scholarly journals Comprehensive Investigation of Moringa oleifera from Different Regions by Simultaneous Determination of 11 Polyphenols Using UPLC-ESI-MS/MS

Molecules ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 676 ◽  
Author(s):  
Yanqin Zhu ◽  
Qinhong Yin ◽  
Yaling Yang
Keyword(s):  
Moringa Oleifera ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Soil Environment ◽  
Cultivation Conditions ◽  
Esi Ms ◽  
Analysis Methodology ◽  
Polyphenol Profile

In this study, we develop and validate a simultaneous quantification of polyphenols method based on an ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) to adequately understand how different habitats influence the quality and profile of Moringa oleifera polyphenol. Furthermore, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to compare and discriminate 25 samples collected from different areas. A significant correlation was found between the polyphenol profile and the collection area. Significant differences in the polyphenol content of Moringa oleifera from different regions indicate that the genetic diversity of Moringa oleifera was relatively rich, possibly due to differences in cultivation conditions, climate, or soil environment resulting in the accumulation of different polyphenols. These observations provide a theoretical basis for subsequent Moringa oleifera germplasm selection and development research. Furthermore, the quantitative analysis methodology used to characterize the polyphenols may be used toward developing quality assessment and future pharmacodynamic investigations of Moringa oleifera.

scholarly journals Simultaneous determination of various platycosides in Four Platycodon grandiflorum cultivars by UPLC-QTOF/MS

2019 ◽  
Vol 62 (1) ◽  
Author(s):  
Dae Young Lee ◽  
Bo-Ram Choi ◽  
Jae Won Lee ◽  
Yurry Um ◽  
Dahye Yoon ◽  
...  
Keyword(s):  
Principal Component ◽  
Ultra Performance Liquid Chromatography ◽  
Platycodon Grandiflorum ◽  
Pentacyclic Triterpenoid ◽  
Flight Mass Spectrometry ◽  
Platycodi Radix ◽  
Isomeric Pairs ◽  
Different Levels

Abstract In Platycodi Radix (root of Platycodon grandiflorum), there are a number of platycosides that consist of a pentacyclic triterpenoid aglycone and two sugar moieties. Due to the pharmacological activities of platycosides, it is critical to assess their contents in PR, and develop an effective method to profile various platycosides is required. In this study, an analytical method based on ultra performance liquid chromatography coupled with quadrupole time-of-flight/mass spectrometry (UPLC-QTOF/MS) with an in-house library was developed and applied to profile various platycosides from four different Platycodi Radix cultivars. As a result, platycosides, including six isomeric pairs, were successfully analyzed in the PRs. In the principal component analysis, several platycosides were represented as main variables to differentiate the four Platycodi Radix cultivars. Their different levels of platycosides were also represented by relative quantification. Finally, this study indicated the proposed method based on the UPLC-QTOF/MS can be an effective tool for identifying the detail characterization of various platycosides in the Platycodi Radix.

scholarly journals Development and Validation of UPLC-ESI-MS/MS Technique for the Determination of 2-Isopropyl-4-(chloromethyl)thiazole in Ritonavir

2020 ◽  
Vol 32 (7) ◽  
pp. 1733-1740
Author(s):  
K. Durga Raja ◽  
V. Saradhi Venkata Ramana ◽  
K. Raghu Babu ◽  
B. Kishore Babu ◽  
V. Jagadeesh Kumar ◽  
...  
Keyword(s):  
High Strength ◽  
Gradient Elution ◽  
Ultra Performance Liquid Chromatography ◽  
Internal Diameter ◽  
Esi Ms ◽  
Quantitation Limit ◽  
Highly Sensitive ◽  
Liquid Chromatography Tandem Mass ◽  
Development And Validation

