Dynamic changes and the effects of key procedures on the characteristic aroma compounds of Lu'an Guapian green tea during the manufacturing process.

As a kind of green tea with unique multiple baking processes, the flavor code of Lu'an Guapian (LAGP) has recently been revealed. To improve and stabilize the quality of LAGP, further insight into the dynamic changes in odorants during the whole processing is required. In this study, 50 odorants were identified in processing tea leaves, 14 of which were selected for absolute quantification to profile the effect of processes. The results showed that spreading is crucial for key aroma generation and accumulation, while these odorants undergo significant changes at the deep baking stage. By adjusting the conditions of the spreading and deep baking, it was found that low-temperature (4 °C) spreading for 6 h and low-temperature with long-time baking (final leaf temperature: 102 °C, 45 min) could improve the overall aroma quality. These results provide a new direction for enhancing the quality of LAGP green tea.

Exploring the effect of different tea varieties on the quality of Lu'an Guapian tea based on metabolomics and molecular sensory science.

Lu'an Guapian (LAGP) tea is one of the most famous teas in China. However, research on its suitable processing varieties is still lacking. This study analyzed the quality of LAGP tea made from three different tea varieties, namely, 'Anhui1' (AH1), 'Quntizhong' (QTZ), and 'Shuchazao' (SCZ), using molecular sensory science and metabolomics techniques. The results showed that AH1 had a strong floral aroma and the strongest umami flavor, while QTZ had a distinct roasted aroma and a mellow taste. SCZ had a cooked corn-like aroma and the highest bitterness and astringency owing to the high tea polyphenol contents and low free amino acid contents. The study also identified 12 key aroma-active compounds, with trans-beta-ionone and 2-ethyl-3,5-dimethyl-pyrazine contributing the most to floral and roasted aromas, respectively. The results of this study provide a theoretical and practical basis for selecting and breeding high-quality varieties of LAGP tea and stabilizing its quality.

The shaking and standing processing improve the aroma quality of summer black tea.

Black teas harvested during the summer season usually have the defect of low aroma intensity, resulting in unacceptability from consumers. The shaking and standing (SS) process is key to the production of oolong tea and is believed to significantly improve the aroma quality. However, the specific effects of the shaking process on the aroma quality of black tea have not been elucidated. SSBT has a higher aroma intensity than BT, especially floral and sweet odors. By Aroma Extract Dilution Analysis (AEDA), 27 volatiles with flavor dilution factor (FD) above 8 were selected, of which 20 had odor activity values (OAV) values above 1; among them, 9 floral and sweet volatiles with high OAV were linalool (485 for BT, 918 for SSBT), (E)-ß-ionone (389, 699), geraniol (315, 493), ß-myrcene (25, 62), (E)-2-hexenal (2, 7), phenylacetaldehyde (44, 75), (Z)-3-hexenyl hexanoate (19, 41), 1-hexanol (9, 26), and 2-phenylethanol (2,3). Aroma reconstitution of these 20 volatiles showed reliable results of floral, sweet, fruity, and roasted odors, further validating the aroma and intensity profiles of the key odorants. Overall, our results reveal that the metabolite mechanism of the SS process improves the aroma quality of black tea, providing a theoretical basis and guiding measures for the production of high-aroma black tea.

The enhancement of flowery-like aroma in green tea under optimized processing conditions by sensory-directed flavor analysis.

Flowery-like aroma are positive contributors to green tea. Here, the optimal processing conditions for green tea with flowery-like aroma were designed using spreading time, fixation time and drying temperature as three factors designed by response surface methodology (RSM), and the response value of aroma sensory evaluation score. The volatiles in batches of tea samples were analyzed by GC-MS. The optimal quality was obtained with a flowery-like aroma by RSM under a spreading time of 8.97 h, fixation time of 162.3 s, and drying temperature of 103.32 °C. GC-O and odor activity values further revealed floral-like volatiles, including decanal, linalool oxide, ß-lonone, geraniol, (Z)-jasmone, linalool, nonanal, and benzeneacetaldehyde. The recombination of these floral volatiles confirmed the consistency with the floral green tea. Furthermore, the extending spreading duration (8-10 h), reducing fixation duration (160-190 s), and increasing drying temperature (100-115 °C) promote their accumulation in green tea. This study provides new perspectives for the precise enhancement of floral odorants for green tea.

Fatty acid degradation driven by heat during ripening contributes to the formation of the "Keemun aroma".

