Exploration of liquid chromatographic-diode array data for Argentinean wines by extended multivariate curve resolution

Abstract

Second-order data were measured using high-performance liquid-chromatography with diode array detection (HPLC-DAD) for a number of wine samples, which were directly injected in the HPLC-DAD system without sample pre-treatment. The data were arranged in data matrices whose modes were elution time and UV–visible absorption wavelength, and processed by extended multivariate curve resolution coupled to alternating leastsquares (MCR–ALS). The individual data matrices were organized in a row-wise augmented data matrix sharing the time subspace, due to the high spectral similarity among several sample components. This required previous time alignment of the chromatograms using a suitable synchronization algorithm, in order to produce a bilinear augmented data matrix to be processed by MCR–ALS. The latter algorithm led to resolved component chromatograms and spectra, from which component scores could be estimated, which are proportional to the relative component concentrations in each studied sample. The matrix of sample scores was then submitted to principal component analysis, which was applied for data exploration according to grape varietal and geographical origin. The results showed that the present data generation and analysis are useful for the discrimination of all samples of the Malbec varietal from the remaining ones, but achieved partial success regarding geographical origin.