GC-MS of natural essential oils and development of a statistic model for quality control Gabriele Poloniato1, Valeria Baldan1, Stefania Sut1, Marta Faggian1,

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GC-MS of natural essential oils and development of a statistic model for quality control Gabriele Poloniato1, Valeria Baldan1, Stefania Sut1, Marta Faggian1, Gregorio Peron1, Filippo Maggi2, Stefano Dall’Acqua1 1Department of Pharmaceutical and Pharmacological sciences, University of Padova, Via F. Marzolo 5, Padova 35131 Italy 2 School of Pharmacy, University of Camerino, Via Sant’Agostino 1, Camerino 62032 , Italy Introduction Essential oils are volatile mixtures having a complex composition of substances, such as alcohols, aldehydes, ketones, oxides, terpenes and phenols, which are widely used in the parfumes, aromatherapy, repellents and pharmaceutical preparations. The quality control of essential oils needs time consuming analysis by GC/MS and identification of several constituents. The aim of the work is to study a multivariate system for the analysis of different batches of essential oils and to develop a model that can be useful for assessment of quality and non-adulteration of essential oils. Materials and Methods In the characterization of essential oils, gas chromatography is particularly useful, especially when associated with mass spectrometry (GC/MS). 10l of the sample were diluted in 1ml diethyl ether. Constituents were identified using Kovats Retention index, matching with different Mass Spectra libraries and comparing with authentic standards. In general, more than 85% of constituents were identified and quantified. b c Figure 1 Work’s phases The different chromatograms of each sample were then transformed into a numerical data matrix, using Mzmine software, characterized by the sample identifier, the retention time of each peak, the mass spectrum of each peak, and the area of ​​each peak, and multivariate elaborations were obtained using Simca 13. Results The GC/MS method used by combining the data obtained through Mass and calculating the Kovats indexes has allowed to characterize all the essential oils considered, that have been then classified on the basis of the chemical constituents. The multivariate analysis tool has been able to build preliminary computational data that highlight the possibility of clustering essential oils from different botanical families of starting materials. Family of different essential oils were considered and a model for identification of non adulterated essential oil have been proposed. By adding adulterated essential oils to the model, these ones will collocate themselves in a different clusterization respect the corresponding natural oils. Figure 4 Biplot showing oils clusterization based on chemical constituents Figure 2 Clusterization of oils based on the different botanical families Figure 3 Clusteriaztion of chemical species and the samples Conclusion References GC/MS method has allowed a qualiquantitative characterization of the considered essential oils, while the multivariate analysis tool has allowed to build a preliminary computing datasets that highlight the possibility of cluster essential oils from different botanical families. The multivariate model will allow to have a composition evaluation tool of essential oils, useful for highlighting possible adulterations or sophistications. Tadrent, W., Kabouche, A., Touzani, R., & Kabouche, Z. (2016). Chemotypes investigation of essential oils of chamomile herbs: A short review. Journal of Materials and Environmental Science, 7(4), 1229-1235 Singh, G., Singh, O. P., & Maurya, S. (2002). Chemical and biocidal investigations on essential oils of some indian curcuma species. Progress in Crystal Growth and Characterization of Materials, 45(1-2), 75-81.