The objective of this work was to develop and validate a rapid, highly sensitive ultra performance liquid chromatography-tandem mass spectrometry (UPLC-ESI-MS/MS) method for the quantification of 2-isopropyl-4-(chloromethyl)thiazole in ritonavir. Chromatographic conditions of this impurity were achieved on an AQUITY UPLC column HSS (high strength silica) T3 column (100 mm long, 2.1 mm internal diameter, 1.8 μm diameter) using a gradient elution with 0.1% formic acid in water and methanol at a flow rate of 0.3 mL/min. LCMS/MS was operated under the multiple reaction mode (MRM) using electrospray ionization technique in positive ion mode and the transitions of m/z 176.1[M+H]+→140.1 for quantifier, 176.1[M+H]+→71.0 for qualifier were used to measure the impurity, respectively. The total chromatographic run time was 10 min. Full validation of the analytical method was carried out, including its system precision, selectivity, linearity, accuracy, recovery, ruggedness, stability and robustness. A linear response function was achieved in the concentration range of 0.12-1.86 μg/g with r > 0.99. The detection limit and quantitation limit of this impurity were 0.06 and 0.12 μg/g, respectively. Consistent recoveries were obtained during intra- and inter-day precision experiments in validation ranged from 80-120%. The developed method could be helpful not only for quality control and also for risk management of potential genotoxicity of this impurity in ritonavir drug substance.

scholarly journals Simultaneous Determination Of Tartrazine, Patented Blue V And Brilliant Blue FCF By Spectrophotometry With Chemometric Algorithms

2019 ◽  
Vol 14 (3) ◽  
pp. 153-162 ◽  
Author(s):  
O.O. Lukianova ◽  
A.N. Chebotarev ◽  
D.V. Snigur
Keyword(s):  
Simultaneous Determination ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Brilliant Blue ◽  
Regression Equations ◽  
Brilliant Blue Fcf ◽  
Real Objects ◽  
Chemometric Algorithms ◽  
Quinoline Yellow

Mixtures containing tartrazine (TAN) and brilliant blue (BB) or patented blue (PB) were investigated in this work. The optimal pH for the simultaneous determination of these dyes is 1.5 and 7 (for pH=7: ε430(ТАN)=3.2·104, ε635(ТАN)=5.3·102, ε430(PB)=3.3·103, ε635(PB)=8.7·104; for pH=1.5: ε430(ТАN)=2.1·104, ε630(ТАN)=9.6·102, ε430(BB)=9.3·103, ε630(BB)=8.3·104). Classification models, that allow to identify mixtures containing TAN and BB, TAN and PB, chlorophyll and quinoline yellow with BB or PB, have been developed using methods of hierarchical cluster analysis, factor analysis (FA), partial least squares (PLS) and principal component analysis (PCA). Model solutions of dyes and 12 real objects (tarkhun, low-alcohol drinks, tonics and absinthe of various brands) were used for the classification. The best classification results were achieved at pH 1.5 using PLS and PCA. Quantitative models, based on the additivity of spectral signals and PLS, have been developed for determining the permittivity of these dyes in the simultaneous presence. In order to make it possible to analyse alcoholic drinks, the dependence of the molar attenuation coefficient on the dielectric conductivity of solvents was studied. The obtained regression equations were taken into account in the calibration for absorbance additivity. Methods for the quantitative determination of the investigated dyes were developed for the concentration range 0.2-2.0∙10-5 М.

scholarly journals Analysis of Flavonoid Metabolites in Buckwheat Leaves Using UPLC-ESI-MS/MS

Molecules ◽  
2019 ◽  
Vol 24 (7) ◽  
pp. 1310 ◽  
Author(s):  
Jing Li ◽  
Pu Yang ◽  
Qinghua Yang ◽  
Xiangwei Gong ◽  
Hongchi Ma ◽  
...  
Keyword(s):  
Clustering Analysis ◽  
Principal Component ◽  
Ultra Performance Liquid Chromatography ◽  
Tartary Buckwheat ◽  
Biological Functions ◽  
Common Buckwheat ◽  
Flavonoid Content ◽  
Esi Ms ◽  
Orthogonal Signal Correction ◽  
Signal Correction

