GCMS and PCA

Principal Component Analysis (PCA) is a method of multivariate data analysis. Using this method, it has been possible to improve the quality. In essence, the method is able to remove noise from both the mass spectral and chromatographic components of the data. This results in inproved mass spectral searches and improved S/N.



Before and after for a six component mixture - chromatographic data



Before and after for a representative mass spectum.

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