Factor analysis and Kalman filter studies of severely overlapped amino acid derivatives in thin-layer chromatography

Abstract

The performance of several mathematical approaches for quantification of components in cases of severe chromatographic and spectroscopic overlap has been investigated. The problem under consideration was the separation of two amino acids, glycine and glutamine, on high-performance thin-layer chromatographic plates, followed by derivatiration with o-phthaidiaidehyde. The chromatographic characteristics of these two amlno acids are very similar, and the fluorescence responses of the two derivatives are very similar as well. Here, five approaches, based on two data analysis methods, factor analysis and Kaiman filtering, have been studied. Each approach was able to detect the presence of the two amino acids in a mixture chromatogram, and the resolved responses showed a peak-shaped morphology. The concentration estimates were within an order of magnitude of the correct values, with the results for the derivativeadaptive Kaiman filtering approach showing the smallest errors, 5.9% error for glycine and -6.4% for glutamine.In the past several years, mathematical and statistical tools have been used increasingly to enhance the analysis of chemical data. In particular, several methods have been developed for the resolution of overlapped responses, which can arise in chromatographic and spectroscopic methods of analysis. In many cases, chromatographic methods can be coupled with multiwavelength spectroscopic detection approaches to enhance the analyst's ability to distinguish a number of coeluting components. Two classes of curve resolution approaches have been employed those that require a model for the spectral or chromatographic characteristics and those that are "self-modeling". The model-based curve resolution approaches are most useful for determining the relative contributions of each of the coeluting components to the overall spectroscopic response in cases where the identities of the contributing chemical species are known. These approaches include factor analysis methods ( l ) , linear leastsquares methods (2,3), modified least-squares approaches (4, 5), and Kalman filtering techniques (6, 7). One major requirement for successful implementation of all of these techniques is that the responses due to each of the components must be linearly independent of one another. This requirement means that inaccurate concentration estimates may be obtained for compounds that cannot be resolved chromatographically and that give rise to very similar spectral responses.One area where severely overlapped chromatographic and spectroscopic responses may cause difficulties in obtaining accurate concentration estimates is when derivatization methods are employed in chromatography to increase the detection sensitivity. In particular, fluorogenic reagents are often used to form fluorescent molecules from nonfluorescent Present address:analytes. The spectroscopic characteristics of these fluorescent derivatives are usually very similar, due to the fact that the energy levels in the fluorescent moiety are not substantially perturbed by th...

Chemometrics

“…Brown has reviewed the theory and applications of the Kalman filter (137). Rutan examined various chemical problems which have been solved with the Kalman filter (138) and presented an interesting method to resolve and quantify severly overlapped amino acid derivatives in thin-layer chromatography (139). Scolari and Brown were able to resolve overlapping square-wave voltammetric response curves applied to various systems by using Kalman filtering methods (140).…”

Background correction for fluorescence detection in thin-layer chromatography using factor analysis and the adaptive Kalman filter

“…In this case, the low-frequency variability in the spectrum is decreased using the derivative method, and the adaptive Kalman filter is used to determine the relative contribution of the background signal to the fluorescence spectrum. This approach has been shown to work well for removal of background contributions from fluorescence spectra aldehyde derivatives of amino acids (15). A complementary approach to the derivative-adaptive Kalman filter method discussed above is described in this paper.…”