Identification and similarity analysis of aroma substances in main types of Fenghuang Dancong tea

Fenghuang Dancong tea covers the oolong tea category and is widely acknowledged for its unique floral and honey flavor. In order to characterize the volatile components in nine different aroma types of Fenghuang Dancong tea, the Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC- MS) were employed. In addition, the similarity analysis and cluster analysis (CA) were performed to compare the aroma characteristics and establish the correlation between the nine types of teas. The principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) method were employed to determine the volatile components with a high contribution to the overall aroma of each type of tea. The results presented a total of 122 volatile aroma components including 24 kinds of alcohol, 23 kinds of esters, 15 kinds of olefins, 12 kinds of aldehydes, 12 kinds of ketones, 13 kinds of alkanes and 23 kinds of other components from the nine types of Fenghuang Dancong tea. Of these volatile aroma components, 22 types were common with linalool, dehydrolinalool, linalool oxide I, linalool oxide II, etc. The similarity of the nine types of Fenghuang Dancong tea was found between 46.79% and 95.94%. The CA indicated that the nine types of Fenghuang Dancong tea could be clustered into four categories when the ordinate distance reached to 10. The PCA demonstrated that decane, octadecane, 2,2,4,6,6-pentamethylheptane, dehydrolinalool, geraniol and nerol were the important aroma components to Fenghuang Dancong Tea. OPLS-DA proved that 2,2,4,6,6-pentamethylheptane, dehydrolinalool, phenylacetaldehyde, nerolidol, linalool oxide I and hexanal were the key differential compounds between the various types of tea samples. This study provides a theoretical basis for characterizing the volatile aroma components in the main types of Fenghuang Dancong tea as well as the similarity and correlation between various types of Fenghuang Dancong tea.

Black and Green Tea Supplements Ameliorate Male Infertility in a Murine Model of Obesity

Obesity, a chronic metabolic disorder, can affect male reproductive function. As a functional beverage, tea has many biological activities and potential in the treatment of obesity. However, its effects on male reproductive damage induced by obesity are not yet clear. In this study, a murine model of obesity was established by feeding with high-fat diet (HF). A total of 24 male mice were divided into four groups: normal diet (control), HF, HF supplemented with 5% green tea powder (HF+G), and HF supplemented with 5% black tea powder (HF+B). The results showed that the HF + B significantly reduced the mouse body weight gain and testicular coefficient and lowered the serum insulin and leptin levels compared with the HF group. The sperm malformation rate of mice in the HF group had a significant increase when compared with the control group, the HF + B group had a significant decrease compared with the HF group, and no difference from the control group. The HF + G and HF + B significantly increased testosterone levels in serum compared with the HF group. The testosterone production-related gene cytochrome P450 family 11 subfamily a member (CYP11A1) and cytochrome p450 family 17 subfamily a member 1 (CYP17A1) expressions in testis were significantly increased in the HF + G group compared with HF group. In addition, the HF + G and HF + B abolished the effects of HF on superoxide dismutase (SOD), malondialdehyde, and glutathione levels in testis and antioxidant-related gene expressions of XRCC1 and SOD1. Overall, our findings have provided evidence that black and green tea has a positive effect on reducing reproductive damage in a male murine model of obesity, and that black tea is more effective than green tea.

Highly identification of keemun black tea rank based on cognitive spectroscopy: Near infrared spectroscopy combined with feature variable selection

From the perspective of combating fraud issues and examining keemun black tea properties, there was a contemporary urgent demand for a keemun black tea rankings identification system. Current rapid evaluation systems had been mainly developed for green tea grade evaluation, but there was space for improvement to establish a highly robust model. The present study proposed cognitive spectroscopy that combined near infrared spectroscopy (NIRS) with multivariate calibration and feature variable selection methods. We defined "cognitive spectroscopy" as a protocol that selects characteristic information from complex spectral data and showed optimal results without human intervention. 700 samples representing keemun black tea from seven quality levels were scanned applying an NIR sensor. To differentiate which wavelength variables of the acquired NIRS data carry key and feature information regarding keemun black tea grades, there were four different variables screening approaches, namely genetic algorithm (GA), successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and shuffled frog leaping algorithm (SFLA), were compared in this study. Cognitive models were developed using least squares support vector machine (LSSVM), back propagation neural network (BPNN) and random forest (RF) methods combined with the optimized characteristic variables from the above variables selection algorithms for the identification of keemun black tea rank quality. Experimental results showed that all cognitive models utilizing the SFLA approach achieved steady predictive results based on eight latent variables and selected thirteen characteristic wavelength variables. The CARS-LSSVM model with the best predictive performance was proposed based on selecting ten characteristic latent variables, and the best performance indicators of the model were as follows: the root mean square error of prediction (RMSEP) was 0.0413, the correlation coefficients of prediction set (R_p) was 0.9884, and the correct discriminant rate (CDR) was 99.01% in the validation process. This study demonstrated that cognitive spectroscopy represented a proper strategy for the highly identification of quality rankings of keemun black tea.

Evaluation of matcha tea quality index using portable NIR spectroscopy coupled with chemometric algorithms

BACKGROUND

The study reports a portable near infrared (NIR) spectroscopy system coupled with chemometric algorithms for prediction of tea polyphenols and amino acids in order to index matcha tea quality.

RESULTS

Spectral data were preprocessed by standard normal variate (SNV), mean center (MC) and first-order derivative (1^st D) tests. The data were then subjected to full spectral partial least squares (PLS) and four variable selection algorithms, such as random frog partial least square (RF-PLS), synergy interval partial least square (Si-PLS), genetic algorithm-partial least square (GA-PLS) and competitive adaptive reweighted sampling partial least square (CARS-PLS). RF-PLS was established and identified as the optimum model based on the values of the correlation coefficients of prediction (R_P ), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD), which were 0.8625, 0.82% and 2.13, and 0.9662, 0.14% and 3.83, respectively, for tea polyphenols and amino acids. The content range of tea polyphenols and amino acids in matcha tea samples was 8.51-14.58% and 2.10-3.75%, respectively. The quality of matcha tea was successfully classified with an accuracy rate of 83.33% as qualified, unqualified and excellent grade.

CONCLUSION

The proposed method can be used as a rapid, accurate and non-destructive platform to classify various matcha tea samples based on the ratio of tea polyphenols to amino acids. © 2019 Society of Chemical Industry.

Formation of α-Farnesene in Tea (Camellia sinensis) Leaves Induced by Herbivore-Derived Wounding and Its Effect on Neighboring Tea Plants

Herbivore-induced plant volatiles (HIPVs) play important ecological roles in defense against stresses. In contrast to model plants, reports on HIPV formation and function in crops are limited. Tea (Camellia sinensis) is an important crop in China. α-Farnesene is a common HIPV produced in tea plants in response to different herbivore attacks. In this study, a C. sinensis α-farnesene synthase (CsAFS) was isolated, cloned, sequenced, and functionally characterized. The CsAFS recombinant protein produced in Escherichia coli was able to transform farnesyl diphosphate (FPP) into α-farnesene and also convert geranyl diphosphate (GPP) to β-ocimene in vitro. Furthermore, transient expression analysis in Nicotiana benthamiana plants indicated that CsAFS was located in the cytoplasm and could convert FPP to α-farnesene in plants. Wounding, to simulate herbivore damage, activated jasmonic acid (JA) formation, which significantly enhanced the CsAFS expression level and α-farnesene content. This suggested that herbivore-derived wounding induced α-farnesene formation in tea leaves. Furthermore, the emitted α-farnesene might act as a signal to activate antibacterial-related factors in neighboring undamaged tea leaves. This research advances our understanding of the formation and signaling roles of common HIPVs in crops such as tea plants.

