9 research outputs found
Analysis of mainstream tobacco smoke particulate phase using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry
In tobacco research, the comparison of different tobacco blends as well as the puffdependent
behaviour of cigarettes is a matter of particular interest. For the investigation
of smoke characteristics, GC6GC offers different ways for data analysis,
namely, compound target analysis, automated peak-based compound classification
and comprehensive pixel-based data analysis. This study will show the application
as well as the pros and cons of these types of data analysis for very complex matrices
like cigarette particulate matter. In addition, new aspects about the recently discovered
puff-dependent behaviour of compounds in cigarette smoke will be presented.
Automated peak-based compound classification including mass spectrometric pattern
recognition is used for the classification of tobacco particulate matter samples
and the puff-dependent investigation of different compound classes. This compound
group specific analysis is further reinforced by applying an even more comprehensive
pixel-based analysis. This kind of analysis is used to generate fingerprints of
different types of cigarettes. The combination of fast feature reduction methods like
analysis of variance (ANOVA) and t-test with multivariate feature transformation
methods like partial least squares discriminate analysis (PLSDA) for feature selection
provides a powerful tool for a detailed inspection of different types of cigarettes