Discrimination of Semen cassiae from two related species based on the multivariate analysis of high‐performance liquid chromatography fingerprints

A simple and efficient high‐performance liquid chromatography fingerprint method was developed to discriminate Semen cassiae from two related species: Cassia obtusifolia L. (CO) and Cassia tora L. (CT), the seeds of which are abbreviated as COS and CTS, respectively. 22 major bioactive ingredients in 42 samples (20 COS and 22 CTS) collected from different provinces of China were identified. The statistical methods included similarity analysis and partial least‐squares discriminant analysis. The pattern analysis method was specific and could be readily used for the comprehensive evaluation of Semen cassiae samples. Therefore, high‐performance liquid chromatography fingerprint in combination with pattern analysis provided a simple and reliable method for discriminating between COS and CTS.     

Boosting partial least‐squares discriminant analysis with application to near infrared spectroscopic tea variety discrimination

In the present study, boosting has been combined with partial least‐squares discriminant analysis (PLS‐DA) to develop a new pattern recognition method called boosting partial least‐squares discriminant analysis (BPLS‐DA). BPLS‐DA is implemented by firstly constructing a series of PLS‐DA models on the various weighted versions of the original calibration set and then combining the predictions from the constructed PLS‐DA models to obtain the integrative results by weighted majority vote. Coupled with near infrared (NIR) spectroscopy, BPLS‐DA has been applied to discriminate different kinds of tea varieties. As comparisons to BPLS‐DA, the conventional principal component analysis, linear discriminant analysis (LDA), and PLS‐DA have also been investigated. Experimental results have shown that the inter‐variety difference can be accurately and rapidly distinguished via NIR spectroscopy coupled with BPLS‐DA. Moreover, the introduction of boosting drastically enhances the performance of an individual PLS‐DA, and BPLS‐DA is a well‐performed pattern recognition technique superior to LDA. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

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.     

Chemotaxonomic study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) using ultra‐high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis

We investigated a strategy for the chemotaxonomy study of Chrysobalanus icaco Linnaeus (Chrysobalanaceae) based on ultra‐high performance liquid chromatography coupled with diode array detection fingerprint in combination with multivariate analysis. Two models using principal component analysis and partial least squares discriminant analysis were developed, and the samples could be successfully classified into two classes: Class 1 (red morphotype) and Class 2 (white and black morphotypes). Furthermore, ultra‐high performance liquid chromatography coupled with diode array and electrospray ionization tandem mass spectrometry was used to identify the main compounds responsible for class separation. The partial least squares discriminant analysis model accurately classified the C. icaco samples using an external validation subset with prediction ability of 100% and revealed the existence of two chemotypes. The most important finding obtained in this study is that the three morphotypes distinguished by the mature fruit color (white, red, and black) are not all phytoequivalent to each other.     

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.     

Quantitative determination and evaluation of Paris polyphylla var. yunnanensis with different harvesting times using UPLC‐UV‐MS and FT‐IR spectroscopy in combination with partial least squares discriminant analysis

A rapid method was developed and validated by ultra‐performance liquid chromatography–triple quadrupole mass spectroscopy with ultraviolet detection (UPLC‐UV‐MS) for simultaneous determination of paris saponin I, paris saponin II, paris saponin VI and paris saponin VII. Partial least squares discriminant analysis (PLS‐DA) based on UPLC and Fourier transform infrared (FT‐IR) spectroscopy was employed to evaluate Paris polyphylla var. yunnanensis (PPY) at different harvesting times. Quantitative determination implied that the various contents of bioactive compounds with different harvesting times may lead to different pharmacological effects; the average content of total saponins for PPY harvested at 8 years was higher than that from other samples. The PLS‐DA of FT‐IR spectra had a better performance than that of UPLC for discrimination of PPY from different harvesting times.     

