Your browser doesn't support javascript.
loading
Optimization of Water Extraction Technology of Taohe Chengqi Decoction by Response Surface Methodology Combined with Information Entropy Theory / 中国药房
China Pharmacy ; (12): 2210-2215, 2019.
Article de Zh | WPRIM | ID: wpr-817160
Bibliothèque responsable: WPRO
ABSTRACT
OBJECTIVE: To optimize the water extraction technology of classic formula Taohe chengqi decoction. METHODS: Based on single factor test, combined with response surface methodology and information entropy theory, the soaking time, solid-liquid ratio and extraction time were investigated. Using the contents of rhein, amygdalin, cinnamaldehyde and glycyrrhizic acid in Taohe chengqi decoction as indexes, information entropy theory was used to assign weight coefficients to each evaluation index and calculate the comprehensive score. Through Design-Expert 10 software, the interactions of each factor were analyzed. Water extraction technology was optimized, and validation test was also performed. RESULTS: According to information entropy theory, the weight coefficients of rhein, amygdalin, glycyrrhizic acid and cinnamaldehyde were located at 0.097 6, 0.363 2, 0.173 5 and 0.365 7. The results of interaction analysis showed that the material-liquid ratio had a greater impact on the comprehensive score. The optimal water extraction technology of Taohe chengqi decoction were determined as that soaking time was 60 min; the ratio of material to liquid was 1 ∶ 10 (g/mL); total extraction time was 130 min (extracting for 3 times, lasting for 65, 33, 32 min each time). The results of verification test showed that RSD of content of each index component and the comprehensive score was less than 3%. CONCLUSIONS: The optimal water extraction technology is proved to be stable and feasible, which can provide the basis for the further development and utilization of Taohe chengqi decoction.
Mots clés
Texte intégral: 1 Base de données: WPRIM Langue: Zh Journal: China Pharmacy Année: 2019 Type de document: Article
Texte intégral: 1 Base de données: WPRIM Langue: Zh Journal: China Pharmacy Année: 2019 Type de document: Article