Determination of total antioxidant capacity in green tea by near-infrared spectroscopy and multivariate calibration

A principal component regression (PCR) model is built for prediction of total antioxidant capacity in green tea using near-infrared (NIR) spectroscopy. The modelling procedures are systematically studied with the focus on outlier detection. Different outlier detection methods are used and compared. The root mean square error of prediction (RMSEP) of the final model is comparable to the precision of the reference method.     

Prediction of total green tea antioxidant capacity from chromatograms by multivariate modeling

In this paper, a fast strategy for determining the total antioxidant capacity of Chinese green tea extracts is developed. This strategy includes the use of experimental techniques, such as fast high-performance liquid chromatography (HPLC) on monolithic columns and a spectrophotometric approach to determine the total antioxidant capacity of the extracts. To extract the chemically relevant information from the obtained data, chemometrical approaches are used. Among them there are correlation optimized warping (COW) to align the chromatograms, robust principal component analysis (robust PCA) to detect outliers, and partial least squares (PLS) and uninformative variable elimination partial least squares (UVE-PLS) to construct a reliable multivariate regression model to predict the total antioxidant capacity from the fast chromatograms.     

Potential antioxidant compounds in Mallotus species fingerprints. Part I: Indication, using linear multivariate calibration techniques

Some Mallotus species are used in traditional medicine in Vietnam and China. Some also show interesting activities, such as antioxidant and cytotoxic ones. Combining fingerprint technology with data-handling techniques allows indicating the peaks potentially responsible for given activities. In this study it is aspired to indicate from chromatographic fingerprints the peaks potentially responsible for the antioxidant activity of several Mallotus species. Relevant information was extracted using linear multivariate calibration techniques, both before and after alignment of the fingerprints with correlation optimized warping (COW). From the studied techniques, Stepwise Multiple Linear Regression is least recommended as it made an inadequate variable selection. Principal Component Regression theoretically can take largely varying variables uncorrelated to the antioxidant activity into account. However, in practice in the actual case study this problem was limited. These problems in principle do not occur using Partial Least Squares (PLS) models. Of the tested PLS methods, Orthogonal Projections to Latent Structures was preferred because of its simplicity, reproducibility, reduced model complexity and improved interpretability of the regression coefficients, yielding a clearer view on the individual contribution of the compounds. Furthermore, reducing analysis times from 60 min to 35 and 22.5 min resulted in the same main compounds, indicated responsible for the antioxidant activity. Models built after alignment by COW did not result in additional information.     

Robust partial least squares model for prediction of green tea antioxidant capacity from chromatograms

In this paper a robust version of the partial least squares model (partial robust M-regression, PRM) was built to predict the total antioxidant capacity of green tea extracts. In order to construct a calibration model, chromatograms obtained by a fast high-performance liquid chromatographic method on a monolithic silica column were related with the total antioxidant capacity of green tea extracts as determined by the Trolox antioxidant capacity method. Since natural samples are the subject of the study, some outlying samples are present in the data, as shown in an earlier work. Therefore, to construct reliable calibration models, they were detected and removed prior to modeling. With the applied robust partial least squares approach, where a weighting scheme is embedded to down-weight the negative influence of outliers upon the model it is possible to construct a robust calibration model, without prior identification of outlying objects. It was shown that a robust model, allowing satisfactory prediction for test samples, can be used in controlling green tea antioxidant capacity based on their chromatograms. The constructed robust partial least squares model was shown to have virtually the same fit and predictive power as the classical partial least squares model when outlying samples were removed from the data.     

