Qualitative analysis of the roots of Salvia miltiorrhiza and Salvia yunnanensis based on NIR, UHPLC and LC–MS-MS

Ni, Lei; Zhang, Fangfang; Han, Mingyue; Zhang, Liguo; Luan, Shaorong; Li, Wei; Deng, Hai-Xing; Lan, Zhu-Hui; Wu, Zhiqiang; Luo, Xiang; Leslaw, Mleczko

doi:10.1016/j.jpba.2019.01.010

Cited by 24 publications

(9 citation statements)

References 35 publications

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“…Principal component analysis (PCA), a multivariate statistics-based detection method, could be used to transform multiple indicators into a few comprehensive indicators for extracting features and revealing the relationship between variables. Recently, PCA has been widely used in food classification [ 23 ], such as identification of significant organic substances in raw materials or food products [ 24 ], as well as the demonstration of changes in food or raw material under the influence of technological processes [ 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Effect of Drying Methods on Volatile Compounds of Citrus reticulata Ponkan and Chachi Peels as Characterized by GC-MS and GC-IMS

Chen

et al. 2022

Foods

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To reflect the volatile differences of dried citrus peel as affected by cultivars and drying methods, the volatile compounds of dried citrus peel of two cultivars (Citrus reticulata “Chachi” and Citrus reticulata “Ponkan”), prepared under three drying methods (sun-drying (SD), hot-air-drying (AD), and freeze-drying (FD)), were analyzed by GC-MS, odor activity values (OAVs), and GC-IMS. GC-MS data indicated that SD was favorable to preserve terpenic alcohols (linalool, α-terpineol and terpinene-4-ol), β-cymene, methyl methanthranilate, and monoterpenes; while AD was favorable to preserve aliphatic aldehydes and sesquiterpenes; and SD was more similar with AD in GC-MS analysis of volatile profile (of higher MW) for both cultivars from the PCA outcome. Furthermore, significant difference in volatile isomeric composition of different samples was also clearly demonstrated through extracted ion chromatogram (EIC) by GC-MS analysis. GC-IMS analysis showed the favorability of FD to preserve ketones, phenols, esters, and aromatic aldehydes; and SD was more similar with FD in GC-IMS analysis of volatile profile (of smaller MW) for both cultivars from the PCA outcome. Moreover, the OAVs indicate that 2-methoxy-4-vinylphenol contributed much to the flavor of dried Ponkan peel, while 2-methoxy-4-vinylphenol, methyl methanthranilate, and methyl anthranilate played an important role in the flavor of dried Chachi peel; and the highest OAVs for monoterpenes were observed at SD for both cultivars. Thus, the combination of GC-MS and GC-IMS analyses with PCA in this paper suggested the superiority of SD to preserve volatiles and characteristic aroma in dried citrus peel, and that SD contributed much to the quality of dried Chachi peel.

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Section: Introductionmentioning

confidence: 99%

Effect of Drying Methods on Volatile Compounds of Citrus reticulata Ponkan and Chachi Peels as Characterized by GC-MS and GC-IMS

Chen

et al. 2022

Foods

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“…Near infrared spectroscopy (NIR spectroscopy) is a type of molecular spectroscopy, which has gradually gained widespread attention, and widely applied in determining authenticity of TCM, 16,17 species identification, 18,19 geographical origin analysis, 20,21 quantitative analysis, 22,23 rapid detection, adulteration detection 24 and online monitoring. 25 The recent application of handheld infrared spectroscopy in the rapid non-destructive testing of traditional Chinese medicine products has become a significanct technology to ensure quality.…”

Section: Introductionmentioning

confidence: 99%

Qualitative classification of Dendrobium huoshanense (Feng dou) using fast non-destructive hand-held near infrared spectroscopy

