Quantification of analytes in overlapping peaks from capillary electrophoresis using multivariate curve resolution-alternating least squares methods.

Abstract

Application of multivariate curve resolution with alternating least squares (ALS) methods to second-order data from capillary electrophoresis diode array detector (CE-DAD) is shown. Second-order data are easily obtained by setting individual data matrix of CE run one in top of the other. Initial qualitative solutions obtained by evolving factor analysis can be further optimized by simultaneous analysis of multiple electrophoresis run data with ALS regression. Quantification is achieved by the comparison of the analyte peak areas with that of pure standards. During the ALS regression procedure, the following constraints were applied: (i) both concentrations and unit pure spectra of the resolved components must be positive; (ii) elution profiles have an unimodal shape; (iii) correspondence exists between common species in the different data matrices; (iv) the pure spectrum of each species is the same in all runs where it is present. The above methods were applied for the determination of dinitrotoluene (DNT) isomeric compounds in overlapping peaks from CE.