Authentication of Herbal Medicines Based on Modern Analytical Technology Combined with Chemometrics Approach: A Review.

Since ancient times, herbal medicines (HMs) have been widely popular with consumers as a "natural" drug for health care and disease treatment. With the emergence of problems, such as increasing demand for HMs and shortage of resources, it often occurs the phenomenon of shoddy exceed and mixing the false with the genuine in the market. There is an urgent need to evaluate the quality of HMs to ensure their important role in health care and disease treatment, and to reduce the possibility of threat to human health. Modern analytical technology is can be analyzed for analyzing chemical components of HMs or their preparations. Reflecting complex chemical components' characteristic curves in the analysis sample, and the comprehensive effect of active ingredients of HMs. In this review, modern analytical technology (chromatography, spectroscopy, mass spectrometry), chemometrics methods (unsupervised, supervised) and their advantages, disadvantages, and applicability were introduced and summarized. In addition, the authentication application of modern analytical technology combined with chemometrics methods in four aspects, including origin, processing methods, cultivation methods, and adulteration of HMs have also been discussed and illustrated by a few typical studies. This article offers a general workflow of analytical methods that have been applied for HMs authentication and explains that the accuracy of authentication in favor of the quality assurance of HMs. It was provided reference value for the development and application of modern HMs.

Practical Qualitative Evaluation and Screening of Potential Biomarkers for Different Parts of Wolfiporia cocos Using Machine Learning and Network Pharmacology.

Wolfiporia cocos is a widely used traditional Chinese medicine and dietary supplement. Artificial intelligence algorithms use different types of data based on the different strategies to complete multiple tasks such as search and discrimination, which has become a trend to be suitable for solving massive data analysis problems faced in network pharmacology research. In this study, we attempted to screen the potential biomarkers in different parts of W. cocos from the perspective of measurability and effectiveness based on fingerprint, machine learning, and network pharmacology. Based on the conclusions drawn from the results, we noted the following: (1) exploratory analysis results showed that differences between different parts were greater than those between different regions, and the partial least squares discriminant analysis and residual network models were excellent to identify Poria and Poriae cutis based on Fourier transform near-infrared spectroscopy spectra; (2) from the perspective of effectiveness, the results of network pharmacology showed that 11 components such as dehydropachymic acid and 16α-hydroxydehydrotrametenolic acid, and so on had high connectivity in the "component-target-pathway" network and were the main active components. (3) From a measurability perspective, through orthogonal partial least squares discriminant analysis and the variable importance projection > 1, it was confirmed that three components, namely, dehydrotrametenolic acid, poricoic acid A, and pachymic acid, were the main potential biomarkers based on high-performance liquid chromatography. (4) The content of the three components in Poria was significantly higher than that in Poriae cutis. (5) The integrated analysis showed that dehydrotrametenolic acid, poricoic acid A, and pachymic acid were the potential biomarkers for Poria and Poriae cutis. Overall, this approach provided a novel strategy to explore potential biomarkers with an explanation for the clinical application and reasonable development and utilization in Poria and Poriae cutis.

Evaluation of Ecological Suitability and Quality Suitability of Panax notoginseng Under Multi-Regionalization Modeling Theory.

Panax notoginseng is an important medicinal plant in China, but there are some limitations in the ecological suitability study, such as incomplete investigation of species distribution, single regionalization modeling, and lack of collaborative evaluation of ecological suitability, and quality suitability. In this study, the maximum entropy model was used to analyze the ecological suitability of P. notoginseng under current and future climates. The multi-source chemical information of samples was collected to evaluate the uniformity between quality and ecology. The results showed that the current suitable habitat was mainly in southwest China. In the future climate scenarios, the high suitable habitat will be severely degraded. Modeling based on different regionalization could predict larger suitable habitat areas. The samples in the high suitable habitat had both quality suitability and ecological suitability, and the accumulation of chemical components had different responses to different environmental factors. Two-dimensional correlation spectroscopy combined with deep learning could achieve rapid identification of samples from different suitable habitats. In conclusion, global warming is not conducive to the distribution and spread of P. notoginseng. The high suitable habitat was conducive to the cultivation of high-quality medicinal materials. Actual regionalization modeling had more guiding significance for the selection of suitable habitats in a small area. The multi-regionalization modeling theory proposed in this study could provide a new perspective for the ecological suitability study of similar medicinal plants. The results provided a reference for the introduction and cultivation, and lay the foundation for the scientific and standardized production of high-quality P. notoginseng.

