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標題: Analysis of Volatile Compounds Emitted from Chimonanthus praecox (L.) Link in Different Florescence and QSRR Study of GC Retention Indices
作者: Li, Z.G.
Cao, H.
Lee, M.R.
Shen, D.L.
關鍵字: Gas chromatography-mass spectrometry;Solid-phase microextraction;Quantitative structure-retention relationship;Multiple linear;regression;Volatile compounds;Chimonanthus praecox (L.) Link;solid-phase microextraction;multiple linear-regression;topological;indexes;sample preparation;mass-spectrometry;screening systems;saturated esters;flavor profile;prediction;spme
Project: Chromatographia
期刊/報告no:: Chromatographia, Volume 70, Issue 7-8, Page(s) 1153-1162.
The volatile compounds emitted from fresh flowers of Chimonanthus praecox (L.) Link were analyzed by headspace solid-phase microextraction combined with gas chromatography-mass spectrometry. The main volatiles from fresh flowers in different florescence were also studied in this paper. It can be seen that the 71 compounds separated and identified, mainly included myrcene, benzyl alcohol, (E)-ocimene, beta-linalool, benzyl acetate, methyl salicylate, alpha-copaene, longifolene, isocaryophillene, allo-aromadendrene and cedrol. The relative contents of the main volatile fragrance from flowers of Chimonanthus praecox (L.) Link in various florescence were different. After analyzing the volatile compounds, multiple linear regression within Cerius(2) molecular modeling program package was used for building the regression model. Then the quantitative structure-retention relationship model was validated by predictive-ability test. The regression coefficient r (2) was 0.972. The prediction results were in good agreement with the experimental values. The results demonstrated that headspace SPME-GC-MS is a simple, rapid and solvent-free method suitable for analysis of volatile compounds emitted from fresh flowers in various florescence. This investigation provided an effective method for predicting the retention index of new compounds even in the absence of the standard candidates. It is worthwhile in future study for GC-MS qualitative analysis.
ISSN: 0009-5893
DOI: 10.1365/s10337-009-1289-3
Appears in Collections:化學系所

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