Comprehensive evaluation of chemical stability of Xuebijing injection based on multiwavelength chromatographic fingerprints and multivariate chemometric techniques

A strategy for monitoring and analyzing the chemical stability of Xuebijing injection (XBJ) by multiwavelength chromatographic fingerprints and multivariate classification techniques is presented in this paper. Multiwavelength chromatographic fingerprints were constructed using chromatographic data obtained at four wavelengths (260, 280, 320, and 400?nm). The raw chromatography data were preprocessed by noise reduction, baseline correction, data normalization, and interval correlation optimized shifting (icoshift). Using this method, fingerprints of 166 samples of XBJ subjected to different forced degradation conditions (irradiation, high temperature, and a range of pH values) were properly represented. Forty-one chemical components were identified using the iPeak program. In addition, the identified peak area profiling of chemical components were used for multivariate classification analysis. Principal component analysis (PCA) and Ward’s method were used to classify different XBJ degradation samples. The PCA score plot showed that XBJ degradation samples were clustered into four groups, and the results are confirmed by Ward’s method. Ten key chemical markers under different degradation conditions were found and identified by counterpropagation artificial neural networks (CP-ANN), statistical t-tests, and UPLC-Q-TOF-MS. The results suggest that the proposed strategy could be successfully applied to the comprehensive analysis of complex chemical systems.     

Identification of potential antioxidant compounds in the essential oil of thyme by gas chromatography with mass spectrometry and multivariate calibration techniques

Thyme species are used in traditional medicine throughout the world and are known for their antiseptic, antispasmodic, and antitussive properties. Also, antioxidant activity is one of the interesting properties of thyme essential oil. In this research, we aim to identify peaks potentially responsible for the antioxidant activity of thyme oil from chromatographic fingerprints. Therefore, the chemical compositions of hydrodistilled essential oil of thyme species from different regions were analyzed by gas chromatography with mass spectrometry and antioxidant activities of essential oils were measured by a 1,1‐diphenyl‐2‐picrylhydrazyl radical scavenging test. Several linear multivariate calibration techniques with different preprocessing methods were applied to the chromatograms of thyme essential oils to indicate the peaks responsible for the antioxidant activity. These techniques were applied on data both before and after alignment of chromatograms with correlation optimized warping. In this study, orthogonal projection to latent structures model was found to be a good technique to indicate the potential antioxidant active compounds in the thyme oil due to its simplicity and repeatability.     

Total ion chromatographic fingerprints combined with chemometrics and mass defect filter to predict antitumor components of Picrasma quassioids

A method of total ion chromatogram combined with chemometrics and mass defect filter was established for the prediction of active ingredients in Picrasma quassioides samples. The total ion chromatogram data of 28 batches were pretreated with wavelet transformation and correlation optimized warping to correct baseline drifts and retention time shifts. Then partial least squares regression was applied to construct a regression model to bridge the total ion chromatogram fingerprints and the antitumor activity of P. quassioides. Finally, the regression coefficients were used to predict the active peaks in total ion chromatogram fingerprints. In this strategy, mass defect filter was employed to classify and characterize the active peaks from a chemical point of view. A total of 17 constituents were predicted as the potential active compounds, 16 of which were identified as alkaloids by this developed approach. The results showed that the established method was not only simple and easy to operate, but also suitable to predict ultraviolet undetectable compounds and provide chemical information for the prediction of active compounds in herbs.     

Electrochemical determination of the total antioxidant capacity of human plasma

Electrochemical reduction of oxygen at a glassy carbon electrode in a 0.05 mol L^–1 solution of (C₂H₅)₄NI in dimethylformamide leads to generation of the superoxide anion-radical. This product of reversible one-electron oxygen reduction reacts with antioxidants, a process which is based on protonation of the anion-radical by the antioxidant. Rate constants of this interaction have been calculated. Human plasma antioxidants also react with electrochemically generated superoxide anion-radical. A voltammetric method is proposed for estimation of the total antioxidant capacity (TAC) of plasma on the basis of on this reaction. The TAC of plasma was also determined using constant-current coulometry with electrogenerated bromine as the active species. A correlation was observed between TAC data obtained by voltammetry ( , in -tocopherol units) and coulometry (Br₂ as titrant). TAC of plasma from patients with purulent infections was determined. Statistically significant differences were found between TAC of patients and control group. Treatment of purulent infections increases the TAC of plasma. So, use of electrochemical methods (voltammetry and coulometry) for determination of TAC can be used for estimation of the effectiveness of treatment.     