The Traditional Usages, Chemical Components and Pharmacological Activities of Wolfiporia cocos: A Review.

As an endemic species,Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. is widely distributed, such as in China, Korea, Japan, and North America, which have had a dual-purpose resource for medicines and food for over 2000 years. The applications of W. cocos were used to treat diseases including edema, insomnia, spleen deficiency, and vomiting. What's more, there have been wide uses of such edible fungi as a function food or dietary supplement recently. Up until now, 166 kinds of chemical components have been isolated and identified from W. cocos including triterpenes, polysaccharides, sterols, diterpenes, and others. Modern pharmacological studies showed that the components hold a wide range of pharmacological activities both in vitro and in vivo, such as antitumor, anti-inflammatory, antibacterial, anti-oxidant, and antidepressant activities. In addition, present results showed that the mechanisms of pharmacological activities were closely related to chemical structures, molecular signaling paths and the expression of relate proteins for polysaccharides and triterpenes. For further in-depth studies on this fungus based on the recent research status, this review provided some perspectives and systematic summaries of W. cocos in traditional uses, chemical components, pharmacological activities, separation and analysis technologies, and structure-activity relationships.

Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning.

Introduction: The cultivation and sale of medicinal plants are some of the main ways to meet the increased market demand for plant-based drugs. Panax notoginseng is a widely used Chinese medicinal material. The growth and accumulation of bioactive constituents mainly depend on a satisfactory growing environment. Additionally, the occurrence of market fraud means that care should be taken when purchasing. Methods: In this study, we report the correlation between saponins and climate factors based on high performance liquid chromatography (HPLC), and evaluate the influence of climate factors on the quality of P. notoginseng. In addition, the synchronous two-dimensional correlation spectroscopy (2D-COS) images of near infrared (NIR) data combined with the deep learning model were applied to traceability of geographic origins of P. notoginseng at two different levels (district and town levels). Results: The results indicated that the contents of saponins in P. notoginseng are negatively related to the annual mean temperature and the temperature annual range. A lower annual mean temperature and temperature annual range are favorable for the content accumulation of saponins. Additionally, high annual precipitation and high humidity are conducive to the content accumulation of Notoginsenoside R1 (NG-R1), Ginsenosides Rg1 (G-Rg1), and Ginsenosides Rb1 (G-Rb1), while Ginsenosides Rd (G-Rd), this is not the case. Regarding geographic origins, classifications at two different levels could be successfully distinguished through synchronous 2D-COS images combined with the residual convolutional neural network (ResNet) model. The model accuracy of the training set, test set, and external validation is achieved at 100%, and the cross-entropy loss function curves are lower. This demonstrated the potential feasibility of the proposed method for P. notoginseng geographic origin traceability, even if the distance between sampling points is small. Discussion: The findings of this study could improve the quality of P. notoginseng, provide a reference for cultivating P. notoginseng in the future and alleviate the occurrence of market fraud.

A Novel Multi-Preprocessing Integration Method for the Qualitative and Quantitative Assessment of Wild Medicinal Plants: Gentiana rigescens as an Example.

Until now, the over-exploitation of wild resources has increased growing concern over the quality of wild medicinal plants. This led to the necessity of developing a rapid method for the evaluation of wild medicinal plants. In this study, the content of total secoiridoids (gentiopicroside, swertiamarin, and sweroside) of Gentiana rigescens from 37 different regions in southwest China were analyzed by high performance liquid chromatography (HPLC). Furthermore, Fourier transform infrared (FT-IR) was adopted to trace the geographical origin (331 individuals) and predict the content of total secoiridoids (273 individuals). In the traditional FT-IR analysis, only one scatter correction technique could be selected from a series of preprocessing candidates to decrease the impact of the light correcting effect. Nevertheless, different scatter correction techniques may carry complementary information so that using the single scatter correction technique is sub-optimal. Hence, the emerging ensemble approach to preprocessing fusion, sequential preprocessing through orthogonalization (SPORT), was carried out to fuse the complementary information linked to different preprocessing methods. The results suggested that, compared with the best results obtained on the scatter correction modeling, SPORT increased the accuracy of the test set by 12.8% in qualitative analysis and decreased the RMSEP by 66.7% in quantitative analysis.

