<abstract xmlns="http://www.w3.org/1999/xhtml"><p>For the first time, pyrolysis - field ionization (Py-FI) mass spectra of the tobacco blends of three different cigarette brands have been recorded in the mass range up to 1000 mass units and evaluated by operational fingerprinting techniques. Due to the high reproducibility of the applied methods, all three tobacco blends could be differentiated clearly with several univariate or multivariate statistical methods. Feature scaling with Fisher ratios revealed that the signal at m/z 93, mainly due to aniline, is the most suited to distinguishing the tobacco blends analysed. Principal component analysis showed the variety of pyrolytic reactions during the thermal decomposition of tobacco in high vacuum. It revealed that, in addition to aniline, lignin-related signals can also be used for a clear differentiation. From the whole pattern of Py-FI mass spectrum, nearest-neighbour relationships are visualized by the non-linear mapping technique and further classification of tobacco blends is obtained by hierarchical cluster analysis. A thorough chemical interpretation of the data obtained should give new insights into the structure of tobacco and its pyrolytic decomposition. Pyrolysis - soft ionization mass spectrometry in combination with pattern recognition techniques appears to provide a useful tool for future investigations connected with the quality control of commercial tobacco products.</p></abstract>

For the first time, pyrolysis - field ionization (Py-FI) mass spectra of the tobacco blends of three different cigarette brands have been recorded in the mass range up to 1000 mass units and evaluated by operational fingerprinting techniques. Due to the high reproducibility of the applied methods, all three tobacco blends could be differentiated clearly with several univariate or multivariate statistical methods. Feature scaling with Fisher ratios revealed that the signal at m/z 93, mainly due to aniline, is the most suited to distinguishing the tobacco blends analysed. Principal component analysis showed the variety of pyrolytic reactions during the thermal decomposition of tobacco in high vacuum. It revealed that, in addition to aniline, lignin-related signals can also be used for a clear differentiation. From the whole pattern of Py-FI mass spectrum, nearest-neighbour relationships are visualized by the non-linear mapping technique and further classification of tobacco blends is obtained by hierarchical cluster analysis. A thorough chemical interpretation of the data obtained should give new insights into the structure of tobacco and its pyrolytic decomposition. Pyrolysis - soft ionization mass spectrometry in combination with pattern recognition techniques appears to provide a useful tool for future investigations connected with the quality control of commercial tobacco products.

Pyrolysis - Field lonization Mass Spectrometry - A New Method for Direct, Rapid Characterization of Tobacco

Department of Trace Analysis, Fachhochschule Fresenius, Wiesbaden, Germany

Contributions to Tobacco & Nicotine Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

For the first time, pyrolysis - field ionization (Py-FI) mass spectra of the tobacco blends of three different cigarette brands have been recorded in the mass...

Pyrolysis - Field lonization Mass Spectrometry - A New Method for Direct, Rapid Characterization of Tobacco

Published Online: Jan 06, 2015

Page range: 219 - 227

Received: Mar 17, 1986

Accepted: Oct 30, 1986

DOI: https://doi.org/10.2478/cttr-2013-0571

© 1986 Beiträge zur Tabakforschung International

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.