Research on grade prediction of Spatholobi Caulis via components-anti-oxidant activity correlations / 中草药
Zhongcaoyao
; Zhongcaoyao;(24): 943-949, 2020.
Article
in Zh
| WPRIM
| ID: wpr-846594
Responsible library:
WPRO
ABSTRACT
Objective: The model for grade evaluation of Spatholobi Caulis medicinal slices was constructed based on the quality control idea of traditional Chinese medicines that “components reflect activity and activity points to efficacy”. Methods: A method to determinate catechin and epicatechin content by using ultra performance liquid chromatography (UPLC) was proposed. ABTS•+ clearance rate, hydroxyl radical clearance rate and DPPH• clearance rate were used as evaluation indexes of biological activity. Correlations between content and anti-oxidant activity were analyzed by the logistic algorithm. Finally, a “principal component analysis-logistic regression” model for grade prediction of Spatholobi Caulis was constructed. Results: Catechin and epicatechin content in Spatholobi Caulis medicinal slices from different origins was between 0.40-1.26 mg/g and 0.57-2.02 mg/g, respectively. The anti-oxidant indexes ABTS•+, hydroxyl radical and DPPH• clearance rate were between 12.96%-51.76%, 30.65%-66.65%, and 37.65%-60.33%, respectively. The binary logistic regression analysis results showed that five batches were evaluated as excellent, average and poor rank, and four batches were considered as good rank (P > 94%) among 17 batches of Spatholobi Caulis herbal pieces and its two kinds of counterfeit (Sargentodoxa cuneata and Mucuna sempervirens). Conclusion: Binary logistic regression model for grade evaluation of Spatholobi Caulis medicinal slices was constructed preliminarily. It is applicable to assess quality of Spatholobi Caulis herbal pieces. The grading evaluation model of Spatholobi Caulis via logistic regression analysis can be used to classification of Spatholobi Caulis from different sources.
Full text:
1
Index:
WPRIM
Type of study:
Prognostic_studies
Language:
Zh
Journal:
Zhongcaoyao
Year:
2020
Type:
Article