Effect of inorganic salt on partition of high‐polarity parishins in two‐phase solvent systems and separation by high‐speed counter‐current chromatography from Gastrodia elata Blume

Parishins are high‐polarity and major bioactive constituents in Gastrodia elata Blume. In this study, the effect of several inorganic salts on the partition of parishins in two‐phase solvent systems was investigated. Adding ammonium sulfate, which has a higher solubility in water, was found to significantly promote the partition of parishins in the upper organic polar solvents. Based on the results, a two‐phase solvent system composed of butyl alcohol/acetonitrile/near‐saturated ammonium sulfate solution/water (1.5:0.5:1.2:1, v/v/v/v) was used for the purification of parishins by high‐speed counter‐current chromatography. Fractions obtained from high‐speed counter‐current chromatography were subjected to semi‐preparative high‐performance liquid chromatography to remove salt and impurities. As a result, parishin E (6.0 mg), parishin B (7.8 mg), parishin C (3.2 mg), gastrodin (15.3 mg), and parishin A (7.3 mg) were isolated from water extract of Gastrodia elata Blume (400 mg). These results demonstrated that adding inorganic salt that has high solubility in water to the two‐phase solvent system in high‐speed counter‐current chromatography was a suitable approach for the purification of high‐polarity compounds.     

Approach based on high‐performance liquid chromatography fingerprint coupled with multivariate statistical analysis for the quality evaluation of Gastrodia Rhizoma

Gastrodia Rhizoma is a Traditional Chinese Medicine applied in the treatment of stroke, numbness of limb, headache and dizziness. However, its clinical effect is threatened by sulfur‐fumigation used in the process of storage. This article employs content determination coupled with high‐performance liquid chromatography fingerprint to investigate the effect of sulfur‐fumigation on Gastrodia Rhizoma so as to evaluate the quality of Gastrodia Rhizoma. The result was that most active ingredient in Gastrodia Rhizoma decreased after sulfur‐fumigation and the fingerprints analyzed by mathematical statistics between sulfur‐fumigated Gastrodia Rhizoma and unfumigated Gastrodia Rhizoma have substantial differences, which reveals that sulfur‐fumigation has a significant influence on the quality of Gastrodia Rhizoma. The conclusion of hierarchical clustering analysis, principal component analysis and partial least squares could validate each other, which implies that the method of mathematical statistics applied for assessing the quality of Gastrodia Rhizoma is effective and stable. The method not only affords a viable strategy for distinguishing Gastrodia Rhizoma whether sulfur‐fumigated or not and assessment of the quality of Gastrodia Rhizoma, but also provides a reference for other herbal medicine that suffers from sulfur‐fumigation.     

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.     

Differentiating Westlake Longjing tea from the first‐ and second‐grade producing regions using ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry‐based untargeted metabolomics in combination with chemometrics

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first‐ and second‐grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry‐based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high‐resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two‐way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.     

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.     

Chemical fingerprint of Ganmaoling granule by double‐wavelength ultra high performance liquid chromatography and ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry

A method incorporating double‐wavelength ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry was developed for the investigation of the chemical fingerprint of Ganmaoling granule. The chromatographic separations were performed on an ACQUITY UPLC HSS C₁₈ column (2.1 × 50 mm, 1.8 μm) at 30°C using gradient elution with water/formic acid (1%) and acetonitrile at a flow rate of 0.4 mL/min. A total of 11 chemical constituents of Ganmaoling granule were identified from their molecular weight, UV spectra, tandem mass spectrometry data, and retention behavior by comparing the results with those of the reference standards or literature. And 25 peaks were selected as the common peaks for fingerprint analysis to evaluate the similarities among 25 batches of Ganmaoling granule. The results of principal component analysis and orthogonal projection to latent structures discriminant analysis showed that the important chemical markers that could distinguish the different batches were revealed as 4,5‐di‐O‐caffeoylquinic acid, 3,5‐di‐O‐caffeoylquinic acid, and 4‐O‐caffeoylquinic acid. This is the first report of the ultra high performance liquid chromatography chemical fingerprint and component identification of Ganmaoling granule, which could lay a foundation for further studies of Ganmaoling granule.     