Wang

Jia

Dai

et al. 2022

Journal of Near Infrared Spectroscopy

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Because of the similar appearance and properties of different quality grades of the product, super Dendrobium huoshanense could be easily adulterated with first-grade D. huoshanense and second-grade D. huoshanense products, thereby affecting its clinical application and causing market distortion. In this study, a combination of hand-held near infrared spectroscopy and chemometrics was used to classify different grades of D. huoshanense. The standard normal variate was employed to preprocess the original near infrared spectra, following which linear analysis models (principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), and a non-linear support vector machine (SVM) model, were utilized to establish the identification models. The results showed that PCA analysis could not identify the three grades of D. huoshanense, and the LDA analysis could distinguish the second-grade from the other two grades. The PLSDA model resulted in prediction accuracies for the calibration cross-validation, and test sets of 91.83%, 83.58%, and 84.29%, respectively. Unfortunately, the super and first-grade D. huoshanense were not identified by the linear analysis model. Further analysis was performed with a non-linear model, where SVM was used to analyze all grades of D. huoshanense. The recognition rate of thel training set and validation set were 88% and 84%, respectively. All in all, the use of a hand-held near infrared spectrometer combined with chemometrics could identify the quality grade of D. huoshanense samples on-site in real-time, and provide a simple, fast, and reliable method for the quality control of the traditional Chinese medicine herb of D. huoshanense.

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“…Principal component analysis is an unsupervised pattern recognition method that utilizes dimension reduction technology to transform multiple indicators into a few representative comprehensive indicators, which can classify samples simply and intuitively. It has been reported that principal component analysis and heatmap hierarchical clustering analysis have been applied in the determination of raw cocoa, processed chocolate [ 11 ], monofloral honey [ 12 ], Salvia miltiorrhiza, Salvia yunnanensis [ 13 ], thyme [ 14 ], and fried foods [ 15 ] to obtain inter-sample correlations and different factors. The quantitative analysis of important organic substances in Chinese herbal medicine or food is very important for the control of the quality.…”

Section: Introductionmentioning

confidence: 99%

Quantification of Chemical Groups and Quantitative HPLC Fingerprint of Poria cocos (Schw.) Wolf

Huang

Jiang

et al. 2022

Molecules

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(1)Objective: In this study, a quantitative analysis of chemical groups (the triterpenoids, water-soluble polysaccharides, and acidic polysaccharides) and quantitative high liquid performance chromatography (HPLC) fingerprint of Poria cocos (Schw.) Wolf (PC) for quality control was developed. (2) Methodology: First, three main chemical groups, including triterpenoids, water-soluble polysaccharides, and acidic polysaccharides, in 16 batches of PC were evaluated by ultraviolet spectrophotometry. Afterward, the quantitative fingerprint of PC was established, and the alcohol extract of PC was further evaluated. The method involves establishing 16 batches of PC fingerprints by HPLC, evaluating the similarity of different batches of PC, and identifying eight bioactive components, including poricoic acid B (PAB), dehydrotumulosic acid (DTA), poricoic acid A (PAA), polyporenic acid C (PAC), 3-epidehydrotumulosic acid (EA), dehydropachymic acid (DPA), dehydrotrametenolic acid (DTA-1), and dehydroeburicoic acid (DEA), in PC by comparison with the reference substance. Combined with the quantitative analysis of multi-components by a single marker (QAMS), six bioactive ingredients, including PAB, DTA, PAC, EA, DPA, and DEA, in PC from different places were established. In addition, the multivariate statistical analyses, such as principal component analysis and heatmap hierarchical clustering analysis are more intuitive, and the visual analysis strategy was used to evaluate the content of bioactive components in 16 batches of PC. Finally, the analysis strategy of three main chemical groups in PC was combined with the quantitative fingerprint strategy, which reduced the error caused by the single method. (3) Results: The establishment of a method for the quantification of chemical groups and quantitative HPLC fingerprint of PC was achieved as demonstrated through the quantification of six triterpenes in PC by a single marker. (4) Conclusions: Through qualitative and quantitative chemical characterization, a multi-directional, simple and efficient routine evaluation method of PC quality was established. The results reveal that this strategy can provide an analytical method for the quality evaluation of PC and other Chinese medicinal materials.

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Qualitative analysis of the roots of Salvia miltiorrhiza and Salvia yunnanensis based on NIR, UHPLC and LC–MS-MS

Cited by 24 publications

References 35 publications

Effect of Drying Methods on Volatile Compounds of Citrus reticulata Ponkan and Chachi Peels as Characterized by GC-MS and GC-IMS

Effect of Drying Methods on Volatile Compounds of Citrus reticulata Ponkan and Chachi Peels as Characterized by GC-MS and GC-IMS

Qualitative classification of Dendrobium huoshanense (Feng dou) using fast non-destructive hand-held near infrared spectroscopy

Quantification of Chemical Groups and Quantitative HPLC Fingerprint of Poria cocos (Schw.) Wolf

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