Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method

Area of Science:

• Pharmacognosy
• Cheminformatics
• Traditional Chinese Medicine (TCM) analysis

Background:

• Raw Moutan cortex (RMC) is a vital component in traditional Chinese medicine.
• Ensuring comprehensive and objective quality evaluation of RMC is crucial for modern herbal medicine development.

Purpose of the Study:

• To develop and apply a weighted gray correlation-Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method for evaluating and comparing the quality of RMC.
• To establish a reliable and objective quality assessment model for RMC.

Main Methods:

• Quantification of key chemical constituents in RMC: gallic acid, catechin, oxypaeoniflorin, paeoniflorin, quercetin, benzoylpaeoniflorin, and paeonol.
• Development of a gray correlation-TOPSIS assessment model using MATLAB programming for RMC quality evaluation.

Main Results:

• The developed gray correlation-TOPSIS model demonstrated consistent, reliable, and stable quality evaluation results.
• Model-based evaluations aligned with objective assessments, confirming the model's validity.

Conclusions:

• The gray correlation-TOPSIS model is effectively applicable to the quality evaluation of traditional Chinese medicines with multiple chemical components.
• This approach presents a promising and feasible method for quality control in the field of herbal medicine.