Objective:To screen the best decocting technology by multi-index comprehensive score combined with response sur-face. Methods:The content of paeoniflroin and the ratio of dry extraction were used as the indicators, and response surface Central Composite with two factors and five levels was used in the experimental design. The effects of the ratio of solvent to solid, decocting du-ration and decocting times on the preparation process of tonic semifluid extract of ten ingredients were studied. Results:Design Expert 8. 0. 6b software was used for the data analysis. A quadratic mathematical model between the factors and the comprehensive score of paeoniflroin content and the ratio of dry extraction was established. Combined with the actual production, the best decocting conditions were as following:the ratio of solvent to solid was 10. 6 ml·g-1 , the decocting duration was 96 min, and decocted 3 times. Conclu-sion:The optimal decocting technology is scientific, reasonable and stable.

Objective:To obtain the optimum extraction conditions for quercetin and kaempferol from Lindera aggregate leaves. Methods:On the basis of single factor investigation, Box-Behnken experimental design was used to provide the experimental data for establishing a regression model for the extraction of quercetin and kaempferol. Response surface and contour diagrams with the extrac-tion yield of quercetin and kaempferol as the response values,were plotted for analyzing the pairwise interactive effects of hydrochloric acid concentration, hydrolysis temperature and hydrolysis time. Results:The hydrochloric acid concentration of 4. 1%, the hydrolysis temperature of 83℃ and the hydrolysis time of 45min were the optimum extraction conditions. With the above conditions, the content of quercetin and kaempferol from Lindera aggregate leaves was 6. 97 mg·g-1 and 2. 82 mg·g-1 , respectively. The Lindera aggregate beaves from five different habitals were analyzed,and the total content of quercetin and kaempferide from Taizhou Tiantai were highest. Conclusion:The quercetin and kaempferol extraction from Lindera aggregate leaves is optimized by Box-Behnken response surface method and the process is convenient and feasible.

Objective:To obtain the optimum extraction conditions for quercetin and kaempferol from Lindera aggregate leaves. Methods:On the basis of single factor investigation, Box-Behnken experimental design was used to provide the experimental data for establishing a regression model for the extraction of quercetin and kaempferol. Response surface and contour diagrams with the extrac-tion yield of quercetin and kaempferol as the response values,were plotted for analyzing the pairwise interactive effects of hydrochloric acid concentration, hydrolysis temperature and hydrolysis time. Results:The hydrochloric acid concentration of 4. 1%, the hydrolysis temperature of 83℃ and the hydrolysis time of 45min were the optimum extraction conditions. With the above conditions, the content of quercetin and kaempferol from Lindera aggregate leaves was 6. 97 mg·g-1 and 2. 82 mg·g-1 , respectively. The Lindera aggregate beaves from five different habitals were analyzed,and the total content of quercetin and kaempferide from Taizhou Tiantai were highest. Conclusion:The quercetin and kaempferol extraction from Lindera aggregate leaves is optimized by Box-Behnken response surface method and the process is convenient and feasible.

Objective: To established a near-infrared spectroscopy quantitative model for the rapid determination of volatile oils from Rhizoma wenyujin concisum. Methods:Firstly, the volatile oils from Rhizoma wenyujin was determined by the distillation method described in Chinese Pharmacopoeia. The quantitative calibration model was established and optimized by fourier transformation near-infrared spectroscopy ( FT-NIR) combined with partial least square ( PLS) regression. The calibration model was evaluated by the coef-ficient (r), root-mean-square error of calibration (RMSEC) and root mean square of cross-validation (RMSECV) of the calibration model as well as the root mean square of prediction ( RMSEP) of prediction model. Results: In the combination of FT-NIR and PLS regression, the spectrum of 7189-4227 cm-1 , 8813-7478 cm-1 and"second spectrum+MSC" were chosen to establishe and optimize the quantitative calibration model. For the quantitative calibration model, the r, RMSEC and RMSECV of volatile oils was 0. 9769, 0. 0907 and 0. 3773, respectively. For the prediction model, the r and RMSEP of volatile oils was 0. 9053 and 0. 1960, respective-ly. Conclusion:The established near-infrared spectroscopy quantitative model is relatively stable, accurate and reliable in the simulta-neous quantitative analysis of volatile oils, and is expected to be used for the rapid determination of volatile oils from Rhizoma wenyujin concisum.

Objective: To established a near-infrared spectroscopy quantitative model for the rapid determination of volatile oils from Rhizoma wenyujin concisum. Methods:Firstly, the volatile oils from Rhizoma wenyujin was determined by the distillation method described in Chinese Pharmacopoeia. The quantitative calibration model was established and optimized by fourier transformation near-infrared spectroscopy ( FT-NIR) combined with partial least square ( PLS) regression. The calibration model was evaluated by the coef-ficient (r), root-mean-square error of calibration (RMSEC) and root mean square of cross-validation (RMSECV) of the calibration model as well as the root mean square of prediction ( RMSEP) of prediction model. Results: In the combination of FT-NIR and PLS regression, the spectrum of 7189-4227 cm-1 , 8813-7478 cm-1 and"second spectrum+MSC" were chosen to establishe and optimize the quantitative calibration model. For the quantitative calibration model, the r, RMSEC and RMSECV of volatile oils was 0. 9769, 0. 0907 and 0. 3773, respectively. For the prediction model, the r and RMSEP of volatile oils was 0. 9053 and 0. 1960, respective-ly. Conclusion:The established near-infrared spectroscopy quantitative model is relatively stable, accurate and reliable in the simulta-neous quantitative analysis of volatile oils, and is expected to be used for the rapid determination of volatile oils from Rhizoma wenyujin concisum.