Rapid Determination of Saponins in the Honey-Fried Processing of Rhizoma Cimicifugae by Near Infrared Diffuse Reflectance Spectroscopy

Improved quantitative analysis of tenuifolin using hydrolytic continuous-flow system to build prediction models for its content based on near-infrared spectroscopy

This study used two types of analyses and statistical calculations on powdered samples of Polygala root (PR) and Senega root (SR): (1) determination of saponin content by an independently developed quantitative analysis of tenuifolin content using a flow reactor, and (2) near-infrared spectroscopy (NIR) using crude drug powders as direct samples for metabolic profiling. Furthermore, a prediction model for tenuifolin content was developed and validated using multivariate analysis based on the results of (1) and (2). The goal of this study was to develop a rapid analytical method utilizing the saponin content and explore the possibility of quality control through a wide-area survey of crude drugs using NIR spectroscopy. Consequently, various parameters and appropriate wavelengths were examined in the regression analysis, and a model with a reasonable contribution rate and prediction accuracy was successfully developed. In this case, the wavenumber contributing to the model was consistent with that of tenuifolin, confirming that this model was based on saponin content. In this series of analyses, we have succeeded in developing a model that can quickly estimate saponin content without post-processing and have demonstrated a brief way to perform quality control of crude drugs in the clinical field and on the market.

Rapid evaluation of Ziziphi Spinosae Semen and its adulterants based on the combination of FT-NIR and multivariate algorithms

Ziziphi Spinosae Semen (ZSS) is a valued seed renowned for its sedative and sleep-enhancing properties. However, the price increase has been accompanied by adulteration. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) combined with multivariate algorithms were employed to identify the adulteration and quantitatively predict the adulteration ratio. The findings suggested that the utilization of chromaticity extractor was insufficient for identification of adulteration ratio. The raw spectrum of ZMS and HAS adulterants extracted by FT-NIR was processed by SNV + CARS and 1d + SG + ICO respectively, the average accuracy of machine learning classification model was improved from 77.06 % to 97.58 %. Furthermore, the R2 values of the calibration and prediction set of the two quantitative prediction regression models of adulteration ratio are greater than 0.99, demonstrating excellent linearity and predictive accuracy. Overall, this study demonstrated that FT-NIR combined with multivariate algorithms provided a significant approach to addressing the growing issue of ZSS adulteration.

Rapid evaluation of Radix Paeoniae Alba and its processed products by near-infrared spectroscopy combined with multivariate algorithms

It is well known that the processing method of herbal medicine has a complex impact on the active components and clinical efficacy, which is difficult to measure. As a representative herb medicine with diverse processing methods, Radix Paeoniae Alba (RPA) and its processed products differ greatly in clinical efficacy. However, in some cases, different processed products are confused for use in clinical practice. Therefore, it is necessary to strictly control the quality of RPA and its processed products. Giving that the time-consuming and laborious operation of traditional quality control methods, a comprehensive strategy of near-infrared (NIR) spectroscopy combined with multivariate algorithms was proposed. This strategy has the advantages of being rapid and non-destructive, not only qualitatively distinguishing RPA and various processed products but also enabling quantitative prediction of five bioactive components. Qualitatively, the subspace clustering algorithm successfully differentiated RPA and three processed products, with an accuracy rate of 97.1%; quantitatively, interval combination optimization (ICO), competitive adaptive reweighted sampling (CARS), and competitive adaptive reweighted sampling combined with successive projections algorithm (CARS-SPA) were used to optimize the PLS model, and satisfactory results were obtained in terms of wavelength selection. In conclusion, it is feasible to use NIR spectroscopy to rapidly evaluate the effect of processing methods on the quality of RPA, which provides a meaningful reference for quality control of other herbal medicines with numerous processing methods.

Recent Advances in Separation and Analysis of Saponins in Natural Products

To better control the quality of saponins, ensure their biological activity and clinical therapeutic effect, and expand the development and application of saponins, this paper systematically and comprehensively reviews the separation and analytical methods of saponins in the past decade. Since 2010, the electronic databases of PubMed, Google Scholar, ISI Web of Science, Science Direct, Wiley, Springer, CNKI (National Knowledge Infrastructure, CNKI), Wanfang Med online, and other databases have been searched systematically. As a result, it is found that ionic liquids and high-performance countercurrent chromatography are the most popular extraction and separation techniques for saponins, and the combined chromatography technique is the most widely used method for the analysis of saponins. Liquid chromatography can be used in combination with different detectors to achieve qualitative or quantitative analysis and quality control of saponin compounds in medicinal materials and their preparations. This paper provides the latest valuable insights and references for the analytical methods and continued development and application of saponins.

Determination of Total Saccharide Content in Auricularia auricula Based on Near-Infrared Spectroscopy

In this paper, the content of total saccharide in Auricularia auricula from different regions was determined. Then, near-infrared (NIR) technology was used to collect the spectral information of the samples. The sample data were divided into calibration set and validation set. The best quantitative model of the total saccharide content of A. auricula was established by selecting the parameters such as spectral range, pretreatment method, and partial least square method (PLS) main factor number of the calibration set data. The validation set data were used to verify the reliability of this model. In this model, the original spectrum was used to preprocess by standard normal variate (SNV) + second derivative (SD) to eliminate the scattering effect caused by uneven particle distribution and the influence of noise on spectral data. The spectrum range was 4000–10000 cm−1, and the final choice of PLS main factor number was 11. Under this condition, the calibration set Rc2 of the model was 0.9092, the root mean square error of calibration (RMSEC) was 1.405, the root mean square error of prediction (RMSEP) was 1.507, and the residual predictive deviation (RPD) was 3.32. The validation samples were used to test the model, and the result showed that Rv2 = 0.9048 of the validation set. The result proved that the predicted value of the validation samples had a good linear relationship with the measured value. According to the T-test of the two sets of data in the validation set, the difference between the predicted value and the chemical value was not significant ( $P$  ≥ 0.05). The results were in line with the expected objectives. The established NIR quantitative model can be used to predict the total saccharide content of the black fungus sample to be tested.

Simultaneous determination of 19 constituents in Cimicifugae Rhizoma by HPLC-DAD and screening for antioxidants through DPPH free radical scavenging assay

Cimicifugae Rhizoma (sheng ma) is a well-known traditional Chinese medicine, which has been demonstrated to possess anti-inflammatory, antipyretic and analgesic activities. In the present study, a simple and efficient HPLC-DAD (high-performance liquid chromatography coupled with diode array detection) method was developed and validated for simultaneous quantification of 19 chemical components (including 16 phenolic acids, one coumarin and two alkaloids) in Cimicifugae Rhizoma. The result indicated that this method could effectively evaluate the quality of Cimicifugae Rhizoma and provide a valuable reference for further study. Additionally, the antioxidant activity of Cimicifugae Rhizoma was evaluated by DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging assay. The results showed that the content of phenolic acids and antioxidant activity exhibited significant correlation coefficients.