Departamento de Química, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 31270-901, Brazil.
Rapid Commun Mass Spectrom. 2020 May 15;34(9):e8752. doi: 10.1002/rcm.8752.
Smoking is responsible for one in five deaths around the world. Thus, governments have been trying to reduce the number of active smokers by increasing taxes on products. This scenario creates a new problem by raising the consumption of illegally traded cigarettes, which are often seized and analyzed by police forces.
Legal and illegal cigarette samples were extracted and analyzed using paper spray ionization mass spectrometry (PS-MS). The mass spectrometer was set to operate in full-scan positive ion mode to yield representative chemical profiles of each sample. The results were used to build a chemometric model using partial least squares discriminant analysis (PLS-DA) to discriminate between both sets of samples, i.e. legal and illegal.
The PS-MS procedure was fast, simple and efficient, yielding high-quality and reproducible mass spectra with a very good signal-to-noise ratio. Even though all samples displayed visually indistinguishable mass spectra, the PS-MS data handled by the PLS-DA approach furnished a model that reached sample classification with rates of 100% and 80% for the training and validation sets, respectively.
A novel methodology was successfully developed associating the PS-MS technique with chemometric analysis to differentiate between legal and illegal cigarettes. The PS-MS technique proved to be adequate for obtaining fingerprints of such types of samples despite high complexity, and a PLS-DA model was successfully constructed achieving 82.1% accuracy.
吸烟导致全球五分之一的人死亡。因此，各国政府一直试图通过提高产品税收来减少吸烟者的数量。这一情况通过增加非法交易香烟的消费而产生了一个新问题，这些香烟经常被警察没收并进行分析。
使用纸喷雾电离质谱（PS-MS）提取和分析合法和非法香烟样本。质谱仪设置为全扫描正离子模式，以获得每个样本的代表性化学特征。使用偏最小二乘判别分析（PLS-DA）建立化学计量学模型，以区分两组样本，即合法和非法。
PS-MS 程序快速、简单、高效，产生高质量且重现性好的质谱，具有非常好的信噪比。尽管所有样本的质谱图谱肉眼上无法区分，但通过 PLS-DA 方法处理的 PS-MS 数据提供了一个模型，该模型对训练集和验证集的分类率分别达到 100%和 80%。
成功开发了一种将 PS-MS 技术与化学计量学分析相结合的新方法，用于区分合法和非法香烟。尽管样本非常复杂，但 PS-MS 技术被证明足以获取此类样品的指纹图谱，并且成功构建了一个 PLS-DA 模型，准确率达到 82.1%。