Evaluation of the chemical consistency of Yin‐Chen‐Hao‐Tang prepared by combined and separated decoction methods using high‐performance liquid chromatography and quadrupole time‐of‐flight mass spectrometry coupled with multivariate statistical analysis

In this study, Yin‐Chen‐Hao‐Tang prepared by two decoction methods, namely, combined decoction (modern decoction method) and separated decoction (traditional decoction method), was analyzed by high‐performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry. The acquired datasets containing sample codes, t_R‐m/z pairs and ion intensities were processed with multivariate statistical analyses, such as principal component analysis and an orthogonal partial least squared discriminant analysis model, to globally compare the chemical differences between the different decoction samples. Then, the chemical differences between the combined and separated decoctions were screened out by S‐plots generated from the orthogonal partial least squared discriminant analysis model and compared with chemical information from an established in‐house library. The six components that contributed the most to the chemical differences were identified as chlorogenic acid, caffeic acid, geniposide, genipin, scopoletin, and 3,5‐dicaffeoylquinic acid. The concentrations of genipin and caffeic acid from the separated decoction were higher than those from the combined decoction, indicating that the separated decoction may present a stronger hepatoprotective effect. However, the results still require further investigation through pharmacological and clinical studies. Our findings not only establish a strategy to evaluate chemical consistency of Yin‐Chen‐Hao‐Tang but also provide the scientific basis for using traditional separated decoction method.     

Non‐targeted volatile profiles for the classification of the botanical origin of Chinese honey by solid‐phase microextraction and gas chromatography–mass spectrometry combined with chemometrics

A potential method for the discrimination and prediction of honey samples of various botanical origins was developed based on the non‐targeted volatile profiles obtained by solid‐phase microextraction with gas chromatography and mass spectrometry combined with chemometrics. The blind analysis of non‐targeted volatile profiles was carried out using solid‐phase microextraction with gas chromatography and mass spectrometry for 87 authentic honey samples from four botanical origins (acacia, linden, vitex, and rape). The number of variables was reduced from 2734 to 70 by using a series of filters. Based on the optimized 70 variables, 79.12% of the variance was explained by the first four principal components. Partial least squares discriminant analysis, naïve Bayes analysis, and back‐propagation artificial neural network were used to develop the classification and prediction models. The 100% accuracy revealed a perfect classification of the botanical origins. In addition, the reliability and practicability of the models were validated by an independent set of additional 20 authentic honey samples. All 20 samples were accurately classified. The confidence measures indicated that the performance of the naïve Bayes model was better than the other two models. Finally, the characteristic volatile compounds of linden honey were tentatively identified. The proposed method is reliable and accurate for the classification of honey of various botanical origins.     

Total detection of Tianma Toutong tablets for quality consistency by a five‐wavelength fusion fingerprint and chemometrics

A fingerprint method was developed and combined with chemometrics for quality evaluation of Tianma Toutong tablets, which are herbal medicine tablets used to treat migraine. Samples were analyzed by high‐performance liquid chromatography, where five single‐wavelength profiles (203, 232, 254, 280 and 310 nm) were fused to generate a five‐wavelength fusion fingerprint and were also used for the quantitative analysis of seven chemical markers (gastrodin, caffeic acid, hesperidin, isoimperatorin, chlorogenic acid, ferulic acid and imperatorin). A systematic quantitative fingerprint method and principal component analysis were used to analyze the generated data. Samples could be well distinguished from different manufacturers by analyzing the chromatographic data sets. In addition, the partial least squares model can serve as an antioxidant activity evaluation of Tianma Toutong tablets, as well as a reference for the selection of active constituents to analyze the spectrum–activity relationship. In summary, the integrated use of the fingerprint and chemometric analysis provides a reliable method for the identification of markers and the quality control of Tianma Toutong tablets.     

Study on the spectrum‐effect relationship of the xanthine oxidase inhibitory activity of Ligustrum lucidum

To evaluate the xanthine oxidase inhibitory activity of the chemical constituents of Ligustrum lucidum in vitro, the spectrum‐effect relationship was investigated. The high‐performance liquid chromatography fingerprint was established by ultraviolet spectrophotometry, and the xanthine oxidase inhibitory activity was tested in vitro by a high‐throughput screening method. Cluster analysis, principal component analysis, gray correlation analysis, and partial least squares regression were used to explore the spectrum‐effect relationships. Sixty batches of Ligustrum lucidum were collected from 16 provinces for testing. The results revealed differences among the batches of medicinal materials, and the similarity score was between 0.635 and 0.968. Thirty‐three characteristic peaks (1–33) were calibrated by fingerprint evaluation software for traditional Chinese medicine. The spectrum‐effect relationship study further revealed that the contents of peaks 1, 2, 4, 5, 6, 7, 14, 17, 25, 28, 31, and 33, which are potentially critical ingredients for quality control of Ligustrum lucidum fruit, were highly correlated with the inhibition of xanthine oxidase activity.     

