Quality Assessment of Fructus xanthii Based on Fingerprinting Using High-Performance Liquid Chromatography

2012 ◽  
Vol 95 (4) ◽  
pp. 1053-1058 ◽  
Author(s):  
Liu Yang ◽  
Zhijun Su ◽  
Xing Zeng ◽  
Xiong Li ◽  
Zhifeng Wu ◽  
...  
Keyword(s):  
Quality Assessment ◽  
High Performance ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Multicomponent System ◽  
Principal Component ◽  
Uv Spectra ◽  
Hplc Fingerprint ◽  
Hplc Profiles

Abstract Because almost every traditional Chinese medicine (TCM) is a multicomponent system, QC of TCMs always involves various difficulties. As a current popular quality assessment approach, focusing on qualitative and quantitative analysis of certain compounds contained in herbal medicine has been widely used for the sake of expediency rather than being a practical and realistic way. However, this method does not take the existence of other constituents into account. Comparatively, the chromatographic fingerprint of the components is a more suitable approach to holistically assess the quality of herbal drugs. Fructus xanthii is a well-known herbal drug listed in all editions of the Chinese Pharmacopoeia. However, there is no quality evaluation method given in its monograph, even for the above-mentioned expediency. This paper reports an HPLC fingerprinting method for quality evaluation of F. xanthii. The HPLC profiles of 27 batches of commercial samples were further analyzed using chemometric methods, including similarity evaluation and principal component analysis. As a result, the established HPLC fingerprint contained 23 characteristic peaks; therein, 13 peaks were unambiguously assigned by comparing their retention times and UV spectra with those of reference compounds, and five peaks were tentatively identified on the basis of their MS/MS fragmentation patterns and UV spectra. Moreover, it could be clearly observed that caffeoylquinic acid and its analogs predominate in F. xanthii. Except for three samples identified as outliers, 24 other commercial samples displayed similar HPLC profiles, indicating that the quality of the herbs from different markets is stable and consistent.

scholarly journals HPLC Fingerprint Combined with Quantitation of Main Effective Components and Chemometrics as an Efficient Method for Quality Evaluation of Oviductus Ranae

2017 ◽  
Vol 12 (9) ◽  
pp. 1934578X1701200 ◽  
Author(s):  
Shihan Wang ◽  
Yang Xu ◽  
Yanwei Wang ◽  
Zuying Lv ◽  
Qingyan Cui ◽  
...  
Keyword(s):  
High Performance ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Hierarchical Cluster ◽  
Liaoning Province ◽  
Hplc Fingerprint ◽  
Effective Components ◽  
Hplc Profiles ◽  
Oviductus Ranae

To ensure the highest quality of Oviductus Ranae products for consumers, an accurate, efficient, scientific and comprehensive evaluation method for assessing the quality of Oviductus Ranae was proposed in this paper. The fingerprint of Oviductus Ranae has been established based on the method of high performance liquid chromatography (HPLC). Oviductus Ranae from different habitats were analyzed by hierarchical cluster analysis (HCA). The HPLC profiles of fourteen batches of Oviductus Ranae showed 33 well-resolved common peaks in each chromatogram. Five of these were assigned to 1-methyl hydantoin, 7-ketocholesterol, 4-cholesten-3-one, cholesterol and stigmasterol. Contents of these five main effective components were determined in the meantime. Based on the HPLC profiles of all the samples, the reference HPLC fingerprint and similarity values were calculated by statistical software (SPSS 19.0). It was found that similarity value of all Oviductus Ranae samples were more than 0.85 and Oviductus Ranae from same habitats had similarity to some degree. In conclusion, the proposed method had good specificity, repeatability, stability and precision, which can provide a reference for the quality evaluation and identification of the medicine origin of Oviductus Ranae. Quantitation of effective components revealed that contents of five effective constituents in Oviductus Ranae obtained from Ji Lin province were the highest, followed by Hei Longjiang province and Liaoning province. The results of HCA showed that samples classified into one group were associated with their habitats. HPLC fingerprint combined with quantitation of main effective compounds and data analysis techniques can be an efficient and useful method for monitoring the quality of Oviductus Ranae.

scholarly journals Quality Evaluation of Atractylodis Macrocephalae Rhizoma Based on Combinative Method of HPLC Fingerprint, Quantitative Analysis of Multi-Components and Chemical Pattern Recognition Analysis

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7124
Author(s):  
Cheng Zheng ◽  
Wenting Li ◽  
Yao Yao ◽  
Ying Zhou
Keyword(s):  
Pattern Recognition ◽  
High Performance ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Principal Component ◽  
Hplc Fingerprint ◽  
Atractylenolide I ◽  
Chemical Pattern ◽  
Pattern Recognition Analysis ◽  
Chemical Pattern Recognition

