Quantification of target components in complex mixtures using alternative moving window factor analysis and two-step iterative constraint method

Alternative moving window factor analysis (AMWFA) has shown the powerfulness for comprehensive comparison and individual identification of chemical components among different but related mixture systems. However, quantification of these components can only be attained after extraction of all spectra of pure components in samples with least square technique. In this study, a novel two-step iterative constraint method (TICM) is developed for independent quantification of the interested target analytes. The pure chromatographic profiles of the components can be mined out from mixtures with high complexity using a two-step iterative operation and stepwise purification of the targets from interferers. Some effective constraints of chromatographic profiles, such as non-negative and single-peaked properties, as well as zero-concentration outside of elution windows of components, are employed to further improve the efficiency of the method. One of the strong advantages of TICM is simplification of complex mixtures to several sub-systems for processing easily with the help of AMWFA, as well as bi-linear property of data sets obtained from coupled chromatographic instruments. It meets the urgent requirements and challenges of qualitative and quantitative analysis of complicated systems with multi-component in the investigation of herbal medicines (HMs), metabonomics and systems biology. From the results of simulated LC-DAD data, GC-MS data of volatile chemical components in three kinds of ginseng with different growth conditions, and four different medicinal parts of the same herb, good performance of the proposed method is achieved.