5 to 135.6 μmol·L~(-1).To establish the HPLC fingerprint and multi-component determination method of fried Glycyrrhizae Radix et Rhizoma pieces. HPLC analysis was performed on Thermo Acclaim ~(TM)120 C_(18) column(4.6 mm×250 mm, 5 μm). Acetonitrile-0.1% phosphoric acid aqueous solution was taken as the mobile phase for gradient elution. The flow rate was 1 mL·min~(-1),the column temperature was maintained at 30 ℃, and the detection wavelength was 237 nm and 360 nm. The similarity of 15 batches of fried Glycyrrhizae Radix et Rhizoma pieces was higher than 0.849, and 17 common peaks were identified. Liquiritin, isoliquiritin apioside, isoliquiritin, liquiritigenin, isoliquiritigenin and glycyrrhizic acid were identified; among them, the mass fractions of Liquiritin, isoliquiritin apioside, isoliquiritin, liquiritigenin, glycyrrhizic acid were were 0.519%-3.058%, 0.227%-0.389%, 0.070%-0.439%, 0.038%-0.173%, 1.381%-4.252%, respectively. According to the cluster analysis, the 15 batches of decoction pieces were classified into three categories; principal component analysis screened out four principal components, with the cumulative variance contribution rate of 86.630%, indicating that the principal components contained most information of original data. Partial least squares discriminant ana-lysis marked 6 differential components in the decoction pieces. The established fingerprint and multicomponent determination are stable and reliable, and can provide a reference for the quality control of Radix Glycyrrhizae Radix et Rhizomae and fried Glycyrrhizae Radix et Rhizoma pieces.Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.With the dropping process of Xuesaitong Dropping Pills(XDP) as the study object, critical factors affecting the quality indicators of pill pass rate, average weight of drop pills and roundness were screened out, so as to deepen the understanding of the dropping process. The critical process units, critical quality attributes and potential critical process influencing factors of XDP were determined by risk analysis and prior knowledge, and then the critical influencing factors were screened out by Plackett-Burman design. First, according to the risk assessment, the critical technique of XDP preparation process was dropping, and then the critical quality attributes of dropping process were pill pass rate, average weight of drop pills and roundness. Then, according to fishbone diagram and failure mode and effects analysis(FMEA), potential critical influencing factors were determined as flow rate, matrix ratio, solid-liquid ratio, feed-liquid temperature, top temperature of condensate, bottom temperature of condensate and dropping distance. Finally, among these seven potential factors, the critical influencing factors were determined as material liquid ratio, dropping distance, top temperature of condensate, bottom temperature of condensate. This study revealed the potential of Plackett-Burman design in screening and understanding the influence of selected factors on XDP dropping process, which could provide a reference for studying the dropping process.This study cloned the transcription factor gene PnbHLH which held an open reading frame of 966 bp encoding 321 amino acids. This study constructed the overexpression vector of transcription factor PnbHLH of Panax notoginseng. The combination of PnbHLH overexpression and RNAi of the key enzyme gene PnCAS involved in the phytosterol biosynthesis was achieved in P. Taletrectinib notoginseng cells, thus exploring the biosynthetic regulation of P. notoginseng saponins(PNS) by the synergistic effect of PnbHLH overexpression and PnCAS RNAi. The results showed that the PnbHLH transcription factor interacted with the promoters of key enzyme genes PnDS, PnSS and PnSE in the biosynthetic pathway of PNS, and then regulated the expression levels of key enzyme genes and affected the biosynthesis of saponins indirectly. Further study indicated that the synergistic effect of PnbHLH overexpression and PnCAS RNAi was a more effective approach to regulate the biosynthesis of saponins. Compared with the wild type and PnCAS RNAi cells of P. notoginseng, the contents of total saponins and monomeric saponins(Rd, Rb_1, Re, Rg_1 and R_1) were increased to some extent in the cell lines of PnbHLH overexpression and PnCAS RNAi. This indicated that the two ways of forward regulation and reverse regulation of saponin biosynthesis showed superposition effect. This study explored a more rational and efficient regulation strategy of PNS biosynthesis based on the advantages of multi-point regulation of transcription factors as well as the down-regulation of by-product synthesis of saponins.