Determination of volatile components in cut tobacco with gas chromatography-mass spectrometry and chemometric resolution
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Abstract
Chromatography-mass spectrometry (GC-MS) was used to analyze the volatile components of cut tobacco samples with the help of heuristic evolving latent projections (HELP). After extracting with simultaneous distillation and extraction method, the volatile components in cut tobacco were detected by GC-MS. Then the obtained original two-dimensional data were resolved into pure mass spectra and chromatograms. The qualitative analysis was performed by similarity searches in the national institute of standards and technology (NIST) mass database with the obtained pure mass spectrum of each component and the quantitative results were obtained by calculating the volume of total two-way response. The accuracy of qualitative and quantitative results were greatly improved by using the two-dimensional comprehensive information of chromatograms and mass spectra. 107 of 141 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 88.01% of the total content. The result proves that the developed method is powerful for the analysis of complex cut tobacco samples.
Key words
chemometrics gas chromatography-mass spectrometry heuristic evolving latent projection cut tobacco volatile componentPreview
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References
- [1]CLARKSON P, MICHAEL C. The identification of an unusual volatile component in processed tobacco by gas chromatography with mass spectrometry and atomic emission detection[J]. Analytica Chimica Acta, 1996, 335(3): 253–259.CrossRefGoogle Scholar
- [2]PENG Fu-min, SHENG Liang-quan, LIU Bai-zhan, et al. Comparison of different extraction methods: Steam distillation, simultaneous distillation and extraction and headspace co-distillation, used for the analysis of the volatile components in aged flue-cured tobacco leaves[J]. Journal of Chromatography A, 2004, 1040(1): 1–17.CrossRefGoogle Scholar
- [3]WU Ming, ZHAO Ming-yue, ZHAO Xiao-dong, et al. Comparative analysis of several cut tobaccos from inside and outside China[J]. Chinese Tobacco Acta, 2002, 8(4): 1–9. (in Chinese)Google Scholar
- [4]GORDON B M, UHRIG M S, BORGERDING M F, et al. Analysis of flue-cured tobacco essential oil by hyphenated analytical techniques[J]. J Chromatogr Sci, 1988, 26(4): 174–180.CrossRefGoogle Scholar
- [5]CHIDA M, SONE Y, TAMURA H. Aroma characteristics of stored tobacco cut leaves analyzed by a high vacuum distillation and canister system[J]. J Agric Food Chem, 2004, 52(26): 7918–7924.CrossRefGoogle Scholar
- [6]MAEDER M, ZILIAN A. Evolving factor analysis: A new multivariate techniques in chromatography[J]. Chemom Intell Lab Syst, 1988, 3(3): 205–213.CrossRefGoogle Scholar
- [7]DEN Wei, EDMUND R. Malinowski. Investigation of copper (II)-ethylenediaminetetraacetate complexation by window factor analysis of ultraviolet spectra[J]. Journal of Chemometrics, 1993, 7(2): 89–98.CrossRefGoogle Scholar
- [8]LIANG Y Z, KVALHEIM O M, KELLER H R, et al. Heuristic evolving latent projections: Resolving two-way multicomponent data. Part 2: Detection and resolution of minor constituents[J]. Anal Chem, 1992, 64(8): 946–953.CrossRefGoogle Scholar
- [9]MANNE R, SHEN H L, LIANG Y Z. Subwindow factor analysis[J]. Chemom Intell Lab Syst, 1999, 45(1/2): 171–176.CrossRefGoogle Scholar
- [10]XU Chen-jian, JIANG Jian-hui, LIANG Yi-zeng. Evoling window orthogonal projections method for two-way data resolution[J]. Analyst, 1999, 124(10): 1471–1476.CrossRefGoogle Scholar
- [11]SANCHEZ F C, RUTAN S C, GIL GARCIA N D. Resolution of multicomponent overlapped peaks by the orthogonal projection approach, evolving factor analysis and window factor analysis[J]. Chemom Intell Lab Syst, 1997, 36(2): 153–164.CrossRefGoogle Scholar
- [12]GUO Fang-qiu, LIANG Yi-zeng, XU Cheng-jian, et al. Determination of the volatile chemical constituents of Notoptergium Incium by gas chromatography-mass spectrometry and iterative or non-iterative chemometrics resolution methods[J]. Journal of Chromatography A, 2003, 1016(1): 99–110.CrossRefGoogle Scholar
- [13]HUANG Lan-fang, LI Bo-yan, LIANG Yi-zeng, et al. Application of combined approach to analyze the constituents of essential oil from angelica sinensis[J]. Analytical and Bioanalytical Chemistry, 2004, 378(2): 510–517.CrossRefGoogle Scholar
- [14]WU Ming-jian, SUN Xian-jun, DAI Yuan-hui, et al. Determination of constituents of essential oil from angelica sinesis by gas chromatography-mass spectrometry and chemometric resolution[J]. Journal of Central South University of Technology, 2005, 12(4): 250–254.CrossRefGoogle Scholar
- [15]CAI J B, LIU B Z, LING P, et al. Analysis of free and bound volatiles by gas chromatography and gas chromatography-mass spectrometry in uncased and cased tobaccos[J]. Journal of Chromatography A, 2002, 947(2): 267–275.CrossRefGoogle Scholar
- [16]KELLER H R, MASSART D L. Peak purity control in liquid chromatography with photodiode-array detection by a fixed size moving window evolving factor analysis[J]. Anal Chim Acta, 1991, 246(4): 379–390.CrossRefGoogle Scholar
- [17]LIANG Yi-Zeng, KVALHEIM O M, RAHMANI A. Resolution of strongly overlapping two-way multicomponent data by means of heuristic evolving latent projections[J]. Journal of Chemometrics, 1993, 7(1): 15–43.CrossRefGoogle Scholar