Objective evaluation methods for the bitter and astringent taste intensities of black and oolong teas by a taste sensor

Caffeine weakens the astringency of epigallocatechin gallate by inhibiting its interaction with salivary proteins

The astringency of green tea is an integrated result of the synergic and antagonistic effects of individual tea components, whose mechanism is highly complex and not completely understood. Herein, we used an epigallocatechin gallate (EGCG)/caffeine (CAF)/saliva model to simulate the oral conditions during tea drinking. The effect of CAF on the interaction between EGCG and salivary proteins was first investigated using molecular docking and isothermal titration calorimetry (ITC). Then, the rheological properties and the micro-network structure of saliva were studied to relate the molecular interactions and perceived astringency. The results revealed that CAF partially occupied the binding sites of EGCG to salivary proteins, inhibiting their interaction and causing changes in the elastic network structure of the salivary film, thereby reducing astringency.

Green preparation, safety control and intelligent processing of high-quality tea extract

Tea contains a variety of bioactive components, including catechins, amino acids, tea pigments, caffeine and tea polysaccharides, which exhibit multiple biological activities. These functional components in tea provide a variety of unique flavors, such as bitterness, astringency, sourness, sweetness and umami, which meet the demand of people for natural plant drinks with health benefits and pleasant flavor. Meanwhile, the traditional process of tea plantation, manufacturing and circulation are often accompanied by the safety problems of pesticide residue, heavy metal, organic solvents and other exogenous risks. High-quality tea extract refers to the special tea extract obtained by enriching the specific components of tea. Through green and efficient extraction technologies, diversed high-quality tea extracts such as high-fragrance and high-amino acid tea extracts, low-caffeine and high-catechin tea extracts, high-bioavailability and high-theaflavin tea extracts, high-antioxidant and high-tea polysaccharide tea extracts, high-umami-taste and low-bitter and astringent taste tea extracts are produced. Furthermore, rapid detection, green control and intelligent processing are applied to monitor the quality of tea in real-time, which guarantee the stability and safety of high-quality tea extracts with enhanced efficiency. These emerging technologies will realize the functionalization and specialization of high-quality tea extracts, and promote the sustainable development of tea industry.

Investigation of the effect of over-fired drying on the taste and aroma of Lu'an Guapian tea using metabolomics and sensory histology techniques

Lu'an Guapian (LAGP) tea, a representative Chinese roasted green tea, undergoes significant changes in taste and aroma during over-fired drying. However, limited studies have been conducted on these effects. This study employed metabolomics and sensory histology techniques to analyze non-volatile and volatile compounds the second drying and pulley liquefied gas drying (PLD) samples. The results revealed that after PLD, the samples exhibited lower umami, bitterness, and astringency; whereas floral, sweet, roasted, cooked corn-like, and cooked chestnut-like aromas became stronger. Among them, the content of (-)-epigallocatechin gallate, glutamic acid, and theogallin, which were closely related to taste, decreased by 4.5 %, 12.3 %, and 10.4 %, respectively. Eight key aroma components were identified as the main contributors to the sample aroma changes: (E)-β-ionone, dimethyl sulfide, (E,E)-2,4-heptadienal, geraniol, linalool, benzeneacetaldehyde, 2-ethyl-3,5-dimethylpyrazine, and hexanal. This study provides a theoretical basis for enhancing the quality of LAGP teas.

Aquafeed fermentation improves dietary nutritional quality and benefits feeding behavior, meat flavor, and intestinal microbiota of Chinese mitten crab (Eriocheir sinensis)

Normally, proper fermentation can be an efficient and widely used method to improve feed quality in animal rearing; however, the studies on crustaceans, especially Eriocheir sinensis, remain limited. This study aimed to investigate whether feed fermentation could meliorate dietary nutritional value and benefit E. sinensis rearing. First, non-fermented feed (NFD) and fermented feed (FD) were produced and assessed, respectively. Then, the "Y" maze feed choice behavior test (180 times; 30 times, 6 rounds) was conducted to assess the attractiveness of these 2 feeds for crabs. Finally, a total of 80 crabs (44.10 ± 0.80 g) were randomly assigned into 2 groups with 4 replicates, and fed the experimental diets for 8 weeks to evaluate the effects of each feed on growth, antioxidant capacity, meat flavor, and intestinal microbiota. In this study, FD showed higher levels of crude protein (P < 0.01), soluble protein (P < 0.01), amino acids (P < 0.05), lactic acid (P < 0.001), and lower levels of crude fiber (P < 0.05) and antinutritional factors (agglutinin, trypsin inhibitor, glycinin, and β-conglycinin) (P < 0.001) than NFD. Additionally, FD was more attractive to crabs than NFD (P < 0.01) and it stimulated the appetite of crabs more than NFD (P < 0.05). The growth performance, feed efficiency, and digestive enzyme activity of FD-fed crabs were significantly higher than those of NFD-fed crabs (P < 0.05). The electronic sensory measurements and free amino acid profiles revealed that the FD diet had positive impacts on the meat flavor of crabs, particularly in "sweet" and "umami" tastes. Moreover, the antioxidant capacity of FD-fed crabs was significantly higher than that of NFD-fed crabs (P < 0.05). Fermented feed also affected the diversity and composition of intestinal microflora. The functional prediction of microbial communities showed that crabs fed FD had a better microecological environment in the intestine. In conclusion, the fermentation of aquafeed could be an effective approach to enhance feed quality and therefore benefit E. sinensis rearing.