A method for the quality evaluation of Atractylodis Macrocephalae Rhizoma (AMR) based on high-performance liquid chromatography (HPLC) fingerprint, HPLC quantification, and chemical pattern recognition analysis was developed and validated. The fingerprint similarity of the 27 batches of AMR samples was 0.887–0.999, which indicates there was very limited variance between the batches. The 27 batches of samples were divided into two categories according to cluster analysis (CA) and principal component analysis (PCA). A total of six differential components of AMR were identified in the partial least-squares discriminant analysis (PLS-DA), among which atractylenolide I, II, III, and atractylone counted 0.003–0.045%, 0.006–0.023%, 0.001–0.058%, and 0.307–1.175%, respectively. The results indicate that the quality evaluation method could be used for quality control and authentication of AMR.

scholarly journals Chromatographic Fingerprint Combined with Content of Asperosaponin VI and Antioxidant Activity for Quality Evaluation of Wine-fried Dipsaci Radix

2014 ◽  
Vol 9 (6) ◽  
pp. 1934578X1400900 ◽  
Author(s):  
Li Song ◽  
Shaoyun Wang ◽  
Xiaoju Duan ◽  
Xinhua Liu ◽  
Zhaofang Li ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
High Performance ◽  
Quality Evaluation ◽  
Heating Temperature ◽  
Processing Condition ◽  
Influential Factor ◽  
Multivariate Statistical ◽  
Factors Affecting ◽  
Hplc Fingerprint

Dipsaci Radix, the dry root of Dipsacusasper Wall. ex Henry, is a commonly used traditional Chinese medicine (TCM). A novel comprehensive method was proposed for quality evaluation of wine-fried Dipsaci Radix by an integrated data including three aspects of information: high performance liquid chromatography (HPLC) fingerprint, asperosaponin VI content and antioxidant activity (AA). Various indicators including fingerprint similarity, asperosaponin VI content and AA were respectively employed for quality assessment of processed Dipsaci Radix samples. Results showed that considerable differences existed in quality of processed samples with different processing conditions according to three indicators. Among the factors affecting quality of wine-fried Dipsaci Radix, heating temperature was the most influential factor based on analysis of variance (ANOVA), and should be cautiously controlled. The three evaluation indicators respectively used for optimization of processing technology suggested different optimal conditions of wine-frying. Therefore, a combined indicator based on three evaluation indicators was used for determination of optimal processing condition. Multivariate statistical methods such as Hierarchical Clustering Analysis (HCA) and Principal Components Analysis (PCA) were both employed to classify the processed samples for quality evaluation. To more comprehensively evaluate the quality of wine-fried Dipsaci Radix, HPLC fingerprint combined with content of asperosaponin VI and AA may be a reasonable and practical approach.

scholarly journals A Strategy for Quality Control of Vespa magnifica (Smith) Venom Based on HPLC Fingerprint Analysis and Multi-Component Separation Combined with Quantitative Analysis

Molecules ◽  
2019 ◽  
Vol 24 (16) ◽  
pp. 2920 ◽  
Author(s):  
Si-Tong Zhou ◽  
Kai Luan ◽  
Lian-Li Ni ◽  
Ying Wang ◽  
Shi-Meng Yuan ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
High Performance ◽  
Principal Component ◽  
Good Precision ◽  
Fingerprint Analysis ◽  
Wasp Venom ◽  
Chemical Fingerprint ◽  
Hplc Fingerprint ◽  
Relative Standard

As a folk medicine of the Jingpo minority in Yunnan province, the venom of Vespa magnifica has been commonly used for the treatment of rheumatoid arthritis. Quality standardization of the wasp venom is a necessary step for its pharmaceutical research and development. To control the quality of the wasp venom, a method based on high-performance liquid chromatography (HPLC) was developed for chemical fingerprint analysis. In the chromatographic fingerprinting, chemometrics procedures, including similarity analysis (SA), hierarchical clustering analysis (HCA), and principal component analysis (PCA), were applied to classify 134 batches (S1–S134) of wasp venom from different origins. The HPLC fingerprint method displayed good precision (Relative standard deviation, RSD < 0.27%), stability (in 16 h, RSD < 0.34%), and repeatability (RSD < 1.00%). Simultaneously, four compounds (VMS1, VMS2, VMS3, and VMS4) in the wasp venom were purified and identified. VMS1 was 5-hydroxytryptamine, and the other compounds were three peptides that were sequenced as follows: Gly–Arg–Pro–Hyp–Gly–Phe–Ser–Pro–Phe–Arg–Ile–Asp–NH2 (VMS2), Ile–Asn–Leu–Lys–Ala–Ile–Ala–Ala–Leu–Ala–Lys–Lys–Leu–Leu–NH2 (VMS3), and Phe–Leu–Pro–Ile–Ile–Gly–Lys–Leu–Leu–Ser–Gly–Leu–Leu–NH2 (VMS4). The quantifications for these components were 110.2 mg/g, 26.9 mg/g, 216.3 mg/g, and 58.0 mg/g, respectively. The results of this work indicated that the combination of the chemical fingerprint and quantitative analysis offers a reasonable way to evaluate the quality of wasp venom.

