COMPARATIVE STUDY OF DIFFERENT THIRD-ORDER DATA GENERATION APPROACHES

MONTEMURRO M; ALCARAZ M R; SIANO G G; CULZONI; GOICOECHEA, H

Congreso; XVIII CAC 2016; 2016

Over the last years, it has been demonstrated that the increase of multiway data dimensions has a positiveimpact on analytical figures of merit, e.g. higher sensitivity, lower limits of detection and quantitation,better selectivity, among others. First- and second-order data analyses have become excellent tools forthe resolution of complex samples which would result experimentally challenging from the univariatecalibration standpoint. On the other hand, even though no additional analytical advantages have been yetproved, third-order data analysis for analytical applications constitutes a field worth to be explored [1].Although multidimensional instrumental signals are easy to be obtained with the available moderninstrumentation, and several chemometric algorithms have been successfully developed to solve multiwaydata problems, the way in which the multi-way data are generated may have a significant effect onthe final results. In this work, a comparative study of different third-order data generation approacheswas carried out. Three methods based on identical liquid chromatographic conditions but coupled todifferent emission and excitation fluorescence detection systems were developed for the quantitativeanalysis of antibiotics in aqueous matrices.