用熵最小算法解析桂郁金挥发油GC-MS重叠谱

摘要

The essential oil from curcuma kwangsiensis was analyzed by gas chromatography–mass spectrometry, then the entropy minimization method was applied to analyze pure components in co-eluting chromatographic peaks and estimated pure components were identified by similarity search in NIST library combined with temperature programmed retention index method. Mass spectrometry data of components from curcuma kwangsiensis essential oil were compared with NIST library, 38 components were given. NIST library search on chromatographic peaks would result in misleading information,especially on those co-eluting peaks. Two co-eluting peaks at 1 106.52–1 108.38 s and 1 184 s were analyzed by entropy minimization method andfive pure compounds were gotten. The entropy minimization method can be used to deal with co-eluting chromatographic peaks and reconstruct pure component with better qualitative and quantitative analyses.%采用气相色谱–质谱(GC–MS)联用技术对桂郁金中提取的挥发油成分进行检测，同时用熵最小算法对其中的共流物色谱峰进行解析，并通过质谱库检索和程序升温保留指数相结合的方式对解析得到的各纯组分进行定性分析。将桂郁金挥发油各组分的质谱数据直接与美国国家标准及技术研究所(NIST)数据库进行比对，鉴定出38个化合物；在挥发油的色谱图中，存在一些因分离不完全而导致的共流物色谱峰，以保留时间为1106.52～1108.38 s及1184 s的色谱峰为例，经熵最小算法解析，共发现5个纯组分。采用熵最小算法可以清楚地对共流物色谱峰进行解析并得到所包含的各个纯组分，该法可提高复杂成分定性定量分析结果的准确性。