Hyphenated chromatographic techniques are widely used to analyze and characterize complex samples. Chemometric methods are generally needed to extract the qualitative and quantitative information of the target analytes from complex hyphenated chromatographic data. However, neither two-way nor three-way chemometric methods are efficient enough in analyzing hyphenated chromatographic data with both severe peak overlapping and retention time shift across samples. To address this issue, a practical framework was proposed herein. It consists of three chemometric algorithms, that is, (1) “fix-sized moving window evolving target spectral projection” for locating the possible peak positions of the target analytes, (2) “target identification based on singular value comparison” for determining whether the identified peaks are indeed the chromatographic peaks of the target analytes, and (3) “fix-sized moving window evolving trilinear decomposition” for obtaining the quantitative results of the target analytes. Experimental results on the GC-MS data sets of mixture samples of 10 compounds verified that the proposed framework could deal with the problems of both severe peak overlapping and retention time shift across samples. The proposed framework has the advantages of simplicity in concept, easy implementation, and good performance and hence is expected to be a competitive alternative to existing methods for the analysis of hyphenated chromatographic data of complex samples.
In this work, a simple and fast analytical method based on a self-weighted alternating trilinear decomposition (SWATLD) algorithm coupled with excitation–emission matrix (EEM) fluorescence was developed for the simultaneous determination of sulfamethoxazole (SMZ) and trimethoprim (TMP) illegally added to health products. With the second-order advantage, the proposed method obtained satisfactory results in the presence of peak overlap and unknown interferences. The analysis time for a single sample is only 0.8 minutes. The average spiked recoveries of SMZ and TMP in three health product spiked samples were in the range of 91.0–106.2% and 86.8–107.8%, respectively. The relative standard deviations (RSDs) were lower than 8.6%. In addition, verification parameters including sensitivity (SEN), selectivity (SEL), the limit of detection (LOD), the limit of quantification (LOQ), intra-day precision, and inter-day precision were calculated, and the results show that the proposed method is feasible. The quantitative results of the proposed method were further confirmed by the LC-MS/MS method, which proved that the proposed method was efficient and green for drug-abuse monitoring of SMZ and TMP in health products.