Ripening refers to the process of chemical change during the refinement of Keemun black tea (KBT) and is crucial in the formation of Keemun Congou black tea's quality. In this study, the aroma composition of KBT during the ripening was analyzed. Sensomics indicated that ripening strengthened the coconut and fatty aroma of KBT and contributed to the decrease of green aroma substances, resulting in a shift of the overall aroma type of KBT to an integrated aroma profile, which was consistent with sensory evaluation. Changes in fatty acid content and the results of in vitro addition simulation tests confirmed that heat causes highly degradation of fatty acids into fatty aroma volatiles, which is a key driver of the formation of "Keemun aroma" quality. This study revealed the mechanism behind the formation of KBT's integrated "Keemun aroma" quality and the mode of thermal degradation of major fatty acids.

E-nose and colorimetric sensor array combining homologous data fusion strategy discriminating the roasting degree of large-leaf yellow tea.

Different degrees of roasting result in differences in the quality and flavor of large-leaf yellow tea. The current sensory evaluation and chemical detection methods cannot meet the requirement of online differentiation of LYT roasting degree, so an accurate and comprehensive assessment method needs to be developed urgently. First, the two aroma sensing technologies were compared. Two variable screening methods and three recognition algorithms were employed to build discriminant models. The results showed that the discrimination rate of the colorimetric sensor array (CSA) in the prediction set reached 91.89 %, outperforming that of the E-nose. Subsequently, three fusion strategies were applied to improve the discrimination accuracy. The discrimination rate of the middle fusion strategy resulted in an optimal resolution of 94.59 %. The results obtained from the homologous fusion were able to evaluate the roasting degree comprehensively and accurately, which provides a new method and idea for tea aroma quality.

Rapid detection of ash content in black tea using a homemade miniature near-infrared spectroscopy.

Ash is a testing index with both health inspection value and quality decision value, and it is an essential detection item in the import and export trade of tea. To realize the rapid and effective quantitative analysis of ash content in tea, this study proposed the use of a homemade miniature near-infrared (NIR) spectroscopy combined with multivariate analysis for the rapid detection of ash content in black tea. First, NIR data of black tea samples from different countries were acquired and optimized by the spectral preprocessing method. Then, the optimized pre-processed spectral data were used as features, and four feature wavelength selection algorithms, such as competitive adaptive reweighted sampling, iteratively retaining informative variables (IRIV), variable combination population analysis (VCPA)-IRIV, and interval variable iterative space shrinkage approach (IVISSA), were utilized to optimize the feature spectra. Finally, the support vector machine regression (SVR) algorithm was employed to construct the quantitative models of ash content in black tea by combining the optimal wavelengths obtained from the four feature selection methods mentioned above. The experimental results showed that the IVISSA-SVR model had the best performance, with correlation coefficient (Rp), root mean square errors of prediction (RMSEP), and relative prediction deviation (RPD) of 0.9546, 0.0192, and 5.59 for the prediction set, respectively. The results demonstrate that a miniature NIR sensing system combined with chemometrics as an effective analytical tool can realize the rapid detection of ash content in black tea.

Rapid and comprehensive grade evaluation of Keemun black tea using efficient multidimensional data fusion.

To develop a comprehensive evaluation method for Keemun black tea, we used micro-near-infrared spectroscopy, computer vision, and colorimetric sensor array to collect data. We used support vector machine, least-squares support vector machine (LS-SVM), extreme learning machine, and partial least squares discriminant analysis algorithms to qualitatively discriminate between different grades of tea. Our results indicated that the LS-SVM model with mid-level data fusion attained an accuracy of 98.57% in the testing set. To quantitatively determine flavour substances in black tea, we used support vector regression. The correlation coefficient for the predicted sets of gallic acid, caffeine, epigallocatechin, catechin, epigallocatechin gallate, epicatechin, gallocatechin gallate and total catechins were 0.84089, 0.94249, 0.94050, 0.83820, 0.81111, 0.82670, 0.93230, and 0.93608, respectively. Furthermore, all compounds exhibited residual predictive deviation values exceeding 2. Hence, combining spectral, shape, colour, and aroma data with mid-level data can provide a rapid and comprehensive assessment of Keemun black tea quality.

Sensomics-Assisted Characterization of Fungal-Flowery Aroma Components in Fermented Tea Using Eurotium cristatum.

Fermented tea (FT) using a single Eurotium cristatum strain can produce a pleasant fungal-flowery aroma, which is similar to the composite aroma characteristic of minty, flowery, and woody aromas, but its molecular basis is not yet clear. In this study, solvent-assisted flavor evaporation and gas chromatography-mass spectrometry/olfactometry were applied to isolate and identify volatiles from the FT by E. cristatum. The application of an aroma extract dilution analysis screened out 43 aroma-active compounds. Quantification revealed that there were 11 odorants with high odor threshold concentrations. Recombination and omission tests revealed that nonanal, methyl salicylate, decanoic acid, 4-methoxybenzaldehyde, α-terpineol, phenylacetaldehyde, and coumarin were the major odorants in the FT. Addition tests further verified that methyl salicylate, 4-methoxybenzaldehyde, and coumarin were the key odorants for fungal-flowery aroma, each corresponding to minty, woody, and flowery aromas, respectively. 4-Methoxybenzaldehyde and coumarin were newly found odorants for fungal-flowery aroma in FT, and 4-methoxybenzaldehyde had not been reported as a tea volatile compound before. This finding may guide future industrial production optimization of FT with improved flavor.

