Abstract
A combination of peak alignment methods and multivariate curve resolution (MCR) is proposed for handling retention time shifts and modeling of comprehensive two-dimensional gas chromatographic (GC×GC) data in the case of univariate detection systems such as in flame ionization detection (FID) or in total ion current mass spectrometry (TIC-MS) detection. A new bilinear peak alignment (BPA) method, based on MCR, is first proposed to correct for progressive within run retention time shifts in GC×GC due to temperature programming effects on second chromatographic dimension. The performance of the proposed peak alignment method is compared to that of the correlation optimized warping (COW) method. In addition, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) method, under proper constraints, is also proposed to analyze the augmented GC×GC data matrix for the resolution and quantification of target compounds in complex samples when incomplete separation and co-elution problems exist. For those difficult cases in which large between GC×GC run retention time shifts exist in both dimensions, a preliminary between runs first dimension peak alignment method by Correlation Optimized Shifting (COShift) is used to preserve the bilinearity model assumption needed for MCR-ALS application. The results showed the successful application of the proposed strategy for resolution and quantification of some target compounds in GC×GC analysis of simulated and of real samples.
Published Version
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