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.

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 ß-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.

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)-ß-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.

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.

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 (1st 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 (RP ), 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.

The evaluation of the quality of Feng Huang Oolong teas and their modulatory effect on intestinal microbiota of high-fat diet-induced obesity mice model.

The variations in the contents of tea catechins and free amino acids in relation to the quality of Fenghuang Oolong teas (FOT) were determined. It demonstrated that in FOT, which were grown at a high altitude, the contents of methylated estered tea catechins were relatively higher. By human flora-associated (HFA) mice model, the effect of FOT on high-fat diet-induced obesity was investigated by high-throughput sequencing. The shifts in relative abundance of the dominant taxa at the phylum, family and genus levels showed their dramatically effects. A large increase in Bacteroidetes with decrease of Firmicutes was observed after the administration of FOT for 8 weeks. Together, these results suggest that FOT are rich in tea catechins, especially O-methylated tea catechin derivatives, which may be affected by the unique growth environment, and FOT may have prebiotic-like activity and can be used as functional food components in manipulating intestinal microbiota.

Optimization and validation of Folin-Ciocalteu method for the determination of total polyphenol content of Pu-erh tea.

Pu-erh tea is a post-fermented tea that has recently gained popularity worldwide, due to potential health benefits related to the antioxidant activity resulting from its high polyphenolic content. The Folin-Ciocalteu method is a simple, rapid, and inexpensive assay widely applied for the determination of total polyphenol content. Over the past years, it has been subjected to many modifications, often without any systematic optimization or validation. In our study, we sought to optimize the Folin-Ciocalteu method, evaluate quality parameters including linearity, precision and stability, and then apply the optimized model to determine the total polyphenol content of 57 Chinese teas, including green tea, aged and ripened Pu-erh tea. Our optimized Folin-Ciocalteu method reduced analysis time, allowed for the analysis of a large number of samples, to discriminate among the different teas, and to assess the effect of the post-fermentation process on polyphenol content.

Gallic Acid Content in Taiwanese Teas at Different Degrees of Fermentation and Its Antioxidant Activity by Inhibiting PKCδ Activation: In Vitro and in Silico Studies.

Teas can be classified according to their degree of fermentation, which has been reported to affect both the bioactive components in the teas and their antioxidative activity. In this study, four kinds of commercial Taiwanese tea at different degrees of fermentation, which include green (non-fermented), oolong (semi-fermented), black (fully fermented), and Pu-erh (post-fermented) tea, were profiled for catechin levels by using high performance liquid chromatography (HPLC). The result indicated that the gallic acid content in tea was directly proportional to the degree of fermentation in which the lowest and highest gallic acid content were 1.67 and 21.98 mg/g from green and Pu-erh tea, respectively. The antioxidative mechanism of the gallic acid was further determined by in vitro and in silico analyses. In vitro assays included the use of phorbol ester-induced macrophage RAW264.7 cell model for determining the inhibition of reactive oxygen species (ROS) production, and PKCδ and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunit (p47) activations. The results showed that only at a concentration of 5.00 µM could gallic acid significantly (p < 0.05) reduce ROS levels in phorbol ester-activated macrophages. Moreover, protein immunoblotting expressed similar results in which activations of PKCδ and p47 were only significantly (p < 0.05) attenuated by 5.00 µM treatment. Lastly, in silico experiments further revealed that gallic acid could block PKCδ activation by occupying the phorbol ester binding sites of the protein.

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.

Heterozygosities and genetic relationship of tea cultivars revealed by simple sequence repeat markers and implications for breeding and genetic mapping programs.

Genetic maps are essential tools for quantitative trait locus analysis and marker-assisted selection breeding. In order to select parents that are highly heterozygous for genetic mapping, the heterozygosity (HS) of 24 tea cultivars (Camellia sinensis) was analyzed with 72 simple sequence repeat markers. In total, 359 alleles were obtained with an average of 4.99 per marker. The HS varied greatly from 37.5 to 71.0% with an average of 51.3%. On average, tea cultivars from Fujian Province showed a higher level of heterozygosity (59.8%) than those from Zhejiang (48.5%) and Yunnan (44.5%), and the 12 national tea cultivars were generally more heterozygous than the 12 provincial cultivars. Unweighted pair-group analysis using the arithmetic average grouping divided the 24 cultivars into 2 groups that are consistent with the morphological classification. All dual combinations of the 24 cultivars were studied to calculate the percentage of mappable markers when using pseudo-testcross mapping strategy, and results showed that this value also varied greatly from 51.4 to 90.3%. The genetic relationships and HS differences among different cultivars were discussed, and tea cultivars with high HS were recommended as cross parents for genetic mapping programs.

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.

[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.

[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.

Analysis and classification of tea varieties using high-performance liquid chromatography and global retention models.

As a result of their metabolic processes, medicinal plants produce bioactive molecules with significant implications for human health, used directly for treatment or for pharmaceutical development. Chromatographic fingerprints with solvent gradients authenticate and categorise medicinal plants by capturing chemical diversity. This work focuses on optimising tea sample analysis in HPLC, using a model-based approach without requiring standards. Predicting the gradient profile effects on full signals was the basis to identify optimal separation conditions. Global models characterised retention and bandwidth for 14 peaks in the chromatograms across varied elution conditions, facilitating resolution optimisation of 63 peaks, covering 99.95 % of total peak area. The identified optimal gradient was applied to classify 40 samples representing six tea varieties. Matrices of baseline-corrected signals, elution bands, and band ratios, were evaluated to select the best dataset. Principal Component Analysis (PCA), k-means clustering, and Partial Least Squares-Discriminant Analysis (PLS-DA) assessed classification feasibility. Classification limitations were found reasonable due to tea processing complexities, involving drying and fermentation influenced by environmental conditions.

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.