Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

Nutraceutical Value of Pantelleria Capers (Capparis spinosa L.)

Unopened flower buds of Capparis spinosa L. (capers), generally used in the Mediterranean area as food flavoring, are known to be a good source of bioactive compounds. The aim of this work was to evaluate the nutraceutical value of salt-fermented capers collected from different areas of Pantelleria Island (Italy), testing their methylglyoxal and glyoxal trapping capacity and antioxidant activity by 2,2-diphenyl-1-picryl hydrazyl (DPPH), [2,2-azinobis(3-ethylben- zothiazoline-6-sulfonic acid)] diammonium salt (ABTS), and oxygen radical absorbance capacity (ORAC) assays. Hydrophilic extracts were also characterized by high-performance liquid chromatography-electrospray ionization/mass spectrometry. Among 24 detected compounds, several flavonol derivatives and glucosinolates were identified. The levels of kaempferol and quercetin derivatives varied considerably among the five accessions considered (6.46 to 267.93 and 22.39 to 367.14 mg kaempferol and quercetin equivalent /g fresh weight, respectively), with kaempferol derivatives more representative than quercetin ones. Person's coefficient indicated a high correlation between total phenolic content and anti-DPPH radical capacity (R² = 0.665), as well as between total flavonoid content and antioxidant capacity (by ORAC assay; R² = 0.888) and between total flavonoid content and glyoxal and methylglyoxal trapping capacity (R² = 0.918). Results indicate that capers from Pantelleria Island represent a rich source of bioactive compounds with potential nutraceutical relevance. PRACTICAL APPLICATION: The findings of this study highlight the health benefits of Pantelleria capers consumption due to their composition in antioxidants and their biological properties (antiradical and alpha-dicarbonyls trapping) correlated with the development of a high number of chronic-degenerative diseases. These results are also important for the agricultural and commercial sectors involved in the production of capers from Pantelleria, which received the Protected Geographical Indications recognition.

Evaluation of the Influence of Sulfur-Fumigated Paeoniae Radix Alba on the Quality of Si Wu Tang by Chromatographic and Chemometric Analysis

An accurate and reliable method of high-performance liquid chromatographic fingerprint combining with multi-ingredient determination was developed and validated to evaluate the influence of sulfur-fumigated Paeoniae Radix Alba on the quality and chemical constituents of Si Wu Tang. Multivariate data analysis including hierarchical cluster analysis and principal component analysis, which integrated with high-performance liquid chromatographic fingerprint and multi-ingredient determination, was employed to evaluate Si Wu Tang in a more objective and scientific way. Interestingly, in this paper, a total of 37 and 36 peaks were marked as common peaks in ten batches of Si Wu Tang containing sun-dried Paeoniae Radix Alba and ten batches of Si Wu Tang containing sulfur-fumigated Paeoniae Radix Alba, respectively, which indicated the changed fingerprint profile of Si Wu Tang when containing sulfur-fumigated herb. Furthermore, the results of simultaneous determination for multiple ingredients showed that the contents of albiflorin and paeoniflorin decreased significantly (P < 0.01) and the contents of gallic acid and Z-ligustilide decreased to some extent at the same time when Si Wu Tang contained sulfur-fumigated Paeoniae Radix Alba. Therefore, sulfur-fumigation processing may have great influence on the quality of Chinese herbal prescription.

Elemental fingerprinting of Hypericum perforatum (St John's Wort) herb and preparations using ICP-OES and chemometrics

St. John's wort (SJW) (Hypericum perforatum) is a herbal remedy commonly used to treat mild depression. The elemental profiles of 54 samples (i.e., dry herbs, tablets and capsules) were evaluated by monitoring 25 elements using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The major elemental constituents in the SJW samples were Ca (300-199,000μg/g), Mg (410-3,530μg/g), Al (4.4-900μg/g), Fe (1.154-760μg/g), Mn (2.4-261μg/g), Sr (0.88-83.6μg/g), and Zn (7-64μg/g). For the sixteen elements that could be reliably quantified, principal component analysis (PCA) was used to investigate underlying patterns in the data. PCA models identified 7 key elements (i.e., Ba, Ca, Cd, Mg, Mo, Ni and Y), which described 85% of the variance in the dataset in the first three principal components. The PCA approach resulted in a general delineation between the three different formulations and provides a basis for monitoring product quality in this manner.