Differences in Chemical Composition among Commercially Important Cultivars of Genus Camellia

Leaves from plants of the genus Camellia are used to make beverages and food products; however, there is limited data that compares the chemical composition of the unprocessed leaves of cultivars traditionally used to make these products. Plucked, fresh leaves from 14 commercially important cultivars were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry. On the basis of assessment of 61 compounds that are known to be affected by postharvest tea processing methods, significant variation among unprocessed cultivar leaves was observed for compounds in five chemical classes: amino acids, catechins, flavonoids and flavone glycosides, phenolic acids, and alkaloids. These chemical differences were of sufficient magnitude to render two distinct chemically defined clusters of Camellia cultivars that did not reflect the traditional grouping of these cultivars based by species variant, tea type, or production region. Advanced statistical techniques identified candidate biomarkers for each chemical class to guide the development of comprehensive targeted analyses for constituents of biosynthetic pathways in which marked expression plasticity was observed. Targeted analyses of this type have the potential to identify Camellia species/cultivars that will facilitate the formulation of new beverages and designer foods with improved organoleptic characteristic and enhanced prebiotic or nutraceutical activity.

Exploration of a Method of Distinguishing Different Nongxiang Tieguanyin Tea Grades Based on Aroma Determined by GC-MS Combined with Chemometrics

An aroma-based method for distinguishing different grades of Nongxiang Tieguanyin was explored by taking special grade (K110) and 1-4 grades (K101, K102, K103, and K104) of this tea as samples. Tea samples were analyzed by gas chromatography-mass spectrometry (GC-MS) combined with chemometrics. Results showed differences in the types and relative contents of aroma components among different grades of Nongxiang Tieguanyin tea. In the principal component analysis (PCA) scoring plot, except for K102 and K103, tea samples of different grades were distributed in different regions. Components satisfying variable important for the projection (VIP) > 1 and peak areas with significant differences (p < 0.05) among different tea grades were screened. Finally, 18 differential variables were screened out from 143 volatiles. The clustering results of these variables were consistent with those of PCA. K102 and K103 were initially clustered into one group and then clustered with K101, K110, and K104 in turn. The clear PCA separation of these samples and uniform hierarchical cluster analysis (HCA) clustering results suggests that GC-MS coupled with chemometrics analysis is a valid and accurate approach for discriminating different grades of Nongxiang Tieguanyin. The screened differential variables could represent a difference in aroma quality among five grades of Nongxiang Tieguanyin tea. Clear rules between peak area and the grade were also observed in some differential variables. 1-Ethylpyrrole and unknown-32 were positively correlated with grade. 2-Methylfuran, 2-ethylfuran, 2-methylidenecyclopentan-1-ol, mesityl oxide, 2-amylfuran, and D-limonene were negatively correlated with grade. The peak areas of methyl acetate, dimethyl sulfide, 6-methylhept-5-en-2-one, and (Z)-β-ocimene initially decreased but then increased with declining grade. The toluene content was especially high in K104 but only a negligible difference was observed among other grades. This study provides a potential method for differentiating Nongxiang Tieguanyin teas of different grades based on aroma. Unknown samples could be classified by comparison of their spatial distribution with those of known standard samples in PCA or HCA, as well as the peak area differences of differential variables between unknown samples and known standard samples.

Influence of leaf age, species and soil depth on the authenticity and geographical origin assignment of green tea

RATIONALE

Stable isotope fractionation occurring during leaf growth provides internal characteristics for identifying the geographical origin, traceability and authentication of tea. Studying the influence of leaf age, species and the relationship with the cultivated soil may reveal previously undocumented stable isotope fractionation mechanisms, and provide a deeper understanding of the physiological isotopic effects on the tractability and authentication accuracy of green tea to combat mislabeling and fraudulent conduct.

METHODS

A total of 36 pairs of young (one bud with one leaf) and mature growth (older leaf) samples from two species of Longjing tea (Longjing #43 and Colonial cultivar) and corresponding cultivation soil samples from two different depth layers (0-20 cm and 20-40 cm) were collected in Westlake district, Hangzhou, Zhejiang province, China. Four stable isotope ratios (δ¹³ C, δ¹⁵ N, δ² H, and δ¹⁸ O values) were measured using an elemental analyzer coupled with an isotope ratio spectrometer. Linear correlation and one-way analysis of variance (ANOVA) statistical analyses were performed to investigate isotopic fractionation mechanisms during plant growth, and reflect the dynamic physiological processes from soil to leaf.

RESULTS

The carbon and nitrogen isotope ratios (δ¹³ C and δ¹⁵ N values) reflected the absorption, migration and fractionation of carbon dioxide and nitrogenous nutrients during photosynthesis, nutrient uptake, nitrogen fixation and leaf respiration. The water isotope ratios (δ² H and δ¹⁸ O values) reflected the use and fractionation of water by tea plants at different growth stages.

CONCLUSIONS

Considerable differences were found for hydrogen and oxygen isotope ratios according to leaf age, revealing complex isotopic fractionation mechanisms and possible interference factors. Leaf maturity effects should be considered, as they will influence the precision and accuracy of models when assigning the geographical origin, traceability and authentication of tea.

Evaluating green tea quality based on multisensor data fusion combining hyperspectral imaging and olfactory visualization systems

BACKGROUND

The instrumental evaluation of tea quality using digital sensors instead of human panel tests has attracted much attention globally. However, individual sensors do not meet the requirements of discriminant accuracy as a result of incomprehensive sensor information. Considering the major factors in the sensory evaluation of tea, the study integrated multisensor information, including spectral, image and olfaction feature information.

RESULTS

To investigate spectral and image information obtained from hyperspectral spectrometers of different bands, principal components analysis was used for dimension reduction and different types of supervised learning algorithms (linear discriminant analysis, K-nearest neighbour and support vector machine) were selected for comparison. Spectral feature information in the near infrared region and image feature information in the visible-near infrared/near infrared region achieved greater accuracy for classification. The results indicated that a support vector machine outperformed other methods with respect to multisensor data fusion, which improved the accuracy of evaluating green tea quality compared to using individual sensor data. The overall accuracy of the calibration set increased from 75% using optimal single sensor information to 92% using multisensor information, and the overall accuracy of the prediction set increased from 78% to 92%.

CONCLUSION

Overall, it can be concluded that multisensory data accurately identify six grades of tea. © 2018 Society of Chemical Industry.

