کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1202887 | 1493562 | 2014 | 12 صفحه PDF | دانلود رایگان |
• A novel chemometrics-enhanced strategy combing HPLC-DAD with ATLD algorithm was developed.
• The proposed strategy was employed to determine eight co-eluted compounds in Chinese tea.
• Results indicated that the strategy can solve baseline drifts and co-eluted peaks in LC analysis.
• Satisfactory results could be obtained in all kinds of Chinese tea samples studied.
• Tea species were successfully classified by PCA based on our quantitative results.
In this work, an attractive chemometrics-enhanced high performance liquid chromatography-diode array detection (HPLC-DAD) strategy was proposed for simultaneous and fast determination of eight co-eluted compounds including gallic acid, caffeine and six catechins in ten kinds of Chinese teas by using second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm. This new strategy proved to be a useful tool for handling the co-eluted peaks, uncalibrated interferences and baseline drifts existing in the process of chromatographic separation, which benefited from the “second-order advantages”, making the determination of gallic acid, caffeine and six catechins in tea infusions within 8 min under a simple mobile phase condition. The average recoveries of the analytes on two selected tea samples ranged from 91.7 to 103.1% with standard deviations (SD) ranged from 1.9 to 11.9%. Figures of merit including sensitivity (SEN), selectivity (SEL), root-mean-square error of prediction (RMSEP) and limit of detection (LOD) have been calculated to validate the accuracy of the proposed method. To further confirm the reliability of the method, a multiple reaction monitoring (MRM) method based on LC–MS/MS was employed for comparison and the obtained results of both methods were consistent with each other. Furthermore, as a universal strategy, this new proposed analytical method was applied for the determination of gallic acid, caffeine and catechins in several other kinds of Chinese teas, including different levels and varieties. Finally, based on the quantitative results, principal component analysis (PCA) was used to conduct a cluster analysis for these Chinese teas. The green tea, Oolong tea and Pu-erh raw tea samples were classified successfully. All results demonstrated that the proposed method is accurate, sensitive, fast, universal and ideal for the rapid, routine analysis and discrimination of gallic acid, caffeine and catechins in Chinese tea samples.
Journal: Journal of Chromatography A - Volume 1364, 17 October 2014, Pages 151–162