Standardization of strawberry sourness and sweetness intensities using a taste sensor system and an invariant taste standard solution

Taste is an essential factor for evaluating the quality of agricultural products. However, it is usually difficult to compare data acquired at different times or by different people because there is no invariant reference and because the evaluation methods are largely subjective. Here, we addressed these problems by developing a method for standardizing strawberry sourness and sweetness intensities using a taste sensor approach with a taste standard solution composed of sour and sweet compounds. This standard solution allows highly efficient sensor measurements because it contains the standard compounds citric acid and sucrose. In addition, we found that polyphenol destabilized the sensor response for strawberry sweetness, and its removal from the sample by appropriate treatment with polyvinylpolypyrrolidone allowed stable evaluation of the sweetness intensity. The taste sensor data obtained using this method were in good agreement with the chemical analysis values related to human sensory evaluation.

Detection of catechins using a fluorescent molecule and its application toward the evaluation of astringent intensity

It is possible to estimate astringent intensities of catechin solutions based on changes in the intensity of fluorescence emission.

Evaluation of black tea by using smartphone imaging coupled with micro-near-infrared spectrometer

Tea quality is generally assessed through panel sensory evaluation, which requires elaborate sample preparation steps. Here, a novel and low-cost evaluation method of using smartphone imaging coupled with micro-near-infrared (NIR) spectrometer based on digital light processing is proposed to classify the quality grades of Keemun black tea. RGB color information was obtained by Image J software, eight texture characteristics, including scheme, contrast, dissimilarity, entropy, correlation, second moment and variance, and homogeneity were obtained by ENVI software based on co - occurrence method from smartphone images, and spectral data were preprocessed with standard normal variate. A principal component analysis (PCA)-support vector machine (SVM) model was established to analyze the color, texture, and spectral data. Low-level and middle-level fusion strategies were introduced for analyzing the fusion data. The results indicated that the accuracy of the SVM model on mid-level data fusion (100.00%, 94.29% for calibration set and prediction set, respectively) was higher than that obtained for separate color (97.14%, 88.57%), texture (84.29%, 60%), spectrum (74.29%, 68.57%) evaluation, or low-level data fusion (88.57%, 82.86%). The best SVM model yielded satisfactory performance with 94.29% accuracy for the prediction sets. These results suggested that smartphone imaging coupled with micro-NIR spectroscopy is an effective and low-cost tool for evaluating tea quality.

Quantification of Pharmaceutical Bitterness Using a Membrane Electrode Based on a Hydrophobic Tetrakis [3,5-Bis (trifluoromethyl) phenyl] Borate

Technologies for quantifying bitterness are essential for classifying medicines. As previously reported, taste sensors with lipid polymer membranes can respond to bitter hydrochloride substances in pharmaceuticals. However, the acid hydrolysis reaction between the lipid phosphoric acid di-n-decyl ester (PADE) and the plasticizer tributyl o-acetylcitrate (TDAB) led to a deterioration in sensor responses during storage. Given the cost of transportation and preservation for commercialization, membrane components that maintain physical and chemical stability during long-term storage are needed. Here we present a membrane electrode based on hydrophobic tetrakis [3,5-bis (trifluoromethyl) phenyl] borate (TFPB) and a plasticizer 2-nitrophenyl octyl ether (NPOE) for the quantification of pharmaceutical bitterness; they maintain a stable response before and after accelerated deterioration, as well as high selectivity and sensitivity. It is a first attempt to use a completely dissociative substance to replace non-completely dissociative lipids. Our work offsets the long-term stability issue of a bitterness sensor with a negatively charged hydrophobic membrane. Meanwhile, we provide the opportunity to select surface charge modifiers for a membrane surface using ester plasticizers containing oppositely charged impurities.

