基于高分辨质谱-相依成分分析的怀菊花泡饮过程分析
Analysis of brewing process of Huai chrysanthemum based on high resolution mass spectrometry and dependent component analysis
-
摘要: 采用高分辨质谱法(HRMS)对菊花泡饮过程分析,以准确分子量直接定性菊花泡饮过程中27种典型成分,结合其典型成分质谱响应强度,得到菊花泡饮过程的高分辨质谱指纹图.进一步以相依成分分析(DCA)解析,得到能够体现菊花泡饮过程典型化学成分特征的3组相依组分(DC),并以DC相对浓度变化表征菊花泡饮过程.研究结果表明,3组DC与挥发油、氨基酸、黄酮类为主要特征的菊花中典型成分相对应,不同类型的化合物质谱相应值具有较大的差异,菊花泡饮时前2次相依组分相对含量变化较大;冲泡5次后菊花中溶于水的活性成分的种类明显减少、相对含量也明显降低而不再具有饮用价值.HRMS-DCA为菊花泡饮过程高分辨质谱指纹图谱解析利用提供了新途径.Abstract: Using high resolution mass spectrometry (HRMS) to analyze the brewing process of Huai chrysanthemum,27 typical components in drinking process were directly qualified with accurate molecular weight,and the high resolution mass spectrometric (MS) fingerprints of chrysanthemum tea process were obtained combined with the mass spectrometric response strength of the components. The fingerprints were processed by dependent component analysis (DCA),and 3 groups of dependent components (DCs) that can used to characterize the characteristics of the typical components in the drink chrysanthemum bubble and the brewing process. Research results showed that the 3 groups of DCs are corresponding to volatile oil, amino acids,and flavonoids as the main components of the Huai chrysanthemum,there are great differences among the response MS values of of different components. The relative concentration of DCs obviously de-creased during the first 2 times of the brewing process; while after 5 times brewing,the variation of DCs are negligible and there is no drinking value. HRMS-DCA provides a new way to resolve HRMS fingerprints of chrysanthemum brewing process.
-
-
[1]
谢媛媛,袁丹,田慧芳,等.怀菊花化学成分的研究[J].中国药物化学杂志,2009,19(4):270.
-
[3] Alvarez Castellanos P P,Bishop C D,Pascual Villalobs M J.Antifungal activity of the essential oil of flowerheads of garland chrysanthemum (Chrysanthemum coronarium) against agricultural pathogens[J].Phytochemistry,2001,57(7):99.
-
[6] Wang Guoqing,Ding Qingzhu,Hou Zhenyu.Independent component analysis and its applications in signal processing for analytical chemistry[J].TrAC-Trends in Analytical Chemistry,2008,27:368.
-
[8] Wang Guoqing,Dong Chunhong,Shang Yukuan,et al.Characterization of radix rehmanniae processing procedure using FT-IR spectroscopy through nonnegative independent component analysis[J].Analytical and Bioanalytical Chemistry,2009,394(3):827.
-
[9] Wang Guoqing,Hou Zhenyu,Peng Yang,et al.Adaptive kernel independent component analysis and UV spectrometry applied to characterize the procedure for processing prepared rhubarb roots[J].Analyst,2011,136:4552.
-
[6]
[11] Li Rui,Li Hongwei,Wang Fasong.Dependent component analysis:Concepts and algorithms[J].Journal of Computers,2010,5(4):589.
-
[7]
[12] Kopriva I,Peršin A,Puizina-Ivic N,et al.Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images[J].Journal of Photochemistry and Photobiology B,2010,100(1-2):10.
-
[8]
[13] Hyvärinen A,Shimizu S A.Quasi-stochastic gradient algorithm for variance-dependent component analysis[J].Lecture Notes in Computer Sciences,2006,41(32):211.
-
[1]
计量
- PDF下载量: 35
- 文章访问数: 1044
- 引证文献数: 0