scholarly journals Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Platycladi cacumen by Ultra-performance Liquid Chromatography Coupled with Hierarchical Cluster Analysis

2017 ◽  
Vol 56 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Mingqiu Shan ◽  
Sam Fong Yau Li ◽  
Sheng Yu ◽  
Yan Qian ◽  
Shuchen Guo ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Liquid Chromatography ◽  
Quantitative Analysis ◽  
Hierarchical Cluster Analysis ◽  
Quality Evaluation ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Chemical Fingerprint

Simultaneous Determination of 17 Constituents of Chinese Wild Radix Salvia miltiorrhiza from Different Geographical Areas by Ultra-High Performance Liquid Chromatography Coupled to Triple Quadrupole Mass Spectrometry

2020 ◽  
Vol 16 (3) ◽  
pp. 280-290
Author(s):  
Xiao-Dan Zhang ◽  
Ye-Sheng Cen ◽  
Yan-Ge Yu ◽  
Zhe-Chen Qi ◽  
Dong-Feng Yang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cluster Analysis ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Hierarchical Cluster Analysis ◽  
High Performance ◽  
Salvia Miltiorrhiza ◽  
Hierarchical Cluster ◽  
Relative Standard ◽  
Radix Salvia Miltiorrhiza

Background and Objective: Radix Salvia miltiorrhiza (RSM) has been used clinically for the prevention and treatment of cardiovascular diseases; therefore, it is important to strengthen its quality management. Considering multiple constituents when assessing RSM quality is essential. We established a simple, rapid method to identify and quantify the major bioactive constituents in RSM using ultra high performance liquid chromatography (UPLC) coupled to a triple quadruple mass spectrometry (QqQ-MS). Methods: We analyzed 17 markers from 50 batches of wild S. miltiorrhiza samples that were collected from different locations in China. The ultrasonic extracts of all samples were determined using the UPLC-QqQ-MS method and were assessed by hierarchical cluster analysis (HCA). Results: We used this method to analyze 50 sample batches of the 17 compounds and obtained results with excellent linearity (R2, 0.9915-0.9997), precision (relative standard deviation, RSD, 0.15-1.94%), repeatability (RSD, 1.28-4.71%), stability (RSD, 0.97-5.60%) and recovery (RSD, 0.305-6.40%). The hierarchical cluster analysis was used to classify the 50 samples based on the characteristics of the 17 compound markers. Conclusion: We demonstrated that the developed method was simple, reproducible and sensitive, and it is capable of systematic and scientific evaluation for quality control of RSM. The HCA clearly demonstated that the RSM samples from different locations were significantly different and the quality of wild Radix S. miltiorrhiza could generally be judged according to its geographical origin.

scholarly journals Evaluation and Discrimination of Cortex Magnoliae Officinalis Produced in Zhejiang Province (Wen-Hou-Po) by UPLC-DAD-TOF-MS Fingerprint

2010 ◽  
Vol 5 (10) ◽  
pp. 1934578X1000501 ◽  
Author(s):  
Lin Wang ◽  
Ke Yuan ◽  
Wei-Wu Yu ◽  
Jing Wang
Keyword(s):  
Cluster Analysis ◽  
Quality Control ◽  
Hierarchical Cluster Analysis ◽  
Cross Validation ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Zhejiang Province ◽  
Source Discrimination ◽  
Tof Ms ◽  
Fingerprint Data

An ultra performance liquid chromatography tandem TOF mass spectrometric (UPLC-DAD-TOF-MS) fingerprinting method was developed for the quality control and source discrimination of Cortex magnoliae officinalis produced in Zhejiang Province (Wen-Hou-Po). Twelve samples of Wen-Hou-Po collected from two species in five areas in Zhejiang Province of China were used to establish the fingerprint. Data were evaluated statistically using similarity analysis, hierarchical cluster analysis (HCA) and discriminant analysis (DA) in order to establish a similarity standard of fingerprint for quality control of Wen-Hou-Po, then to classify the Wen-Hou-Po samples and to identify key categorizing parameters. The similarity indexes were all above 0.95 between the reference chromatogram and that of each sample. By comparing the UV and MS data with those of the authentic standards and literature, nine main peaks in the fingerprints were identified. The result of hierarchical cluster analysis showed that the samples from two species in five areas could be divided into two distinct groups (the same as the groups of the samples divided by their species) based on their compositional fingerprints. A rapid and convenient discriminant function was then established to discriminate the species of unknown Wen-Hou-Po, and the cross validation result was 100%. In this study, the methods established are reliable, and could be used to evaluate the quality and to identify the species of Wen-Hou-Po in the future.

scholarly journals Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

Molecules ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 432
Author(s):  
Nduvho Mulaudzi ◽  
Chinedu P. Anokwuru ◽  
Sidonie Y. Tankeu ◽  
Sandra Combrinck ◽  
Weiyang Chen ◽  
...  
Keyword(s):  
Quality Control ◽  
Liquid Chromatography ◽  
Bioactive Compounds ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Retardation Factor ◽  
Root Bark ◽  
High Concentration ◽  
Chemical Fingerprint

Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-β-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.

scholarly journals FLAVONOID DISTRIBUTION IN FOUR VARIETIES OF Ficus deltoidea (JACK)

2016 ◽  
Vol 11 (1) ◽  
pp. 3314-3323 ◽  
Author(s):  
Syazwani Dzolin ◽  
Rohaya Ahmad ◽  
Mazatulikhma Mat Zain ◽  
Mohd Ikhwan Ismail
Keyword(s):  
Cluster Analysis ◽  
Liquid Chromatography ◽  
Mass Spectrometer ◽  
Aqueous Extract ◽  
Hierarchical Cluster Analysis ◽  
Radical Scavenging ◽  
Hierarchical Cluster ◽  
Aqueous Extracts ◽  
Ficus Deltoidea ◽  
Plant Parts

We have previously reported the antioxidant and neuroprotective activities of the aqueous extract of four varieties of Ficus deltoidea (Fd) (Moraceae) namely var kunstleri (Fdvk), var angustifolia (Fdva), var deltoidea (Fdvd) and var intermedia (Fdvi). In this study, flavonoid constituents in aqueous leaf and fig extracts of the four varieties were analyzed and characterized using liquid chromatography mass spectrometer quadrupole-time of flight (LCMS-Q-TOF) via hierarchical cluster analysis (HCA) technique. The HCA dendrogram revealed that the abundant flavonoids among the eight samples are epicatechin, quercetin-3-rutinoside, quercetin 5,4'-di-O-beta-D-glucopyranoside, myricetin and naringenin. The study found that the distribution of the flavonoids differed between the four varieties and varied within the plant parts. To date, the flavonoid distribution of the different plant parts of the four varieties has not been documented. A positive correlation was observed between flavonoid constituents present and radical scavenging activities of the aqueous extracts. 

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