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Tuning a Parallel Segmented Flow Column and Enabling Multiplexed Detection
Published on: December 15, 2015
Improved 2D-HPLC of red wine by incorporating pre-process signal-smoothing algorithms
Paul G Stevenson1, Danielle N Bassanese, Neil W Barnett
1Centre for Chemistry and Biotechnology, Faculty of Science, Engineering and Built Environment, Deakin University, Victoria, Australia.
Abstract:
Two multidimensional HPLC separations of an Australian red wine are presented, >70% of the available separation space was used. A porous graphitic carbon (PGC) stationary phase was used as the first dimension in both separations with both RP core-shell and hydrophilic interaction chromatography fully porous columns used separately in the second dimension. To overcome peak analysis problems caused by signal noise and low detection limits, the data were pre-processed with penalised least-squares smoothing. The PGC × RP combination separated 85 peaks with a spreading angle of 71° and the PGC × hydrophilic interaction chromatography separated 207 peaks with a spreading angle of 80°. Both 2D-HPLC steps were completed in 76 min using a comprehensive stop-and-go approach. A smoothing step was added to peak-picking processes and was able to greatly reduce the number of false peaks present due to noise in the chromatograms. The required thresholds were not able to ignore the noise because of the small magnitude of the peaks; 1874 peaks were located in the non-smoothed PGC × RP separation that reduced to 227 peaks after smoothing was included.
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