Current application of chemometrics in traditional Chinese herbal medicine research

Traditional Chinese herbal medicines (TCHMs) are promising approach for the treatment of various diseases which have attracted increasing attention all over the world. Chemometrics in quality control of TCHMs are great useful tools that harnessing mathematics, statistics and other methods to acquire information maximally from the data obtained from various analytical approaches. This feature article focuses on the recent studies which evaluating the pharmacological efficacy and quality of TCHMs by determining, identifying and discriminating the bioactive or marker components in different samples with the help of chemometric techniques. In this work, the application of chemometric techniques in the classification of TCHMs based on their efficacy and usage was introduced. The recent advances of chemometrics applied in the chemical analysis of TCHMs were reviewed in detail.

Combined NIR/MIR analysis: a novel method for the classification of complex substances such as Illicium verum Hook. F. and its adulterants

A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95-100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.

Chemometrics: A new scenario in herbal drug standardization

Chromatography and spectroscopy techniques are the most commonly used methods in standardization of herbal medicines but the herbal system is not easy to analyze because of their complexity of chemical composition. Many cutting-edge analytical technologies have been introduced to evaluate the quality of medicinal plants and significant amount of measurement data has been produced. Chemometric techniques provide a good opportunity for mining more useful chemical information from the original data. Then, the application of chemometrics in the field of medicinal plants is spontaneous and necessary. Comprehensive methods and hyphenated techniques associated with chemometrics used for extracting useful information and supplying various methods of data processing are now more and more widely used in medicinal plants, among which chemometrics resolution methods and principal component analysis (PCA) are most commonly used techniques. This review focuses on the recent various important analytical techniques, important chemometrics tools and interpretation of results by PCA, and applications of chemometrics in quality evaluation of medicinal plants in the authenticity, efficacy and consistency.

Application of chemometrics in authentication of herbal medicines: a review

INTRODUCTION

Herbal medicines (HM) and their preparations have been widely used for hundreds of years all over the world. However, they have not been officially recognised due to a lack of adequate or accepted research methodology for their evaluation.

OBJECTIVE

To present a concise overview of the recent applications of chemometrics in solving the ambiguity of herbal medicine authentication during the last two decades.

METHODOLOGY

Studies involving the applications of chemometric analysis in combination with different analytical methods were classified according to the method of analysis used including chromatographic (HPLC, GC and CE), spectroscopic (NMR, IR, UV and ICP) and genetic analysis (RAPD). The purpose of each of these studies was classified into one of three main categories: taxonomic discrimination, quality assessment or classification between plants of different geographic origins.

RESULTS

This review comprises over 150 studies, covering the past two decades, emphasising the significance of chemometric methods in the discrimination of many herbs from closely related species and from adulterants, based on the principal bioactive components and phytochemical diversity. Furthermore, the differentiation between varieties and hybrids was achieved in addition to the prediction of the active components by quantitative methods of analysis. Discrimination according to geographical origin and localities, processing methods, DNA profiling and metabolomics were also efficiently investigated.

CONCLUSION

Chemometric methods have provided an efficient and powerful tool for the quality control and authentication of different herbs.

Chemometrics in Fingerprinting by Means of Thin Layer Chromatography

The paper is written as an introductory review, presenting summary of current knowledge about chemometric fingerprinting in the context of TLC, due to a rather small interest in the literature about joining TLC and chemometrics. The paper shortly covers the most important aspects of the chemometric fingerprinting in general, creating the TLC fingerprints, denoising, baseline removal, warping/registering, and chemometric processing itself. References being good candidates as a starting point are given for each topic and processing step.

Classification of raw and roasted Semen Cassiae samples with the use of Fourier transform infrared fingerprints and least squares support vector machines