Flavonoids from plants are particularly important in our diet. Buckwheat is a special crop that is rich in flavonoids. In this study, four important buckwheat varieties, including one tartary buckwheat and three common buckwheat varieties, were selected as experimental materials. The total flavonoid content of leaves from red-flowered common buckwheat was the highest, followed by tartary buckwheat leaves. A total of 182 flavonoid metabolites (including 53 flavone, 37 flavonol, 32 flavone C-glycosides, 24 flavanone, 18 anthocyanins, 7 isoflavone, 6 flavonolignan, and 5 proanthocyanidins) were identified based on Ultra Performance Liquid Chromatography–Electrospray Ionization–Tandem Mass Spectrometry (UPLC-ESI-MS/MS) system. Through clustering analysis, principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA), different samples were clearly separated. Considerable differences were observed in the flavonoid metabolites between tartary buckwheat leaves and common buckwheat leaves, and both displayed unique metabolites with important biological functions. This study provides new insights into the differences of flavonoid metabolites between tartary buckwheat and common buckwheat leaves and provides theoretical basis for the sufficient utilization of buckwheat.

scholarly journals Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

Molecules ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 432
Author(s):  
Nduvho Mulaudzi ◽  
Chinedu P. Anokwuru ◽  
Sidonie Y. Tankeu ◽  
Sandra Combrinck ◽  
Weiyang Chen ◽  
...  
Keyword(s):  
Quality Control ◽  
Liquid Chromatography ◽  
Bioactive Compounds ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Retardation Factor ◽  
Root Bark ◽  
High Concentration ◽  
Chemical Fingerprint

Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-β-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.

scholarly journals GC-MS and HPLC-ESI-MS-MS Characterization of Sanchezia oblonga (Acanthaceae) Extracts

2020 ◽  
Vol 9 (1) ◽  
pp. 57
Author(s):  
Juliana Mourão Ravasi ◽  
Giuseppina Negri ◽  
Antonio Salatino ◽  
Maria Luiza Faria Salatino ◽  
Marco Aurelio Sivero Mayworm
Keyword(s):  
Sinapic Acid ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Lilium Longiflorum ◽  
Potential Health ◽  
Esi Ms ◽  
Aerial Parts ◽  
Sorghum Grain ◽  
New Compounds

The genus Sanchezia (Acanthaceae) comprises neotropical herbs and shrubs with showy flowers. Sanchezia oblonga (syn. S. nobilis) is a shrub of the rainforests of central and south America. The ethanolic extracts of leaves and stems from S. oblonga were analyzed by GC-EI-MS and RPHPLC-DAD-ESI-MS/MS. Fatty acids (free and esterified) and phytosterols were detected by the former method. Benzyl alcohol glycosides (21 and 25), sinapic acid glycoside esters (29 and 31), ethyl rosmarinate (24), sinapic acid-O-glucoside (28), dihydrosinapic acid-O-glucoside (26), catechin-O-arabinoside (36), in addition to flavonols glycosides (23, 32, 33 and 35) and rosmarinic acid-3’-O-glucoside (34) were detected by RPHPLC-DAD-ESI-MS/MS. Three new compounds, detected only in leaves, were tentatively identified as phenylpropane glyceride derivatives 1-O-coumaroyl-2-hydroxy propanal (20) and 1-O-coumaroyl-2-O-glycosyl propanal (22, 30). Compounds 20, 22 and 30 from S. oblonga are similar with phenylpropane glycerides present in red sorghum (Sorghum bicolor L. (Moench) and Lilium longiflorum Thunb. It is noteworthy that S. oblonga could be used in cooking as a complement after more detailed studies. Sorghum grain foods exhibit potential health benefits against chronic diseases related to over-nutrition. Lilium longiflorum possess flower buds and bulbs that are used for both culinary and medicinal purposes in many parts of the world. Studies on chemical composition and biological activity of the genus Sanchezia are scarce. The presence of phytosterols and flavonol glycosides were recently reported in leaves from this species. However, the chemical profile of the extracts analyzed in this work differs from that previously reported for aerial parts of S. nobilis (sin. S. oblonga). Further studies, including statistical methods, such as principal component analysis and hierarchical cluster analysis will be needed to evaluate chemical markers for this species.

