Advanced data preprocessing for Comprehensive two-dimensional Gas Chromatography with Vacuum Ultraviolet Spectroscopy detection (vol 44, pg 4141, 2021)

Comprehensive two-dimensional gas chromatography with vacuum ultraviolet detection results in sizable data for which noise and baseline drift ought to be corrected. As the data is acquired from multiple channels, preprocessing steps have to be applied to the data from all channels while being robust and rather fast with respect to the significant size of the data. In this study, we have described advanced data preprocessing techniques for such data which were not available in the existing commercial software solutions and which were dedicated primarily to noise and baseline correction. Noise reduction was performed on both the spectral and the time dimension. For the baseline correction, a morphological approach based on iterated convolutions and rectifier operations was proposed. On the spectral dimension, much less noisy and reliable spectra were obtained. From a quantitative point of view, mentioned preprocessing steps significantly improved the signal-to-noise ratio for the analyte detection (circa six times in this study). These preprocessing methods were integrated into the plugim! platform ().