Standardization of tomato juice tastes using a taste sensor approach

To enable the taste evaluation of many food samples at a time as well as the comparison of taste evaluation data acquired at different times, a standardization method for taste intensities was developed by a combination of a taste sensor system and a standard solution prepared with taste substances. In the case of tomato juices, citric acid, sucrose, and monosodium glutamate were used as standard taste substances for sourness, sweetness, and umami taste, respectively. Each standard point of the taste intensities was determined using only one standard solution including these standard substances. The taste intensity was described as a value on a scale based on discrimination thresholds of human gustation, where intensities of sourness, sweetness, and umami taste of the tomato juices were classified into multiple levels. Organoleptic evaluation supported these results. Validation for the present standardization method revealed that this approach has enough precision for practical tomato taste evaluation.

Taste Sensor: Electronic Tongue with Lipid Membranes

Taste is of five basic types, namely, sourness, saltiness, sweetness, bitterness and umami. In this review, we focus on a potentiometric taste sensor that we developed and fabricated using lipid polymer membranes. The taste sensor can measure the taste perceived by humans and is called an electronic tongue with global selectivity, which is the property to discriminate taste qualities and quantify them without discriminating each chemical substance. This property is similar to the gustatory system; hence, the taste sensor is a type of biomimetic device. In this paper, we first explain the sensing mechanism of the taste sensor, its application to beer evaluation and the measurement mechanism. Second, results recently obtained are introduced; i.e., the application of the senor to high-potency sweeteners and the improvement of the bitterness sensor are explained. Last, quantification of the bitterness-masking effect of high-potency sweeteners is explained using a regression analysis based on both the outputs of bitterness and sweetness sensors. The taste sensor provides a biomimetic method different from conventional analytical methods.

Interaction of polyphenols with model membranes: Putative implications to mouthfeel perception

Food polyphenols in fruits juices, tea, coffee, wine and beer confer sensory properties such as colour, astringency and bitterness. The development of functional healthy drinks without the unpleasant sensory feeling is boosting research for a clearer understanding on the interactions of polyphenols within the oral mucosa. In this study we investigated the interaction of astringent polyphenols, namely ECG, EGCG, procyanidin B4 and PGG, with lipids in model membranes by spectroscopic techniques. The membrane model was built varying the cholesterol content to mimic mouth regions and experiments were conducted at pH 5 to mimic the pH drop at the moment of beverage (e.g. green tea, red wine) intake. Fluorescence quenching results conducted on LUVs with cholesterol molar fractions ranging between 0.34 < χ_chol < 0.74 and similar size distributions (122.9 ± 3.7 nm) showed that interaction of polyphenols is structure- and concentration-dependent. Also, the decrease of partition constants (K_p) with increasing cholesterol content (χchol) suggest that the affinity of polyphenols is weaker in cholesterol-rich liposomes. STD results revealed that the interaction of EGCG and PGG with membrane lipids involved mainly galloyl residues. Overall, spectroscopic data show that polyphenols interact to higher extent with more polar regions found in buccal, flour of the mouth and gingiva regions than with more hydrophobic regions located in the palate and tongue supporting that lipid microenvironments play a role in oral sensory perception.

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.

Detection of bitterness and astringency of green tea with different taste by electronic nose and tongue

An electronic nose was used to evaluate the bitterness and astringency of green tea, and the possible application of the sensor was assessed for the evaluation of different tasting green tea samples. Three different grades of green tea were measured with the electronic nose and electronic tongue. The sensor array of the E-nose was optimized by correlation analysis. The relationship between the signal of the optimized sensor array and the bitterness and astringency of green tea was developed using multiple linear regression (MLR), partial least squares regression (PLSR), and back propagation neural network (BPNN). BPNN is a multilayer feedforward neural network trained by an error propagation algorithm. The results showed that the BPNN model possessed good ability to predict the bitterness and astringency of green tea, with high correlation coefficients (R = 0.98 for bitterness and R = 0.96 for astringency) and relatively lower root mean square errors (RMSE) (0.25 for bitterness and 0.32 for astringency) for the calibration set. The R value is 0.92 and 0.87, and the RMSE is 0.34 and 0.55, for bitterness and astringency, respectively, of the prediction set. These results indicate that the electronic nose could be used as a feasible and reliable method to evaluate the taste of green tea. These results can provide a theoretical reference for rapid detection of the bitter and astringent taste of green tea using volatile odor information.

Joint Voltammetry Technology with a Multi-electrode Array for Four Basic Tastes

Background:

Rapid and easy technology which can mimic the tongue for the simultaneous perception of several tastes based on sensory analysis and mathematical statistics is sorely needed.

Methods:

Joint voltammetry technology was developed to qualitatively and quantitatively analyze four basic tastes namely sweetness, saltiness, sourness and bitterness with the multi-electrode array. Four taste stimuli were corresponded to four tastes. Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Square Wave Voltammetry (SWV) were employed. The original voltammetric signals were transformed by Continuous Wavelet Transform (CWT) in order to reveal more feature information for sensing taste stimuli. Joint voltammetry was applied via the combination of voltammetry. The data of feature points from the transformed signal as the input were used for neural network model.

