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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