Tea types classification with data fusion of UV-Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis

The potential of selected spectroscopic methods - UV-Vis, synchronous fluorescence and NIR as well a data fusion of the measurements by these methods - for the classification of tea samples with respect to the production process was examined. Four classification methods - Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Regularized Discriminant Analysis (RDA) and Support Vector Machine (SVM) - were used to analyze spectroscopic data. PCA analysis was applied prior to classification methods to reduce multidimensionality of the data. Classification error rates were used to evaluate the performance of these methods in the classification of tea samples. The results indicate that black, green, white, yellow, dark, and oolong teas, which are produced by different methods, are characterized by different UV-Vis, fluorescence, and NIR spectra. The lowest error rates in the calibration and validation data sets for individual spectroscopies and data fusion models were obtained with the use of the QDA and SVM methods, and did not exceed 3.3% and 0.0%, respectively. The lowest classification error rates in the validation data sets for individual spectroscopies were obtained with the use of RDA (12,8%), SVM (6,7%), and QDA (2,7%), for the UV-Vis, SF, and NIR spectroscopies, respectively. NIR spectroscopy combined with QDA outperformed other individual spectroscopic methods. Very low classification errors in the validation data sets - below 3% - were obtained for all the data fusion data sets (SF + UV-Vis, SF + NIR, NIR + UV-Vis combined with the SVM method). The results show that UV-Vis, fluorescence and near infrared spectroscopies may complement each other, giving lower errors for the classification of tea types.

Differentiation of key biomarkers in tea infusions using a target/nontarget gas chromatography/mass spectrometry workflow

Climatic conditions affect the chemical composition of edible crops, which can impact flavor, nutrition and overall consumer preferences. To understand these effects new data analysis software capable of tracking hundreds of compounds across years of samples under various environmental conditions is needed. Our recently developed mass spectral (MS) subtraction algorithms have been used with spectral deconvolution to efficiently analyze complex samples by 2-dimensional gas chromatography/mass spectrometry (GC-GC/MS). In this paper, we address the accuracy of identifying target and nontarget compounds by GC/MS. Findings indicate that Yunnan tea contains higher concentrations of floral compounds. In contrast, Fujian tea contains higher concentrations of compounds that exhibit fruity characteristics, but contains much less monoterpenes. Principal components analysis shows that seasonal changes in climate impact tea plants similarly despite location differences. For example, spring teas contained more of the sweet, floral and fruity compounds compared to summer teas, which had higher concentrations of green, woody, herbal compounds.

Evaluation of the in vitro α-glucosidase inhibitory activity of green tea polyphenols and different tea types

BACKGROUND

The objective of this study was to determine whether green tea, black tea and oolong tea have inhibitory potential against α-glucosidase which may be used to control postprandial hyperglycemia in type 2 diabetes mellitus.

RESULTS

Green tea polyphenols (TPs) strongly inhibited α-glucosidase activity by non-competitive inhibition with an IC50 value of 2.33 µg mL(-1) and the inhibitory effect was dependent on TP concentration and incubation order. Green tea, black tea and oolong tea also had dose-dependent inhibitory potential with IC50 values of 2.82, 2.25 and 1.38 µg mL(-1) (µg polyphenol mL(-1)), respectively. The study also showed that the content of unprecipitated TPs changed during enzymatic hydrolysis, leading to the change of the antioxidant activity. The change of the antioxidant activity of tea extracts revealed a similar trend to that of green TPs during enzymatic hydrolysis.

CONCLUSION

Green TPs, green tea, black tea and oolong tea are excellent α-glucosidase inhibitors and their inhibitory potency is mainly attributed to TPs. These findings suggest that green tea, black tea and oolong tea can potentially be used to control postprandial hyperglycemia.

Differing chemical compositions of three teas may explain their different effects on acute blood pressure in spontaneously hypertensive rats

BACKGROUND

Heavy tea consumption is suggested to be unsuitable for hypertensive people. However, the bioactive substances in different varieties of tea leaves are very different. This study compares the effects of three Chinese teas - C. sinensis, C. ptilophylla and C. assamica var. kucha - on blood pressure (BP) and heart rate in spontaneously hypertensive rats (SHRs).

RESULTS

Intragastric administration of C. sinensis extract led to an acute increase in systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate in SHRs. However, C. ptilophylla and C. assamica var. kucha exerted no obvious influences on SBP, DBP or heart rate. Similar to the extract of C. sinensis, intragastric administration of caffeine also led to an acute increase in BP and heart rate in SHRs. In contrast, theobromine and theacrine - purine alkaloids predominantly contained in C. ptilophylla and C. assamica var. kucha, respectively - had no pressor effects. The effect of caffeine on BP was related to the regulation of plasma epinephrine and norepinephrine levels in SHRs.

CONCLUSION

The different effects of C. sinensis, C. ptilophylla and C. assamica var. kucha on BP might be explained, at least partially, by the differences in the varieties and contents of purine alkaloids.

[Reason analysis of inadaptability and its correction research on the authenticity identification model of West Lake Longjing tea based on LVF micro-NIR spectrometer]

In the present paper, the micro-NIR spectrometer with the splitter of linear variable filter was used to develop the recognition models of the West Lake Longjing tea and the ordinary flat tea of the year 2012 and 2013. The NIR spectral data of different years and different storage times were decomposed by PCA algorithm. The PLS-DA models were developed by the representative samples selected by the mathematical characteristics of PCA-scores' distribution in order to analyze the reason for the inadaptability of the models according to mathematical principles and find out the solution for its correction. Being examined by the external validation set, the adaptability of the authenticity identification model was enhanced effectively. The result of this research indicated that, for the West Lake Longjing tea and the ordinary flat tea, the correct recognition rate of the model developed by all different-year samples' NIR spectral data would be enhanced effectively. The model developed by the NIR spectral data of different storage time samples indicated that the physicochemical properties of the ordinary flat tea have changed remarkably after cryopreservation for 3 months, while the physicochemical properties of the West Lake Longjing tea are relatively stable. The model adaptabilities for different years and different storage times were studied according to the mathematical perspective of the principal component characteristics of spectral data. After the authenticity identification model of West Lake Longjing tea was developed, the prediction accuracy was enhanced effectively. This research would provide reference for not only the application of NIR spectroscopy in quality grading and safety of agricultural products, but also the enhancement of the prediction accuracy of the NIR grading models for agricultural products.

[Identification of green tea brand based on hyperspectra imaging technology]

Hyperspectral imaging technology was developed to identify different brand famous green tea based on PCA information and image information fusion. First 512 spectral images of six brands of famous green tea in the 380 approximately 1 023 nm wavelength range were collected and principal component analysis (PCA) was performed with the goal of selecting two characteristic bands (545 and 611 nm) that could potentially be used for classification system. Then, 12 gray level co-occurrence matrix (GLCM) features (i. e., mean, covariance, homogeneity, energy, contrast, correlation, entropy, inverse gap, contrast, difference from the second-order and autocorrelation) based on the statistical moment were extracted from each characteristic band image. Finally, integration of the 12 texture features and three PCA spectral characteristics for each green tea sample were extracted as the input of LS-SVM. Experimental results showed that discriminating rate was 100% in the prediction set. The receiver operating characteristic curve (ROC) assessment methods were used to evaluate the LS-SVM classification algorithm. Overall results sufficiently demonstrate that hyperspectral imaging technology can be used to perform classification of green tea.

