GC-MS和紫外光谱法分析中国蜂胶乙醇提取物

发布时间：2018-05-06 08:19

本文选题：蜂胶 + 醇提物　；参考：《南昌大学》2017年硕士论文

【摘要】：为了进一步研究中国蜂胶的化学组成,探索不同气候带和颜色蜂胶间的差异,同时获得用于分区的特征化合物。本研究采用气相色谱质谱联用(Gas chromatography-mass spectrometry,GC-MS)结合硅烷化衍生对采自中国22个省的37个蜂胶和1个树胶的乙醇提取物进行成分鉴定,并进行多变量分析。另外为实现对蜂胶进行简便、快捷地初步品质检测,对37个中国蜂胶的醇提物(Ethanol extract of propolis,EEP)进行紫外光谱(Ultraviolet spectrum,UV)扫描,获得EEP的UV扫描数据,并进行多变量分析,同时测定EEP的总酚、总黄酮含量、特定吸收率和清除DPPH自由基活性,初步建立回归模型。研究结果如下:1.GC-MS结合硅烷化衍生对37个蜂胶和1个树胶的乙醇提取物进行成分鉴定,结果显示,37个EEP共鉴定出124种化合物,包括25个多酚类化合物,8个萜类化合物,40个糖类及其衍生物,且主要是单糖,7个脂肪酸及其酯类、7个醇类、7个酸类、11个酮类、2个醚类、9个甾体类化合物,此外还鉴定出8个其他类别化合物。其中主要成分为苯甲酸(0.13%~0.48%)、3,4-二甲氧基肉桂酸(0.13%~1.28%)、阿魏酸(0.28~4.02%)、咖啡酸(0.18%~7.14%)和油酸(0.06%~7.56%),以咖啡酸的出现频率最高,在除了FJ-1、HN-3和HN-4的34个蜂胶样品中检测到。本研究还鉴定出Muco-肌醇、2-氨基-3-羟基苯甲酸甲酯、β-木栓醇、1,1-二-C-辛基,D-葡萄糖醇、羟基锥栗烯酮等40种化合物,均未在前期蜂胶研究中发现。同时检测到咖啡酸、3,4-二甲氧基肉桂酸、对香豆酸、阿魏酸等典型的杨树型蜂胶化合物,进一步证明了中国蜂胶为杨树型蜂胶。此外在两个山东蜂胶样品中鉴定出白桦脂醇,是桦树皮的主要成分,说明桦树可能是其胶源植物之一。主成分分析(Principal component analysis,PCA)结果表明,黄绿色和黄色蜂胶化学成分相似,并与黑色蜂胶有较大差异,热带蜂胶的糖类化合物含量较高,与其他气候带蜂胶差异显著。线性判别分析(Linear discriminant analysis,LDA)建立判别函数模型可有效区分不同颜色蜂胶,双氢酒石酸、白桦脂醇、α-古芸烯等19种成分在不同颜色蜂胶中含量差异较大。按气候带分类变量,建立判别函数模型,可有效区分热带蜂胶,其中α-古芸烯、D-阿拉伯糖、D-果糖等10种化合物在不同气候带蜂胶中含量差异较大。2.对37个中国EEP进行UV扫描,并对UV扫描数据进行PCA和LDA分析,并测定EEP的总酚、总黄酮含量、特定吸收率和清除DPPH自由基活性。结果显示,UV扫描数据的PCA提取了三个主成分,累计贡献为82.6%,黑色蜂胶与其他颜色蜂胶完全分离;UV扫描积分数据的PCA分析提取了三个主成分,累计贡献率为92.8%,可将不同品质的蜂胶进行一定区分;LDA对蜂胶样品的分类正确率为97.297%,交叉验证分析成功率为91.891%,该模型可对不同颜色蜂胶进行有效区分,可见多变量分析可有效区分不同颜色的蜂胶,由于不同颜色蜂胶存在品质差异,因此,UV结合多变量分析可将不同品质的蜂胶进行区分。同时,初步建立了总酚、总黄酮含量和清除DPPH自由基活性的多元线性回归模型。通过对EEP的成分分析,发现检测方法对蜂胶成分的鉴定有很大影响,硅烷化衍生结合GC-MS分析对蜂胶新成分的发现具有积极作用,结合多变量分析对研究蜂胶影响因素和化学组成的关系具有重要意义。另外UV结合多变量分析可将不同品质的蜂胶进行区分,为蜂胶品质的初步鉴定提供了研究思路。
[Abstract]:In order to further study the chemical composition of Chinese propolis, explore the differences between different climatic zones and color propolis, and obtain the characteristic compounds used for zoning. This study uses gas chromatography mass spectrometry (Gas chromatography-mass spectrometry, GC-MS) and silanizing derivatization for 37 propolis and 1 gum from 22 provinces of China The ethanol extracts were identified and analyzed by multivariable. In addition, the preliminary quality detection of propolis was made, the Ethanol extract of propolis (EEP) of 37 Chinese propolis (Ultraviolet spectrum, UV) was scanned by Ultraviolet spectrum, UV, and the EEP UV scanning data were obtained, and the multivariable analysis was carried out. The total phenol, total flavone content, specific absorption rate and DPPH radical scavenging activity of EEP were determined. The results were as follows: 1.GC-MS combined with silanylation was used to identify the ethanol extracts of 37 propolis and 1 gum. The results showed that 124 compounds, including 25 polyphenols, 8, were identified by 37 EEP. Terpenoids, 40 carbohydrates and their derivatives, and mainly monosaccharides, 7 fatty acids and their esters, 7 alcohols, 7 acids, 11 ketones, 2 ethers and 9 steroid compounds. In addition, 8 other types of compounds are identified. The main components are benzoic acid (0.13%~0.48%), 3,4- two methoxy cinnamic acid (0.13%~1.28%) and ferulic acid (0.28~4). .02%), caffeic acid (0.18%~7.14%) and oleic acid (0.06%~7.56%) have the highest frequency of occurrence of caffeic acid in 34 propolis samples, except FJ-1, HN-3 and HN-4. This study also