Comparative analysis of the volatile components in cut tobacco from different locations with gas chromatography–mass spectrometry (GC–MS) and combined chemometric methods

Huang, Lan-Fang; Zhong, Kangping; Xiao-guang, Sun; Wu, Mingjian; Huang, Kelong; Liang, Yi‐Zeng; Guo, Fang-Qiu; Li, Ya-Wen

doi:10.1016/j.aca.2006.05.079

Cited by 40 publications

(18 citation statements)

References 27 publications

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“…Compound 1 was identified by comparison of its mass spectral data with NIST mass-spectral library [21] and other reported spectroscopic data [6,7,8]. …”

Section: Resultsmentioning

confidence: 99%

Cytotoxic Components of Pereskia bleo (Kunth) DC. (Cactaceae) Leaves

et al. 2009

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Dihydroactinidiolide (1) and a mixture of sterols [campesterol (2), stigmasterol (3) and β-sitosterol (4)], together with the previously isolated individual compounds β-sitosterol (4), 2,4-di-tert-butylphenol (5), α-tocopherol (6), phytol (7) were isolated from the active ethyl acetate fraction of Pereskia bleo (Kunth) DC. (Cactaceae) leaves. Cytotoxic activities of the above mentioned compounds against five human carcinoma cell lines, namely the human nasopharyngeal epidermoid carcinoma cell line (KB), human cervical carcinoma cell line (CasKi), human colon carcinoma cell line (HCT 116), human hormone-dependent breast carcinoma cell line (MCF7) and human lung carcinoma cell line (A549); and non-cancer human fibroblast cell line (MRC-5) were investigated. Compound 5 possessed very remarkable cytotoxic activity against KB cells, with an IC50 value of 0.81µg/mL. This is the first report on the cytotoxic activities of the compounds isolated from Pereskia bleo.

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“…Compound 1 was identified by comparison of its mass spectral data with NIST mass-spectral library [21] and other reported spectroscopic data [6,7,8]. …”

Section: Resultsmentioning

confidence: 99%

Cytotoxic Components of Pereskia bleo (Kunth) DC. (Cactaceae) Leaves

et al. 2009

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“…On the one hand, these methods have been demonstrated to be appropriate to provide certain profiles of volatiles. On the other hand, numerous studies have revealed certain limitations of these methods, including incompleteness of metabolite profiles, labor intensity, apparatus dependence and cost-consumption [2,[4][5][6]. Accordingly, continuous efforts are necessary to understand aromatic and flavoring volatile compositions formed in tobacco leaves.…”

Section: -Damascenone and Megastigmatrienones (Includingmentioning

confidence: 99%

Integration of GC-MS Based Non-Targeted Metabolic Profiling with Headspace Solid Phase Microextraction Enhances the Understanding of Volatile Differentiation in Tobacco Leaves from North Carolina, India and Brazil

Ma¹,

Gandra²,

Sharma³

et al. 2012

AJPS

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In this report, gas chromatography-mass spectrometry (GC-MS) based non-targeted metabolomics is used to develop appropriate headspace solid phase microextractions (HS-SPME) to enhance the understanding of volatile complexity of flue-cured tobacco leaves. Non-targeted metabolic profiling of GC-MS shows that the extraction condition of HS-SPME at 100˚C for 30 min provides a better metabolite profile than other extraction conditions tested. GC-MS and principal component analyses (PCA) show that among five types of fibers tested, 100 μm polydimethylsiloxane (PMDS), 65 μm polydimethylsiloxane/divinylbenzene (PMDS/DVB) and 75 μm carboxen/polydimethylsiloxane (CAR/ PMS) provide a better reproducible metabolite profile. Based on an appropriate PDMS extraction condition optimized, we use GC-MS analysis and PCA to compare metabolite profiles in flue-cured leaves of tobacco plants grown in North Carolina, India and Brazil, respectively. The resulting data of PCA show that the global metabolic profiles in North Carolina samples are separated from those in Brazil and India samples, two groups of which are characterized by a partially overlapped pattern. Several peaks that were differentially accumulated in samples were annotated to known metabolites by deconvolution analysis, such as norsolanadione, solavetivone and rishitin. Norsolanadione is detected only in Brazil samples. Solavetivone is detected in samples of India and Brazil but not in those of North Carolina. Rishitin is detected in samples of North Carolina and India but not in Brazil samples. These data indicate that not only can a non-targeted metabolic profiling approach enhance the understanding of volatile complexity, but also can identify marker volatile metabolites in tobacco leaves produced in different growth regions.

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“…Instrumental techniques have inevitably been brought into this effort. Methods based on gas and liquid chromatography, usually combined with mass spectrometric (MS) detection for the identification of major organic constituents [2][3][4] and inductively coupled plasma spectrometry for the determination of a multitude of inorganic elements [5,6], have been successfully employed to obtain a more accurate assessment of tobacco samples. However, tobacco contains over 3000 organic compounds and a large number of trace elements which are practically impossible to determine [5][6][7].…”

Section: Introductionmentioning

confidence: 99%