Advanced data pre−processing for Comprehensive two−dimensional Gas Chromatography with Vacuum Ultraviolet Spectroscopy detection
Résumé
Comprehensive two−dimensional Gas Chromatography with Vacuum Ultraviolet detection (GC×GC/VUV) results in sizable data for which noise and baseline drift ought to be corrected. As GC×GC/VUV signal is acquired from multiple channels, these pre−processing steps have to be applied to data from all channels while being robust and rather fast with respect to significant size of the GC×GC/VUV data. In this study, we describe advanced GC×GC/VUV data pre−processing techniques for noise and baseline correction that are not available in commercial softwares. Noise reduction was performed on both the spectral and the time dimension. For baseline correction, a morphological approach based on iterated convolutions and rectifier operations is proposed. On the spectral dimension, much less noisy and reliable spectra are obtained. From a quantitative point of view, mentioned pre−processing steps significantly improve signal to noise ratio for analyte detection and hence improve their limit of detection (circa 6 times in this study). These pre−processing methods were integrated into plug im! platform (https://www.plugim.fr/).
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