Title: | Headspace-Low Water Absorption Trap Technique: Analysis of Low-Abundance Volatile Compounds from Fresh Artemisia Annua L. with GC-MS |
Address: | "Shanghai University of Sport, 399 Changhai Road, Shanghai 200438, P.R. China. Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai 201203, P.R. China. National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Science, 345 Lingling Road, Shanghai 200032, P.R. China" |
ISSN/ISBN: | 1945-239X (Electronic) 0021-9665 (Linking) |
Abstract: | "Conventional headspace (HS) method could not meet the requirement of analyzing low-abundance volatile compounds in high water content samples. A HS-low water absorption trap technique coupled with gas chromatography-mass spectrometry was introduced to remove the large amount of water vapor; therefore, the low-abundance volatile compounds could be detected with better analytical sensitivity. With this method, a total of 81 volatile compounds were identified from fresh Artemisia annua L. by mass spectral library search, retention index and accurate mass measurement, which could make the qualitative results more accurate and reliable. These compounds belonged to different species, including terpene, cycloparaffin, aliphatic aldehyde, aromatic ketone, aromatic aldehyde and so on. The 2,5,6-trimethyl-1,3,6-heptatriene (8.23%) was the most principal compound, followed by gamma-muurolene (6.80%), beta-caryophyllenea (6.24%), 1,8-cineol (5.76%), 2-carene (5.65%), borneol (5.57%), isocaryophyllene (4.91%), bornylene (4.78%), camphene (4.30%) and beta-pinene (4.26%) as the main components. The results indicated that this method presents a great potential for the trace analysis of volatile compounds in complex high water content samples" |
Keywords: | Gas Chromatography-Mass Spectrometry/methods *Artemisia annua/chemistry *Volatile Organic Compounds/analysis Terpenes Aldehydes/analysis; |
Notes: | "MedlineLiu, Mengpan Su, Yue Guo, Yinlong eng 19142201400/Science and Technology Innovation Action Plan of Shanghai/ 2022/01/10 J Chromatogr Sci. 2022 Dec 13; 60(10):907-915. doi: 10.1093/chromsci/bmab143" |