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超声辅助提取华细辛挥发油的成分分析及提取动力学研究

Chemical Component Analysis of Volatile Oil in Asarumsieboldii Miq. Using Ultrasonic Assisted Extraction and Study of Kinetics for Extraction

【作者】 潘红亮

【导师】 欧阳天贽;

【作者基本信息】 武汉理工大学 , 物理化学, 2011, 硕士

【摘要】 细辛为我国传统常用中药,其挥发油具有抗炎、镇咳、镇痛等药理活性。主要药效成分为甲基丁香酚,具有抗组胺作用。本文以华细辛挥发油组分为研究对象,以其化学成分分析、优选提取方法及优化提取工艺为目标,采用气相色谱-质谱联用(GC-MS)技术,研究水蒸气蒸馏法(SD)和超声辅助提取法(UAE)提取华细辛挥发油的化学成分,分析比较不同提取方法对华细辛挥发油化学成分的提取效果,正交法优化UAE法提取挥发油中甲基丁香酚的工艺条件,建立了SD和UAE法提取挥发油及甲基丁香酚的动力学模型。研究结果如下:1.采用GC-MS联用技术对SD和UAE法提取华细辛挥发油的组分进行分离鉴定,共鉴定了24种化学成分,鉴定成分占SD和UAE法提取成分总峰面积的比例分别为90.10和91.31%。两种方法提取出的主要成分为优葛缕酮、3,5-二甲氧基甲苯、黄樟醚、甲基丁香酚、十五烷、卡枯醇、N-异丁基十二碳四烯酰胺、芝麻素等。UAE法所得部分成分质量分数比SD法提取的高1.2~24倍,其中芝麻素和6-十八烯酸的质量分数分别相差24及21倍。UAE法对华细辛挥发油中热不稳定和高沸点化合物有更好的提取效果。2.正交试验法优化的UAE法提取华细辛挥发油中甲基丁香酚的最佳工艺条件为:料液比1:40,提取温度60℃,提取时间40min,浸泡时间3h。料液比对提取结果的影响最大,其次是提取温度和提取时间,浸泡时间对甲基丁香酚的提取影响最小3.采用SD法提取华细辛挥发油的实验数据,对提取挥发油过程的动力学模型Vt=Vt∞(1-e-kt)进行拟合,表明动力学模型可较好描述华细辛挥发油的SD法提取过程。通过拟合UAE法提取挥发油中甲基丁香酚过程的两种动力学模型,相比有效成分扩散控制动力学模型,细胞破碎控制动力学模型可以更好的描述UAE法提取过程。

【Abstract】 The plants of Asarum had a long centuries-old history as crude drugs in China, its volatile oil was used in the treatment of anti-inflammatory, antitussive, antalgic and so on. It was implied that methyleugenol was the effective substance for antihistamine activity in the volatile oil of Asarum. This article mainly studied the object of the chemical constituents of volatile oil in Asarum sieboldii Miq, aimed at analying chemical composition, finding the best extraction method and the optimum extraction process. In present work, both the steam distillation(SD) and ultrasonic assisted extraction(UAE) methods were applied to extract the volatile oil from Asarum sieboldii Miq.respectively. The gas chromatography-mass spectrometry (GC-MS) analysis showed that two approaches afford the same constituents of the volatile oil. The efficiency and chemical constituents of ultrasonic assisted extraction were compared with that of traditional steam distillation. The optimum extraction process for volatile oil obtained by ultrasonic assisted extraction method was investigated by the orthogonal design, has established two dynamics model by using steam distillation and ultrasonic assisted extraction to extract the methyleugenol from volatile oil. The findings are as follows:1.24 compounds were identified, represented 90.10% and 91.31% of the total volatile oil respectively, which include mainly eucarvone,3,5-dimethoxytoluene, safrole, methyleugenol, pentadecane, kakuol, N-isobutyldodecatetraenamide, sesamin and so on. However, for partial ingredient mass fractions, the ultrasonic assisted extraction was larger than that by the steam distillation method in the range of 1.2-24 times, e.g. the mass fractions for sesamin and 6-octadecenoic acid obtained by the ultrasonic assisted extraction were 24 and 21 times larger than that by the steam distillation method, respectively. It indicates that for the thermal instability and high boiling compounds in the volatile oil of Asarum sieboldii Miq., the ultrasonic assisted extraction is superior to the steam distillation method.2. The optimum extraction process for volatile oil obtained by ultrasonic assisted extraction was as follows:ratio of solid to liquid of 1:40, extraction temperature of 60℃, extraction time of 40 min and soak time of 3 h. The sequence of factors according to the effects was as follows:ratio of solid to liquid>extraction temperature> extraction time>soak time.3. Used steam distillation to extract the volatile oil from Asarum sieboldii Miq. and used the the empirical datum to Linear fit according to dynamics model, the volatile oil extraction quantity which was calculates with the fitting parameter consistents with the experimental data. It indicates that dynamics model may describe the process of using steam distillation to withdraw the volatile oil in Asarum sieboldii Miq. Through fiting the two dynamics model of using ultrasonic assisted extraction to extract methyleugenol from volatile oil. It indicates that for the methyleugenol of volatile oil in Asarum sieboldii Miq., the cell disruption control model is superior to the diffusion control dynamics model.

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