PHOTOMETRY-BASED PREDICTION MODEL FOR THE CONTENT OF OLEANOLIC ACID IN PERIPLOCAFORRESTIISCHLTR

Abstract

To realize rapid, low-cost identification and ensure quality control of Periplocaforrestii Schltr., a Miao ethnomedicine, a prediction model for oleanolic acid was built based on photometry. The total saponin content and oleanolic acid content inPeriplocaforrestiiSchltr. were analyzed by spectrophotometry and HPLC, respectively, and good linearity was observed for both of these methods. The Pearson correlation coefficient of the two data groups was 0.99, indicating a significant positive correlation. Thus, a prediction curve for the content of oleanolic acid in PeriplocaforrestiiSchltr. was constructed by fitting the relationship between these two indicators to a parabolic curve (R2 = 0.987). This model was successfully applied to predict the content of oleanolic acid in two samples, with a discrepancy rate of <3% between of the predicted values and the experimental values. This method exhibited an excellent goodness of fit and showed high precision for determining the content of oleanolic acid in Periplocaforrestii Schltr. samples. As the total saponin content can be determined using simple photometric methods, this prediction model allows rapid and convenient determination of oleanolic acid inPeriplocaforrestiiSchltr. This approach may be useful for identifying natural medicines in ethnic