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.

Region identification of Xinyang Maojian tea using UHPLC-Q-TOF/MS-based metabolomics coupled with multivariate statistical analyses.

Xinyang Maojian tea is a kind of famous roasted green tea produced in the middle of China. Ultra-high performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-Q-TOF/MS)-based metabolomics coupled with multivariate statistical analyses, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were carried out in XMMJTs collected from Luoshan, Shangcheng, and Shihe Counties, respectively. Additionally, seven catechins, four flavonoids, two purine alkaloids, and gallic acid contents were determined by HPLC. Differential metabolites were selected by p-value <0.05, and fold change >1.50 or < 0.66 among 745 detected metabolites in metabolomics analysis. The results showed significant (p < 0.05) differences of three catechins including (-)-epicatechin, (-)-epicatechin gallate, and (-)-gallocatechin gallate, four flavonoids (i.e. quercetin, kaempferol, myricetin, and rutin), and theobromine among three various regions, and significant (p < 0.05) differences of (-)-epicatechin gallate, (-)-epigallocatechin, (+)-catechin, gallic acid, and kaempferol between Shuchazao and Group cultivar. The HCA showed that, except for two samples (i.e. LS 2 and SH 2) of Shuchazao cultivar clustered together, others could be clustered completely according to production place. The 63 relevant differential metabolites could achieve the purpose of region identification through PCA. Kyoto encyclopedia of genes and genomes (KEGG) metabolic pathway analysis elaborated the impact of geographical origin and tea cultivar on physiological metabolism in tea tree. PRACTICAL APPLICATION: Ultra-high performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-Q-TOF/MS)-based liquid chromatography-tendem mass spectrometry (LC-MS/MS) metabolomics coupled with multivariate statistical analyses, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), revealed 63 differential metabolites related to production place, which contributed to the region identification of Xinyang Maojian teas.

Differentiating Pu-erh raw tea from different geographical origins by 1 H-NMR and U-HPLC/Q-TOF-MS combined with chemometrics.

Pu-erh tea is believed to be a beneficial beverage for health due to its many kinds of pharmacological effects. Nevertheless, detailed information related to differences in metabolites of Pu-erh raw tea from different geographical origins remains scarce. In this study, 43 elements were found in water-soluble components of Pu-erh raw tea by highly sensitive ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (U-HPLC/Q-TOF-MS). The characteristic groups of 29 metabolites from nondestructive proton nuclear magnetic resonance (1 H-NMR) spectroscopy were assigned. The variables contributed largely to the origin classification, mainly including valine, threonine, chlorogenic acid, quinic acid, epiafzelechin, and gallic acid ester, were screened out by sparse partial least squares discriminant analysis (sPLS-DA) method. This study provided a feasible and rapid technique for distinguishing Pu-erh tea from different areas by 1 H-NMR combined with sPLS-DA.

Anti-obesity effect of Liupao tea extract by modulating lipid metabolism and oxidative stress in high-fat-diet-induced obese mice.

Liupao tea (LPT) is traditional dark Chinese tea. The effect of LPT extract on high-fat-diet-induced obese mice was investigated systematically. The results showed that LPT extract could reduce body weight and significantly alleviate liver damage and fat accumulation. LPT could also decrease the levels of alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (AKP), total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) and increase the level of high-density lipoprotein cholesterol (HDL-C) in the liver. It also decreased the serum levels of inflammatory cytokines, including tumor necrosis factor alpha (TNF-α), interferon gamma (IFN-γ), interleukin (IL)-1ß, and IL-6 and increased the serum levels of anti-inflammatory cytokines, including IL-10 and IL-4. Moreover, LPT improved the levels of total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) and reduced the level of malondialdehyde (MDA) in the liver. Moreover, LPT could upregulate the mRNA and protein expressions of peroxisome proliferator-activated receptor alpha (PPAR-α), lipoprotein lipase (LPL), carnitine palmitoyltransferase 1(CPT1), and cholesterol 7 alpha-hydroxylase (CYP7A1) and downregulate those of PPAR-γ and CCAAT/enhancer-binding protein alpha (C/EBP-α) in the liver. It also increased the mRNA expression of copper/zinc superoxide dismutase (SOD1), manganese superoxide dismutase (SOD2), CAT, gamma-glutamylcysteine synthetase 1 (GSH1), and GSH-Px. The components of LPT extract include catechin, rutin, taxifolin, and astragalin, which possibly have a wide range of biological activities. In conclusion, our work verified that LPT extract possessed an anti-obesity effect and alleviated obesity-related symptoms, including lipid metabolism disorder, chronic low-grade inflammation, and liver damage, by modulating lipid metabolism and oxidative stress.

