The volatile compounds emitted from Mosla chinensis Maxim were analyzed by headspace solid-phase micro- extraction （HS-SPME） and headspace liquid-phase microextraction （HS-LPME） combined with gas chromatography-ma...The volatile compounds emitted from Mosla chinensis Maxim were analyzed by headspace solid-phase micro- extraction （HS-SPME） and headspace liquid-phase microextraction （HS-LPME） combined with gas chromatography-mass spectrometry （GC-MS）. The main volatiles from Mosla chinensis Maxim were studied in this paper. It can be seen that 61 compounds were separated and identified. Forty-nine volatile compounds were identified by SPME method, mainly including myrcene, a-terpinene, p-cymene, （E）-ocimene, thymol, thymol acetate and （E）-fl-farnesene. Forty-five major volatile compounds were identified by LPME method, including a-thujene, a-pinene, camphene, butanoic acid, 2-methylpropyl ester, myrcene, butanoic acid, butyl ester, a-terpinene, p-cymene, （E）-ocimene, butane, 1,1-dibutoxy-, thymol, thymol acetate and （E）-fl-farnesene. After analyzing the volatile compounds, multiple linear regression （MLR） method was used for building the regression model. Then the quantitative structure-retention relationship （QSRR） model was validated by predictive-ability test. The prediction results were in good agreement with the experimental values. The results demonstrated that headspace SPME-GC-MS and LPME-GC-MS are the simple, rapid and easy sample enrichment technique suitable for analysis of volatile compounds. This investigation provided an effective method for predicting the retention indices of new compounds even in the absence of the standard candidates.展开更多
目的:研究有机溶剂及二氧化碳超临界萃取提取石香薷挥发油的提取条件,对比不同方法提取的挥发油成分上的差异。方法:有机溶剂和二氧化碳超临界萃取提取石香薷挥发油,成分分析采用GC-MS。结果:有机溶剂法提取石香薷挥发油的最佳提取条件...目的:研究有机溶剂及二氧化碳超临界萃取提取石香薷挥发油的提取条件,对比不同方法提取的挥发油成分上的差异。方法:有机溶剂和二氧化碳超临界萃取提取石香薷挥发油,成分分析采用GC-MS。结果:有机溶剂法提取石香薷挥发油的最佳提取条件为:提取总时间210 m in,溶剂与原料的投放总比例8∶1(m l∶g),提取温度65℃,提取率可达1.83%。超临界CO2法萃取石香薷挥发油,萃取率为3.4%。GC-MS分析鉴定结果表明:超临界CO2法萃取的石香薷挥发油主要成分为百里香酚,香荆芥酚,对聚伞花素,葎草烯等,其中百里香酚含量最高,占挥发油总量的56.25%,其次是香荆芥酚为19.21%;有机溶剂提取的挥发油中百里香酚和香荆芥酚的含量分别为58.33%和22.54%。结论:有机溶剂提取与超临界提取各具优点,有机溶剂法提取百里香酚和香荆芥酚含量高于超临界提取法,超临界法提取成分则多于有机溶剂提取法,本实验采用的超临界提取条件下有10种化合物首次在石香薷挥发油中发现。展开更多
基金Project supported by the Natural Science Foundation Programof Zhejiang Province （No. Y407308）, the Ministry of Science and Technology of Zhejiang Province （No. 201 OR 10044） and the Sprout Talented Project Program of Zhejiang Province （No. 2008R40G2020019）.
文摘The volatile compounds emitted from Mosla chinensis Maxim were analyzed by headspace solid-phase micro- extraction （HS-SPME） and headspace liquid-phase microextraction （HS-LPME） combined with gas chromatography-mass spectrometry （GC-MS）. The main volatiles from Mosla chinensis Maxim were studied in this paper. It can be seen that 61 compounds were separated and identified. Forty-nine volatile compounds were identified by SPME method, mainly including myrcene, a-terpinene, p-cymene, （E）-ocimene, thymol, thymol acetate and （E）-fl-farnesene. Forty-five major volatile compounds were identified by LPME method, including a-thujene, a-pinene, camphene, butanoic acid, 2-methylpropyl ester, myrcene, butanoic acid, butyl ester, a-terpinene, p-cymene, （E）-ocimene, butane, 1,1-dibutoxy-, thymol, thymol acetate and （E）-fl-farnesene. After analyzing the volatile compounds, multiple linear regression （MLR） method was used for building the regression model. Then the quantitative structure-retention relationship （QSRR） model was validated by predictive-ability test. The prediction results were in good agreement with the experimental values. The results demonstrated that headspace SPME-GC-MS and LPME-GC-MS are the simple, rapid and easy sample enrichment technique suitable for analysis of volatile compounds. This investigation provided an effective method for predicting the retention indices of new compounds even in the absence of the standard candidates.
文摘目的:研究有机溶剂及二氧化碳超临界萃取提取石香薷挥发油的提取条件,对比不同方法提取的挥发油成分上的差异。方法:有机溶剂和二氧化碳超临界萃取提取石香薷挥发油,成分分析采用GC-MS。结果:有机溶剂法提取石香薷挥发油的最佳提取条件为:提取总时间210 m in,溶剂与原料的投放总比例8∶1(m l∶g),提取温度65℃,提取率可达1.83%。超临界CO2法萃取石香薷挥发油,萃取率为3.4%。GC-MS分析鉴定结果表明:超临界CO2法萃取的石香薷挥发油主要成分为百里香酚,香荆芥酚,对聚伞花素,葎草烯等,其中百里香酚含量最高,占挥发油总量的56.25%,其次是香荆芥酚为19.21%;有机溶剂提取的挥发油中百里香酚和香荆芥酚的含量分别为58.33%和22.54%。结论:有机溶剂提取与超临界提取各具优点,有机溶剂法提取百里香酚和香荆芥酚含量高于超临界提取法,超临界法提取成分则多于有机溶剂提取法,本实验采用的超临界提取条件下有10种化合物首次在石香薷挥发油中发现。
