A study on the rapidly non-destructive detection method of Huoxiang Zhengqi oral liquid using near infrared spectroscopy / 药学学报

Based on near infrared spectroscopy and high performance liquid chromatography, this paper established the regression relationship between near infrared spectroscopy and index component content of Huoxiang Zhengqi oral liquid, so as to realize the rapid detection of index component content based on near infrared spectroscopy. Magnolol, honokiol and hesperidin were used as the quality indexes of Huoxiang Zhengqi oral liquid. After using the first derivative and normalization pretreatment method, characteristic variables were screened by CARS, and the correction model was finally established by partial least-squares regression (PLSR) method. The method accuracy was evaluated with the external validation, and the prediction results were tested for significance. The results indicated that when the near infrared spectrum was scanned through the bottle, the model's correlation coefficients of prediction (Rp) were higher than 0.99, the root mean square errors of the prediction models (RMSEP) were all less than 0.008 4, and the relative standard errors of prediction set (RSEP) were all less than 2.83%. There was no significant difference in the predicted results between these two kinds of model. The models established in the non-destructive way have good performance and high prediction accuracy. The rapid and nondestructive way has application value in the quality control of Huoxiang Zhengqi oral liquid.

Rapid determination of active components in Ginkgo biloba leaves by near infrared spectroscopy combined with genetic algorithm joint extreme learning machine / 中国中药杂志

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.

Simultaneous determination of five saponins in Yaobitong capsule by HPLC-CAD / 药学学报

A high performance liquid chromatography charged aerosol detector (HPLC-CAD) method was established for the simultaneous determination of five saponins (notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, Ginsenoside Rd) in Yaobitong capsule, providing a method for quality control. The sample was extracted with methanol and chromatographic separation was performed on a Waters Xbridge Phenol column (150 mm×4.6 mm, 3.5 μm) using acetonitrile-water as the mobile phase with gradient elution at a flow rate of 1.0 mL·min-1. The column temperature was 30 ℃ and the injection volume was 10 μL. The nebulizer temperature of CAD was 35 ℃ and the air pressure was 60.2 psi, the filtration was 3.6 s, and the collection frequency was 5 Hz. Notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1 and ginsenoside Rd showed a good linear relationship in the range of 16.96-203.5 μg·mL-1 (R2 = 0.999 3), 54.46-653.5 μg·mL-1 (R2 = 0.999 3), 10.96-131.5 μg·mL-1 (R2 = 0.999 6), 51.50-618.0 μg·mL-1 (R2 = 0.999 0), 15.94-191.3 μg·mL-1 (R2 = 0.999 4), respectively. The average recoveries were 98.96%, 100.8%, 94.76%, 100.1%, 103.1%, and RSDs were 0.87%, 1.46%, 1.85%, 2.06%, 0.96% (n = 6), respectively. The proposed method is accurate, simple and reliable, and can be used for the determination of five saponins in Yaobitong capsule.