scholarly journals Determination of minced meat quality using machine learning

2017 ◽  
Author(s):  
Αθηνά Ροπόδη
Keyword(s):  
Discriminant Analysis ◽  
Multispectral Imaging ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Support Vector ◽  
Linear Discriminant ◽  
Vector Machines ◽  
Ftir Spectrometry ◽  
Minced Meat

Τη σημερινή εποχή, οι καταναλωτές απαιτούν συνεχή επιβεβαίωση της προέλευσης, της ποιότητας και της συμμόρφωσης με την ετικέτα των τροφίμων που αγοράζουν. Για το λόγο αυτό, οι βιομηχανίες τροφίμων, οι έμποροι και οι αρχές είναι αναγκαίο να αναπτύξουν προηγμένες, αποτελεσματικές και χαμηλού κόστους λύσεις για τη διασφάλιση της ποιότητας και τον εντοπισμό δόλιων πρακτικών. Σε αυτό το πλαίσιο, η μελέτη αυτή εστιάζει (α) στην πολυφασματική απεικόνιση (Multispectral Imaging-MSI), (β) την φασματοσκοπία υπέρυθρου με μετασχηματισμό Fourier (Fourier Transform Infrared -FTIR spectrometry) και (γ) την εφαρμογή προηγμένων μεθόδων ανάλυσης δεδομένων και μηχανικής μάθησης. Όσον αφορά την ποιότητα, εξετάστηκε η αποτελεσματικότητα των προαναφερόμενων μεθόδων σε σχέση με (α) τον εντοπισμό της μη-συμμόρφωσης με την ετικέτα ή/και δόλιων πρακτικών και (β) τη μικροβιολογική αλλοίωση. Οι ακόλουθες αναλύσεις, έλαβαν χώρα:Στην 1η περίπτωση, εξετάστηκε η νοθεία του μοσχαρίσιου κιμά με χοιρινό. Χρησιμοποιήθηκαν 220 πολυφασματικές εικόνες δειγμάτων από 4 ανεξάρτητες πειραματικές διαδικασίες (κομμάτια κρέατος διαφορετικής προέλευσης). Η νοθεία έγινε με βήμα 10% w/w, δημιουργώντας 11 κατηγορίες (συμπεριλαμβανομένων των ανόθευτων χοιρινών και μοσχαρίσιων δειγμάτων). Μετά από ένα στάδιο προεπεξεργασίας της εικόνας, εφαρμόστηκαν η Ιεραρχική Ανάλυση Συστάδων (Hierarchical Cluster Analysis - HCA) και Ανάλυση Κυρίων Συνιστωσών (Principal Component Analysis - PCA). Παρατηρήθηκαν δε σημαντικές διαφορές μεταξύ των διαφορετικών κομματιών κρέατος και των διαφορετικών κλάσεων όταν και τα τρία πρώτα ζευγάρια κομματιών κρέατος συμπεριλήφθηκαν στην ανάλυση. Μετά την κατάτμηση των δεδομένων σε σετ εκπαίδευσης και επικύρωσης, τα δεδομένα του τέταρτου ζεύγους χρησιμοποιήθηκαν για ανεξάρτητη επικύρωση και εφαρμόστηκαν οι μέθοδοι Γραμμικής Διακριτικής Ανάλυσης και Μερικών Ελαχίστων Τετραγώνων Linear Discriminant Analysis - LDA, Partial least-squares discriminant analysis – PLSDA) για 11 και για 3 (ανόθευτα χοιρινά, μοσχαρίσια και νοθευμένα) κλάσεις. Στην περίπτωση των 11 κλάσεων, 98.48% και 96.97% των δειγμάτων κατηγοριοποιήθηκαν εντός μιας ±10% κατηγορίας για LDA και PLSDA αντίστοιχα, ενώ στην περίπτωση των τριών επιτεύχθηκε σωστή κατηγοριοποίηση 98.48%. Τα αποτελέσματα της ανεξάρτητης επικύρωσης ήταν λιγότερο ακριβή για την LDA, αλλά με την PLSDA όλα τα δείγματα κατηγοριοποιήθηκαν σωστά, αποδεικνύοντας ότι το ποσοστό 10% είναι εντός των ορίων ανίχνευσης.