Several Typical Traditional Chinese Medicine Volatile Oils By Gas Chromatography Mass Spectrometry Fingerprint Analysis

Essential oil as a group of low-boiling compounds is an important class of pharmacologically active components in Traditional Chinese Medicines (TCM). The composition of essential oil is very complex, and thus the development of comprehensive and effective analytical technology for their characterization and quality control is an important area of research. In this study, the essential oil constituents in chuanxiong , Angelica and Aucklandia lappa Decne collected from different geographical locations were determined by GC–MS under optimized conditions. The aim of the study is to develop and utilize fingerprinting and principal component analysis and cluster analysis technology for the authentication and quality control of the three herbs, namely, the ability to distinguish the substitute or adulterant from the authentic ones, and the differentiation of these herbs of different geographic origins.Chapter 1 provides an overview of the principles, equipment, and applications of GC-MS in TCMs analysis. It reviews new methods for the quality control of TCM, especially the fingerprint technique and principal component analysis and cluster analysis Technology. The current status of research in chuanxiong, Angelica and Aucklandia lappa Decne are outlined and the objectives, significance and main contents of the dissertation are also summarized in this chapter 1.In chapter 2, the different extraction methods for essential oil in chuanxiong, Angelica and Aucklandia lappa Decne were compared. These methods include Accelerated Solvent Extraction(ASE),Supercritical Fluid Extraction(SFE), Ultrasonic Assisted Extraction(UAE), Soxhlet extraction(SHE) and Hydro-distillation extraction(HDE). The results show that ASE is simple, highly efficient, and capable of automation. It has low solvent consumption and can significantly reduce extraction time compared to conventional extraction methods. ASE is ideally suited for the extraction of essential oils in Traditional Chinese medicine. The operating parameters for ASE include extraction solvent, temperature, extraction time, flush volume and numbers of extraction cycles, and all these can be optimized in order to obtain the highest extraction efficiency. Results from this study show that the optimum ASE conditions to obtain the highest extraction efficiency of costunolide, dehydrocostuslactone in Aucklandia lappa Decne were: sample with particle size of 60 mesh; solvent of chloroform; temperature at 100 ?C; static extraction time of 20 min, and flush volume of 60%.In chapter 3, a Gas chromatography-mass method were established for the determination of essential oils in chuanxiong, Angelica and Aucklandia lappa Decne. Nine major peaks of chuanxiong (including six major peaks of Angelica ) in the GC-MS chromatogram have been tentatively identified according to the mass spectrum of each component, and they inlcude 3-butylphthalide, Z-Butyldenephthalide, Senkyunolide I, Senkyunolide H, E-Butyldenephthalide, Senkyunolide A, Neocnidilide, Z-ligustilide and E-ligustilide. In addition, Nine major peaks of Aucklandia lappa Decne have also been tentatively identified, and these areα-costol,saussurealactone, costunolide, iso-costunolide,β-cyclocostunolide, dehydrocostuslactone, dehydrosaussurea lactone, Magnolialide and Reynosin. A reproducible GC-MS fingerprinting technique was developed for the identification and differentiation of the three herbs with other herbs. In this study, ten chuanxiongs samples , seven Angelicas and nine Aucklandia lappa Decne samples were analyzed.In chapter 4, a pattern recognition technique based on principal componet analysis (PCA) and cluster analysis was applied to the treatment of GC/MS data for ten chuanxiongs, seven Angelicas and nine Aucklandia lappa Decne samples. Using the GC/MS fingerprint of GAP herbs as the reference, the other sample herbs were compared and classified using the pattern recognition technique developed in this study. The results show that the technique is able to group herbs based on their quality, namely, their similarity to the reference herb. Furthermore, consistent results from principal component analysis and cluster analysis techniques were obtained.