Chronoamperometric evaluation of the antioxidant capacity of tea on a polyquercetin-modified electrode

It was established that the components of tea are oxidized on a glassy carbon electrode modified with carbon nanotubes and electropolymerized quercetin in a phosphate buffer solution (pH 7.0) as a supporting electrolyte under conditions of differential pulse voltammetry. The oxidation potentials of the individual phenolic antioxidants of tea (gallic acid, rutin, quercetin, catechin, epigallocatechin gallate, and tannin) on the modified electrode were found. A method for the chronoamperometric determination of the antioxidant capacity (AOC) of tea was developed based on the oxidation of tea antioxidants at a potential of 0.20 V. The AOC of tea was evaluated using а difference between the oxidation currents of the analyte and a supporting electrolyte after 50 s of electrolysis in terms of gallic acid. The analytical range of gallic acid was 0.25?750 μM with a detection limit of 0.063 μM. Positive correlations of the AOC with antioxidant activity in a reaction with 2,2-diphenyl-1-picrylhydrazyl and the total phenolic content were found (r = 0.700 and 0.647 at r _crit = 0.396, respectively).     

Capillary electrophoresis fingerprints combined with chemometric methods to evaluate the quality consistency and predict the antioxidant activity of Yinqiaojiedu tablet

The quality consistency of Yinqiaojiedu tablets (YQJDTs) was monitored by extracting their electrophoretic fingerprint and marker compound data that were obtained using capillary electrophoresis. To select the suitable background electrolyte, wing‐shape method was proposed. A background electrolyte composed of 103.1 mM boric acid, 51.6 mM sodium borate, 9.8 mM disodium hydrogen phosphate, and 15.6 mM sodium dihydrogen phosphate was used to separate compounds. Under the optimized conditions, the content of three marker compounds was determined in 25 YQJDT samples. The capillary electrophoresis fingerprints were developed simultaneously, then 25 samples from two manufacturers were clearly divided into two clusters based on the principal component analysis. In fingerprint assessments, systematic quantified fingerprint method was adopted for integrative quality discrimination of YQJDTs from both qualitative and quantitative perspectives, by which the qualities of 25 samples were well differentiated. In addition, partial least squares model was established to explore fingerprint–efficacy relationship between the fingerprints and the antioxidant activities in vitro, providing clinically useful information for quality control. The proposed method was reliable and comprehensive, which could be used for a valuable reference to monitor the quality consistency of traditional Chinese medicines.     

A novel algorithm for linear multivariate calibration based on the mixed model of samples

We present a novel algorithm for linear multivariate calibration that can generate good prediction results. This is accomplished by the idea of that testing samples are mixed by the calibration samples in proper proportion. The algorithm is based on the mixed model of samples and is therefore called MMS algorithm. With both theoretical support and analysis of two data sets, it is demonstrated that MMS algorithm produces lower prediction errors than partial least squares (PLS2) model, has similar prediction performance to PLS1. In the anti-interference test of background, MMS algorithm performs better than PLS2. At the condition of the lack of some component information, MMS algorithm shows better robustness than PLS2.     

Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea

In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.     

Comparative evaluation of various total antioxidant capacity assays applied to phenolic compounds with the CUPRAC assay

