ABSTRACT
Objective:To optimize the entropy TOPSIS model to evaluate the quality of Hemerocallis Flava from different regions,in order to provide a new evaluation method for the quality control of traditional Chinese medicine. Method:The entropy weight TOPSIS model optimized by analytic hierarchy process(AHP) method was used to analyze the quality of Hemerocallis Flava from 14 different regions, and a comprehensive evaluation index system for the quality of Hemerocallis Flava, which covered 3 layers (target layer,decision layer and index layer),and 10 indexes (corolla of Hemerocallis Flavathe's bud,pistils,stamens,peduncle length,extract,total ash,quercetin,β-rhamnocitrin,kaempferol,sitosterin) was established. Result:Qingyang showed the best quality of Hemerocallis Flava,which was followed by Weinan,and the lowest quality was found in Datong, Shanxi, and Xiaowan village, Sichuan. The results were consistent with the evaluation results of traditional empirical identification,suggesting the successful modeling. The contents of β-rhamnocitrin and kaempferol in Qingyang were 1.72 times and 2.74 times of those of Xiaowan village, Sichuan. There was no significant difference in other active ingredients from different regions. It was suggested that quercetin and kaempferol could be used as the identification and quality evaluation indexes of cauliflower. Conclusion:The entropy TOPSIS model based on the AHP method is clear,simple to use and easy to calculate, with distinct evaluation indexes. It is a practical,quick and effective comprehensive evaluation method for multi-objective decision analysis.