Open access · Peer reviewed · No APCs
Original ArticlePharmacognosy MagazineVol. 13 | Issue 51 | 2017 | pp. 528–533Open access
Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method
- 1*,
- 1*,
- *
- 1 Department of Automation, Guangdong University of Technology, China.
- 2 College of Medical Information Engineering, Guangdong Pharmaceutical University, China.
- 3 College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, People’s Republic of, China.
Published in Pharmacognosy Magazine
Correspondence: Sujuan Zhou
Department of Automation, Guangdong University of Technology, China.
Email: jiangmeng666@126.com
Correspondence: Bo Liu
Department of Automation, Guangdong University of Technology, China.
Email: jiangmeng666@126.com
Correspondence: Jiang Meng
Email: jiangmeng666@126.com
Copyright: © 2017 Manuscript Technomedia. This is an open access article.
- Published:
- Jul 19, 2017
- Received:
- Jun 5, 2016
How to cite
Zhou, S., Liu, B., & Meng, J. (2017). Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method. Pharmacognosy Magazine, 13(51), 528–533. https://doi.org/10.4103/0973-1296.211029
Abstract
Background: Raw Moutan cortex (RMC) is an important Chinese herbal medicine. Comprehensive and objective quality evaluation of Chinese herbal medicine has been one of the most important issues in the modern herbs development. Objective: To evaluate and compare the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Materials and Methods: The percentage composition of gallic acid, catechin, oxypaeoniflorin, paeoniflorin, quercetin, benzoylpaeoniflorin, paeonol in different batches of RMC was determined, and then adopting MATLAB programming to construct the gray correlation-TOPSIS assessment model for quality evaluation of RMC. Results: The quality evaluation results of model evaluation and objective evaluation were consistent, reliable, and stable. Conclusion: The model of gray correlation- TOPSIS can be well applied to the quality evaluation of traditional Chinese medicine with multiple components and has broad prospect in application. SUMMARY • The experiment tries to construct a model to evaluate the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Results show the model is reliable and provide a feasible way in evaluating quality of traditional Chinese medicine with multiple components.
Keywords
Subject
Article metadata
| Title | Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method |
|---|---|
| Authors | Sujuan Zhou; Bo Liu; Jiang Meng |
| Affiliations | Department of Automation, Guangdong University of Technology, China.; College of Medical Information Engineering, Guangdong Pharmaceutical University, China.; College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, People’s Republic of, China. |
| Corresponding author | jiangmeng666@126.com |
| Journal | Pharmacognosy Magazine |
| Volume / Issue | Vol. 13, Issue 51 (2017) |
Also in this issue
- Quantification Analysis and In Vitro Anti-Inflammatory Effects of 20-Hydroxyecdysone, Momordin Ic, and Oleanolic Acid from the Fructus of Kochia scopariapp. 339–344
- Anticancer Potential of Steviol in MCF-7 Human Breast Cancer Cellspp. 345–350
- Antitumor Effects and Mechanism of n‑butanol Fraction from Aril of Torreya grandis in H22 Micepp. 351–357
- Using Molecular Docking Analysis to Discovery Dregea sinensis Hemsl. Potential Mechanism of Anticancer, Antidepression, and Immunoregulationpp. 358–362
- Wound‑healing Activity of Zanthoxylum bungeanum Maxim Seed Oil on Experimentally Burned Ratspp. 363–371
Readers Also Viewed
Development and Validation of UV/visible Spectrophotometric Method for Estimation of Piroxicam from Bulk and Formulation
Sandip Mohan Honmane, Kunal Rajaram Yadav, Yuvraj Dilip Dange
Apr 23, 2025
Effects of Artificial Intelligence on Academic Performance of Library and Information Science University Students: A Meta-Analysis (2023-2025)
Kayode Sunday John Dada
Aug 6, 2026
Bridging Innovation and Impact: A Multidisciplinary Approach to Contemporary Research Challenges
Mueen Ahmed KK
Aug 11, 2026