New background correction method for liquid chromatography with diode array detection, infrared spectroscopic detection and Raman spectroscopic detection.

Abstract

A new method to eliminate the background spectrum (EBS) during analyte elution in column liquid chromatography (LC) coupled to spectroscopic techniques is proposed. This method takes into account the shape and also intensity differences of the background eluent spectrum. This allows the EBS method to make a better estimation of the background eluent spectrum during analyte elution. This is an advantage for quantification as well as for identification of analytes. The EBS method uses a two-step procedure. First, the baseline spectra are modeled using a limited number of principal components (PCs). Subsequently, an asymmetric least squares (asLS) regression method is applied using these principal components to correct the measured spectra during elution for the background contribution. The asymmetric least squares regression needs one parameter, the asymmetry factor p. This asymmetry factor determines relative weight of positive and negative residuals. Simulations are performed to test the EBS method in well-defined situations. The effect of spectral noise on the performance and the sensitivity of the EBS method for the value of the asymmetry factorp is tested. Two applications of the EBS method are discussed. In the first application, the goal is to extract the analyte spectrum from an LC-Raman analysis. In this case, the EBS method facilitates easy identification of unknown analytes using spectral libraries. In a second application, the EBS method is used for baseline correction in LC-diode array detection (DAD) analysis of polymeric standards during a gradient elution separation. It is shown that the EBS method yields a good baseline correction, without the need to perform a blank chromatographic run.