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Objective: To comprehensively evaluate the quality of Radix et Rhizoma Rhei based on gray correlationalanalysis and functional components, and to explore the difference of Radix et Rhizoma Rhei in different genuineproducing areas. Methods: HPLC was utilized to analyze 14 main compositions contained in the samples, includingemodin, rhein, chrysophanol, aloe-emodin, physcion, rheinoside, physcion glucoside, chrysophan, aloe-emodinglucoside, emodin methyl glycoside, sennoside, sennoside B, catechin and gallic acid. Then python 2.7 software wasemployed for gray correlation analysis of functional components closely related to the traditional efficacy of Radix et Rhizoma Rhei. Results: The qualities of Radix et Rhizoma Rhei grow in different areas were different. Tanggute Radix et Rhizoma Rhei grew in Tianzhu Gansu had the best effects of "expelling water retention and attacking the accumulation", and that grew in Yajiang Sichuan had the best effects of "clearing heat and removing toxin". Zhangye Radix et Rhizoma Rhei grew in Lixian Gansu had the best effect of"expelling stasis and unblocking the channels". Conclusion: Patternrecognition has broad prospects in the field of quality evaluation of traditional Chinese medicine. From the clinicalefficacy of traditional Chinese medicine, pattern recognition at the level of efficacy components can provide a new ideafor establishing a more complete and scientific quality evaluation system for traditional Chinese medicine.
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Glycyrrhizae Radix et Rhizoma is one of the traditional herbal medicine used in China, study on the correlation between the cross-section color and HPLC fingerprints of them have important significance for promoting the development of traditional disciplines. Quantitative analysis of the color of sample cross section was carried out by color digital method, fingerprint analysis was carried out by HPLC, and the canonical correlation analysis was carried out between them. The results showed that there was a significant correlation between the color of Glycyrrhizae Radix et Rhizoma cross section and the information of HPLC fingerprinting. Results indicated that, The digitized indexes of color of cross section could reflect the result of fingerprint analysis to some extent.
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After the present situation and characteristics of literature novelty assessment of traditional Chinese medicine were described, the importance of characteristic traditional Chinese medicine literacy of literature novelty assessors of traditional Chinese medicine was elaborated, the effect of literature novelty assessors on the literature novelty assessment of traditional Chinese medicine and the training of literature novelty assessors were studied in order to provide reference for other colleges and universities or scientific research institutions.
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This study was aimed to establish an objective and convenient method to evaluate the quality of licorice through the study on correlation between the cross section color and contents of active ingredients of licorice.Therefore,colorimeter was introduced and applied to determinate cross section color of licorice.Meanwhile,contents of five active ingredients of licorice were also determined.HPLC was used to determine liquiritin and glycyrrhizic acid.Colorimetric method was used to determine total saponins.Ultraviolet spectrophotometry was used to determine total flavonoids.Sulphuric acid-phenol colorimetry was used to determine polysaccharides.Correlation between the cross section color and content determination result was analyzed.The results showed that the correlation coefficient of glycyrrhizic acid content and L* was-0.578,P ＜ 0.001,the correlation coefficient with b* was 0.596,P ＜ 0.001;the correlation coefficient of liquiritin content and L* was-0.503,P =0.002,the correlation coefficient with b* was 0.890,P ＜ 0.001;the correlation coefficient of total flavonoids content and L* was-0.729,P ＜ 0.001,the correlation coefficient with b* was 0.724,P ＜ 0.001;the correlation coefficient of polysaccharides content and L* was 0.230,P =0.190,the correlation coefficient with b* was-0.390,P =0.023;the correlation coefficient of total saponins content and L* was-0.411,P =0.016,the correlation coefficient with b* was 0.738,P ＜ 0.001.It was concluded that the cross section color index of licorice has significant correlation with contents of glycyrrhizic acid,liquiritin,total flavonoids and total saponins.There was no significant correlation with content of polysaccharides.It illustrated the close correlation between cross section color of licorice and its active ingredients.Through the digitalized determination on color,contents of chemical composition in licorice can be initially determined or predicted objectively.It provided a new idea and method for the quality evaluation of Chinese herbal medicine.
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This study was aimed to identify Chrysanthemi Flosbefore and after sulfur fumigation based on its different odour by the electronic nose technology.It was expected to explore a new method for the Chrysanthemi Flos identification according to the odour.The electronic nose technology was used in the detection of peak response values of Chrysanthemi Flos on sensor array.The principal component analysis (PCA) and 10 machine learning (ML) ways were used in the analysis of response values and establishment of optimized identification models.The results showed that there was a significant difference in the odour between sulfur fumigated Chrysanthemi Flos and non-sulfur fumigated ones.The identification models were successful with high correct judge rate by PCA and 6 ML ways including BF Tree,J48 and Random Tree.It was concluded that the electronic nose technology can be used for the accurate identification of sulfur fumigated Chrysanthemi Flos and non-sulfur fumigated ones.The electronic nose technology combined with multiple ML methods can be introduced in the quality evaluation of Chrysanthemi Flos.It provided more ideas for the application of electronic nose in data mining for traditional Chinese medicine (TCM) studies.
