiautomated method combining intensity normalization with effective elimination of the solvent signal and non-Raman background is presented for Raman spectra of biochemical and biological analytes in aqueous solutions. The method is particularly suitable for rapid and effortless preprocessing of extensive datasets taken as a function of gradually varied physicochemical parameters, e.g. analyte and/or ligand concentration, temperature, pH, pressure, ionic strength, time, etc. For intensity normalization, the strong Raman OH stretching band of water in the range of 2700-3900 cm −1 recorded together with the analyte spectrum in the fingerprint region below 1800 cm −1 is employed as internal intensity standard. Concomitant dependences of the solvent Raman spectra are taken into account and, in some cases, turned into advantage. Once the Raman spectra of the solvent are acquired for a particular range of the parameter varied, solvent contribution can be subtracted correctly from any analyte spectrum taken within this range. The procedure presented can be efficiently applied only for the analytes having their own Raman signal in the range of OH stretching vibrations much weaker than that of the solvent. However, this is the case for a great number of biochemical and biological samples. Accuracy, reliability and robustness of the method were tested under the conditions of spontaneous Raman, resonance Raman and surface-enhanced Raman scattering. Serviceability of the method is demonstrated by several real-world examples.

Multivariate Analysis for the Processing of Signals

“…Palakyé t al. demonstrated this process for Raman spectra of aqueous cacodylate, using the procedure to reproducibly eliminate the signal of water that dominated the original signals [45] as shown in Figure 9. The problem of subtracting off the spectrum of water from a Raman spectrum is that the shape of the Raman bands is influenced by solvent-solute interactions, ionic strength, pH, temperature etc.…”

“…This approach was computationally intensive and at risk of local, non-optimal, solutions. Two studies developed this approach to use the scores of the multivariate analysis to calculate the combination of backgrounds required, eliminating the calculation of the linear combination and streamlining the process [44,45], since applied to two new datasets [16,46]. As indicated above, the loadings are the score weighted average of the dataset, which means they bear a simple relationship with the original signals.…”

“…Consequently any signal manipulations applied to these loadings will have a simple relationship to the original signals, one defined by the scores (these are the measure of the contribution of the loading to the signals). In the papers by Beattie [44], Beattie and McGarvey [39] and by Palacky´et al [ 45] standard baseline estimation methods similar to local minima interpolation were exploited to estimate the background within each loading. Some loadings were clearly peaks in one direction superimposed on a broad bandwidth background and the local minima between the peaks were used to define the baseline points.…”

Circumventing substrate interference in the Raman spectroscopic identification of blood stains

“…Manual and semi-automatic subtraction methods are Forensic Science International 231 (2013) 157-166 typically used to deal with spectral contributions from solvents [11] or common substrates [12]. In composite systems, individual component contributions can be isolated by spectral subtraction of pure components [13].…”

Automatic Baseline Recognition for the Correction of Large Sets of Spectra Using Continuous Wavelet Transform and Iterative Fitting

“…A more sophisticated variant has manual correction performed on the principle components of a set of spectra. 9 Although the manual approach is still widely used, it is subjective, not perfectly reproducible, and time consuming. 10 Many different methodologies were developed to obtain an objective and reproducible baseline correction.…”