Study on the identification and evaluation of growth years for Paris polyphylla var. yunnanensis using deep learning combined with 2DCOS.

Paris polyphylla var. yunnanensis, as perennial plants, its quality is closely related to growth period. Different harvest years determine the dry matter accumulation of its medicinal parts and the dynamic accumulation of active ingredients, as well as its economic value and medicinal value. Therefore, it is necessary to establish a systematic evaluation method for the identification and evaluation of P. polyphylla var. yunnanensis with different growth years. Deep learning has a powerful ability in recognition. This study extends it to the identification analysis of medicinal plants from the perspective of spectrum. For the first time, two-dimensional correlation spectroscopy (2DCOS) based on the attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR) combined with residual neural network (Resnet) was used to identify growth years. 525 samples were collected, 4725 2DCOS images were drawn, and the dry matter accumulation in rhizomes of different growth years and different sampling sites were briefly analyzed. The results show that the eight-year-old P. polyphylla var. yunnanensis in Dali has higher economic value and medicinal value. The synchronous 2DCOS models based on ATR-FTIR can realize the identification of growth years with accuracy of 100%. Synchronous 2DCOS are more suitable for the identification of medicinal plants with complex systems. 2DCOS images with different colors and second derivative processing cannot optimize the modeling results. In summary, the method we established is innovative and feasible. It not only solved the identification of growth years, expanded the application field of deep learning, but could also be extended to further research on other medicinal plants.

The traditional uses, phytochemistry, and pharmacological properties of Paris L. (Liliaceae): A review.

ETHNOPHARMACOLOGICAL RELEVANCE: Paris L. (Liliaceae) consisted of 33 species, of which the study focused on Paris polyphylla Smith, P. polyphylla var. chinensis (Franch.) Hara, and P. polyphylla Smith var. yunnanensis (Franch.) Hand. -Mazz. Due of course to the good effects of analgesia and hemostasis, it was traditionally used to treat trauma by folk herbalists. AIM OF THIS REVIEW: This study summarized the traditional uses, distributions, phytochemical components, pharmacological properties, and toxicity evaluation of the genus Paris, and reviewed the economic value of cultivate P. polyphylla. This aim was that of providing a new and comprehensive recognition of these medicinal plants for the further utilization of Paris plants. MATERIALS AND METHODS: The literature about traditional and folk uses of genus Paris was obtained from Duxiu Search, and China National Knowledge Infrastructure (CNKI). The other literature about genus Paris was searched online on Web of Science, PubMed, Google Scholar, Baidu Scholar, Scifinder database, and Springer research. The Scientific Database of China Plant Species (DCP) (http://db.kib.ac.cn/Default.aspx) databases were used to check the scientific names and provide species, varieties, and distribution of genus Paris. The botany studies information of genus Paris was available online from Plant Plus of China (www.iplant.cn). All the molecular structures of chemical compounds displayed in the text were produced by ChemBioDraw Ultra 14.0. RESULTS: The plants of genus Paris, containing about 33 species and 15 varieties, are mainly distributed in Southwest China (Yunnan, Sichuan, and Guizhou provinces). More than 320 chemical components have been isolated from genus Paris since 2020, including steroidal saponins, C-21 steroids, phytosterols, insect hormones, pentacyclic triterpenes, flavonoids, and other compounds. Arrays of pharmacological investigations revealed that compounds and extracts of Paris species possess a wide spectrum of pharmacological effects, such as antitumor, cytotoxic, antimicrobial, antifungal, hemostatic, and anti-inflammatory activities. The studies about toxicity evaluation suggested that Rhizome Paridis had slight liver toxicity. CONCLUSIONS: The dried rhizomes of P. polyphylla, P. polyphylla var. chinensis, and P. polyphylla var. yunnanensis were used to treat wound, bleeding, and stomachache, etc. in folk medicine. Phytochemistry researches showed that different species had pretty similarities especially in terms of chemical constituents. Pharmacological studies witnessed that Rhizome Paridis has various activities. Among these activities, steroidal saponins were the main active ingredients. Furthermore, an important aspect responsible for increasing interest in genus Paris is the use of antifertility-nonhormonal contraceptives by women. Also, the development of TCM (Traditional Chinese medicine) planting industry can improve the income of ethnic minorities and promote economic development.

Application of Identification and Evaluation Techniques for Ethnobotanical Medicinal Plant of Genus Panax: A Review.

Genus Panax, as worldwide medicinal plants, has a medical history for thousands of years. Most of the entire genus are traditional ethnobotanical medicine in China, Myanmar, Thailand, Vietnam and Laos, which have given rise to international attention and use. This paper reviewed more than 210 articles and related books on the research of Panax medicinal plants and their Chinese patent medicines published in the last 30 years. The purpose was to review and summarize the species classification, geographical distribution, and ethnic minorities medicinal records of the genus Panax, and further to review the analytical tools and data analysis methods for the authentication and quality assessment of Panax medicinal materials and Chinese patent medicines. Five main technologies applied in the identification and evaluation of Panax have been introduced and summarized. Chromatography was the most widely used one. Further research and development of molecular identification technology had the potential to become a mainstream identification technology. In addition, some novel, controversial, and worthy methods including electronic noses, electronic eyes, and DNA barcoding were also introduced. At the same time, more than 80% of the researches were carried out by a combination of chemometric pattern-recognition technologies and multi-analysis technologies. All the technologies and methods applied can provide strong support and guarantee for the identification and evaluation of genus Panax, and also conduce to excellent reference value for the development and in-depth research of new technologies in Panax.

Study on Quality Response to Environmental Factors and Geographical Traceability of Wild Gentiana rigescens Franch.

Gentiana rigescens Franch. ex Hemsl. is an important medicinal plant in China and the over exploitation of wild resources has affected its quality and clinical efficacy. The accumulation of plant secondary metabolites is not only determined by their genetic characteristics but also influenced by environmental factors. At present, many studies on evaluating the environmental conditions of its planting area are still in the qualitative stage. Therefore, it is necessary to establish a systematic evaluation method to deeply analyze the impact of environmental factors on the quality of medicinal materials and quickly verify the geographical origin. In this study, the contents of five iridoids (loganic acid, swertiamarin, sweroside, gentiopicroside and 6'-O-ß-D-glucopyranosylgentiopicroside) of G. rigescens from 45 different origins (including 441 individuals) of Yunnan Province in China were analyzed by high performance liquid chromatography. Analytical procedures of one-way analysis of variance, correlation analysis, principal components analysis, and hierarchical cluster analysis were employed to interpret the correlation of iridoid content and environmental factors. Fourier transform infrared spectroscopy (FT-IR) combined with two multivariate analysis methods (partial least squares discriminant analysis; support vector machines, SVM) was used to discriminate four major producing areas (158 individuals). The combination of SVM with grid search algorithm achieved an accuracy of 100% in the test set. One-way analysis of variance showed that the contents of five iridoids in root tissues of G. rigescens varied significantly among different origins, which was also verified by the chemometrics analysis results of hierarchical cluster analysis. The results of correlation analysis indicated that the high value of altitude and precipitation were unfavorable for the accumulation of these five iridoids. A correlation between increase of temperature and iridoid accumulation was observed. This study provided a certain theoretical basis for the resource protection and development of G. rigescens based on the correlation analysis between the ecological environment factors and quality.

Investigation of a Medical Plant for Hepatic Diseases with Secoiridoids Using HPLC and FT-IR Spectroscopy for a Case of Gentiana rigescens.

Secoiridoids could be used as a potential new drug for the treatment of hepatic disease. The content of secoiridoids of G. rigescens varied in different geographical origins and parts. In this study, a total of 783 samples collected from different parts of G. rigescens in Yunnan, Sichuan, and Guizhou Provinces. The content of secoiridoids including gentiopicroside, swertiamarin, and sweroside were determined by using HPLC and analyzed by one-way analysis of variance. Two selected variables including direct selected and variable importance in projection combined with partial least squares regression have been used to establish a method for the determination of secoiridoids using FT-IR spectroscopy. In addition, different pretreatments including multiplicative scatter correction (MSC), standard normal variate (SNV), first derivative and second derivative (SD), and orthogonal signal correction (OSC) were compared. The results indicated that the sample (root, stem, and leaf) with total secoiridoids, gentiopicroside, swertiamarin, and sweroside from west Yunnan had higher content than samples from the other regions. The sample from Baoshan had more total secoiridoids than other samples for the whole medicinal plant. The best performance using FT-IR for the total secoiridoid was with the direct selected variable method involving pretreatment of MSC+OSC+SD in the root and stem, while in leaf, of the best method involved using original data with MSC+OSC+SD. This method could be used to determine the bioactive compounds quickly for herbal medicines.

Comparison and quantitative analysis of wild and cultivated Macrohyporia cocos using attenuated total refection-Fourier transform infrared spectroscopy combined with ultra-fast liquid chromatography.

Dried sclerotium of Macrohyporia cocos is a well-known and widely-consumed traditional Chinese medicine and is also used as dietary supplement. According to the differential treatment between cultivation and wild habitats in the market, the comparison and quantitative analysis of wild and cultivated M. cocos were performed using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy and ultra-fast liquid chromatography combined with partial least squares discriminant analysis and partial least squares regression (PLSR). 636 samples were used for the spectral scan and chromatographic analysis. Results indicated that contents of dehydrotumulosic acid, poricoic acid A and dehydrotrametenolic acid in cultivated samples were significantly different from wild samples in two medicinal parts. Differences of dehydropachymic acid and pachymic acid just existed in inner part samples (P < 0.05). Wild M. cocos samples could be discriminated with cultivated samples with >95.14% efficiency using spectral data. ATR-FTIR combined with PLSR provided satisfactory performance for content predictions of poricoic acid A and dehydrotrametenolic acid. This study demonstrated that growth patterns could affect the quality of inner part and epidermis of M. cocos, and ATR-FTIR was a promising technique for the identification of wild and cultivated M. cocos and the rapid determination of triterpene acids contents.

Origin identification of Panax notoginseng by multi-sensor information fusion strategy of infrared spectra combined with random forest.

Traditional Chinese medicine Panax notoginseng is a valuable geo-authentic herbal material. The difference of growth environment in different producing areas has significant influence on the quality of traditional Chinese medicine, and origin identification is an important part of the quality assessment of P. notoginseng. In this study, Fourier transform mid-infrared (FT-MIR) and near infrared (NIR) sensor technologies combined with single spectra analysis and multi-sensor information fusion strategy (low-, mid- and high-level) for the origin identification of 210 P. notoginseng samples from five cities in Yunnan Province, China. FT-MIR spectra were considered to play a greater role in data analysis than NIR spectra. Random forest (RF) was used to establish classification models. The result of the random forest Boruta (RF-Bo) model and the random forest variable selection (RF-Vs) model based on high-level multi-sensor information fusion strategy was satisfactory. In addition, the RF-Bo model based on high-level multi-sensor information fusion strategy was faster and simpler in data analysis and the accuracy was 95.6%.

Comparison and Identification for Rhizomes and Leaves of Paris yunnanensis Based on Fourier Transform Mid-Infrared Spectroscopy Combined with Chemometrics.