Στην δεύτερη περίπτωση, 110 δείγματα κιμά τριών διαφορετικών κομματιών κρέατος από μοσχάρι και άλογο και επιπλέον εικόνες που ελήφθησαν μετά από 6, 24 και 48 ώρες χρησιμοποιήθηκαν για την ανίχνευση νοθείας. Η PCA χρησιμοποιήθηκε για οπτικοποίηση των δεδομένων, ενώ οι μέθοδοι PLSDA και Random Forest (RF) για κατηγοριοποίηση μεταξύ διαφορετικών ποσοστών νοθείας (4 κλάσεις), ανόθευτων μοσχαρίσιων, ανόθευτων αλογίσιων και νοθευμένων, ανόθευτων και νοθευμένων, και τέλος μεταξύ φρέσκων και συντηρημένων δειγμάτων. Τα μοντέλα κατά την ανεξάρτητη επικύρωση δεν είχαν υψηλή ακρίβεια. Στο τέλος, προτιμήθηκε η χρήση μηχανών διανυσμάτων υποστήριξης (Support Vector Machines – SVMs) σε δύο στάδια προκειμένου να διαχωριστούν τα φρέσκα από τα συντηρημένα δείγματα και μετά τα νοθευμένα από τα ανόθευτα. Έτσι, επιτεύχθηκε ποσοστό σωστής κατηγοριοποίησης 95.31% στο ανεξάρτητο σετ επικύρωσης.Στην τρίτη περίπτωση, ελήφθησαν πολυφασματικές εικόνες και φάσματα FTIR από κιμά επτά διαφορετικών κομματιών και από αντίστοιχα αποψυγμένα δείγματα που είχαν καταψυχθεί στους -20°C για 7 και 32 μέρες (συνολικά 105 εικόνες και φάσματα). Η PCA χρησιμοποιήθηκε για τη διερεύνηση των δεδομένων, ενώ PLSDA και SVM πέτυχαν 100% σωστή κατηγοριοποίηση μεταξύ φρέσκων και αποψυγμένων κατά την επικύρωση και την ανεξάρτητη επικύρωση με χρήση πολυφασματικών εικόνων. Η FTIR ήταν λιγότερο ακριβής με 93.3 και 96.7% αντίστοιχα.Στην 4η και 5η περίπτωση, διερευνήθηκε η αλλοίωση του βοδινού κιμά. Στην 4η περίπτωση, χρησιμοποιώντας τη διαδικτυακή εφαρμογή “MeatReg”, χρησιμοποιήθηκαν επτά διαφορετικές μέθοδοι για την εκτίμηση του μικροβιακού πληθυσμού. Τα δεδομένα αποτελούνταν από 105 δείγματα συντηρημένα σε δυο διαφορετικές συσκευασίες -αέρας και modified air packaging (MAP - 20% CO2/ 80% O2)- και δύο θερμοκρασίες (4 και 10°C), μικροβιολογικές αναλύσεις (Pseudomonads, Lactobacilli, B. thermosphacta and Enterobacteriaceae, Ολική Μεσόφιλη Χλωρίδα - ΟΜΧ). Τα δεδομένα πολυφασματικής απεικόνισης και FTIR συγκρίθηκαν με αυτά από ηλεκτρονική μύτη, υγρή χρωματογραφία υψηλής απόδοσης (HPLC) και αέρια χρωματογραφία/ φασματοσκοπία μάζας (GC-MS). Τα αποτελέσματα διαφοροποιήθηκαν αρκετά ανάλογα το είδος του οργάνου και της ομάδας μικροοργανισμών. Παρόλα αυτά υπήρξε καλή ακρίβεια, με την μέθοδο RF να δίνει τα καλύτερα αποτελέσματα.Ομοίως στην 5η περίπτωση, 168 δείγματα βοδινού κιμά αναλύθηκαν ως προς την ΟΜΧ, ενώ παράλληλα έγιναν μετρήσεις FTIR. Τα δείγματα είχαν συντηρηθεί σε αέρα και MAP στους 4 και 10°C. Χρησιμοποιήθηκε μία προσέγγιση βασισμένη στην μεθοδολογία των ensemble μοντέλων, όπου η εκτίμηση της αλλοίωσης έγινε βάσει μίας μίξης αποτελεσμάτων επιμέρους νευρωνικών δικτύων (artificial neural networks). Το μέσο τετραγωνικό σφάλμα της πρόβλεψης ήταν 0.16 (log CFU/g)^2.