It would be desirable to establish and standardize methods that can measure the total antioxidant capacity level directly from vegetable extracts containing phenolics. Antioxidant capacity assays may be broadly classified as electron transfer (ET)- and hydrogen atom transfer (HAT)-based assays. The majority of HAT assays are kinetics-based, and involve a competitive reaction scheme in which antioxidant and substrate compete for peroxyl radicals thermally generated through the decomposition of azo compounds. ET-based assays measure the capacity of an antioxidant in the reduction of an oxidant, which changes colour when reduced. ET assays include the ABTS/TEAC, CUPRAC, DPPH, Folin-Ciocalteu and FRAP methods, each using different chromogenic redox reagents with different standard potentials. This review intends to offer a critical evaluation of existing antioxidant assays applied to phenolics, and reports the development by our research group of a simple and low-cost antioxidant capacity assay for dietary polyphenols, vitamins C and E, and human serum antioxidants, utilizing the copper(II)-neocuproine reagent as the chromogenic oxidizing agent, which we haved named the CUPRAC (cupric ion reducing antioxidant capacity) method. This method offers distinct advantages over other ET-based assays, namely the selection of working pH at physiological pH (as opposed to the Folin and FRAP methods, which work at alkaline and acidic pHs, respectively), applicability to both hydrophilic and lipophilic antioxidants (unlike Folin and DPPH), completion of the redox reactions for most common flavonoids (unlike FRAP), selective oxidation of antioxidant compounds without affecting sugars and citric acid commonly contained in foodstuffs and the capability to assay -SH bearing antioxidants (unlike FRAP). Other similar ET-based antioxidant assays that we have developed or modified for phenolics are the Fe(III)- and Ce(IV)-reducing capacity methods.     

Voltammetric evaluation of the antioxidant capacity of tea on electrodes modified with multi-walled carbon nanotubes

The characteristics of the voltammograms of tea polyphenols on a glassy carbon electrode modified with multi-walled carbon nanotubes (MCNT-GCE) were evaluated. With the use of atomic force microscopy, it was found that MCNTs are oriented as rows 0.8–1.0 μm wide with alternating hills to 586 nm in height. Polyphenols other than of tannin are reversibly oxidized at the first step. Corresponding electrode reaction schemes are proposed. A voltammetric procedure for the estimation of the antioxidant capacity (AOC) of tea based on the oxidation of its polyphenol compounds was developed. The voltammograms of tea exhibited clearly defined peaks and oxidation steps whose potentials depend on the type of tea. The area of oxidation peaks was chosen as the parameter that characterizes antioxidant properties. The AOC of tea was expressed in terms of catechin equivalents per 100 mL of a beverage. 27 tea samples were analyzed. It was found that the AOC of green tea is 79% higher than that of black tea (290 ± 40 and 54 ± 22 mg/100 mL, respectively, P < 0.05). The AOC of oolong tea (70 ± 5 mg/100 mL) is considerably lower than that of green tea and statistically insignificantly higher than that of black tea. The AOC of white tea is comparable with the AOC of green tea (255 ± 11 and 290 ± 40 mg/100 mL, respectively, P > 0.05).     

Improvement of multivariate calibration techniques applied to 1-to-N component mixtures through an optimized experimental design

This work describes a novel experimental design aimed at building a calibration set constituted by samples containing a different number of components. The algorithm performs a reiteration process to maintain the number of samples at the lower value as possible and to ensure an homogeneous presence of all the concentration levels. The mixture design was applied to a drug system composed by one-to-four components in different combination. The resolution of the system was performed by three multivariate UV spectrophotometric methods utilizing principal component regression (PCR) and partial last squares (PLS1 and PLS2) algorithms. The calibration set was composed by 61 references on four concentration levels, including 15 samples for each quaternary, ternary and binary composition and 16 one-component samples. The calibration models were optimized through a careful selection of number of factors and wavelength zones, in such a way as to remove interferences from instrumental noise and excipients present in the pharmaceutical formulations. The prediction power of the regression models were verified and compared by analysis of an external prediction set. The models were finally used to assay pharmaceutical specialities containing the studied drugs in one-to-four formulations.     

The application of multivariate techniques to data from spanish glass-making objects from the Roman Era

Three multivariate techniques (principal components analysis, correspondence factor analysis and spectral map analsis) are applied to x-ray fluorescence data from glass-making objects from the 5th century AD found in Tarragona (Tarraco in the Roman Empire). The information obtained by displaying th eobjects and variables in each reduced factor space is compared. The presence of redundant information is shown. The visualization of groups of objects and of the relationship between objects and variables allows the formulation of hypotheses concerning the origin of the samples and the presence of local glassworks.     

