A simple method for direct modeling of second-order liquid chromatographic data with retention time shifts and holding the second-order advantage

Abstract

Retention time shifts in chromatographic data severely affect the quantitative analysis of analytes of interest in complex systems. This paper offers a simple method for directly handing second-order liquid chromatographic data with retention time shift, and achieving qualitative and quantitative analysis of target analytes in the presence of overlapping peaks and unknown interference, which is the so-called “second-order advantage”. The proposed method is named the alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) because it absorbs the basic philosophy of alternating trilinear decomposition (ATLD) algorithm and multivariate curve resolution (MCR). ATLD-MCR was implemented by using the pre-decomposition results of ATLD as the initial values, MCR strategy for each sample slice matrix and the least squares optimization strategy. Three simulated data sets, a semi-simulated LC–MS data set and a real HPLC-DAD data set were investigated by the proposed method, respectively. In addition, the resolved qualitative profiles and concentration values were compared with those obtained by the other three classical second-order calibration algorithms. ATLD-MCR performed well and obtained satisfactory qualitative and quantitative results for the analytes of interest in both the simulated and experimental systems, which proved that the newly proposed method could properly model the second-order chromatographic data with retention time shifts and severe signal overlapping.