title: A simple approach to reduce dimensionality from comprehensive two-dimensional liquid chromatography coupled with a multichannel detector.
abstract: Comprehensive two-dimensional liquid chromatographic (LC×LC) systems play an ever increasing role in separation and characterization of complex samples. When coupled with multichannel detectors, such as the diode array detector, these LC×LC systems become especially useful for non-target analysis and identification of patterns based on the information extracted from those complex samples. Nevertheless, due to the large amount of data generated by these systems, the extraction of useful information for the identification of patterns still is one of the major drawbacks for a wider application of this technique. As a preliminary step in data treatment, we have developed a simple and fast way to deal with this large amount of multi-dimensional data by identifying the three-dimensional (3D) regional maxima of each chromatographic peak generated in a LC×LC-DAD system: retention times at the peak maximum in the first- and second-dimensions and the wavelength of the maximum UV absorption. This dataset is then used to build a 3D fingerprinting of the given sample, which alongside the 3D fingerprinting of other samples, can be used to identify different patterns associated with the specific properties of every sample under study. The applicability of the developed methodology was further assessed by performing a non-target LC×LC-DAD analysis of four Portuguese red wine samples.
authors.affiliation: Department of Chemistry and CESAM, University of Aveiro, 3810-193 Aveiro, Portugal. Electronic address: jtmatos@ua.pt.
authors.forename: João T V
authors.initials: JT
authors.lastname: Matos
authors.forename: Regina M B O
authors.initials: RM
authors.lastname: Duarte
authors.forename: Armando C
authors.initials: AC
authors.lastname: Duarte
keywords: Complex organic mixtures; Comprehensive two-dimensional liquid chromatography; Non-target chromatography; Pattern representation; Peak detection; Portuguese red wines