Application of multivariate curve resolution methods to on-flow LC-NMR

Quantitative determination in chromatographic analysis based on n-way calibration strategies

Chemometric techniques for calibration with three-way signals are sufficiently developed for their use in routine analysis. The advantage of the second order property (the possibility of quantifying an analyte in the presence of interferents) together with the guarantee of the uniqueness of the decomposition, what means to extract the signal corresponding only to the analyte of interest, make these calibration techniques especially useful for the quantification and identification of analytes in complex samples. This has a particular interest in the identification and quantification of banned substances or substances with a specified maximum limit. The paper describes the theory of the calibration methodology in relation to the signal order and then focuses the analysis on the three-way techniques commonly used in calibration: n-way partial least squares, multivariate curve resolution and parallel factor analysis. The figures of merit needed for the accreditation of analytical methods are analyzed from the viewpoint of n-way calibrations in chromatography.

Factor analysis of hyphenated chromatographic data

Factor analysis (FA) is a family of widely used methods to obtain the underlying sources of variation of data tables. Typically, hyphenated chromatographic data provide data tables with one elution direction and another linked to the detector response. In this context, the factors are the eluting compounds and the profiles defining each factor are the elution profile and the pure response of the compound. This article describes the use of FA in chromatography through diverse tools and problems. Examples of determination of number of compounds, peak purity problems, resolution of overlapped compounds or extension to simultaneous analysis of multiple runs (higher-order data structures) to obtain qualitative and quantitative information are reviewed.

Virtual Chromatographic Resolution Enhancement in Cryoflow LC−NMR Experiments via Statistical Total Correlation Spectroscopy

A new approach to enhancing information recovery from cryogenic probe "on-flow" LC-NMR spectroscopic analyses of complex biological mixtures is demonstrated using a variation on the statistical total correlation spectroscopy (STOCSY) method. Cryoflow probe technology enables sensitive and efficient NMR detection of metabolites on-flow, and the rapid spectral scanning allows multiple spectra to be collected over chromatographic peaks containing several species with similar, but nonidentical, retention times. This enables 1H NMR signal connectivities between close-eluting metabolites to be identified resulting in a "virtual" chromatographic resolution enhancement visualized directly in the NMR spectral projection. We demonstrate the applicability of the approach for structure assignment of drug and endogenous metabolites in urine. This approach is of wide general applicability to any complex mixture analysis problem involving chromatographic peak overlap and with particular application in metabolomics and metabonomics.