Results:

Layer-Recurrent neural network (LRNN) could effectively identify the types of stimuli. The accuracies of the training set and test set by joint voltammetry were both higher than that of regular voltammetry, confirming that Back Propagation neural network (BPNN) could quantitatively predict single taste stimulus of the mixture.

Conclusion:

Joint voltammetry technology had a strong ability to sense basic tastes as human tongue.

Influence of brewing conditions on taste components in Fuding white tea infusions

BACKGROUND

White tea has received increasing attention of late as a result of its sweet taste and health benefits. During the brewing of white tea, many factors may affect the nutritional and sensory quality of the resulting infusions. The present study aimed to investigate the effect of various infusion conditions on the taste components of Fuding white tea, including infusion time, ratio of tea and water, number of brewing steps, and temperature.

RESULTS

Brewing conditions had a strong effect on the taste compound profile and sensory characteristics. The catechin, caffeine, theanine and free amino acid contents generally increased with increasing infusion time and temperature. Conditions comprising an infusion time of 7 min, a brewing temperature of 100 °C, a tea and water ratio of 1:30 or 1:40, and a second brewing step, respectively, were shown to obtain the highest contents of most compounds. Regarding tea sensory evaluation, conditions comprising an infusion time of 3 min, a brewing temperature of 100 °C, a tea and water ratio of 1:50, and a first brewing step, resulted in the highest sensory score for comprehensive behavior of color, aroma and taste.

CONCLUSION

The results of the present study reveal differences in the contents of various taste compounds, including catechins, caffeine, theanine and free amino acids, with respect to different brewing conditions, and sensory scores also varied with brewing conditions. © 2016 Society of Chemical Industry.

Sensory and nutritional attributes of pomegranate juices extracted from separated arils and pressed whole fruits

BACKGROUND

The present study aimed to compare the sensory and nutritional attributes of 'Wonderful' pomegranate juices extracted from separated arils with those from pressed whole fruits.

RESULTS

Five different sensory tests were conducted to evaluate the flavor quality of 'Wonderful' pomegranate juices. Consumer acceptance tests revealed that juice from separated arils achieved significantly higher likability scores than that from whole pressed fruits. Furthermore, preference tests revealed that 84% of the tasters preferred the juice extracted from separated arils whereas only 16% preferred the juice from whole pressed fruits. Sensory discrimination tests (triangle tests) revealed that tasters significantly distinguished between the two juices at P ≤ 0.01. Descriptive tests by a trained panel and sensory analysis with an electronic tongue demonstrated that juice from whole pressed fruits was more astringent and had a stronger aftertaste than juice from separated arils. Juice from pressed whole fruits contained significantly higher levels of phenols and hydrolysable tannins, which led to higher astringency.

CONCLUSIONS

Pomegranate juice extracted from separated arils was less astringent and more preferred by tasters than juice from whole pressed fruits. Nonetheless, juice from separated arils has lower nutritional benefits.

The human bitter taste receptor hTAS2R39 is the primary receptor for the bitterness of theaflavins

We purified several hundred mgs of four major theaflavins (theaflavin, theaflavin-3-O-gallate, theaflavin-3′-O-gallate, and theaflavin-3,3′-O-digallate). Among the 25 hTAS2Rs expressed in HEK293T cells, hTAS2R39 and hTAS2R14 were activated by theaflavins. Both hTAS2R39 and hTAS2R14 responded to theaflavin-3′-O-gallate. In addition, hTAS2R39 was activated by theaflavin and theaflavin-3,3′-O-gallate, but not by theaflavin-3-O-gallate. In contrast, hTAS2R14 responded to theaflavin-3-O-gallate.

Discrimination of Chinese teas with different fermentation degrees by stepwise linear discriminant analysis (S-LDA) of the chemical compounds

This study aimed to construct objective and accurate analytical models of tea categories based on their polyphenols and caffeine. A total of 522 tea samples of 4 commonly consumed teas with different fermentation degrees (green tea, white tea, oolong tea, and black tea) were analyzed by high-performance liquid chromatography (HPLC) coupled with spectrophotometry, utilizing ISO 14502, as analytical tools. The content of polyphenols and caffeine varied significantly according to differently fermented teas, indicating that these active constituents may discriminate fermentation degrees effectively. By principal component analysis (PCA) and stepwise linear discriminant analysis (S-LDA), the vast majority of tea samples could be successfully differentiated according to their chemical markers. This study yielded three discriminant functions with the capacity to simultaneously discriminate the four tea categories with a 97.8% correct rate. In classification of oolong and other teas, there were one discriminant function and two equations with best discriminant capacity. Furthermore, the classification of different degrees of fermentation of oolong and external validation achieved the desired results. It is suggested that polyphenols and caffeine are the distinct variables to establish internationally recognized models of teas.