Application of Multivariate curve resolution-alternating least square methods on the resolution of overlapping CE peaks from different separation conditions.
Discussed in this paper is the development of a new strategy to improve resolution of overlapping CE peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added, respectively, in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3,4-Dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, and 10% relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three-way data) analysis.
Zhang
Fang
F
Institute of Analytical Science, Northwest University, Xi'an, People's Republic of China.
Chen
Yan
Y
Li
Hua
H
D000465:Algorithms; D002138:Calibration / Q000592:standards; D003198:Computer Simulation / Q000706:statistics & numerical data*; D019075:Electrophoresis, Capillary / Q000379:methods / Q000706:statistics & numerical data*; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D010865:Pilot Projects; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013056:Spectrophotometry, Ultraviolet / Q000379:methods; D013816:Thermodynamics