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BACKGROUND Keemun black tea (KBT) is one of the most popular tea beverages in China as a result of its unique flavor and potential health benefits. The geographical origin of KBT influences its quality and price. The present study aimed to apply a head‐space solid phase microextraction approach and gas chromatography–mass spectrometry combined with chemometric analysis to profile the volatile compounds of KBT collected from five production areas. RESULTS: Thirty‐one peaks were detected in 61 KBT samples. Hierarchical cluster analysis, principal component analysis (PCA), k‐nearest neighbor (k‐NN) and stepwise linear discriminant analysis (SLDA) were employed to visualize the volatile fractions. The results of unsupervised statistical tools were compared using a test for similarities and distinctions, which showed that different sources may be associated. A satisfying combination of average recognition (91.7%) and cross‐validation prediction abilities (84.6%) was obtained for the PCA–k‐NN. Among all of the statistical tools, SLDA provided promising results, with 100% recognition and 96.4% prediction ability. CONCLUSION: The results obtained in the present study indicate that the volatile compounds can be used as indicators to identify the geographical origin of KBT. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

BACKGROUND Theabrownins ( TB) are bioactive components that are usually extracted from Chinese dark tea, in which they are present at low concentrations. The present study aimed to produce an instant dark tea high in theabrownins via submerged fermentation by the fungus Aspergillus niger. Three fermentation parameters that affect theabrownins content (i.e. inoculum size, liquid-solid ratio and rotation speed) were optimized using response surface methodology. RESULT Optimum fermentation conditions were modeled to be an inoculum of 5.40% (v/v), a liquid-solid ratio of 27.45 mL g−1 and a rotation speed of 184 rpm and were predicted to yield 292.99 g kg−1 TB. Under these experimentally conditions, the TB content of the instant dark tea was 291.93 g kg−1. The antioxidant capacity and α-glucosidase and pancreatic lipase inhibitory activities of the high- TB instant black tea were higher than four other typical instant dark tea products. CONCLUSION The results of the present study show that careful management of culture conditions can produce a dark tea high in theabrownins. Furthermore, high-theabrownins instant dark tea could serve as a source of bioactive products and be used in functional foods as an ingredient imparting antioxidant properties and the ability to inhibit pancreatic lipase and α-glucosidase. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Tea quality is often evaluated by experienced tea tasters; however, their assessments are subjective, being influenced by their individual physiological and psychological condition. Herein, we fabricated a colorimetric sensor array-based artificial olfactory system for sensing the quality of Chinese green tea. First, the colorimetric sensors array was man-made using printing 12 chemically responsive dyes (9 porphyrins, metalloporphyrins and 3 pH indicators) on silica-gel flat plate. The plate was exposed to volatile organic compounds, and the colour changes in each sample were obtained by distinguishing between the images of sensor array before and after contact with tea sample. The values of colour composition changes were extracted from the dyes’ colour sections. Multivariate calibrations were applied through principal component analysis and back propagation artificial neural network (BP-ANN) for modelling. The optimum BP-ANN model was obtained with nine principal components, and the discrimination rate was equal to 85% and 86% in the calibration and prediction sets, respectively. We thus conclude that the low cost colorimetric sensor array-based artificial olfactory technique has great potential for application in intelligent evaluation of the quality of green tea. [ABSTRACT FROM AUTHOR]

A total 206 samples of green, yellow, white, black, and Oolong teas were utilized to acquire hyperspectral imaging, and five tea categories were identified based on visible and near-infrared (NIR) hyperspectral imaging, combined with classification pattern recognition. The characteristic spectra were extracted from the region of interest (ROI), and the standard normal variate (SNV) method was preprocessed to reduce background noise. Four dominant wavelengths (589, 635, 670, and 783 nm) were selected by principal component analysis (PCA) as spectral features. Textural features were extracted by the Grey-level co-occurrence matrix (GLCM) from images at selected dominant wavelengths. Linear discriminant analysis (LDA), library support vector machine (Lib-SVM), and extreme learning machine (ELM) classification models were established based on full spectra, spectral features, textural features, and data fusion, respectively. Lib-SVM was the best model with the input data fusion, and the correct classification rate (CCR) achieved 98.39%. The results implied that visible and NIR hyperspectral imaging combined with Lib-SVM has the capability of rapidly and non-destructively classifying tea categories. [ABSTRACT FROM AUTHOR]