Near-infrared reflectance spectroscopy and multivariate calibration techniques applied to modelling the crude protein, fibre and fat content in rapeseed meal

Near-infrared reflectance spectroscopy (NIRS) is often applied when a rapid quantification of major components in feed is required. This technique is preferred over the other analytical techniques due to the relatively few requirements concerning sample preparations, high efficiency and low costs of the analysis. In this study, NIRS was used to control the content of crude protein, fat and fibre in extracted rapeseed meal which was produced in the local industrial crushing plant. For modelling the NIR data, the partial least squares approach (PLS) was used. The satisfactory prediction errors were equal to 1.12, 0.13 and 0.45 (expressed in percentages referring to dry mass) for crude protein, fat and fibre content, respectively. To point out the key spectral regions which are important for modelling, uninformative variable elimination PLS, PLS with jackknife-based variable elimination, PLS with bootstrap-based variable elimination and the orthogonal partial least squares approach were compared for the data studied. They enabled an easier interpretation of the calibration models in terms of absorption bands and led to similar predictions for test samples compared to the initial models.     

Optimum conditions for the water extraction of L-theanine from green tea

Theanine is a unique non-protein amino acid found in tea (Camellia sinensis). It contributes to the favourable umami taste of tea and is linked to various beneficial effects in humans. There is an increasing interest in theanine as an important component of tea, as an ingredient for novel functional foods and as a dietary supplement. Therefore, optimal conditions for extracting theanine from tea are required for the accurate quantification of theanine in tea and as an efficient first step for its purification. This study examined the effects of four different extraction conditions on the yield of theanine from green tea using water and applied response surface methodology to further optimise the extraction conditions. The results showed that temperature, extraction time, ratio of water-to-tea and tea particle sizes had significant impacts on the extraction yield of theanine. The optimal conditions for extracting theanine from green tea using water were found to be extraction at 80 °C for 30 min with a water-to-tea ratio of 20:1 mL/g and a tea particle size of 0.5-1 mm.     

An approach to comparative analysis of chromatographic fingerprints for assuring the quality of botanical drugs

The present study was focused on developing the chemometric methods for analysis of the chromatographic fingerprint to control the quality of botanical drugs, which has gained attention in Asia and other countries. We developed a novel approach to generate a set of fingerprint features, called Fisher components (FCs) that were extracted from the chromatographic fingerprint. The method greatly reduces the dimensionality of the fingerprint vector, and the resulting FCs still retain most discriminatory information of the original fingerprint. Choosing an example of relevance to contemporary botanical drugs, we applied the FCs to a set of Shenmai injection samples. We successfully identified the manufacturers of the samples using two classifiers, linear discriminant analysis (LDA) and k-Nearest Neighbor (k-NN) based on the FCs. We also applied a similarity assessment together with the visual analysis using the FCs to exam the products from different manufacturers. We found that the lot-to-lot consistency of products can be accurately determined using the FCs. Finally, we demonstrated that the application of chemometric methods for chromatographic fingerprinting offers reliability to detect suspected fraud samples. In summary, we demonstrated that the presented approaches could be useful to determine the identity, consistency, and authenticity of Shenmai injection through chromatographic fingerprinting. The methods are equally applicable to other botanical drugs.     

Reproducibility of the high-performance liquid chromatographic fingerprints obtained from two soybean cultivars and a selected progeny

Roots from soybean cultivars Williams 82 and Hartwig along with one of their progeny 14a, were extracted with non-polar, moderately polar, and highly polar solvent systems. Extracts were compared by thin-layer chromatography and by HPLC. Methanol extractions conducted at ambient temperature coupled with analysis by reversed-phase HPLC using UV detection provided the most representative sets of reproducible fingerprints. Further optimization of the overall protocol should allow for the profiling of different soybean cultivars when their roots are exposed to various environments and insults during early growth.