Effects of different over-fired drying methods on the aroma of Lu'an Guapian tea.

Over-fired drying, a crucial process in the production of Lu'an Guapian (LAGP) tea, greatly enriches the tea's aroma. In this study, the aroma compounds of LAGP tea processed through pulley charcoal drying (PCD), roller drying (RD), roller-conveyor drying (RCD), and hot air drying (HD) were analyzed using gas chromatography-mass spectrometry. A subsequent analysis of aroma extraction dilution analysis and odor activity values revealed that (E)-ß-ionone, dimethyl sulfide, (E,E)-2,4-heptadienal, geraniol, linalool, benzeneacetaldehyde, coumarin, 2-ethyl-3,5-dimethyl-pyrazine, indole, hexanal, (Z)-jasmone, and (Z)-3-hexen-1-ol were the key contributors to the samples' aroma variation. Moreover, a quantitative descriptive analysis and aroma recombination and omission experiments analysis revealed that (E)-ß-ionone is the most critical contributor to the formation of floral aroma in tea processed using PCD, whereas (E,E)-2,4-heptadienal is responsible for the more pronounced fresh aroma in tea processed using HD. In addition, 2-ethyl-3,5-dimethyl-pyrazine contributes to the formation of a roasted aroma in tea processed using RD and RCD. The study results provide a theoretical basis for choosing the processing method, especially for drying, to obtain high-quality LAGP tea.

Metabolomics analysis reveals the mechanism underlying the improvement in the color and taste of yellow tea after optimized yellowing.

In this study, an optimized yellowing process for yellow tea (YT) was developed by response surface methodology. The results showed that increasing the yellowing temperature from 20 °C to 34 °C, increasing the relative humidity from 55% to 67%, and reducing the yellowing time from 48 h to 16 h, caused a 40.5% and 43.2% increase in the yellowness and sweetness of YT, respectively, and improved the consumer acceptability by 36.8%. Moreover, metabolomics was used to explore the involved mechanisms that resulted in the improved YT quality. The optimized yellowing promoted the hydrolysis of 5 gallated catechins, 6 flavonoid glycosides, theogallin and digalloylglucose, resulting in the accumulation of 5 soluble sugars and gallic acid. Meanwhile, it promoted the oxidative polymerization of catechins (e.g., theaflagallin, δ-type dehydrodicatechin and theasinensin A), but decelerated the degradation of chlorophylls. Overall, this optimized yellowing process could serve as a guide to a shorter yellowing cycle.

A rapid aroma quantification method: Colorimetric sensor-coupled multidimensional spectroscopy applied to black tea aroma.

Aroma affects the quality of black tea, and the rapid evaluation of aroma quality is the key to realize the intelligent processing of black tea. A simple colorimetric sensor array coupled with a hyperspectral system was proposed for the rapid quantitative detection of key volatile organic compounds (VOCs) in black tea. Feature variables were screened based on competitive adaptive reweighted sampling (CARS). Furthermore, the performance of the models for VOCs quantitative prediction was compared. For the quantitative prediction of linalool, benzeneacetaldehyde, hexanal, methyl salicylate, and geraniol, the CARS-least-squares support vector machine model's correlation coefficients were 0.89, 0.95, 0.88, 0.80, and 0.78, respectively. The interaction mechanism of array dyes with VOCs was based on density flooding theory. The optimized highest occupied molecular orbital levels, lowest unoccupied molecular orbital energy levels, dipole moments, and intermolecular distances were determined to be strongly correlated with interactions between array dyes and VOCs.

Tracing the origin of Taiping Houkui green tea using 1H NMR and HS-SPME-GC-MS chemical fingerprints, data fusion and chemometrics.

The narrow geographical traceability of green tea is both important and challenging. This study aimed to establish multi-technology metabolomic and chemometric approaches to finely discriminate the geographic origins of green teas. Taiping Houkui green tea samples were analyzed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and 1H NMR of polar (D2O) and non-polar (CDCl3). Common dimension, low-level and mid-level data fusion approaches were tested to verify if the combination of several analytical sources can improve the classification ability of samples from different origins. In assessments of tea from six origins, the single instrument data test set results in 40.00% to 80.00% accuracy. Data fusion improved single-instrument performance classification with mid-level data fusion to obtain 93.33% accuracy in the test set. These results provide comprehensive metabolomic insights into the origin of TPHK fingerprinting and open up new metabolomic approaches for quality control in the tea industry.

