Unfolded partial least-squares with residual quadrilinearization: A new multivariate algorithm for processing five-way data achieving the second-order advantage. Application to fou...

• Autores: Maggio, Ruben Mariano; Peña, Arsenio Muñoz de la; Olivieri, Alejandro Cesar
• Año de publicación: 2011
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Five-way data; Partial least-squares; Residual quadrilinearization; Fluorescent analysis
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Unfolded partial least-squares in combination with residual quadrilinearization (U-PLS/RQL), is developed as aew latent structured algorithm for the processing of fourth-order instrumental data. In order to check its analytical predictive ability, fluorescence excitation-emission-kinetic-pH data were measured and processed. The concentration of the fluorescent pesticide carbaryl was determined in the presence of the pesticides fuberidazole and thiabendazole as uncalibrated interferents, in the first example of fourth-order multivariate calibration. The hydrolysis of the analyte was followed at different pH values using a fast-scanning spectro fluorimeter, recording the excitation-emission fluorescence matrices during its evolution to produce 1-naphthol, which does also emit fluorescence. A set of test samples containing the above mentioned fluorescent contaminants was analyzed with the new model, comparing the results with those from parallel factor analysis (PARAFAC). The newly developed U-PLS/RQL model provides betterfigures of merit for analyte quantitation (average prediction error, 7μg/L, relative prediction error, 5%, calibration range, 50–250 μg/L), and is considerably simpler than PARAFAC in its implementation. The latter, however, furnishes important physicochemical information regarding the chemical process under study, although this requires the data to be unfolded into an array of lower dimensions, due to the lack of quadrilinearity of the experimental data.
Fil: Maggio, Ruben Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Peña, Arsenio Muñoz de la. Universidad de Extremadura; España
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina