Differentiation of Mint (Mentha haplocalyx Briq.) from different regions in China using gas and liquid chromatography

In this study, complex substances such as Mint (Mentha haplocalyx Briq.) samples from different growing regions in China were analyzed for phenolic compounds by high‐performance liquid chromatography with diode array detection and for the volatile aroma compounds by gas chromatography with mass spectrometry. Chemometrics methods, e.g. principal component analysis, back‐propagation artificial neural networks, and partial least squares discriminant analysis, were applied to resolve complex chromatographic profiles of Mint samples. A total of 49 aroma components and 23 phenolic compounds were identified in 79 Mint samples. Principal component analysis score plots from gas chromatography with mass spectrometry and high‐performance liquid chromatography with diode array detection data sets showed a clear distinction among Mint from three different regions in China. Classification results showed that satisfactory performance of prediction ability for back‐propagation artificial neural networks and partial least squares discriminant analysis. The major compounds that contributed to the discrimination were chlorogenic acid, unknown 3, kaempherol 7‐O‐rutinoside, salvianolic acid L, hesperidin, diosmetin, unknown 6 and pebrellin in Mint according to regression coefficients of the partial least squares discriminant analysis model. This study indicated that the proposed strategy could provide a simple and rapid technique to distinguish clearly complex profiles from samples such as Mint.     

Metabolite profiling to discriminate different species and genus from thistles in Korea using liquid chromatography with quadrupole time‐of‐flight mass spectrometry

This study was designed to classify and identify closely related thistle species in the genus Cirsium, as well as Carduus and Cephalonoplos species, which are also thistles. The comprehensive and untargeted metabolite profiles of nine Korean thistles were determined using ultra high performance liquid chromatography combined with hybrid quadrupole time‐of‐flight mass spectrometry. The difference in metabolite profiles among species was explored using principal component analysis and hierarchical clustering analysis. The significantly different metabolites (Bonferroni‐corrected P‐value < 0.001) were used to construct a partial least squares discriminant analysis model to predict the species of thistle. Nine species were successfully classified using a partial least squares discriminant analysis model and confirmed using a cross‐validation method. Species with similar features were grouped based on unique patterns in variable clusters. The present study suggests that liquid chromatography with quadrupole time‐of‐flight mass spectrometry untargeted metabolomic profiling with chemometric analysis is an efficient and powerful tool for discriminating between different species of medicinal herbs.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Two‐way and three‐way approaches to ultra high performance liquid chromatography–photodiode array dataset for the quantitative resolution of a two‐component mixture containing ciprofloxacin and ornidazole

Two‐way and three‐way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three‐way calibrations for the decomposition of the tensor, whereas three‐way unfolded partial least squares was applied as a two‐way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two‐way and three‐way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two‐way and three‐way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole.     

Metabolomics based on liquid chromatography with mass spectrometry reveals the chemical difference in the stems and roots derived from Ephedra sinica

To better understand different traditional uses of the stems (known as Mahuang) and roots (known as Mahuanggen) of Ephedra sinica, their chemical difference should be investigated. In this study, an ultra‐fast liquid chromatography coupled with ion trap time‐of‐flight mass spectrometry untargeted metabolomics approach was established to reveal global chemical difference between Mahuang and Mahuanggen. Clear separation was observed in scores plots of principal component analysis and orthogonal partial least squares‐discriminant analysis. Twenty two chemical markers responsible for such separation were screened out and unambiguously/tentatively characterized. Then chemical markers of pharmacologically important ephedrine and pseudoephedrine were absolutely quantified using liquid chromatography coupled with tandem mass spectrometry under multiple reaction monitoring mode. The results showed that Mahuang was rich in ephedrine‐type alkaloids, while Mahuanggen was rich in macrocyclic spermine alkaloids. Additionally, different types of flavan‐3‐ols and flavones exist in Mahuang and Mahuanggen extracts. This research facilitates a better understanding of different traditional uses of Mahuang and Mahuanggen and provides references for chemical analysis of other medicinal plants.     

A useful approach for the differentiation of wines according to geographical origin based on global volatile patterns

In this study, the feasibility of solid‐phase extraction combined with gas chromatography and mass spectrometry in tandem with partial least squares discriminant analysis was evaluated as a useful strategy to differentiate wines according to geographical origin (Azores, Canary and Madeira Islands) and types (white, red and fortified wine) based on their global volatile patterns. For this purpose, 34 monovarietal wines from these three wine grape‐growing regions were investigated, combining the high throughput extraction efficiency of the solid‐phase extraction procedure with the separation and identification ability. The partial least squares discriminant analysis results suggested that Madeira wines could be clearly discriminated from Azores and Canary wines. Madeira wines are mainly characterized by 2‐ethylhexan‐1‐ol, 3,5,5‐trimethylhexan‐1‐ol, ethyl 2‐methylbutanoate, ethyl dl ‐2‐hydroxycaproate, decanoic acid, 3‐methylbutanoic acid, and (E)‐whiskey lactone, whereas 3‐ethoxypropan‐1‐ol, 1‐octen‐3‐ol, (Z)‐3‐hexenyl butanoate, 4‐(methylthio)‐1‐butanol, ethyl 3‐hydroxybutanoate, isoamyl lactate, 4‐methylphenol, γ‐octalactone and 4‐(methylthio)‐1‐butanol, are mainly associated with Azores and Canary wines. The data obtained in this study revealed that solid‐phase extraction combined with gas chromatography and quadrupole mass spectrometry data and partial least squares discriminant analysis provides a suitable tool to discriminate wines, both in terms of geographical origin as well as wine type and vintage.     

Identification of four cornua by ultra‐performance liquid chromatography with time‐of‐flight mass spectrometry coupled with principal component analysis

An ultra‐high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry method coupled with principal component analysis was developed and applied to the identification of Cornu Antelopis, Cornu Bubali, Cornu Naemorhedi, and Cornu Bovis. The data obtained from the trypsin‐digested samples were subjected to principal component analysis to classify these four cornua. Additionally, marker peptides of the cornua were determined by orthogonal partial least‐squares discriminant analysis, and fragmentation tandem mass spectra of these marker peptides were evaluated. The results from this study indicate that the proposed method is reliable, and it has been successfully applied to the identification of variants of cornua commonly used in traditional Chinese medicine.     

Urinary metabolomic study of non‐small cell lung carcinoma based on ultra high performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

Metabolic profiles from human urine reveal the significant difference of carnitine and acylcarnitines levels between non‐small cell lung carcinoma patients and healthy controls. Urine samples from cancer patients and healthy individuals were assayed in this metabolomic study using ultra high performance liquid chromatography coupled to quadrupole time‐of‐flight mass spectrometry. The data were normalized by the sum of all intensities and creatinine calibration, respectively, before orthogonal partial least squares discriminant analysis. Twenty differential metabolites were identified based on standard compounds or tandem mass spectrometry fragments. Among them, some medium‐/long‐chain acylcarnitines, for example, cis‐3,4‐methylene heptanoylcarnitine, were found to be downregulated while carnitine was upregulated in urine samples from the cancer group compared to the control group. Receiver operating characteristic analysis of the two groups showed that the area under curve for the combination of carnitine and 11 selected acylcarnitines was 0.958. This study suggests that the developed carnitine and acylcarnitines profiling method has the potential to be used for screening non‐small cell lung carcinoma.     

Ultra high performance liquid chromatography with synapt high‐definition mass spectrometry and a pattern recognition approach to characterize chemical constituents and rat metabolites after the oral administration of Phellinus igniarius

Phellinus igniarius has antibacterial, antiviral, antioxidative, antitumor, and antimutagenic effects. In this study, an integrative pattern recognition approach using principal component analysis and orthogonal partial least squares discriminant analysis was successfully applied for the rapid analysis of natural compounds in traditional Chinese medicine. An ultra high performance liquid chromatography with synapt high‐definition mass spectrometry method and MassLynx software was used. This method employed gradient elution to rapidly analyze and characterize chemical constituents and metabolites after the oral administration of a P. igniarius ethanol extract. There were 24 peaks within 10 min of the analysis time and 20 of these were identified or tentatively characterized on the basis of their fragmentation behaviors. In the S‐plot of the orthogonal partial least squares discriminant analysis, 27 ions were extracted to make the serum. Among them, nine absorbed the prototype components and 18 metabolites were identified in vivo. Glucuronidation, oxidation, and methylation were the major metabolic reactions. This study is the first systematic analysis and characterization of the chemical constituents and metabolites in an ethanol extract of P. igniarius. This method can be applied to the rapid analysis and characterization of constituents in rat serum after the oral administration of other compounds used in traditional Chinese medicines.     

Influence of different processing times on the quality of Polygoni Multiflora Radix by metabolomics based on ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry

A metabolomics method based on ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry was developed to evaluate the influence of processing times on the quality of raw and processed Polygoni Multiflora Radix . Principal component analysis and partial least‐squares discriminant analysis was used to screen the potential maker metabolites that were contributed to the quality changes. Then these marker metabolites were selected as variables in Fisher's discriminant analysis to establish the models that were used to distinguish the raw and processed Polygoni Multiflora Radix in the markets. Additionally, 36 compounds were identified. Twelve raw Polygoni Multiflora Radix samples and 23 processed Polygoni Multiflora Radix samples were distinguished. The results showed that the 12 raw Polygoni Multiflora Radix samples belonged to the group of processing time of 0 h, and two processed Polygoni Multiflora Radix samples were part of the group of processing times of 4 h, 12 samples belonged to group of processing times of 8 to 16 h, and nine samples were the group of processing times of 24 to 48 h. The results demonstrated that the method could provide scientific support for the processing standardization of Polygoni Multiflora Radix .     

Quality evaluation of Salvia miltiorrhiza Bge. by ultra high performance liquid chromatography with photodiode array detection and chemical fingerprinting coupled with chemometric analysis

An ultra high performance liquid chromatography with photodiode array detection method is developed for the simultaneous quantitative determination of five water‐soluble compounds including danshensu, protocatechualdehyde, rosmarinic acid, salvianolic acid B, and salvianolic acid A in Salvia miltiorrhiza Bge. samples. Through method optimization, the five compounds all expressed good linearity (R² > 0.9990) in a wide concentration range together with satisfactory accuracy, precision, and stability. Moreover, through qualitative analysis of the chemical fingerprint combined with similarity analysis, hierarchical cluster analysis, principle component analysis, and partial least‐squares discriminate analysis, we determined that the 13 batches of Salvia miltiorrhiza Bge. were similar in internal quality and the differences resulted from various cultivation environments, recovery elements, and others. Seen from the results of hierarchical cluster analysis and principle component analysis, the classification of 13 batches was in accordance, and partial least‐squares discriminate analysis technique was more suitable than the principle component analysis model to provide a distinct classification of test samples on the basis of their different components. Moreover, a permutation test verified the rationality of partial least‐squares discriminate analysis and variable importance plot showed that peaks 37 and 38 were the most significant variables in distinguishing the Salvia miltiorrhiza Bge. samples. The idea of the quantitative and qualitative analysis of Salvia miltiorrhiza Bge. was convenient, sensitive, and comprehensive, which could be applied to evaluate the quality of more traditional Chinese medicines.     

Quantitative and qualitative analysis of Artemisiae Verlotori Folium and Artemisiae Argyi Folium by high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry

Artemisiae Argyi Folium (Aiye in Chinese) has been widely used since ancient times. In the Lingnan region (Southern China), the leaf of Artemisia verlotorum Lamotte, which is named Hongjiaoai (HJA) because the roots are red (Hongjiao means red foot in Chinese), has been used as a local substitute for Artemisiae Argyi Folium. The plant has a long medicinal and edible history that can be traced to the Jin Dynasty. However, there is no systematic and reliable method to control the quality of Artemisiae Verlotori Folium. In this study, a comprehensive method involving high-performance liquid chromatography coupled with diode array detection and quadrupole-time-of-flight high-definition mass spectrometry was established to identify and quantify eight constituents (including organic acids and flavonoids) in Artemisiae Verlotori Folium and Artemisiae Argyi Folium as well as high-performance liquid chromatography fingerprints of the two varieties. Moreover, dissimilarities of chemical compositions among the two varieties were further investigated by orthogonal partial least squares discrimination analysis and cluster analysis. This research not only explored the similarities and differences between Artemisiae Verlotori Folium and Artemisiae Argyi Folium in eight components but also provided a qualitative and quantitative analytical method that quickly, accurately, and comprehensively assesses the quality of Artemisiae Verlotori Folium.     

Identification of Salvia species using high‐performance liquid chromatography combined with chemical pattern recognition analysis

Salvia miltiorrhiza, also known as Danshen, is a widely used traditional Chinese medicine for the treatment of cardiovascular diseases and hematological abnormalities. The root and rhizome of Salvia przewalskii and Salvia yunnanensis have been found as substitutes for Salvia miltiorrhiza in the market. In this study, the chemical information of 14 major compounds in Salvia miltiorrhiza and its substitutes were determined using a high‐performance liquid chromatography method. Stepwise discriminant analysis was adopted to select the characteristic variables. Partial least squares discriminant and hierarchical cluster analysis were performed to classify Salvia miltiorrhiza and its substitutes. The results showed that all of the samples were correctly classified both in partial least squares discriminant analysis and hierarchical cluster analysis based on the four compounds (caffeic acid, rosmarinic acid, salvianolic acid B, and salvianolic acid A). This method can not only distinguish Salvia miltiorrhiza and its substitutes, but also classify Salvia przewalskii and Salvia yunnanensis. The method can be applied for the quality assessment of Salvia miltiorrhiza and identification of unknown samples.     

Screening bioactive quality control markers of QiShenYiQi dripping pills based on the relationship between the ultra‐high performance liquid chromatography fingerprint and vascular protective activity

Traditional Chinese medicine consists of complex phytochemical constituents. Selecting appropriate analytical markers of traditional Chinese medicine is a critical step in quality control. Currently, the combination of fingerprinting and efficacy evaluation is considered as a useful method for screening active ingredients in complex mixtures. This study was designed to develop an orthogonal partial least squares model for screening bioactive quality control markers of QishenYiqi dripping pills based on the fingerprint–efficacy relationship. First, the chemical fingerprints of 49 batches of QishenYiqi dripping pill samples were established by ultra‐high performance liquid chromatography coupled with a photodiode array detector. Second, ultra‐high performance liquid chromatography coupled with quadrupole‐time‐of‐flight mass spectrometry was exploited to systematically investigate the 36 copossessing fingerprint components in QishenYiqi dripping pills. The vascular protective activity of QishenYiqi dripping pills was determined by using a cell counting kit‐8 assay. Finally, fingerprint–efficacy relationship was established by orthogonal partial least squares model. The results indicated that ten components exhibited strong correlation with vascular protective activity, and these were preliminarily screened as quality control markers. The present study provided a novel idea for the study of the pharmacodynamic material basis and quality evaluation of QishenYiqi dripping pills.     

Strategies for determining the bioactive ingredients of honey‐processed Astragalus by serum pharmacochemistry integrated with multivariate statistical analysis

Honey‐processed Astragalus is a widely used traditional Chinese medicine that has a better effect on reinforcing “Qi” (vital energy) than the raw one. A comparative study of metabolites analysis between them in rat serum for finding the bioactive ingredients was carried out using serum pharmacochemistry and multivariate statistical analysis. The blood collection methods and time were optimized first. Then the prototypes and metabolites in serum samples after oral administration were investigated by ultra‐high‐performance liquid chromatography coupled with electrospray ionization quadrupole time‐of‐flight mass spectrometry integrated with principal component analysis and orthogonal partial least squares discriminant analysis. The contents of metabolites were also analyzed to evaluate the metabolic profile differences. As a result, nine prototypes and 36 metabolites were identified. Only two prototypes and 15 metabolites were different between raw and honey‐processed Astragalus. Their biotransformation reactions contained the process of oxidation, demethylation, and hydrolysis in phase I and glucuronide conjugation or sulfate conjugation in phase II. Most of the detected metabolites were transformed from isoflavones and isoflavanes. Our results expand the knowledge about the influence of honey‐processing on Astragalus and suggest the different curative effects between raw and honey‐processed Astragalus might due to their therapeutic material discrepancy.     

Metabolic fingerprinting based on high-resolution tandem mass spectrometry: a reliable tool for wine authentication?

Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (MS) and an alternative technology represented by direct analysis in real time coupled with quadrupole time-of-flight MS were investigated for metabolic fingerprinting of 343 red and white wine samples. Direct injection of pure wine and an extraction procedure optimized for isolation of polyphenols were used to compare different analytical and data handling strategies. After data processing and data pretreatment, principal component analysis was initially used to explore the data structure. Initially, the unsupervised models revealed a notable clustering according to the grape varieties, and therefore supervised orthogonal partial least squares discriminant analysis models were created and validated for separation of red and white wines according to the grape variety. The validated orthogonal partial least squares discriminant analysis models based on data (ions) recorded in positive ionization mode were able to classify correctly 95 % of samples. In parallel, authentication parameters, such as origin and vintage, were evaluated, and they are discussed. A tentative identification of markers was performed using accurate mass measurement of MS and MS/MS spectra, different software packages and different online libraries. In this way, different flavonol glucosides and polyphenols were identified as wine markers according to the grape varieties.     

Chemometric analysis of metabolism disorders in blood plasma of S180 and H22 tumor‐bearing mice by high performance liquid chromatography‐diode array detection

The aim of this paper is to characterize metabolism disorders in Kunming mice induced by S180 and H22 tumor cells. Metabolic fingerprint based on high performance liquid chromatography‐diode array detector (HPLC‐DAD) was developed to map the disturbed metabolic responses. In vivo testing of the antitumor activity of paclitaxel (Taxol) was carried out by inhibiting the growth of S180 and H22 tumor cells. Based on 27 common peaks, principal component analysis (PCA) and partial least squares‐discriminant analysis (PLS‐DA) were used to distinguish the abnormal from control and to find significant endogenous compounds (SECs) which have significant contributions to classification. The tumor growth inhibition ratios (TIRs) of Taxol groups were used to validate the predictive accuracies of the PLS‐DA models. The predictive accuracies of PLS‐DA models for S180 and H22 tumor model groups were 97.6 and 100%, respectively. Nine (S180) and seven (H22) SECs were discovered, including uric acid and cytidine. In addition, the correlations between relative tumor weights (RTWs) and chromatographic data for the SECs were significant (p < 0.05). Investigations on the stability and precision of the established metabolic fingerprints demonstrate that the experiment is well controlled and reliable. This work shows that the platform of HPLC‐DAD coupled with chemometric methods provides a promising method for the study of metabolism disorders induced by tumor cells. Copyright © 2011 John Wiley & Sons, Ltd.     

Investigation of the chemical markers for experiential quality evaluation of crude aconite by UHPLC–Q‐TOF‐MS

Many foods and herbs are experientially classified into different commodity grades in commercial circulation. Regarding the hypertoxic herb aconite, large samples are considered to be of better quality. However, this experiential classification lacks a scientific basis. In this study, we focused on the quality diversity among different grades and studied it using the minimum lethal dose assay and a novel ultra high performance liquid chromatography coupled with time‐of‐flight mass spectrometry method. Toxicity assay result suggested grade I aconite had the lowest toxicity (p < 0.05). Using this method with partial least squares‐discriminant analysis, we discovered nine chemomarkers, including neoline, songorine, fuziline, mesaconitine, talatizidine, dexyaconitine, talatisamine, hypaconitine, and fuzitine. Considering their toxicity and activity, we found the levels of toxic ingredients hypaconitine, dexyaconitine, and mesaconitine in grade I were lower than those in grade II (p < 0.01), while the levels of efficacy ingredients songorine, talatisamine, and neoline were the highest in grade I (p < 0.01). Further study demonstrated that the quality variation was associated with plant tissue development and toxic ingredient distribution law. Our results provide scientific evidence for the experiential quality evaluation of aconite, and it will be of great utility for other foods and herbs.     

Rapid identification and comparative analysis of the chemical constituents and metabolites of Phellodendri amurensis cortex and Zhibai dihuang pill by ultra‐performance liquid chromatography with quadrupole TOF‐MS

Zhibai dihuang pill is a famous traditional Chinese medicine formula containing the herbal medicine Phellodendri amurensis cortex. In this work, an integrative pattern recognition approach including principal component analysis and orthogonal partial least squared discriminant analysis based on ultra‐performance liquid chromatography coupled to MS was successfully applied for the rapid discovery of natural compounds from herbal medicines. In a 24 min analysis, 93 compounds were identified or tentatively characterized from Zhibai dihuang pill based on their fragmentation behaviors, 23 of which were from Phellodendri amurensis cortex. A total of 26 metabolites in plasma were identified from Phellodendri amurensis cortex in Zhibai dihuang pill formula, among them, 12 prototypes and 14 metabolites through metabolic pathways of demethylation, methylation, hydrolysis, sulfate conjugation, and glucuronide conjugation, which were seven metabolites more than that of the single drug, suggesting the importance of the compatibility of traditional Chinese medicine. The present study provided important structural information on the metabolism of Zhibai dihuang pill. Furthermore, the results of this work have demonstrated the feasibility of ultra‐performance liquid chromatography coupled to MS for the rapid and reliable characterization of metabolites from herbal medicines. Based on these results, this method could be a novel approach for identifying potentially bioactive components in other traditional Chinese medicines.     

High‐performance liquid chromatography–based fingerprint analysis with chemical pattern recognition for evaluation of Mahonia bealei (Fort.) Carr

A simple and efficient high‐performance liquid chromatography method combined with chemical pattern recognition was established for quality evaluation of Mahonia bealei (Fort.) Carr. A common pattern of 30 characteristic peaks was applied for similarity analysis, hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis in the 37 batches of M. bealei (Fort.) Carr. to discriminate wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes. The results showed that partial least squares discriminant analysis was the most effective method for discrimination. Eight characteristics peaks with higher variable importance in projection values were selected for pattern recognition model. A permutation test and 26 batches of testing set samples were performed to validate the model that was successfully established. All of the training and testing set samples were correctly classified into three clusters (wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes) based on the selected chemical markers. Moreover, 26 batches of unknown samples were used to predict the accuracy of the established model with a discrimination accuracy of 100%. The obtained results indicated that the method showed great potential application for accurate evaluation and prediction of the quality of M. bealei (Fort.) Carr.