scholarly journals Correlation between Quality and Geographical Origins of Poria cocos Revealed by Qualitative Fingerprint Profiling and Quantitative Determination of Triterpenoid Acids

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2200 ◽  
Author(s):  
Li-Xia Zhu ◽  
Jun Xu ◽  
Ru-Jing Wang ◽  
Hong-Xiang Li ◽  
Yu-Zhu Tan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Multiple Reaction Monitoring ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Ultra Performance Liquid Chromatography ◽  
Poria Cocos ◽  
Flight Mass Spectrometry ◽  
Geographical Regions ◽  
Array Detection

Poria cocos (Schw.) Wolf (PC) is a well-known saprophytic fungus, and its sclerotium without the epidermis (PCS) is widely used in traditional Chinese medicine and as a functional food in many countries. PCS is normally collected from multiple geographical regions, but whether and how the quality of PCS correlates with where it grows have not been determined. This correlation could be significant both for quality control and optimum utilization of PCS as a natural resource. In this study, a qualitative fingerprint profiling method performed by ultra-performance liquid chromatography (UHPLC) with diode array detection (DAD) combining quadrupole time-of-flight-mass spectrometry (QTOF-MS/MS) and a quantitative UHPLC coupled with triple quadrupole mass spectrometry (QqQ-MS/MS) approach were established to investigate whether and how the quality of PCS correlates with its collection location. A standard fingerprint of PCS was generated by median simulation of 25 tested samples collected from four main producing areas of China, and similarity analysis was applied to evaluate the similarities between the fingerprints of samples and the standard fingerprint. Twenty three common peaks occurring in the fingerprint were unequivocally or tentatively identified by UHPLC-QTOF-MS/MS. Meanwhile, principal component analysis (PCA), supervised orthogonal partial least squares-discriminate analysis (OPLS-DA) and hierarchical cluster analysis (HCA) were employed to classify 25 batches of PCS samples into four groups, which were highly consistent with the four geographical regions. Ten compounds were screened out as potential markers to distinguish the quality of PCS. Nine triterpene acids, including five compounds that played important roles in the clusters between different samples collected from the four collection locations, were simultaneously quantified by using the multiple reaction monitoring (MRM) mode of UHPLC-QqQ-MS/MS. The current strategy not only clearly expounded the correlation between quality and geographical origins of PCS, but also provided a fast, accurate and comprehensive qualitative and quantitative method for assessing the quality of PCS.

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