Raw and roasted Semen Cassiae seeds, a complex traditional Chinese medicine (TCM), are used as examples to research and develop a method of classification analysis based on measurements of Fourier transform infrared (FT-IR) spectral fingerprints. Eighty samples of the TCM were measured in the mid-infrared range, 400-2000 cm(-1) (KBr pellets), and the complex overlapping spectra were submitted for interpretation to a principal component analysis least squares support vector machine (PC-LS-SVM), kernel principal component analysis least squares support vector machine (KPC-LS-SVM), and radial basis function artificial neural networks (RBF-ANN). The LS-SVM models were developed with an RBF kernel function and a grid search technique. Training models were constructed with the use of raw and first-derivative spectra and these were then verified by another data set containing both raw and roasted spectral objects. It was demonstrated that the first-derivative data set produced the best separation of the spectral objects. In general, satisfactory analytical performance was obtained with the PC-LS-SVM, KPC-LS-SVM, and RBF-ANN training models and with the classification of the verification spectral objects. With regard to chemometrics modeling, the performance of KPC-LS-SVM was somewhat more economical than that of the PC-LS-SVM model. It would appear that the latter relatively simple model would be sufficient for application to most small to medium sized FT-IR fingerprint data sets, but with larger matrices the more complex models, such as the RBF-ANN and KPC-LS-SVM, may be more advantageous on a computational basis.

Ultra-high performance liquid chromatography/time-of-flight mass spectrometry (UHPLC/TOFMS) for time-dependent profiling of raw and steamed Panax notoginseng

The metabolic profiles of Panax notoginseng and its associated therapeutic values are critically affected by the duration of steaming. The time-dependent steaming effect of P. notoginseng is not well-characterized and there is also no official guideline on its duration of steaming. In this paper, a UHPLC/TOFMS-based metabolomic platform was developed for the qualitative profiling of multiparametric metabolic changes of raw P. notoginseng during the steaming process. Our method was successful in discriminating the differentially processed herbs. Both the unsupervised principal component analysis (PCA) score plot (R(2)X=0.664, Q(2) (cum)=0.622, and PCs=2) and the supervised partial least square-data analysis (PLS-DA) model (R(2)X=0.708, R(2)Y=0.461, and Q(2)Y=0.271) demonstrated strong classification and clear trajectory patterns with regard to the duration of steaming. The PLS-DA model was validated for its robustness via a prediction set, confirming that the UHPLC/TOFMS metabolic profiles of the raw and differentially steamed P. notoginseng samples were highly reproducible. Based on our method, the minimum durations of steaming for the maximum production of bioactive ginsenosides such as Rg3 and Rh2 were also predicted. Our novel time-dependent metabolic profiling approach represents the paradigm shift in the quality control of P. notoginseng products.

Recent analytical approaches in quality control of traditional Chinese medicines--a review

Traditional Chinese medicines (TCMs) are gaining more and more attention all over the world, due to their specific theory and long historical clinical practice. But the uncontrollable quality is a bottleneck for its modernization and globalization. This paper reviewed the recent analytical methods in the quality control of TCMs, including screening strategies of bioactive markers from TCMs through biochromatographic methods, the traditional chromatographic methods, DNA methods, as well as the spectroscopic methods, including FT-IR, NIR and NMR. The comprehensive methods, such as fingerprint and multi-component quantification are emphasized; hyphenated techniques, like HPLC-MS, GC-MS, CE-MS, LC-NMR, chemometric methods, and combination of chemical and biological methods, such as biofingerprint, metabolic fingerprint are now more and more widely used in TCMs. In a few word, the analysis and quality control of TCMs are moving towards an integrative and comprehensive direction, in order to better address the inherent holistic nature of TCMs.

Combining orthogonal signal correction and wavelet packet transform with partial least squares to analyze overlapping spectra of three kinds of metal ions

A novel method named OSC-WPT-PLS approach based on partial least squares (PLS) regression with orthogonal signal correction (OSC) and wavelet packet transform (WPT) as pre-processed tools was proposed for the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). This method combines the ideas of OSC and WPT with PLS regression for enhancing the ability of extracting characteristic information and the quality of regression. OSC is used to remove information in the response matrix D by subtracting the structured noise that is orthogonal to the concentration matrix C. Wavelet packet transform was applied to perform data compression, to extract relevant information, and to eliminate noise and collinearity. PLS was applied for multivariate calibration and noise reduction by eliminating the less important latent variables. In this case, using trials, the kind of wavelet function, the decomposition level, the number of OSC components and the number of PLS factors for the OSC-WPT-PLS method were selected as Daubechies 4, 3, 2 and 3, respectively. A program (POSCWPTPLS) was designed to perform the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). The relative standard errors of prediction (RSEP) obtained for total elements using OSC-WPT-PLS, WPT-PLS and PLS were compared. Experimental results demonstrated that the OSC-WPT-PLS method had the best performance among the three methods and was successful even when there was severe overlap of spectra.