Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

Using second-order calibration method based on trilinear decomposition algorithms coupled with high performance liquid chromatography with diode array detector for determination of quinolones in honey samples.

A novel strategy that combines the second-order calibration method based on the trilinear decomposition algorithms with high performance liquid chromatography with diode array detector (HPLC-DAD) was developed to mathematically separate the overlapped peaks and to quantify quinolones in honey samples. The HPLC-DAD data were obtained within a short time in isocratic mode. The developed method could be applied to determine 12 quinolones at the same time even in the presence of uncalibrated interfering components in complex background. To access the performance of the proposed strategy for the determination of quinolones in honey samples, the figures of merit were employed. The limits of quantitation for all analytes were within the range 1.2-56.7 µg kg(-1). The work presented in this paper illustrated the suitability and interesting potential of combining second-order calibration method with second-order analytical instrument for multi-residue analysis in honey samples.