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Objective Fructus Amomi(Sharen) is derived from the dry ripe fruit of Amomum villosum Lour., A.villosum Lour. var. xanthioides T.L. Wu et Senjen and A.longiligulate T.L.Wu, which is widely utilized for its clinic effects on digestive system. However, Fructus Amomi from different species and habitats, possessing different quality, is difficult to identify. In this study, we aim to develop a simple, rapid and reliable method for authentication of Fructus Amomi. Methods Twenty-five batches of samples of Fructus Amomi were collected and electronic nose was introduced into analyzing their odor with multiple mathematical statistics methods. Na?ve bayes network (NBN), radical basis function (RBF) and random forest (RF) were applied to establish different classifiers while BestFirst+CfsSubsetEval (BC) was used to screen the attributes for searching sensor array with higher contributions. Results Firstly, after attribute-screening via BC, the established discriminative models via NBN, RBF and RF could successfully identify genuine and non-genuine samples, presenting correct judging ratios of 78% and 84% through ten-fold cross validation and external test set validation, respectively. Besides, quantity predictive models were constructed as well. In case of content of bornyl acetate, one of the effective components in Fructus Amomi, values were higher than 3.5 mg/g and lower than 1.8 mg/g with sensor response of 0.04 and 0.03, respectively. Conclusion In this paper, quality discriminative model and quantity predictive model of Fructus Amomi were established via electronic nose and multiple mathematical statistics methods. It indicates that electronic nose could be a promising method for quality evaluation of Chinese material medica.
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Objective To compare differences and similarities of the content of trigonelline in Himalaica mirabilis of either wild or cultivated materials from different places. Methods An HPLC method was established to determine the content of trigonelline in Himalaica mirabilis. ZORBAX XDB-CN column (4.6 mm×250 mm, 5 μm) was used, with mobile phase of acetonitrile-0.03%acetic acid (85∶15), flow rate of 0.8 mL/min, detection wavelength of 265 nm, determination wavelength of 360 nm, and column temperature of 30 ℃. Results Regression calculation was made on peak area with the reference solution concentration, and then got the regression equation A=23.409C-26.398, r=0.999 8. Trigonelline showed good linear relation with peak area among the range of 2.004-200.400 μg/mL. The average recovery of trigonelline was 99.57%, RSD=1.11%. Conclusion There was no significant difference in the content of trigonelline of either wild or cultivated materials from different places. This study laid the foundation of application of the cultivated Himalaica mirabilis.
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This study was aimed to establish a method for sensorial color digitalization of Chinese herbal medicines (CHMs) with the application of spectrocolorimeter. The discussion was focused on difficulties of distinguishing surface and section color of CHMs. Based on uniform color space system of CIE1976L*a*b*, two methods for determination of section and surface color were constructed with two different kinds of spectrocolorimeters taking Glycyrrhizae Radix et Rhizoma as the experimental objective. In this paper, different kinds of sample preparation methods were used. Based on results, the method of scraping and grinding was proposed to prepare samples for section color determination. The method of wet pressing and peeling was proposed to prepare samples for surface color determination. Besides, RSD and dE*ab were served as evaluation indexes. This paper provided a simple, rapid and reliable analysis method for the color determination of CHMs. It also gave insight to future research on digitalization and modernization of CHMs' organoleptic characteristics based on traditional macroscopic identification.
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This study was aimed to establish the TLC identification method of Radix Mirab ilis himalaic a. The β-sitosterol and daucosterol were used as the reference substances. The single-factor test was used. A variety of factors which affected TLC were systematically investigated to filter out the best TLC conditions for identification of different batches of medicines. The results showed that the best TLC conditions were as follows: silica gel G plates, extraction solvent (methanol), reagent (5% sulfuric acid in ethanol), extraction method (ultrasonic extraction with methanol), ex-tracted time (30 min), the agent (petroleum ether-ethyl acetate-acetone (5:2:1)) and sample volume (6 μL). It was concluded that the method, which had high separation degree, was reproducible and simple. It can be used as the quality control of Radix Mirab ilis himalaic a.
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This study was aimed to apply the electronic nose (E-nose) in the research of traditional Chinese medicine (TCM). The discussion was made on difficulties of using E-nose. The solution plan was proposed and the discrimination model was established. It provided a simple, rapid and effective analysi method in the identification of TCM. It also provided new ideas for the research and application of gas sensor arrays. E-nose was used in the ex-traction of TCM scent characteristics. Based on ion mobility spectrometry of MOS sensor, the fingerprint of TCM scent was established. The maximum response value of the sensor was used as analysis index. According to the diffi-culties of identification, two solution plans were proposed. Firstly, different detectors were employed to complete the classification. Secondly, radial basis function (RBF) and random forests (RF) were combined and then a cascade classifier was constructed in order to achieve the maximum of information obtained in conditions where the number of measurements, metal oxide semiconductor sensors in E-nose was limited. The results showed that both plans were accurate and practical with relatively high upper correct judge rate and better cross-validation (The highest upper correct judge rates were 95% and 100%, 96% and 80%, respectively). It was concluded that this study firstly ap-plied cascade classifier in the establishment of TCM identification by E-nose. With limited amount of sensors, the maximum information was received through data mining. Using E-nose in the identification of TCM was rapid and accurate. The established pattern recognition method was maneuverable with accurate identification rate and stability compared to conventional sensory identification method. It provided a simple and rapid analysis method for the iden-tification of TCM.