[Discrimination of Minnan oolong tea varieties by NIR spectroscopy]

The present paper presented a fast and non-destructive method for the discrimination of minnan oolong tea varieties by near-infrared spectroscopy technology. Two hundred ten samples including Tieguanyin, Huangjingui, Benshan, Maoxie and Meizhan were collected in different tea plantations of Minnan. NIR spectra of 1,100-1,300 nm and 1,640-2,498 nm were successfully obtained. Prediction model was built by principal component analysis (PCA), and the effects of multiplicative scatter correction (MSC) and standard normal variate (SNV) on the model were observed and compared. It was indicated that the effect of MSC on the model was superior for the effect of SNV because the classification accuracy of model for the calibration samples reached 96%, and this number to the prediction samples was about 90%. These results demonstrated that the near-infrared spectroscopy method established could be an efficient and accurate way for the discrimination of minnan oolong teas and would have a strong practical value.

Comparative analysis of Pu-erh and Fuzhuan teas by fully automatic headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and chemometric methods

Thirteen Pu-erh teas and 13 Fuzhuan teas obtained from two different production areas in China were profiled using fully automatic headspace solid-phase microextraction (HS-SPME)/gas chromatography-mass spectrometry (GC-MS) coupled with chemometric methods. A total of 93 aroma components were identified in 26 dark teas; among them, methoxyphenolic compounds (31.77%) were the most abundant components in Pu-erh teas, whereas ketone compounds were the most abundant components (25.42%) in Fuzhuan teas. Cluster analysis (CA) and principal component analysis (PCA) showed that these two types of dark teas could be clearly distinguished according to their chemical characteristics. This study suggested that the proposed strategy could provide a feasible and rapid technique to differentiate dark teas with similar morphological characteristics from different production areas by their volatile composition and relative content.

Discrimination of Sri Lankan black teas using fluorescence spectroscopy and linear discriminant analysis

BACKGROUND

The quality of teas is currently graded using trained tea tasters, whose evaluation can sometimes be subjective. In this study the simple fluorescence-based technique of total luminescence spectroscopy (TLS) in conjunction with data classification using principal component analysis (PCA) was applied to discriminate between teas from 11 different Sri Lankan plantations. Solvent extraction of the tea samples was followed by TLS to record excitation-emission matrices in the excitation range 250-590 nm and emission range 300-700 nm.

RESULTS

The application of PCA and linear discriminant analysis (LDA) allowed the successful classification of all 11 teas using only the first two principal components. LDA demonstrated how the technique was able to discriminate between all teas correctly with 100% classification.

CONCLUSION

Further development of this work could lead to a simple device that could be used by tea manufacturers instead of or alongside trained tea tasters to grade teas.

[Study on effective substances of tea for chemoprevention of lung cancer based on principal component analysis]

OBJECTIVE

To study the effective substances of tea for chemoprevention of lung cancer based on Principal Component Analysis (PCA).

METHODS

UPLC was used to determine the content of each component in tea, MTT was used to analyze the survival of CSE-induced NHBE cells. DTNB and the colorimetric assay were used to detect the rate of GSH/GSSG, PCA was used to calculate the correlation coefficient matrix, eigen values and variance of contribution ratio to chemoprevention of lung cancer.

RESULTS

Longjing (L) was the most effective one to protect NHBE cells from damaging, and the IC50 of L for prevention of NHBE cells was 0.2559 mg/mL and could make the GSH/GSSG ratio recovery ranging from 0.142 to 0.858 in a dose-dependent manner. The contribution of GCG prevention of lung cancer was 79.602% and that of GA was 11.037% by PCA.

CONCLUSION

Different kinds of tea have different protective effect on NHBE cells. GCGC and GA are the main active ingredients in tea for chemoprevention of lung cancer by PCA.

Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation

Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis was used to train a predictive chemometric model and a leave-one-out methodology was used to classify the types and evaluate the quality of the tea samples. The predicted classification of the oolong teas and the grade of the jasmine teas were estimated using this method. The agreement between the grades evaluated by the tea experts and by the chemometric model shows the potential of this technique to be used for practical assessment of tea grades.

Evaluation of soluble oxalates content in infusions of different kinds of tea and coffee available on the Polish market

BACKGROUND

Tea and coffee are the potentially rich source of oxalic acid, which can act as a antinutrient.

OBJECTIVE

The aim of this study was to determine and evaluate the content of soluble oxalates in teas and coffees available on the Polish market.

MATERIAL AND METHOD

The green, red and black teas, and black natural ground and instant coffees were used for preparing the infusions. The manganometric method was used for the determination of the oxalates in the infusions.

RESULTS

The mean oxalates content in the infusions from 3 g of black teas was 115.68 mg/100 cm3 and was higher as compared to red teas (101.91 mg/100 cm3) and green teas (87.64 mg/100 cm3). Disregarding the variety of analyzed teas, the largest oxalates content was in infusions of pure one-component tea--"Sir Roger" (164.82-174.22 mg/100 cm3), while the lowest oxalates content was noted in the tea containing the components from other plants ("Bio-Active" with grapefruit juice--reaching as low level as 39.00 mg/100 cm3). Instant coffees contained larger amount of oxalates than natural ground coffees. Irrespective of the kind of the tested coffees, the lowest oxalates content was found in the infusions from the following coffees: Tchibo Exclusive--19.62 mg/100 cm3, Gala ulubiona--37.32 mg/100 cm3, and Maxwell House--38.40 mg/100 cm3, while the highest oxalates content in instant coffee--Nescafe Espiro 51.80 mg/100 cm3.

CONCLUSIONS

The results revealed a significant relation between phytochemical composition of analyzed teas and coffees and the level of soluble oxalates in infusions prepared from the tested products.

Predicting the age and type of tuocha tea by fourier transform infrared spectroscopy and chemometric data analysis

Fourier transform infrared (FTIR) spectroscopy combined with chemometric multivariate methods was proposed to discriminate the type (unfermented and fermented) and predict the age of tuocha tea. Transmittance FTIR spectra ranging from 400 to 4000 cm(-1) of 80 fermented and 98 unfermented tea samples from Yunnan province of China were measured. Sample preparation involved finely grinding tea samples and formation of thin KBr disks (under 120 kg/cm(2) for 5 min). For data analysis, partial least-squares (PLS) discriminant analysis (PLSDA) was applied to discriminate unfermented and fermented teas. The sensitivity and specificity of PLSDA with first-derivative spectra were 93 and 96%, respectively. Multivariate calibration models were developed to predict the age of fermented and unfermented teas. Different options of data preprocessing and calibration models were investigated. Whereas linear PLS based on standard normal variate (SNV) spectra was adequate for modeling the age of unfermented tea samples (RMSEP = 1.47 months), a nonlinear back-propagation-artificial neutral network was required for calibrating the age of fermented tea (RMSEP = 1.67 months with second-derivative spectra). For type discrimination and calibration of tea age, SNV and derivative preprocessing played an important role in reducing the spectral variations caused by scattering effects and baseline shifts.

