scholarly journals Regions in China identification and quality control of radix Codonopsis by chemical fingerprint: Evaluation of lobetyolin from different cultivated

2006 ◽  
Vol 6 (4) ◽  
pp. 293-299 ◽  
Keyword(s):  
Quality Control ◽  
Chemical Fingerprint

Chemical fingerprint analysis for quality control of Fructus Aurantii Immaturus based on HPLC-DAD combined with chemometric methods

2010 ◽  
Vol 2 (12) ◽  
pp. 2002 ◽  
Author(s):  
Xiaona Xu ◽  
Junhui Jiang ◽  
Yizeng Liang ◽  
Lunzhao Yi ◽  
Jinle Cheng
Keyword(s):  
Quality Control ◽  
Chemometric Methods ◽  
Fingerprint Analysis ◽  
Chemical Fingerprint

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.

Chemical Fingerprint for Identification and Quality Control of Saccharides in Danhong Injection Based on HPLC-ELSD with Chemometrics

2019 ◽  
Vol 35 (5) ◽  
pp. 782-787 ◽  
Author(s):  
Hao Li ◽  
Zhenzhong Yang ◽  
Jiaojiao Wang ◽  
Yun An ◽  
Chenchen Wang ◽  
...  
Keyword(s):  
Quality Control ◽  
Chemical Fingerprint ◽  
Danhong Injection

Chemical fingerprint analysis for quality control and identification of Ziyang green tea by HPLC

2015 ◽  
Vol 171 ◽  
pp. 405-411 ◽  
Author(s):  
Xiaoye He ◽  
Jianke Li ◽  
Wei Zhao ◽  
Run Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Control ◽  
Green Tea ◽  
Fingerprint Analysis ◽  
Chemical Fingerprint

Quantitative and chemical fingerprint analysis for quality control of Rhizoma Coptidischinensis based on UPLC-PAD combined with chemometrics methods

Phytomedicine ◽  
2009 ◽  
Vol 16 (10) ◽  
pp. 950-959 ◽  
Author(s):  
Wei-Jun Kong ◽  
Yan-Ling Zhao ◽  
Xiao-He Xiao ◽  
Cheng Jin ◽  
Zu-Lun Li
Keyword(s):  
Quality Control ◽  
Fingerprint Analysis ◽  
Chemical Fingerprint

scholarly journals Traceability and Quality Control in Traditional Chinese Medicine: From Chemical Fingerprint to Two-Dimensional Barcode

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Yong Cai ◽  
Xiwen Li ◽  
Mei Li ◽  
Xiaojia Chen ◽  
Hao Hu ◽  
...  
Keyword(s):  
Quality Control ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
High Performance ◽  
Information Storage ◽  
Two Dimensional ◽  
Data Format ◽  
Chemical Fingerprint ◽  
Chemical Fingerprints ◽  
Chemical Fingerprinting

Chemical fingerprinting is currently a widely used tool that enables rapid and accurate quality evaluation of Traditional Chinese Medicine (TCM). However, chemical fingerprints are not amenable to information storage, recognition, and retrieval, which limit their use in Chinese medicine traceability. In this study, samples of three kinds of Chinese medicines were randomly selected and chemical fingerprints were then constructed by using high performance liquid chromatography. Based on chemical data, the process of converting the TCM chemical fingerprint into two-dimensional code is presented; preprocess and filtering algorithm are also proposed aiming at standardizing the large amount of original raw data. In order to know which type of two-dimensional code (2D) is suitable for storing data of chemical fingerprints, current popular types of 2D codes are analyzed and compared. Results show that QR Code is suitable for recording the TCM chemical fingerprint. The fingerprint information of TCM can be converted into data format that can be stored as 2D code for traceability and quality control.

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