Paris polyphylla, as a traditional herb with long history, has been widely used to treat diseases in multiple nationalities of China. Nevertheless, the quality of P. yunnanensis fluctuates among from different geographical origins, so that a fast and accurate classification method was necessary for establishment. In our study, the geographical origin identification of 462 P. yunnanensis rhizome and leaf samples from Kunming, Yuxi, Chuxiong, Dali, Lijiang, and Honghe were analyzed by Fourier transform mid infrared (FT-MIR) spectra, combined with partial least squares discriminant analysis (PLS-DA), random forest (RF), and hierarchical cluster analysis (HCA) methods. The obvious cluster tendency of rhizomes and leaves FT-MIR spectra was displayed by principal component analysis (PCA). The distribution of the variable importance for the projection (VIP) was more uniform than the important variables obtained by RF, while PLS-DA models obtained higher classification abilities. Hence, a PLS-DA model was more suitably used to classify the different geographical origins of P. yunnanensis than the RF model. Additionally, the clustering results of different geographical origins obtained by HCA dendrograms also proved the chemical information difference between rhizomes and leaves. The identification performances of PLS-DA and the RF models of leaves FT-MIR matrixes were better than those of rhizomes datasets. In addition, the model classification abilities of combination datasets were higher than the individual matrixes of rhizomes and leaves spectra. Our study provides a reference to the rational utilization of resources, as well as a fast and accurate identification research for P. yunnanensis samples.

Comprehensive quality assessment of Dendrubium officinale using ATR-FTIR spectroscopy combined with random forest and support vector machine regression.

Dendrobium officinale, as a tonic herb, has attracted more and more consumers to consume in daily life. In order to protect the wild resource, the herb has made great progress though cultivation in vitro. However, the quality is fluctuated in Chinese herbal medicine market due to influence such as cultivated areas and harvesting period. Therefore, the herbal samples from different cultivated locations were evaluated with high-performance liquid chromatography with diode array detector (HPLC-DAD) in terms of two chemical components, quercetin and erianin. In addition, two markers in leaf and stem also were used for support vector machine regression (SVMR) prediction. Samples from different harvesting periods were also classified using attenuated total reflectance mid-infrared spectroscopy coupled with random forest model. The results indicated that Pu'er and Menghai in Yunnan Province were suitable places for the herb cultivation and the leaf of the herb was also an exploitable resource just in light of the content of two components. What's more, combination of suitable spectra pretreatment and grid search method efficiently improved the prediction performance of the regression model. The results of random forest model indicated that important variables combination between stem and leaf was an effective tool to predict the harvesting time of the herb with 94.44% accuracy in calibration set and 97.92% classification correct rate in validation set. The results of combination were better than the models using individual stem and leaf spectra. In addition, the suitable harvesting time (December) could be classified efficiently. Our study provides a reference for quality control of raw materials from D. officinale herb.

Quantification and Discrimination of in Vitro Regeneration Swertia nervosa at Different Growth Periods using the UPLC/UV Coupled with Chemometric Method.

BACKGROUND: Swertia nervosa (Wall. ex G. Don) C. B. Clarke, a promising traditional herbal medicine for the treatment of liver disorders, is endangered due to its extensive collection and unsustainable harvesting practices. OBJECTIVE: The aim of this study is to discuss the diversity of metabolites (loganic acid, sweroside, swertiamarin, and gentiopicroside) at different growth stages and organs of Swertia nervosa using the ultra-high-performance LC (UPLC)/UV coupled with chemometric method. METHODS: UPLC data, UV data, and data fusion were treated separately to find more useful information by partial least-squares discriminant analysis (PLS-DA). Hierarchical cluster analysis (HCA), an unsupervised method, was then employed for validating the results from PLS-DA. RESULTS: Three strategies displayed different chemical information associated with the sample discrimination. UV information mainly contributed to the classification of different organs; UPLC information was prominently responsible for both organs and growth periods; the data fusion did not perform with apparent superiority compared with single data analysis, although it provided useful information to differentiate leaves that could not be recognized by UPLC. The quantification result showed that the content of swertiamarin was the highest compared with the other three metabolites, especially in leaves at the rooted stage (19.57 ± 5.34 mg/g). Therefore, we speculated that interactive transformations occurred among these four metabolites, facilitated by root formation. CONCLUSIONS: This work will contribute to exploitation of bioactive compounds of S. nervosa, as well as its large-scale propagation. HIGHLIGHTS: The roots formation may influence the distribution and accumulation of metabolites.