[Identification of Pu'er teas with different storage years by FTIR spectroscopy]

Infrared spectra of Pu'er raw tea and Pu'er ripe tea were investigated using Fourier transform spectroscopy, in order to exploit a rapid method for discrimination of aging period for Pu' er tea samples. The results showed that the two kinds of Pu'er teas shared a similar woveform of infrared spectrum. However, due to the variations of aging time, leading to different chemical composition in pu'er teas, both Pu'er raw tea and ripe tea displayed corresponding different characteristic peaks. And the extent of aging of Pu'er tea had a significant relationship with optical density and waveforms of absorption peaks in the wave number range of 1 120-1 570 cm(-1) and 400-853 cm(-1), suggesting that the extent of aging of Pu'er tea may be identified by infrared spectrum technology rapidly and simply.

Commercial teas highlight plant DNA barcode identification successes and obstacles

Appearance does not easily identify the dried plant fragments used to prepare teas to species. Here we test recovery of standard DNA barcodes for land plants from a large array of commercial tea products and analyze their performance in identifying tea constituents using existing databases. Most (90%) of 146 tea products yielded rbcL or matK barcodes using a standard protocol. Matching DNA identifications to listed ingredients was limited by incomplete databases for the two markers, shared or nearly identical barcodes among some species, and lack of standard common names for plant species. About 1/3 of herbal teas generated DNA identifications not found on labels. Broad scale adoption of plant DNA barcoding may require algorithms that place search results in context of standard plant names and character-based keys for distinguishing closely-related species. Demonstrating the importance of accessible plant barcoding, our findings indicate unlisted ingredients are common in herbal teas.

[In situ and rapid identification of tea by direct analysis in real time mass spectrometry]

By applying an ambient mass spectrometric method--direct analysis in real time mass spectrometry (DART MS), a method was developed for rapid identification of the principal constituents in different kinds of tea. The identification of different kinds of tea was also achieved by characteristic mass spectrometric signals. Under atmospheric pressure, DART MS method does not require any sample preparation, greatly reduces the analysis time, realizes the in situ, rapid, accurate, and high-throughput analysis.

Determination of enantiomeric fractions of cypermethrin and cis-bifenthrin in Chinese teas by GC/ECD

BACKGROUND

The pyrethroids cypermethrin and cis-bifenthrin are the major pesticides used in tea plantations in China. Potential neurotoxic, genotoxic and immunotoxic effects of chronic exposure to pyrethroids have been reported. All synthetic pyrethroids are chiral compounds. There is a need to investigate the chiral transformation among isomers after tea processing in order to obtain an accurate risk assessment of these compounds.

RESULTS

The enantiomeric fraction (EF) of cis-bifenthrin residues was close to 0.5 in all tea samples tested, showing that the levels of (+)-isomer and (-)-isomer were equivalent and there was no preferential degradation. However, the patterns of EFs of cypermethrin residues varied depending on the type of tea. The EF of isomer 1R-3R-alphaS increased in black and dark tea samples (EF = 0.200-0.343) compared with the reference cypermethrin commercial mixture (EF = 0.116). In one oolong tea sample it was found that the relative abundance of some isomers was preferentially enhanced: 1R-3R-alphaS (EF = 0.260), 1S-3S-alphaR (EF = 0.263) and 1R-3S-alphaS/1S-3R-alphaR (the last elution peak, EF = 0.275). The relationship between EF and compound concentration was also analysed, showing that the variation in EFs of cypermethrin was concentration-dependent.

CONCLUSION

These findings appear to be useful for assessing the species-specific risk of exposure to cypermethrin and cis-bifenthrin.

[Polycyclic aromatic hydrocarbons in tea and tea infusions]

Tea is the one of most widely consumed beverage in the world. It is generally believed that tea consumption might have health promoting properties. But residues of certain chemical compounds might impose a health threat on tea drinkers. The main contaminants are heavy metals, fluoride, pesticides and even dioxins. Tea lives which possess a high surface area can be contaminated with atmospheric PAHs. The manufacturing processes may also introduce PAHs into tea lives. The aim of his study was to determine the contamination of black, green, red and white teas by PAHs. In this investigation, content of 23 PAH, i.e 16 EPA PAH and 15 EU PAH were determined in 18 brands of tea and its infusions. The analytical procedure was based on ultrasonic extraction for dried tea and liquid-liquid extraction for infusions. All samples were cleaned up by florisil cartridge. The total content of 23 PAH varied between 22.9 microg/kg to 2945.5 microg/kg and 2.7 microg/kg to 63,1 microg/kg microg/kg for BaP. The analysed tea samples showed an increasing presence of PAH in the following order (mean value): black tea < red tea < green tea < white tea. However the highest content of PAH was found in the one brand of black tea bag both in sum of PAH and BaP content. During tea infusion 1.6% of total PAHs contained in tea was released into the beverage. The dominant PAHs in tea infusion were 2, 3 and 4 rings PAH, while the most toxic compounds were found at trace amounts. The concentrations of total 23 PAHs and BaP in tea infusions ranged from 332.5 ng/dm3 to 2245.9 ng/dm3 and 0.35 ng/dm3 to 18.7 ng/dm3 respectively.

[Identification of tea from different regions using X-ray fluorescence]

The existence of fake tea from non-origin seriously impacts on the credibility of the famous tea. A method was developed to identify tea from difference regions on the basis of the fact that the content of heavy metals in different origin tea is varied by using X-ray fluorescence technique and pattern recognition technique. Samples from different origins were grouped respectively, and their X-ray fluorescence spectra were acquired, and then the principal components of these spectral data were calculated, and the average of the principal components of each group was used as the center of each group. The Mahalanobis distance value between a sample and the center of a group were calculated, when the Mahalanobis distance value reached minimum, the sample was classed to current group, and in this way, a sample was identified. A Niton 792 portable X-ray spectrometer was used to class 120 tea samples from Anji, Jinhua, Hangzhou and Taizhou, in zhejiang province of China. It was found that the spectra between 3 and 13 KeV and the first 4 principal components give enough information for the identification of tea from different regions,and the rate of error was 4.2%.

[Study on discrimination of tea based on color of multispectral image]

Tea is one of the most popular beverages worldwide. Its categories have a great relationship to its beneficial medicinal properties. The present work attempted to study the feasibility to use multispectral imaging technique as a rapid and non-destructive method to discriminate tea varieties. Two categories of tea discriminated hardly by naked eye were sorted. The images were 1 036 pixels vertically by 1 384 pixels horizontally with 24-bit depth, and were captured using a red (R) waveband, near infrared (NIR) waveband and green (G) waveband multispectral digital imager, MS3100 (Duncan Technologies, Inc., CA, USA). The three wavebands of image (Red, Green, NIR) can be composed into one image which contains more information than images recorded by ordinary digital cameras, especially, the NIR image is more sensitive to the color of organic matter than visible spectrum. The three images of one sample can be obtained simultaneously. The color features of tea were calculated using the standard notations: mean and mean square deviation. Then, the two color features of 3CCD and ordinary digital cameras were extracted and calculated by Matlab 7. 3 software respectively, and were contrasted. A total of 60 samples were adopted, and the features of mean and mean square deviation of NIR waveband image were applied as inputs to a back propagation neural network (BP-ANN) with one hidden layer. The forty samples (twenty for each category) were selected randomly to build BP-ANN model, and this model was used to predict the varieties of 20 unknown samples (ten for each category). The two categories of tea can be discriminated by the information of color of images of 3CCD, but can not by the ordinary digital cameras. The result indicted that the discrimination rate of classification set of BP-ANN model was up to 100% within 0.3 of threshold. It concluded that multi-spectral imaging technique has a high potential to identify categories of green tea fast and non-destructively.

