【摘要】 将GC-MS法与新近提出的用于二维数据比较和解析的交互移动窗口因子分析法(AMWFA)结合,对3种不同原植物来源的陈皮挥发油成分的共性和差异性进行分析,并对重叠峰进行解析,总共分辨出138个峰,定性出78个峰,其中共有组分44个.更多还原

【Abstract】 Components in volatile oils of traditional Chinese medicine are very complex. Many of them are main active ingredients. So, the two-dimensional data of volatile oils obtained by GC-MS form a very complicated analysis system with many overlapped peaks. Alternative moving window factor analysis(AMWFA) is a new method using to comparison and resolution of two-dimensional data. In this paper, GC-MS and AMWFA was combined to analyze the commonness and otherness of volatile oils in three Chenpi samples whose original plants are different. Seventy-eight of the 138 separated constituents in essential oils of Chenpi were identified and quantified by the developed method. There are 44 common components among them.更多还原