基于电子鼻和HS-GC-MS分析茶芎酒制前后挥发性成分变化
Analysis of Changes on Volatile Components of Ligusticum sinense cv.Chaxiong Rhizome Before and After Wine Processing Based on Electronic Nose and HS-GC-MS
张文 1郑鹏 1张江山 2肖小林 3吴早丹 4辛力 1龚文慧 1张金莲1
作者信息
- 1. 江西中医药大学药学院,南昌 330004
- 2. 江西中医药大学药学院,南昌 330004;江西景德中药股份有限公司,江西景德镇 333302
- 3. 江西景德中药股份有限公司,江西景德镇 333302
- 4. 江西肿瘤医院,南昌 330029
- 折叠
摘要
目的:通过比较茶芎生品与酒洗品、酒炒品挥发性成分的组成和含量差异,考察酒制对茶芎挥发性成分的影响,为茶芎及其炮制品的质量标准制订提供依据.方法:采用电子鼻识别茶芎、酒洗茶芎和酒炒茶芎的气味,联合顶空气相色谱-质谱法(HS-GC-MS)检测茶芎生品及2种酒制品的挥发性成分,采用峰面积归一化法测定各成分的相对质量分数,通过SIMCA 14.1软件对所得样品数据进行主成分分析(PCA)及正交偏最小二乘法-判别分析(O PLS-DA),根据变量重要性投影(VIP)值＞1筛选得到茶芎生品与酒洗茶芎和酒炒茶芎的差异性成分.结合Pearson相关性分析探究挥发性差异风味成分与电子鼻传感器之间的关联.结果:电子鼻检测结果显示,茶芎、酒洗茶芎与酒炒茶芎气味差异明显,主要涉及传感器S2、S4、S5、S6、S11、S12、S13.从茶芎及其酒制品中共鉴定出62个化合物,其中茶芎生品、酒炒茶芎、酒洗茶芎分别鉴定出46、50、51个化合物.茶芎生品与酒炒茶芎间存在21个差异性成分,经炮制后其中10个成分含量上升,11个成分含量下降;茶芎生品与酒洗茶芎之间存在20个差异性成分,经炮制后其中11个成分含量上升,9个成分含量下降;酒洗茶芎与酒炒茶芎间存在17个差异性成分,与酒洗茶芎比较,酒炒茶芎中13个成分含量上升,4个成分含量下降.苯酞类成分含量上升趋势酒洗较酒炒更明显,但总挥发性成分含量酒炒高于酒洗.相关性分析显示,电子鼻7个差异传感器与24个差异挥发性成分间存在不同程度的相关性,主要为苯酞类和烯烃类成分.结论:茶芎酒制后气味与挥发性成分含量发生了明显变化,其中正丁基苯酞、z-正丁烯基苯酞、E-藁本内酯等成分可作为茶芎酒制前后挥发性成分的候选差异性标志物.
Abstract
Objective:By comparing the composition and content of volatile components in raw products,wine-washed products and wine-fried products of Ligusticum sinense cv.Chaxiong rhizome(LSCR),to investigate the influence of wine processing on the volatile components of LSCR,in order to provide a basis for the development of quality standards for LSCR and its processed products.Methods:Electronic nose was used to identify the odors of LSCR,wine-washed and wine-fried LSCR,and their volatile components were detected by headspace gas chromatography-mass spectrometry(HS-GC-MS),and the relative mass fractions of these components were determined by peak area normalization method.Principal component analysis(PC A)and orthogonal partial least squares-discriminant analysis(OPLS-DA)were performed on the obtained sample data by SIMCA 14.1 software,and the differential components of LSCR,wine-washed and wine-fried LSCR were screened according to the variable importance in the projection(VIP)value＞1.Pearson correlation analysis was used to explore the relationship between volatile differential flavor components and electronic nose sensors.Results:Electronic nose detection results showed that there were significant differences in the odors of LSCR,wine-washed and wine-fried LSCR,mainly reflected in the sensors S2,S4,S5,S6,Sil,S12,S13.And a total of 62 compounds were identified from LSCR and its wine-processed products,among which 46,50 and 51 compounds were identified from LSCR,wine-fried and wine-washed LSCR,respectively.There were 21 differential components between the raw products and wine-fried products,of which 10 components were increased and 11 were decreased after processing.There were 20 differential components between the raw products and wine-washed products,of which 11 constituents increased and 9 decreased after processing.There were 17 differential components between the wine-wash products and wine-fried products.Compared with the wine-washed products,the contents of 13 components in the wine-fried products increased,and the contents of 4 components decreased.The increasing trend of the content of phthalides in the wine-washed products was more obvious than that in the wine-fried products,but the content of total volatile components was higher in the wine-fried products than the wine-washed products.Correlation analysis showed that there were different degrees of correlation between the 7 differential sensors of electronic nose and 24 differential volatile components,mainly phthalides and olefins.Conclusion:The odor and the content of volatile components in LSCR changed obviously after wine processing,and n-butylphthalide,Z-butylidenephthalide and E-ligustilide can be used as the candidate differential markers of volatile components in LSCR before and after wine processing.
关键词
茶芎/酒制/电子鼻/顶空气相色谱-质谱法(HS-GC-MS)/挥发性成分/差异性成分/相关性分析Key words
Ligusticum sinense cv.Chaxiong rhizome/wine processing/electronic nose/headspace gas chromatography-mass spectrometry(HS-GC-MS)/volatile components/differential components/correlation analysis引用本文复制引用
出版年
2025
国家科技期刊平台
NSTL
万方数据