• A productive equipment for sorting famous tea raw materials was designed. • The sorting scheme consists of classification, control and process scheme. • Higher grades of fresh tea leaves have a longer horizontal throwing trajectory. • The sorting effect of high-grade raw material is better under the optimal parameters. • Improving the classification performance of the model using genetic algorithms. Famous tea is a pillar of China's tea industry and must be processed using fresh leaves of consistent tenderness and size. However, equipment with high accuracy and efficiency are unavailable for sorting fresh tea leaves (FTLs). Therefore, in this study, we designed a machine-vision platform for sorting FTLs. This platform subjects FTLs to a horizontal tossing motion and change trajectory by blowing air, thereby achieving the sorting of different types of FTLs. The overall sorting scheme consists of classification scheme, control scheme, and process scheme. We found that different types of FTLs have different flight trajectories when subjected to horizontal tossing. And have different optimal classification features and sorting parameters. When sorting high-grade FTLs (low-grade FTLs), the classification feature used is area and mean saturation (equivalent diameter, major-axis length and G variance), the designed platform achieved a recognition rate, purity, selection rate, and integrity rate of 100% (98.5%), 94.32% (87.47%), 91.67% (90.67%), and 100% (100%), respectively. Under optimal parameters, the production efficiency of the platform reached 25 kg/h. Overall, the results of this study indicate that the designed platform can meet the small-scale production requirements for famous tea. [ABSTRACT FROM AUTHOR]

• Accumulation of specific phenolic compounds in Siqiu and Gujing tea leaves. • Deficient promoter of F3′5′H leads to low accumulation of trihydroxy flavonoids. • Proanthocyanidins and galloylquinic acid is correlated to astringency intensity. Wild tea plants, which are classified into different species in the section Thea of the genus Camellia , are widely distributed in southern China. Tea produced from these plants has a unique flavor, which is different from that of tea produced from tea cultivars. In this study, we performed a comparative analysis of morphology, phylogenetic relationships, and phenolic compound metabolism between two wild tea plants (Gujing and Siqiu) and a tea cultivar (Shuchazao). Siqiu and Gujing tea plants had similar morphological traits and could be phylogenetically classified into a same cluster, which was entirely separate from the cluster containing widely cultivated cultivars such as Camellia sinensis cv. Shuchazao. Combined metabolomic and transcriptome analyses revealed that UGT84a22 was highly expressed in Gujing leaves compared with Shuchazao and Siqiu leaves, which may lead to the high accumulation of galloylquinic acid in Gujing leaves. A 14-bp deletion spanning the −765–(−7 5 1) range in the F3′5′H promoter potentially led to low F3′5′H expression levels in Siqiu and Gujing tea plants, which severely disrupted the accumulation of trihydroxy flavonoids in Gujing and Siqiu tea leaves. The high astringency intensity in Gujing tea could be due to the high accumulation of proanthocyanidins and galloylquinic acid. The results of the present study may improve our understanding of the metabolic characteristics of each evolutionary group of species or varieties in the section Thea of the genus Camellia. [ABSTRACT FROM AUTHOR]

The evaluation of tea quality tended to be subjective and empirical by human panel tests currently. A convenient analytical approach without human involvement was developed for the quality assessment of tea with great significance. In this study, near-infrared hyperspectral imaging (HSI) combined with multiple decision tree methods was utilized as an objective analysis tool for delineating black tea quality and rank. Data fusion that integrated texture features based on gray-level co-occurrence matrix (GLCM) and short-wave near-infrared spectral features were as the target characteristic information for modeling. Three different types of supervised decision tree algorithms (fine tree, medium tree, and coarse tree) were proposed for the comparison of the modeling effect. The results indicated that the performance of models was enhanced by the multiple perception feature fusion. The fine tree model based on data fusion obtained the best predictive performance, and the correct classification rate (CCR) of evaluating black tea quality was 93.13% in the prediction process. This work demonstrated that HSI coupled with intelligence algorithms as a rapid and effective strategy could be successfully applied to accurately identify the rank quality of black tea., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)