[Data fusion and multi-components quantitative analysis for identification and quality evaluation of Gentiana rigescens from different geographical origins].

The accumulation of secondary metabolites of traditional Chinese medicine (TCM) is closely related to its origins. The identification of origins and multi-components quantitative evaluation are of great significance to ensure the quality of medicinal materials. In this study, the identification of Gentiana rigescens from different geographical origins was conducted by data fusion of Fourier transform infrared (FTIR) spectroscopy and high performance liquid chromatography (HPLC) in combination of partial least squares discriminant analysis; meanwhile quantitative analysis of index components was conducted to provide an accurate and comprehensive identification and quality evaluation strategy for selecting the best production areas of G. rigescens. In this study, the FTIR and HPLC information of 169 G. rigescens samples from Yunnan, Sichuan, Guangxi and Guizhou Provinces were collected. The raw infrared spectra were pre-treated by multiplicative scatter correction, standard normal variate (SNV) and Savitzky-Golay (SG) derivative. Then the performances of FTIR, HPLC, and low-level data fusion and mid-level data fusion for identification were compared, and the contents of gentiopicroside, swertiamarin, loganic acid and sweroside were determined by HPLC. The results showed that the FTIR spectra of G. rigescens from different geographical origins were different, and the best pre-treatment method was SNV+SG-derivative (second derivative, 15 as the window parameter, and 2 as the polynomial order). The results showed that the accuracy rate of low- and mid-level data fusion (96.43%) in prediction set was higher than that of FTIR and HPLC (94.64%) in prediction set. In addition, the accuracy of low-level data fusion (100%) in the training set was higher than that of mid-level data fusion (99.12%) in training set. The contents of the iridoid glycosides in Yunnan were the highest among different provinces. The average content of gentiopicroside, as a bioactive marker in Chinese pharmacopoeia, was 47.40 mg·g⁻¹, and the maximum was 79.83 mg·g⁻¹. The contents of loganic acid, sweroside and gentiopicroside in Yunnan were significantly different from other provinces (P<0.05). In comparison of total content of iridoid glycosides in G. rigescens with different geographical origins in Yunnan, it was found that the amount of iridoid glycosides was higher in Eryuan Dali (68.59 mg·g⁻¹) and Yulong Lijiang (66.68 mg·g⁻¹), significantly higher than that in Wuding Chuxiong (52.99 mg·g⁻¹), Chengjiang Yuxi (52.29 mg·g⁻¹) and Xundian Kunming (46.71 mg·g⁻¹) (P<0.05), so these two places can be used as a reference region for screening cultivation and excellent germplasm resources of G. rigescens. A comprehensive and accurate method was established by data fusion of HPLC-FTIR and quantitative analysis of HPLC for identification and quality evaluation of G. rigescens, which could provide a support for the development and utilization of G. rigescens.

Quantitative and Qualitative Characterization of Gentiana rigescens Franch (Gentianaceae) on Different Parts and Cultivations Years by HPLC and FTIR Spectroscopy.

Gentiana rigescens Franch (Gentianaceae) is a famous medicinal plant for treatments of rheumatism, convulsion, and jaundice. Comprehensive investigation of different parts and cultivation years of this plant has not yet been conducted. This study presents the quantitative and qualitative characterization of iridoid glycosides from G. rigescens performed by HPLC and FTIR spectroscopy techniques. The accumulations of loganic acid, swertiamarin, gentiopicroside, and sweroside were determined. Results indicated that their content and distribution in different parts and cultivation years exhibit great variations. Gentiopicroside was identified as the most abundant compound among iridoid glycosides and its highest level was observed in the root of 2-year-old plant. With respect to qualitative variation of metabolic profile, the 1800-800 cm-1 band of FTIR spectra successfully discriminated different parts and cultivation years with the aid of PLS-DA. In addition, combined with PLSR, the feasibility of FTIR spectroscopy for determination of gentiopicroside was investigated by selecting characteristic wavelengths (1800-800 cm-1), which presented a good performance with a residual predictive deviation (RPD) of 3.646. Our results suggested that HPLC and FTIR techniques can complement each other and could be simultaneously applied for comparing and analyzing different parts and cultivation years of G. rigescens.

