THE FEASIBILITY OF LATENT-VARIABLES APPLIED TO GC-MS DATA

This review starts with a brief introduction to gas chromatography-mas s spectrometry (GC-MS) and multivariate analysis. It proceeds with a d escription of the general strategy of extracting relevant quantitative information from GC-MS instrumentation by latent variables in particu lar. With respect to mass spectra and data analysis, several thorough reviews have been written within the two major fields of classificatio n and curve resolution techniques. As a consequence this review will f ocus less on these two fields, and put more emphasis to latent variabl es applied to GC-MS data in environmental field studies and spectrum-s tructure/property modelling. To understand and operate a GC-MS system of today, the chemist must be knowledgeable in gas chromatography, mas s spectrometry, vacuum technology and computer science. It is my hope that this review can aid both the skilled mass spectrometrist within t he latter subject, as well as any scientist to achieve relevant inform ation from supported chemical data in their own field of study.