Determination of in vitro antidiabetic effects, antioxidant activities and phenol contents of some herbal teas

In this research, some herbal teas and infusions traditionally used in the treatment of diabetes in Turkey, have been studied for their antidiabetic effects on in vitro glucose diffusion and phenolic contents and antioxidant activities. Ten aqueous herbal tea extracts were examined using an in vitro method to determine their effects on glucose movement across the gastrointestinal tract. Total phenol content of herbal teas was analyzed by Folin-Ciocalteu's procedure. Antioxidant activities of herbal teas were evaluated by the effect of extracts on DPPH radical and hydrogen peroxide scavenging. Antioxidant activity was defined as the amount of the sample to decrease the initial DPPH concentration by 50% as efficient concentration, EC50. Antiradical activity [AE] was calculated as 1/EC50. Values were evaluated statistically. Results support the view that none of the herbal teas showed antidiabetic effect on glucose diffusion using in vitro model glucose absorption. Teas were arranged in the order of green tea > peppermint > thyme > black tea > relax tea > absinthium > shrubby blackberry > sage > roselle > olive leaves according to their total phenol contents. Among ten herbal teas, green tea had the highest hydrogen-donating capacity against to DPPH radical. Ranking of the herbal teas with respect to their DPPH radical scavenging activity were green tea > peppermint > black tea > thyme > relax tea > absinthium > roselle > olive leaves > sage > shrubby blackberry. It was determined that adding flavoring substances such as lemon, bergamot, clove and cinnamon, which are commonly used in preparation of black tea in Turkey resulted to have synergistic effect on total antioxidant activities of black and peppermint teas. The highest hydrogen peroxide inhibition value (65.50%) was obtained for green tea at a 250 microl/ml concentration. The H2O2 scavenging activity of herbal teas decreased in the order green tea > peppermint > relax tea > black tea > thyme > olive leaves > sage > absinthium > shrubby blackberry > roselle. In particular, their phenolic compounds and antioxidant activities may be useful for meal planning in type 2 diabetes. They could contribute to sustain plasma antioxidant level because antioxidants present in plants and herbs prevent the development of vascular diseases seen in type 2 diabetes.

Potential exposure and risk of fluoride intakes from tea drinks produced in Taiwan

Tea is the second most commonly consumed drink in the world. Excess fluoride intakes from tea drinks may cause health effects. This work assesses infusible fluoride levels in popular tea sold in Taiwan and evaluates potential exposure factors. Lungjing, pouchong, tienguanyin, oolong, pureh, and black tea specimens were purchased from different counties in Taiwan. Fluoride levels were evaluated in one complete cycle of tea making as well as at different calcium carbonate contents in water, with glass or porcelain teapots, and with/without adding sugar. Oolong tea leaves in each manufacturing step were also analyzed for infusible fluoride. Potential fluoride intakes and risks are estimated based on a national survey. Among six kinds of tea, black tea had the highest fluoride concentrations (8.64+/-2.96 mg/l), whereas pureh (1.97+/-2.70 mg/l) had the lowest levels. Higher percentages of infusible fluoride can be rinsed away from tea leaves curved lengthways compared to those curved end-to-end in the first 2.5 min. The use of glass or porcelain teapots and calcium carbonate content (up to 400 mg/l) in water would not affect infusible fluoride levels, whereas adding sugar increased the infusible fluoride in the first few minutes. In addition, it was found that the critical step during the manufacturing process affecting the percentage of infusible fluoride was ball rolling rather than fermentation. Furthermore, intakes of high amounts (> or =5 l/week) of certain tea may result in excess risks of dental or skeletal fluorosis. Tea lovers could be exposed to excess fluoride and may be at risk of fluorosis.

Differential effects of black versus green tea on risk of Parkinson's disease in the Singapore Chinese Health Study

Data from Asian populations on dietary and lifestyle factors associated with Parkinson's disease are sparse. In 1993-2005, the authors examined these factors in relation to Parkinson's disease in the Singapore Chinese Health Study, a prospective cohort of 63,257 Chinese men and women. Baseline data were collected through in-person interviews using structured questionnaires. All 157 incident Parkinson's disease cases were identified either through follow-up interviews or via linkage with hospital discharge databases and Parkinson's disease outpatient registries and were confirmed by review of medical records. Current versus never smokers exhibited a reduced risk of Parkinson's disease (relative risk = 0.29, 95% confidence interval: 0.16, 0.52). Total caffeine intake was inversely related to Parkinson's disease risk (p for trend = 0.002); the relative risk for the highest versus lowest quartile was 0.55 (95% confidence interval: 0.35, 0.88). Black tea, a caffeine-containing beverage, showed an inverse association with Parkinson's disease risk that was not confounded by total caffeine intake or tobacco smoking (p for trend = 0.0006; adjusted relative risk for the highest vs. lowest tertile of intake = 0.29, 95% confidence interval: 0.13, 0.67). Green tea drinking was unrelated to Parkinson's disease risk. Diet had no strong influence on risk. Ingredients of black tea other than caffeine appear to be responsible for the beverage's inverse association with Parkinson's disease.

Rapid differentiation of tea products by surface desorption atmospheric pressure chemical ionization mass spectrometry

Protonated water molecules generated by an ambient corona discharge were directed to impact tea leaves for desorption/ionization at atmospheric pressure. Thus, a novel method based on surface desorption chemical ionization mass spectrometry (DAPCI-MS) has been developed for rapid analysis of tea products without any sample pretreatment. Under the optimized experimental conditions, DAPCI MS spectra of various tea samples are recorded rapidly, and the resulting mass spectra are chemical fingerprints that characterize the tea samples. On the basis of the mass spectral fingerprints, 40 tea samples including green tea, oolong tea, and jasmine tea were successfully differentiated by principal component analysis (PCA) of the mass spectral raw data. The PCA results were also validated with cluster analysis and supervised PCA analysis. The alteration of signal intensity caused by rough surfaces of tea leaves did not cause failure in the separation of the tea products. The experimental findings show that DAPCI-MS creates ions of both volatile and nonvolatile compounds in tea products at atmospheric pressure, providing a practical and convenient tool for high-throughput differentiation of tea products.

