世界科学技术-中医药现代化
世界科學技術-中醫藥現代化
세계과학기술-중의약현대화
WORLD SCIENCE AND TECHNOLOGY-MODERNIZATION OF TRADITIONAL CHINESE MEDICINE
2014年
9期
1942-1945
,共4页
弓建红%张艳丽%冯卫生%匡海学%郑晓珂%董梦珂%潘贝
弓建紅%張豔麗%馮衛生%劻海學%鄭曉珂%董夢珂%潘貝
궁건홍%장염려%풍위생%광해학%정효가%동몽가%반패
南葶苈子%挥发油GC-MS%保留指数
南葶藶子%揮髮油GC-MS%保留指數
남정력자%휘발유GC-MS%보류지수
Seeds ofDeseurainia sophia%essential oil%GC-MS%retention index
目的:首次运用GC-MS结合保留指数分析南葶苈子挥发油成分,为进一步研究南葶苈子挥发油提供实验依据。方法:采用水蒸气蒸馏法提取挥发油,用气相色谱-质谱联用(GC-MS)技术并结合保留指数对其进行分析鉴定。结果:采用GC-MS分析检测出33个组分,利用MS结合保留指数定性,鉴定出其中28个成分,占总检出化合物的99.91%。其中含量较高的组分为3-亚甲基-壬烷,占68.14%,其次为嘧啶(29.32%)、2-庚烯醛(0.58%)、哌啶-3-甲酸甲酯(0.43%)、4-氧代丁腈(0.31%)、8-氯-新异长叶烯(0.25%)等。结论:该方法可以提高定性结果的准确性。
目的:首次運用GC-MS結閤保留指數分析南葶藶子揮髮油成分,為進一步研究南葶藶子揮髮油提供實驗依據。方法:採用水蒸氣蒸餾法提取揮髮油,用氣相色譜-質譜聯用(GC-MS)技術併結閤保留指數對其進行分析鑒定。結果:採用GC-MS分析檢測齣33箇組分,利用MS結閤保留指數定性,鑒定齣其中28箇成分,佔總檢齣化閤物的99.91%。其中含量較高的組分為3-亞甲基-壬烷,佔68.14%,其次為嘧啶(29.32%)、2-庚烯醛(0.58%)、哌啶-3-甲痠甲酯(0.43%)、4-氧代丁腈(0.31%)、8-氯-新異長葉烯(0.25%)等。結論:該方法可以提高定性結果的準確性。
목적:수차운용GC-MS결합보류지수분석남정력자휘발유성분,위진일보연구남정력자휘발유제공실험의거。방법:채용수증기증류법제취휘발유,용기상색보-질보련용(GC-MS)기술병결합보류지수대기진행분석감정。결과:채용GC-MS분석검측출33개조분,이용MS결합보류지수정성,감정출기중28개성분,점총검출화합물적99.91%。기중함량교고적조분위3-아갑기-임완,점68.14%,기차위밀정(29.32%)、2-경희철(0.58%)、고정-3-갑산갑지(0.43%)、4-양대정정(0.31%)、8-록-신이장협희(0.25%)등。결론:해방법가이제고정성결과적준학성。
The analysis of essential oil in seeds ofDeseurainia sophia provided an experimental basis for further research on essential oil activity test at the first time. Essential oil was extracted by steam distillation method. Analysis and identification were made by gas chromatography-mass spectrometry (GC-MS) technology in combination with retention indices. A total of 33 components in seeds ofD. sophia were detected by GC-MS and 28 compounds were identified by MS in combination with Kovats retention index. The compounds with high contents were as follows: 3-methylene-nonane (68.14%), 1,3-diazine (29.32%), 2-n-butylacrolein (0.58%), methyl nipecotate (0.43%), 4-oxo-butanenitrile (0.31%), 8-chloro-neoisol-ongifolene (0.25%) and so on. It was concluded that 28 volatile components were identified by GC-MS combined with retention indices. The total detected components were 99.91%. This method was able to improve the accuracy of qualitative detection results.