scholarly journals Development of HPLC Fingerprint for Quality Assessment of Bulbus Lilii

2013 ◽  
Vol 8 (10) ◽  
pp. 1934578X1300801
Author(s):  
Kunming Qin ◽  
Hao Cai ◽  
Lijuan Zheng ◽  
Miao Zhang ◽  
Xinghai Zhang ◽  
...  
Keyword(s):  
High Performance ◽  
Quality Evaluation ◽  
Quality Analysis ◽  
Analysis Method ◽  
Hplc Fingerprint ◽  
Array Detection ◽  
Different Origins ◽  
First Time ◽  
And Storage

In this study, a simple, sensitive and reliable fingerprint analysis method by high-performance liquid chromatography coupled with diode array detection (HPLC-DAD) was developed for quality analysis of Bulbus Lilii, which is a famous traditional Chinese medicine and widely used as a restorative food. Then the developed method was subsequently applied to analyse 16 samples collected or purchased from different origins. Twelve common fingerprint peaks, including four definitely identified peaks, were found in total, and were involved for further characterisation and quality evaluation of Bulbus Lilii. The chemical quality of commercial samples collected from different origins varied obviously, indicating that more attention should be paid to the standardisation of the process of harvesting, manufacturing and storage of Bulbus Lilii. This is the first time that a new method has been established to control the quality of Bulbus Lilii through HPLC-DAD.

scholarly journals HPLC Fingerprint Combined With Multicomponent Quantification as an Efficient Method for Quality Evaluation of Pharbitidis Semen

2020 ◽  
Vol 15 (6) ◽  
pp. 1934578X2093164
Author(s):  
Huiwei Bao ◽  
Huailei Yang ◽  
Feng Wang ◽  
Kaixuan Zhou ◽  
Yanan Yang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Caffeic Acid ◽  
Evaluation System ◽  
High Performance ◽  
Quality Evaluation ◽  
Hplc Method ◽  
Hplc Fingerprint ◽  
Protocatechuic Aldehyde ◽  
Effective Components

Pharbitidis Semen is a traditional Chinese medicine(TCM) with a long history for treatment of edema and fullness, fecal and urinary retention, phlegm and retained fluid, and abdominal pain due to parasitic infestation. Since Pharbitidis Semen is distributed throughout the country, the quality of the medicine from different origins may be varied. Moreover, the reported method could not control the quality comprehensively. In this article, a fingerprint of Pharbitidis Semen has been established based on a high-performance liquid chromatography (HPLC) method. In addition, the contents of the 2 main effective components were determined simultaneously. The reference HPLC fingerprint was obtained according to the chromatograms of test samples. The similarity values were calculated by the Similarity Evaluation System for Chromatographic Fingerprint of TCM (2004 A edition). Cluster analysis of 10 batches of samples was performed using statistical software (SPSS 20.0). The HPLC fingerprints of 10 batches of Pharbitidis Semen showed 25 well-resolved common peaks in each chromatogram. Two of these peaks were assigned to protocatechuic aldehyde and caffeic acid. As a result, HPLC fingerprint similarities of 10 batches of samples were more than 0.99. Pharbitidis Semen from different habitats could be divided into 3 or 2 groups. The results of cluster analysis showed that samples classified into 1 group were associated with their habitats and breeds. At the same time, quantification results showed that the contents of protocatechuic aldehyde and caffeic acid were in the range of 0.026-0.088 and 0.019-0.053 mg/g−1 respectively. HPLC fingerprint combined with multicomponent quantification and data analysis techniques can be an efficient and useful method for monitoring the quality of Pharbitidis Semen. This study also provides a practical strategy for overall quality evaluation and control of traditional Chinese medicines.

Evaluation of English interpretation teaching quality based on GA optimized RBF neural network

2020 ◽  
pp. 1-8
Author(s):  
Lu Chen ◽  
He Being
Keyword(s):  
Neural Network ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Rbf Neural Network ◽  
Evaluation Model ◽  
Principal Component ◽  
Teaching Quality ◽  
Network Teaching ◽  
Time Performance

Aiming at the problem of low accuracy of the current English interpretation teaching quality evaluation, a teaching quality evaluation method based on a genetic algorithm (GA) optimized RBF neural network is proposed. First, the principal component analysis is used to select the teaching quality evaluation index, and then design The RBF neural network teaching evaluation model is used, and GA is used to optimize the initial weights of the RBF neural network. Experimental results show that this method can effectively evaluate the quality of English interpretation teaching, and has high accuracy and real-time performance.