1H NMR based metabolic profiling in the evaluation of Japanese green tea quality

Classification of tea quality is now mainly performed according to the sensory results by professional tea tasters. However, this evaluation method is inconsistent in differentiating their qualities. A combination of a (1)H NMR technique and a multivariate analysis was introduced to the quality evaluation of green tea by means of a metabolomic technique. A broad range of metabolites were detected by (1)H NMR spectrometry. The principal component analysis (PCA) was used to reduce the complexity of the (1)H NMR spectra data set and provided the quality discrimination result. It offered an extensive clue for classification and quality assessment without any prepurification method. A set of green teas from a Japanese tea contest were analyzed by (1)H NMR to classify the quality with respect to that judged by tea tasters and to conceive a quality prediction model. Metabolic profiling and fingerprinting of (1)H NMR spectra of green teas with different quality were studied. PCA showed a separation between the high- and the low-quality green teas. The taste marker compounds contributing to the discrimination of tea quality were identified. Reliable prediction models were obtained by the partial least-squares projection to latent structure (PLS) analysis together with a preprocessing filter of both orthogonal signal correction (OSC) and a combination between OSC and wavelet transform algorithms.

Differentiation of green, white, black, Oolong, and Pu-erh teas according to their free amino acids content

In this paper, the differentiation of green, black, Oolong, white, and Pu-erh teas has been carried out according to their free amino acid contents. Alanine, arginine, asparagine, aspartic acid, glutamic acid, isoleucine, histidine, leucine, phenylalanine, serine, theanine, threonine, and tyrosine have been determined by liquid chromatography with derivatization with o-phthalaldehyde and fluorescence detection. The chromatographic separation was achieved with a Hypersil ODS column and gradient elution. The amino acid contents were used as chemometric descriptors for classification purposes of different tea varieties. Principal component analysis, k-nearest neighbors, linear discriminant analysis, and artificial neural networks were applied to differentiate tea varieties. Using back-propagation multilayer perceptron artificial neural networks, 100% success in the classification was obtained. The most differentiating amino acids were glutamic acid, asparagine, serine, alanine, leucine, and isoleucine.

Reading the tea leaves: anticarcinogenic properties of (-)-epigallocatechin-3-gallate

Green tea is an extremely popular beverage worldwide. Derivatives of green tea, particularly (-)-epigallocatechin-3-gallate (EGCG), have been proposed to have anticarcinogenic properties based on preclinical, observational, and clinical trial data. To summarize, clarify, and extend current knowledge, we conducted a comprehensive search of the PubMed database and other secondary data sources, as appropriate, regarding the chemopreventive potential of EGCG. Apparently, EGCG functions as an antioxidant, preventing oxidative damage in healthy cells, but also as an antiangiogenic agent, preventing tumors from developing a blood supply needed to grow larger. Furthermore, EGCG may stimulate apoptosis in cancerous cells by negatively regulating the cell cycle to prevent continued division. Finally, EGCG exhibits antibacterial activity, which may be implicated in the prevention of gastric cancer. Although in vitro research of the anticarcinogenic properties of EGCG seems promising, many diverse and unknown factors may influence its in vivo activity in animal and human models. Some epidemiological studies suggest that green tea compounds could protect against cancer, but existing data are inconsistent, and limitations in study design hinder full interpretation and generalizability of the published observational findings. Several clinical trials with green tea derivatives are ongoing, and further research should help to clarify the clinical potential of EGCG for chemoprevention and/or chemotherapy applications.

The effect of green, black and white tea on the level of alpha and gamma tocopherols in free radical-induced oxidative damage of human red blood cells

The present study was undertaken to investigate the effect of aqueous tea extracts on lipid peroxidation and alpha and gamma tocopherols concentration in the oxidative damage of human red blood cells (RBC). RBC was taken as the model for study of the oxidative damage was induced by cumene hydroperoxide (cumOOH). The antioxidative property of leaf green tea, leaf and granulate of black tea and white tea at levels 1, 2, 4 g/150 mL of water were evaluated. The correlation was observed between reducing power of tea extract and formation of malondialdehyde--MDA (an indicator of lipid peroxidation) in oxidative damage of RBC. All tea extracts at level of 4 g/150 mL of water significantly decreased concentration of MDA. The extract of green tea in comparison to black and white tea extracts at the same levels seems to be a better protective agent against oxidative stress. The antioxidant synergism between components extracted from leaves of green tea and endogenous alpha tocopherol in the oxidative damage of red blood cells was observed. The consumption of alpha tocopherol in oxidative damage of RBC was the lowest after treatment with the highest dose of green tea extract. All tea extracts did not protect against decrease of gamma tocopherol in human erythrocytes treated with cumOOH.

Prediction of Japanese green tea ranking by gas chromatography/mass spectrometry-based hydrophilic metabolite fingerprinting

An innovative technique for green tea's quality determination was developed by means of metabolomics. Gas-chromatography coupled with time-of-flight mass spectrometry and multivariate data analysis was employed to evaluate the quality of green tea. Alteration of green tea varieties and manufacturing processes effects a variation in green tea metabolites, which leads to a classification of the green tea's grade. Therefore, metabolic fingerprinting of green tea samples of different qualities was studied. A set of ranked green tea samples from a Japanese commercial tea contest was analyzed with the aim of creating a reliable quality-prediction model. Several multivariate algorithms were performed. Among those, the partial least-squares projections to latent structures (PLS) analysis with the spectral filtering technique, orthogonal signal correction (OCS), was found to be the most practical approach. In addition, metabolites that play an important role in green tea's grade classification were identified.

[Determination of elements related to reducing blood sugar (ERBS) in tea and tea polysaccharide by ICP-MS]

Contents of elements related to reducing blood sugar (ERBS) in several kinds of green tea of Wuyuan county, their tea infusion extracted by warm water and boiling water and tea polysaccharide (TP) were determined by ICP-MS, after the samples were digested with acids by microwave method. The relation between the amount of ERBS and tea quality and the relation between the content of ERBS in TP and the total content in tea were discussed. The results showed that the amounts of ERBS in tea and TP are different in various samples. The amount of ERBS in TP extracted from coarse tea was higher than that from fresh tea. The percentage of certain ERBS in TP accounting for the ERBS in tea ranged from 0.03% to 9.57%. As to the total ERBS in TP extracted from Mt. Zhang super grade tea and grade 5 tea, the percentages were 1.11% and 2.10% respectively. As to Mt. Gu old tea, it was 0.85%. The results could provide data for selecting tea material used to extracting tea polysaccharide and for studying the mechanism of reducing blood sugar.

[Study on the identification of tea using near infrared reflectance spectroscopy]

A rapid tea identification method by near infrared spectroscopy coupled with pattern recognition based on principal components analysis and Mahalanobis' distance technique was proposed. Four famous brand teas in China were studied, including Longjing tea, Biluochun tea, Maofeng tea and Tieguanyin tea in the experiment. In the spectral region between 6 500 and 5 300 cm(-1), through preprocessing method of MSC (multiplicative scatter comection), the prediction model was built. The result showed that the model was the best with 8 principal component factors. The rates of identification in calibration set samples and prediction set samples were 98.75% and 95%, respectively. A new idea about quick and precise identification of tea was offered.