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.

Mixtures of Tea and Citrus maxima (pomelo) Alleviate Lipid Deposition in HepG2 Cells Through the AMPK/ACC Signaling Pathway.

Tea and citrus maxima are natural, medicinal homologous plants, typically used for making beverages, which have anticancer, antiobesity, and antioxidation properties. Green tea, yellow tea, and black tea were combined with citrus maxima to obtain green tea and Citrus maxima (GTCM), yellow tea and Citrus maxima (YTCM), and black tea and Citrus maxima (BTCM). The biochemical components of these mixtures were analyzed, and their possible effects and mechanisms on relieving liver lipid deposition were explored. The tea polyphenols, free amino acids, phenolamine ratio, and caffeine were comparable in YTCM and GTCM, being significantly higher than those in BTCM. In addition, the content of esterified catechins, nonesterified catechins, and total catechins in YTCM was significantly higher than those in GTCM and BTCM. All three mixtures of Citrus maxima tea significantly reduced lipid deposition in HepG2 cells, with GTCM and YTCM being slightly more effective than BTCM. Regarding the possible mechanism, Western blot analysis revealed that the three Citrus maxima tea mixtures could activate the AMPK/ACC signaling pathway, upregulate the expression of p-AMPK, p-ACC, and CPT-1 proteins, and downregulate the expression of SREBP1c and fatty acid synthase proteins to inhibit fat synthesis, thereby relieving lipid deposition in liver cells. In conclusion, as a novel and healthy beverage, Citrus maxima tea has the potential to alleviate liver lipid deposition, and further could be responsible for obesity treatment.

The effects of regular consumption of green or black tea beverage on blood pressure in those with elevated blood pressure or hypertension: A systematic review and meta-analysis.

OBJECTIVE: As a popular beverage, there has been much interest in studying the effects of tea intake on hypertension (HTN), a particular risk factor for cardiovascular disorders (CVDs). We have thus aimed to isolate the randomized controlled trials investigating the efficacy of black or green tea as a beverage in subjects with elevated blood pressure (BP), or HTN. METHODS: PubMed, Scopus, Web of Science, and ProQuest dissertations and theses databases were searched from February 1, 1995, up to July 20, 2019, to identify relevant studies. RESULTS: The search strategy generated 1119 trials, of which finally five trials fulfilled the criteria for being included in the current study. Three out of 5 articles showed a low risk of bias. According to nine measurements derived from 5 trials on 408 individuals, it was found that regular tea intake resulted in the reduction in SBP (weighted mean difference (WMD): -4.81 mmHg, 95 %CI: -8.40 to -1.58, P = .004) and DBP (WMD:-1.98 mmHg, 95 %CI: -3.77 to -0.20, P = .029); however, excluding the most heterogeneous trials showed that regular tea intake might reduce SBP and DBP by about -3.53 and -0.99 mmHg, respectively. Based on meta-regression findings, we found the longer the duration of tea intake (≥3months), the higher the decrease in both SBP and DBP. Categorized studies, according to the tea type, revealed that the hypotensive effects of green tea were more pronounced compared to black tea. None of the studies reported any side effects. CONCLUSION: These results suggest the positive effects of regular tea intake on BP in subjects with elevated BP or HTN. Hence, it may be applicable to physicians, health care providers, and particularly HTN patients.

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 (Rp) 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.

Gas chromatographic Analysis of Organic Acids in Japanese Green Tea Leaves.

Herein, gas chromatography is used to determine and quantify organic acids in Japanese green tea leaves, and the established method is employed to profile the acid components of Matcha, Gyokuro, Sencha green teas, and green tea varieties and thus acquire data needed to ensure the high quality and safety of green tea. The tea leaves were esterified with 10 vol% sulfuric acid in 1-butanol at 100℃ for 2 h. Oxalic acid contents were high in Asatsuyu and Okuyutaka samples and were low in Sofu, increasing in the order of Sencha < Gyokuro < Matcha, while citric acid content increased in the order of Sencha < Matcha < Gyokuro. Moreover, the oxalic acid content of Gyokuro only slightly increased with increasing tea grade. The relative contents of the different fatty acids did not strongly vary between the different green tea varieties. However, the n-3 to n-6 ratio was found to be low in Sofu. The progressing maturity increased the n-3 to n-6 ratio of Yabukita. The n-3 to n-6 ratio was low in high-grade Matcha, Gyokuro, Sencha green teas, and was related to the green tea quality. The developed method was concluded to be suitable for the evaluation of green tea quality.