[Study on Different Parts of Wild and Cultivated Gentiana Rigescens with Fourier Transform Infrared Spectroscopy].

The application of traditional Chinese medicine (TCM) and their preparations have a long history. With the deepening of the research, the market demand is increasing. However, wild resources are so limited that it can not meet the needs of the market. The development of wild and cultivated samples and research on accumulation dynamics of chemical component are of great significance. In order to compare composition difference of different parts (root, stem, and leaf) of wild and cultivated G. rigescens, Fourier infrared spectroscopy (FTIR) and second derivative spectra were used to analyze and evaluate. The second derivative spectra of 60 samples and the rate of affinity (the match values) were measured automatically using the appropriate software (Omnic 8.0). The results showed that the various parts of wild and cultivated G. rigescens. were high similar the peaks at 1732, 1 643, 1 613, 1 510, 1 417, 1 366, 1 322, 1 070 cm(-1) were the characteristic peak of esters, terpenoids and saccharides, respectively. Moreover, the shape and peak intensity were more distinct in the second derivative spectrum of samples. In the second derivative spectrum range of 1 800-600 cm(-1), the fingerprint characteristic peak of samples and gentiopicroside standards were 1 679, 1 613, 1 466, 1 272, 1 204, 1 103, 1 074, 985, 935 cm(-1). The characteristic peak intensity of gentiopicroside of roots of wild and cultivated samples at 1 613 cm(-1) (C-C) was higher than stems and leaves which indicated the higher content of gentiopicroside in root than in stem and leaves. Stems of wild samples at 1 521, 1 462 and 1 452 cm(-1) are the skeletal vibration peak of benzene ring of lignin, and the stem of cultivated sample have stronger peak than other samples which showed that rich lignin in stems. The iInfrared spectrum of samples were similar with the average spectral of root of wild samples, and significant difference was found for the correlation between second derivative spectrum of samples and average spectral of wild samples root, and the sequence of similarity was root > stem > leaf. Therefore, FTIR combined with second derivative spectra was an express and comprehensive approach to analyze and evaluate in the imperceptible differences among different parts of wild and cultivated of G. rigescens.

[Analysis and Discrimination of the Medicinal Plants Swertia Davidi Franch Based on Infrared Spectroscopy].

Fourier-transform infrared spectroscopy combined with partial least squares discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to rapidly discriminate the Swertia davidi Franch which collected from different origins. The original infrared spectra data of different parts of all the 70 samples which collected from four different regions were preprocessed by automatic calibration, automatic smoothing, the first derivative and the,second derivative. Then the processed data were imported into OMNIC 8.2 and the absorption peaks were compared; PLS-DA was performed by SIMCA-P⁺ 10.0 and the effect of discrimination of different origins was compared by 3D score plot of the first three principal components; the infrared spectral data were imported into SPSS 19. 0 for HCA to compare classification results of different parts by the dendrogram. The results showed that: (1) There were differences among the spectra of the roots of different origins in the spectral peaks in 1,739, 1,647, 1,614, 1,503, 1,271, 1,243, 1,072 cm⁻¹. The spectra of the stems of different origins showed differentiation in the wavelength in 1 503, 1 270, 1 246 cm⁻¹; (2) The characteristic peaks of different parts of the same origin were different; (3) PLS-DA indicated that the data which were processed by automatic correction, automatic smoothing and second derivative have showed the best classification. In addition, the discrimination of roots which collected from different origins could be the best; (4) Tree diagram of HCA showed that the accuracy rate of cluster in roots, stems and leaves were 83%, 56%, and 70%, respectively. In conclusion: FTIR combined with PLS-DA and HCA can rapidly and accurately differentiate S. davidi that collected from different origins, the origin discrimination effect of different parts was clearly different that the classification of roots is the best, the second derivative could enhance the specificity of the samples, the classification in 3D score plot could be visualized and obvious.