Two-Trace Two-Dimensional (2T2D) Correlation Spectroscopy with Score-Based Quantitative Principal Component Analysis for the Quantification of Multicomponent Chemical Systems Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectra.

Abstract

The study presents score-based quantitative principal component analysis (SQPCA) combined with two-trace two-dimensional (2T2D) correlation spectroscopy as an approach for semi-quantitative analysis of plant extract using attenuated total reflection infrared (ATR FT-IR) spectral data. The SQPCA algorithm was applied to determine the content of four flavonoids, baicalin, baicalein, wogonin, and wogonoside, in a series of extracts from Scutellaria baicalensis Georgi roots. Due to the complex nature of the spectral profiles, characterized by congested, overlapping bands, appropriate data preprocessing was necessary to enhance the quantitative performance of the SQPCA procedure. A slice of the 2T2D disrelation spectrum was used to construct a multiplicative filter, i.e., disrelation filter (DF), to derive signals corresponding mainly to the analytes of interest. The concentrations of analytes calculated by SQPCA and SQPCA-DF were compared with those determined using the high-performance thin-layer chromatography (HPTLC) method. For the analyzed flavonoids, a reasonable spectral resolution was achieved, making the combined approach especially useful for the identification and quantification of analytes in the presence of interferents.