Second-order advantage from kinetic-spectroscopic data matrices in the presence of extreme spectral overlapping. A multivariate curve resolution - alternating least-squares approach.

MARÍA J. CULZONI, HÉCTOR C. GOICOECHEA, GABRIELA A. IBÁÑEZ, VALERIA A. LOZANO, NILDA R. MARSILI, ALEJANDRO C. OLIVIERI Y ARIANA P. PAGANI.

ANALYTICA CHIMICA ACTA

Año: 2008 p. 46 - 57

0003-2670

AbstractMultivariate curve resolution coupled to alternating least-squares (MCR-ALS) has beenemployed to model kinetic-spectroscopic second-order data, with focus on the achievementof the important second-order advantage, under conditions of extreme spectral overlappingamong sample components. A series of simulated examples shows that MCR-ALS canconveniently handle the studied analytical problem unlike other second-ordermultivariatecalibration algorithms, provided matrix augmentation is implemented in the spectral modeinstead of in the usual kinetic mode. The approach has also been applied to three experimentalexamples, which involve the determination of: (1) the antiparkinsonian carbidopa(analyte) in the presence of levodopa as a potential interferent, both reacting with cerium(IV) to produce the fluorescent species cerium (III) with different kinetics; (2) Fe(II) (analyte)in the presence of the interferent Zn(II), both catalyzing the oxidation of methyl orange withpotassium bromate; and (3) tartrazine (analyte) in the presence of the interferent brilliantblue, both oxidized with potassium bromate, with the interferent leading to a product withan absorption spectrum very similar to tartrazine. The results indicate good analytical performancetowards the analytes, despite the intense spectral overlapping and the presenceof unexpected constituents in the test samples.