Chemometric processing of second-order liquid chromatographic data with UV-visible and fluorescence detection : A comparison of multivariate curve resolution and parallel factor analysis 2

dc.creatorBortolato, Santiago Andrés
dc.creatorOlivieri, Alejandro César
dc.date2018-02-04T19:00:30Z
dc.date2018-02-04T19:00:30Z
dc.date2014-09-09
dc.date2018-02-04T19:00:30Z
dc.date2018-02-04T19:00:30Z
dc.date2014-09-09
dc.date.accessioned2019-05-17T20:24:16Z
dc.date.available2019-05-17T20:24:16Z
dc.identifier0003-2670
dc.identifierhttp://hdl.handle.net/2133/10494
dc.identifierhttp://hdl.handle.net/2133/10494
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2680001
dc.descriptionSecond-order liquid chromatographic data with multivariate spectral (UV-visible or fluorescence) detection usually show changes in elution time profiles from sample to sample, causing a loss of trilinearity in the data. In order to analyze them with an appropriate model, the latter should permit a given component to have different time profiles in different samples. Two popular models in this regard are multivariate curve resolution-alternating least-squares (MCR-ALS) and parallel factor analysis 2 (PARAFAC2). The conditions to be fulfilled for successful application of the latter model are discussed on the basis of simple chromatographic concepts. An exhaustive analysis of the multivariate calibration models is carried out, employing both simulated and experimental chromatographic data sets. The latter involve the quantitation of benzimidazolic and carbamate pesticides in fruit and juice samples using liquid chromatography with diode array detection, and of polycyclic aromatic hydrocarbons in water samples, in both cases in the presence of potential interferents using liquid chromatography with fluorescence spectral detection, thereby achieving the second-order advantage. The overall results seem to favor MCR-ALS over PARAFAC2, especially in the presence of potential interferents.
dc.descriptionFil: Bortolato, Santiago Andrés. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica. Instituto de Química Rosario (IQUIR-CONICET); Argentina.
dc.descriptionFil: Olivieri, Alejandro César. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica. Instituto de Química Rosario (IQUIR-CONICET); Argentina.
dc.formatapplication/pdf
dc.languageeng
dc.publisherElsevier
dc.relationhttps://www.sciencedirect.com/science/article/pii/S0003267014008319?via%3Dihub
dc.relationhttps://doi.org/10.1016/j.aca.2014.07.007
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsBortolato, Santiago Andrés
dc.rightsOlivieri, Alejandro César
dc.rightsUniversidad Nacional de Rosario
dc.rightsElsevier
dc.rightsopenAccess
dc.subjectPesticides
dc.subjectParallel Factor Analysis
dc.subjectMultivariate Curve Resolution-alternating Least-squares
dc.subjectNon-trilinear Chromatographic Data
dc.subjectPolycyclic Aromatic Hydrocarbons
dc.subjectSecond-order Advantage
dc.titleChemometric processing of second-order liquid chromatographic data with UV-visible and fluorescence detection : A comparison of multivariate curve resolution and parallel factor analysis 2


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