scholarly journals New model for flavour quality evaluation of soy sauce

2013 ◽  
Vol 31 (No. 3) ◽  
pp. 292-305 ◽  
Author(s):  
J. Feng ◽  
X.-B. Zhan ◽  
Z.-Y. Zheng ◽  
D. Wang ◽  
L.-M. Zhang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Principal Component ◽  
Objective Evaluation ◽  
Component Analysis ◽  
Soy Sauce ◽  
Complex Information

The soy sauce samples established a model for its flavour quality evaluation. Initially, 39 types of flavour compounds, organic acids and free amino acids in six different types of soy sauce were identified and determined by HS-SPME GC/MS and HPLC. The model was developed based on the principal component analysis method for assessing and ranking of flavour quality of soy sauce. Using the principal component analysis which simplifies complex information, our correlative evaluation model was established, tested by comparing the traditional sensory evaluation method, providing a new methodology for objective evaluation of the flavour quality of soy sauce. &nbsp;

scholarly journals Species Classification and Quality Assessment of Cangzhu (Atractylodis Rhizoma) by High-Performance Liquid Chromatography and Chemometric Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yong-Gang Xia ◽  
Bing-You Yang ◽  
Qiu-Hong Wang ◽  
Jun Liang ◽  
Di Wang ◽  
...  
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Discriminant Analysis ◽  
Quality Assessment ◽  
High Performance ◽  
Principal Component ◽  
Chemometric Methods ◽  
Species Classification ◽  
Linear Discriminant

Fast and sensitive high-performance liquid chromatography (HPLC) coupled with chemometric methods was utilized to assist in the quality assessment of Cangzhu (Atractylodis Rhizoma). By comparative analysis of chromatographic profiles, twelve common peaks were selected for multivariate analysis. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of the chromatographic data demonstrated that 16 batches of Cangzhu samples could be welldifferentiated and categorized into two groups, which were closely related to their species (Atractylodes chinensis and A. lancea). By loading plots of PCA and OPLS-DA, the “common peaks” 2, 10, and 12 were defined as “marker peaks,” which were identified as atractylodinol, (4E,6E,12E)-tetradecatriene-8,10-diyne-1,3-diyl diacetate, and atractylodin, respectively. These three “marker peaks” were then simultaneously quantified for further controlling the quality of Cangzhu, which showed acceptable linearity, both intraday and interday precisions (RSD ≤ 2.30%), repeatability (RSD ≤ 2.82%), and the recoveries of the three analytes in the range of 96.57–100.16%, with RSDs less than 1.46%. Finally, linear discriminant analysis (LDA) was successfully used to build predictive models of the group membership based on the contents of three marker peaks. Results of the present study demonstrated that HPLC-based metabolic profiling coupled with chemometric methods and quantificational determination was a very flexible, reliable, and effective way for homogeneity evaluation and quality assessment of traditional Chinese medicine.

scholarly journals Quality Evaluation of Oviductus Ranae Based on PUFAs Using HPLC Fingerprint Techniques Combined with Chemometric Methods

Foods ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 322 ◽  
Author(s):  
Hongye Guo ◽  
Yuanshuai Gan ◽  
Min Liu ◽  
Shihan Wang ◽  
Shuling Ni ◽  
...  
Keyword(s):  
High Performance ◽  
Quality Evaluation ◽  
Petroleum Ether Extract ◽  
Chemometric Methods ◽  
Ether Extract ◽  
Hplc Fingerprint ◽  
Multiple Factors ◽  
Chromatographic Fingerprints ◽  
Oviductus Ranae

Oviductus Ranae is a nutritional product for both medicine and food. Its quality is uneven due to multiple factors. An efficient method was established to evaluate the quality of Oviductus Ranae using fingerprint techniques and chemometric methods based on the analysis of polyunsaturated fatty acids (PUFAs) in petroleum ether extract by high performance liquid chromatography (HPLC). During this process, 27 batches of Oviductus Ranae were analyzed by HPLC and two types of chromatographic fingerprints were established. The fingerprint that was obtained by matching six known peaks was used for the quantification of six PUFAs. Another fingerprint was obtained by matching sixteen peaks with a peak area ratio greater than 0.5% and it was used to classify the different qualities of Oviductus Ranae by further combining three different chemometric models. The 27 batches of Oviductus Ranae were divided into four categories, which was consistent with the analysis results of six PUFAs contents. The two high-quality samples with significantly higher contents were classified into one category, and samples with medium contents were divided into two categories, including eight and thirteen samples, respectively. The four inferior samples with lower contents were classified into one category. The results indicated that the newly developed method has potential application prospects for the quality evaluation of Oviductus Ranae.

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