IngentaConnect New Robust Bilinear Least Squares Method for the Analysis of Spec...

Authors: Goicoechea, Héctor C.¹; Olivieri, Alejandro C.²

Source: Applied Spectroscopy, Volume 59, Issue 7, Pages 144A-160A and 853-963 (July 2005) , pp. 926-933(8)

Publisher: Society for Applied Spectroscopy

Abstract:

A new second-order multivariate method has been developed for the analysis of spectral-pH matrix data, based on a bilinear least-squares (BLLS) model achieving the second-order advantage and handling multiple calibration standards. A simulated Monte Carlo study of synthetic absorbance-pH data allowed comparison of the newly proposed BLLS methodology with constrained parallel factor analysis (PARAFAC) and with the combination multivariate curve resolution-alternating least-squares (MCR-ALS) technique under different conditions of sample-to-sample pH mismatch and analyte-background ratio. The results indicate an improved prediction ability for the new method. Experimental data generated by measuring absorption spectra of several calibration standards of ascorbic acid and samples of orange juice were subjected to second-order calibration analysis with PARAFAC, MCR-ALS, and the new BLLS method. The results indicate that the latter method provides the best analytical results in regard to analyte recovery in samples of complex composition requiring strict adherence to the second-order advantage. Linear dependencies appear when multivariate data are produced by using the pH or a reaction time as one of the data dimensions, posing a challenge to classical multivariate calibration models. The presently discussed algorithm is useful for these latter systems.

Keywords: MULTIVARIATE CALIBRATION; SPECTRAL-PH MATRIX DATA; BILINEAR LEAST SQUARES; PARALLEL FACTOR ANALYSIS; MULTIVARIATE CURVE RESOLUTION; ASCORBIC ACID

Document Type: Research article

DOI: 10.1366/0003702054411643

Affiliations: 1: Cátedra de Química Analítica, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, Ciudad Universitaria, Santa Fe S3000 CC. 242, Argentina 2: Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531, Rosario (S2002LRK), Argentina

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New Robust Bilinear Least Squares Method for the Analysis of Spectral-pH Matrix Data