Chromatographic background drift correction coupled with parallel factor analysis to resolve coelution problems in three-dimensional chromatographic data: Quantification of eleven antibiotics in tap water samples by high-performance liquid chromatography

Chromatographic background drift correction has been an important field of research in chromatographic analysis. In the present work, orthogonal spectral space projection for background drift correction of three-dimensional chromatographic data was described in detail and combined with parallel factor analysis (PARAFAC) to resolve overlapped chromatographic peaks and obtain the second-order advantage. This strategy was verified by simulated chromatographic data and afforded significant improvement in quantitative results. Finally, this strategy was successfully utilized to quantify eleven antibiotics in tap water samples. Compared with the traditional methodology of introducing excessive factors for the PARAFAC model to eliminate the effect of background drift, clear improvement in the quantitative performance of PARAFAC was observed after background drift correction by orthogonal spectral space projection.