Study of enrichment difference of 64 elements among white tea subtypes and tea leaves of different maturity using inductively coupled plasma mass spectrometry.

A microwave digestion-inductively coupled plasma mass spectrometry (ICP-MS)-based analytical method for 64 elements in white tea was developed. The determination coefficient R2 were ranged from 0.9970 to 1.0000 in 3 orders of magnitude for the 64 detected elements, and the limits of detection (LODs) of the method were from 0.0004 to 35.906 ng/mL. The stability of the method was monitored by quality control samples (QCs) and the accuracy was validated by certified reference material. Application of this method in 3 white tea subtypes showed that most of 54 elements that above LODs (Al, Pb, Cd, Hg, As, rare earth elements, and etc.) displaying gradually increasing trend in subtypes of Baihaoyinzhen, Baimudan, and Shoumei which are manufactured from tea leaves of increasing maturity, while few elements (Zn, P and Ni) decreased. Then, a further application of this method in fresh samples of the bud and the 1st, 2nd, 3rd, 4th, and 5th leaf confirmed that more mature tea leaf has higher enrichment efficiency for most elements. In conclusion, a comprehensive microwave digestion-ICP-MS-based analytical method was established and applied in the content measurements of 64 elements in 3 white tea subtypes and fresh tea leaves of different maturity, and it demonstrated that more mature tea leaf has higher enrichment efficiency for most elements.

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.

Characterization of three different classes of non-fermented teas using untargeted metabolomics.

Non-fermented teas, which are widely consumed in China, Japan, Korea, and elsewhere, have refreshing flavors and valuable health benefits. Various types of non-fermented teas look and taste similar and have no obvious differences in appearance, making their classification challenging. To date, there are very few reports about characterization and discrimination of different types of non-fermented teas. To characterize non-fermented teas and build a standard model for their classification based on their chemical composition, we employed multi-platform-based metabolomics to analyze primary and secondary metabolites in three main categories of non-fermented teas (green, yellow, and white), using 96 samples collected from China. Five hundred and ninety unique tea metabolites were identified and quantified in these three types of teas. Moreover, a partial least squares discriminant analysis (PLS-DA) model was established based on metabolomics data, in order to classify non-fermented teas into these three classes. Furthermore, our results speculate that the health benefits (e.g., antioxidant content) of these three types of non-fermented tea differ primarily because of variation in their metabolic components (e.g., ascorbate, vitexin).

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.

Lexicon development and quantitative descriptive analysis of Hunan fuzhuan brick tea infusion.

Twenty-seven representative Hunan fuzhuan brick teas were collected to develop a terminology lexicon and a quantitative descriptive analysis (QDA) method suitable for the sensory evaluation of Hunan fuzhuan brick tea infusion. Ten trained panelists developed a terminology lexicon comprised of eleven aroma and six taste attributes and evaluated the intensities of sensory attributes of each sample by conducting the QDA method. The QDA results showed that seventeen attributes listed in the final lexicon can be used to evaluate the quality of Hunan fuzhuan brick tea infusion properly, among which five aroma attributes, overall aroma, smoky, floral, fermented, and sweet (fruit), and one taste attribute, bitter, were the characteristic attributes to distinguish the differences in the sample qualities. Another panel made up of four professional cuppers evaluated samples by the cupping method to analyze the applicability and accuracy of the lexicon and the QDA method. The results showed that both the cupping method and QDA can be effectively used to evaluate Hunan fuzhuan brick tea quality, and their evaluation results showed high consistency and mutual complementation. This information will be beneficial for developing a sensory evaluation method and quality control for Hunan fuzhuan brick tea.

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.

Non-targeted metabolomics reveals distinct chemical compositions among different grades of Bai Mudan white tea.

So far, the chemical quality of different grades of white tea has largely remained unexplored. The objective of this study was to establish a model for quality evaluation of different grades of Bai Mudan white tea. We applied non-targeted ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry in combination with multivariate analysis and analyzed four different grades of Bai Mudan white tea. We found that the metabolite composition from the super-grade and the first-grade shared higher similarity compared to the second-grade or the third-grade white tea, and the Partial Least Square-Discriminant Analysis model showed high capability to explain the sample variation (R2Y = 0.998, Q2 = 0.95 in negative ionization modes). In total, 93 metabolites were structurally identified, wherein 21 low abundant metabolites showed distinct changes in abundance that were closely correlated with tea grade variation. These findings suggested their potential as markers to discriminate different grades of Bai Mudan white tea.

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.