Geographical discrimination of Glechomae Herba based on fifteen phenolic constituents determined by LC–MS/MS method combined with chemometric methods

Glechomae Herba (GH) is rich in bioactive phenolic constituents and is widely used for treatment of cholelithiasis, urolithiasis and dropsy. The simultaneous determination of phenolic constituents in GH from different geographical origins is significant for authentication and quality control purposes. In this study, we developed a strategy integrating targeted analysis and chemometric methods for quality evaluation and discrimination of GH from different geographical origins. Firstly, an accurate and reliable liquid chromatography–tandem mass spectrometry method was developed for simultaneous quantification of 15 phenolic constituents in GH from different geographical origins. The established method was well validated in terms of desirable specificity, linearity, precision and accuracy. Secondly, the quantitative data were subjected to principal component analysis and orthogonal partial least squares discriminant analysis. Thirdly, a heatmap visualization was employed for clarifying the distribution of 15 phenolic compounds in GH from different geographical origins. These results indicated that GH samples from Shandong province obviously differ from those from other provinces in the content of bioactive phenolic constituents. Collectively, the proposed platform might be a suitable tool for quality evaluation and discrimination of GH from different geographical origins, providing promising perspectives in tracking the formulation processes of traditional Chinese medicine products.     

Analytical investigation of secondary metabolites extracted from Camellia sinensis L. leaves using a HPLC‐DAD‐ESI/MS data fusion strategy and chemometric methods

Considerable attention has been paid to the study of green tea leaves because of their high consume and beneficial effects on human health. In this work, an appropriate strategy is proposed to investigate and resolve the major metabolites extracted from Camellia sinensis tea leaves. Statistical design mixtures of ethanol, ethyl acetate, dichloromethane, and chloroform were used to study the effects of different solvents and their mixtures on the extraction of the secondary metabolites of C. sinensis tea leaves from two different harvest seasons. Extracted samples were analyzed by high performance liquid chromatography‐diode array detection‐electrospray ionization mass spectrometer allowing the resolution of a large amount of tea metabolites with high relative abundances, especially when their extraction was performed in pure ethanol and with solvent mixtures with ethanol. Resolution of the more relevant metabolites was achieved by the simultaneous analysis of the fused diode array detection and mass spectrometer detectors data from the same samples using the multivariate curve resolution‐alternating least squares chemometric method. Peak areas finally resolved were further analyzed by orthogonal signal correction and partial least squares‐discrimination analysis to discriminate among C. sinensis tea samples. Using the Variable Importance in Projection variable selection method, epigallocatechin and caffeine were finally selected as the two more important chemical constituents of tea leaves that were discriminating more between the tea samples from two different harvest seasons. Copyright © 2016 John Wiley & Sons, Ltd.     

Multicomponent quantitative analysis combined with antioxidant and alpha‐glucosidase inhibitory activities for the quality evaluation of Gastrodia elata from different regions

Gastrodia elata (G. elata), as a natural plant with nourishing and edible value, plays a vital role in food and pharmaceutical production. In the present study, a novel approach for the simultaneous determination of six components based on high‐performance liquid chromatography (HPLC) coupled with photodiode array detection (PDA) was developed for the quality evaluation of G. elata from different regions. Meanwhile, antioxidant and α‐glucosidase inhibitory activities were estimated and compared. The results indicated that the total contents of the six compounds in G. elata from Guizhou and Zhejiang provinces obtained by boiling were higher than those obtained by steaming in Anhui and Yunnan provinces. In addition, samples from Guizhou, Yunnan and Shanxi provinces contained more p‐hydroxybenzyl alcohol, and always possessed higher antioxidant activity, while samples collected from Anhui province showed the highest α‐glucosidase inhibitory activity with the highest gastrodin content. The results revealed that the quality of G. elata was affected by different regions and different initial processing technologies, which provided a reference for the selection and application of G. elata.