Factors affecting transfer of polycyclic aromatic hydrocarbons from made tea to tea infusion

Factors affecting transfer percentages of 12 polycyclic aromatic hydrocarbons (PAHs) were investigated, including tea variety, tea/water ratio (TWR, g/mL), brewing times, washed tea or unwashed tea, and covered cup or uncovered cup. It was observed that %PAH transfer varied with tea variety and increased with the decrease of TWR. The mean %PAH transfer with TWR = 1/150 was 1.12 and 1.65 times higher than that with TWR = 1/100 and 1/50, respectively. %PAH transfer reduced greatly as the brewing times increased. The mean %PAH transfer in the first brewing time occupied 51.6% of the total three mean %PAH transfers in the three brewing times. The mean %PAH transfer decreased by 30.4% after the tea had been washed immediately before brewing. Brewing the tea within uncovered cup diminished %PAH transfer by a degree of 4.31-31.7% compared to brewing the tea within a covered cup.

Qualitative identification of tea categories by near infrared spectroscopy and support vector machine

Near-infrared (NIR) spectroscopy has been successfully utilized for the rapid identification of green, black and Oolong tea. The spectral features of each tea category are reasonably differentiated in the NIR region, and the spectral differences provided enough qualitative spectral information for the identification of tea. Support vector machine (SVM) as the pattern recognition was applied to identify three tea categories in this study. The top five principal components (PCs) were extracted as the input of SVM classifiers by principal component analysis (PCA). The RBF SVM classifiers and the polynomial SVM classifiers were studied comparatively in this experiment. The best experimental results were obtained using the radial basis function (RBF) SVM classifier with sigma=0.5. The accuracies of identification were all more than 90% for three tea categories. Finally, compared with the back propagation artificial neural network (BP-ANN) approach, SVM algorithm showed its excellent generalization for identification results. The overall results show that NIR spectroscopy combined with SVM can be efficiently utilized for rapid and simple identification of the tea categories.

[Determination of nine life elements in brick tea by ICP-AES]

ICP-AES was used for the direct determination of nine life elements (Ca, Mg, K, Al, P, Cu, Zn, Fe and Mn) in brick tea. The RSDs of the method were between 2.11% and 8.68%, and the analytical results of the tea reference samples were consistent with the certified values. The method was simple and accuracy. The analytical results of brick tea were compared with those of the ordinary leaf tea (green tea, scent tea and oolong tea). The Al, Fe, Mn, Ca and Mg contents of brick tea were about 5.78, 3.26, 2.19, 2.11 and 1.64 times higher than those of the ordinary leaf tea respectively. The P, K, Zn and Cu contents of brick tea were 48.70%, 85.68%, 78.19% and 98.78% times lower than those of the ordinary leaf tea respectively.

[The green tea, a good choice for cardiovascular disease prevention?]

Tea (Camellia sinensis) has been used for centuries as a medical drink. Around two-thirds of the world's population drink tea. It is originated from southern China and entensive cultivated in Asia and in central African countries. Tea can be grouped into three main types, black, oolong, and green tea. Green tea is not fermented and is a major beverage consumed in Asian countries. Green tea is produced from freshly harvest leaves of the tea plant and they contain water, proteins, carbohydrates, minerals, vitamins and polyphenols of the flavonoid type. The major flavonoids in green tea are catechins which constitute about one third of its total dry weight. The major catechin present is epigallocatechin gallate (>50%). New data have increased the interest in green tea or its catechins and its role in treatment of cardiovascular disease (CHD) risk factors. The aim of the present paper is to review some studies that have found a relationship between green tea and CHD risk factors. From some of them it can be summarized that of green tea and its catechins consumptions (i) decrease body weight by interfering within the sympathoadrenal system and fatty acid synthesis, (ii) decrease cholesterol absorption and plasma levels, (iii) have strong free radical-scavenging activity inhibiting LDL oxidation, (iv) reduce the adhesion molecule expression, (v) have antitrombotic activities by inhibiting platelet aggregation and (vi) decrease systolic and diastolic blood pressures. The positive effects found suggest that a daily intake of 7 cups of green tea (3.5 g catechins) is a good choose for CHD prevention; however, it is still necessary more studies to check the action of the green tea and its catechins in humans in order to recommended its use in the general population or only in target subjects.

Fluoride content in tea and its relationship with tea quality

The tea plant is known as a fluorine accumulator. Fluoride (F) content in fresh leaves collected from 14 plantations in China was investigated. The F increased with maturity, and the F variation was remarkable in the tender shoots. Furthermore, significant negative relationships were observed between F content and the content of the quality parameters total polyphenols and amino acids. These substances are rich in young leaves and poor in mature ones. With regard to quality of tea products, the relationship with F content was studied using 12 brands of tea products in four categories: green tea, oolong tea, black tea, and jasmine tea collected from six provinces. The F level increased with the decline in quality and showed good correlation with the quality grades. The results suggest that the F content could be used as a quality indicator for tea evaluation.

Ex vivo modulation of chemical-induced mutagenesis by subcellular liver fractions of rats treated with rooibos (Aspalathus linearis) tea, honeybush (Cyclopia intermedia) tea, as well as green and black (Camellia sinensis) teas

Male Fischer rats were given unprocessed (not oxidized) and processed (oxidized) rooibos and honeybush teas as well as green and black teas as a sole source of drinking fluid for 10 weeks, and sub cellular liver fractions were prepared. Cytosolic fractions of rats consuming the unprocessed herbal teas, green and black teas significantly (P < 0.05) protected against 2-acetylaminofluorene (2-AAF)-induced mutagenesis in the Salmonella mutagenicity test with strain TA 98, using Aroclor 1254-induced microsomes. A marginal or no protection was obtained with the processed herbal teas. The mutagenic response of aflatoxin B1 (AFB1) against Salmonella strain TA 100 was significantly (P < 0.05) inhibited by cytosolic fractions from rats treated with processed and unprocessed herbal teas, while no effect was obtained with the green and black teas. Microsomal fractions prepared from livers of rats treated with both the processed and unprocessed rooibos teas and the unprocessed honeybush tea, significantly (P < 0.05) reduced the activation of AFB1 while no protection was observed against 2-AAF-induced mutagenesis. In contrast, microsomal fractions from rats treated with the green, black and unprocessed honeybush teas significantly (P < 0.05) enhanced the mutagenic response of 2-AAF. None of the tea treatments significantly affected the concentration of the microsomal liver cytochrome P450.

The prevalence of tongue lesions in 5150 Turkish dental outpatients

OBJECTIVE

The aim of this study was to assess the prevalence of nine tongue conditions and relate to data obtained about oral hygiene or habits in Turkish dental outpatients.

SUBJECTS

A total of 5150 subjects (2837 women, 2313 men) were included in this study.

RESULTS

Of the 5150 subjects, 2690 subjects were detected as having tongue lesions with a prevalence of 44.2 and 62.0% for women and men, respectively. The difference was found to be statistically significant (P < 0.0001). There was a strong correlation between tongue lesions and increasing age. There was also a strong association between tongue lesions and smoking, black tea drinking, and fair or poor oral hygiene. Hairy and coated tongue was significantly higher in males. Contrary to this, papillary atrophy was more prominent in women.

CONCLUSION

A strong correlation was found between tongue lesions and age, sex, oral hygiene and habits in Turkish dental outpatients. An efficient oral health program such as the elimination of risk habits and attention to cultural practices may improve tongue hygiene.