identified 40 kinds of compounds such as Muco- inositol, 2- amino -3- hydroxybenzoate, beta cork alcohol, 1,1- two -C- octyl, D- glucosol, and hydroxy chestnut, and so on. In the propolis study, it was found that caffeic acid, 3,4- two methoxy cinnamic acid, and typical poplar type propolis compounds, such as coumaric acid and ferulic acid, further proved that Chinese propolis was poplar propolis. In addition, betulin was identified in two Shandong propolis samples, which is the main component of birch bark, indicating that birch may be its Principal component analysis (PCA) results show that the chemical composition of yellow green and yellow propolis is similar, and has great difference from black propolis. The sugar content of tropical propolis is higher, and the difference is significant with other climatological propolis. Linear discriminant analysis (Linear discriminant analysis, LDA) has been established. The difference function model can effectively distinguish different color propolis, dihydrotartaric acid, betulinol, alpha palaeolene and other 19 components in different color propolis. According to the climatic zone, the discriminant function model can be established to distinguish the tropical propolis effectively. Among them, 10 compounds, such as alpha palaeolene, D- Arabia sugar and D- fructose, are in different climate. 37 Chinese EEP were scanned by.2. with high content in propolis, and PCA and LDA analysis of UV scanning data were carried out. The total phenol, total flavonoids content, specific absorption rate and DPPH free radical activity were measured for the UV scanning data. The results showed that PCA of UV scanning data was extracted with three main components, and the cumulative contribution was 82.6%, black propolis and other color bees. Three main components were extracted by PCA analysis of UV scan integral data. The cumulative contribution rate was 92.8%, and different qualities of propolis could be distinguished. The classification accuracy of LDA to propolis samples was 97.297%, and the success rate of cross validation analysis was 91.891%. The model could distinguish the different color propolis effectively, and the multivariable component could be seen. In order to distinguish different colors of propolis effectively, because of the quality difference in different color propolis, UV combined with multivariate analysis can distinguish different qualities of propolis. At the same time, the multiple linear regression model of total phenol, total flavone content and DPPH free radical scavenging activity was established. The detection method was found through the analysis of the components of EEP. It has a great influence on the identification of the composition of propolis. Silane derivatization and GC-MS analysis have a positive effect on the discovery of new propolis. Combined with multivariate analysis, it is of great significance to study the relationship between the influence factors and chemical composition of propolis. In addition, UV can be used to distinguish the different quality propolis and the quality of propolis by the combination of multivariate analysis. Step identification provides research ideas.

【学位授予单位】：南昌大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O657.63;S896.6

【参考文献】