Cost-effective colorimetric sensor for authentication of protected designation of origin (PDO) Longjing green tea.

Traceability and authentication of protected designation of origin (PDO) tea is an important prerequisite to safeguard its production and distribution system. Here, indicator displacement array (IDA) sensors consisting of natural anthocyanidins and edible metal ions were developed to authenticate PDO and non-PDO Longjing from different origins. Five IDA elements were selected for constructing sensors, achieved by an indicator displacement reaction after adding epigallocatechin gallate solution. The obtained sensors were subsequently used for real tea samples. Unsupervised algorithms were used for data exploration among PDO and non-PDO teas. The supervised support vector machine (SVM) model further achieved accurate authentication of PDO and non-PDO Longjing with a correct classification rate of 100% for the 26 validated samples. The developed IDA sensor thus achieves accurate authentication of PDO tea in a hazard-free and cost-efficient way, providing a useful tool for origin authentication of other agricultural products.

Revelation of volatile contributions in green teas with different aroma types by GC-MS and GC-IMS.

Aroma types of green teas associate with their commercial prices and consumer acceptance, mainly including floral-like (HX), chestnut-like (LX), and fresh (QX) aromas. However, the volatile differences and specificities in these aroma types are still unclear. Herein, Taiping Houkui green teas with HX, LX, and QX aromas were processed separately with the same fresh tea leaves. Ninety-four and seventy-eight volatiles were detected and identified by headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), respectively. Candidate differential volatiles among the tea samples were determined by the variable importance in projection (VIP) of the partial least squares-discriminant analysis (PLS-DA) and were further confirmed by the relative odor activity value (ROAV) and odor description. The volatiles 1-hexanol, linalool oxide (furanoid), linalool, geraniol, (E)-ß-ionone, isoamyl acetate, and 2-methylpropanal enriched in HX and contributed to the floral-like aroma, while 3-methylbutanal, 2-ethyl-1-hexanol, indole, ß-damascone, and cedrol enriched in LX and contributed to the chestnut-like aroma. This study reveals the specificities and contributions of volatiles in green teas with different aromas, thus providing new insights into the molecular basis of different flavored teas, benefiting for their precision processing and targeted quality control.

Sensomics-Assisted Characterization of Key Flowery Aroma Compounds in Lu'an Guapian Green Tea Infusion (Camellia sinensis).

The volatile fraction was isolated from the premium and common grade of Lu'an Guapian green tea infusion by solvent-assisted flavor evaporation distillation. With the application of aroma extract dilution analysis, a total of 52 aroma-active compounds were revealed in the flavor dilution (FD) factor area of 32-8192. Besides, five additional odorants with higher volatility were identified using solid-phase microextraction. The aroma profiles, FD factors, and quantitative data of premium Guapian (PGP) and common Guapian (CGP) showed apparent differences. The intensity of the flowery attribute was significantly higher in PGP than in CGP, while cooked vegetable-like was the most outstanding odor note in CGP. The recombination experiment and the omission test of PGP clarified that dimethyl sulfide, (E,E)-2,4-heptadienal, (E)-ß-ionone, (E,Z)-2,6-nonadienal, 2-methylbutanal, indole, 6-methyl-5-hepten-2-one, hexanal, 3-methylbutanal, γ-hexalactone, methyl epijasmonate, linalool, geraniol, and (Z)-3-hexen-1-ol were the key odorants of PGP tea infusion. The omission and addition tests of flowery odorants manifested that (E)-ß-ionone, geraniol, and (E,E)-2,4-heptadienal, with higher odor activity values in PGP than in CGP, contributed to the flowery attribute most. The difference in the concentration of the abovementioned odorants with flowery odor notes could be one of the main factors which led to the difference in aroma quality between the two grades of Lu'an Guapian.

Indicator displacement assay for freshness monitoring of green tea during storage.

Aging of green tea leads to reductions in its flavor and health value, yet in situ testing methods for green tea freshness are lacking. A novel sensitive indicator displacement assay (IDA) sensor was constructed and applied for monitoring of green tea freshness during storage. Low-cost pH dyes and metal ions were used as indicators and receptors, respectively, for the targeted detection of catechins in tea samples. The feasibility of the IDA reaction was verified using images and UV-vis spectroscopy, respectively. IDA combined with supervised algorithms achieved accurate identification of green tea freshness with an accuracy of 86.67%, and acceptable accuracies in the prediction of catechin monomers and total catechins with ratio of prediction to deviation values over 1.5. Thus, the developed IDA sensor is capable of qualitative and quantitative monitoring of the green tea freshness during storage, providing a new option for quality evaluation and control of green teas.

Formation of aroma characteristics driven by volatile components during long-term storage of An tea.

The aim of this study was to reveal the molecular basis of aroma changes during storage of An tea (AT). The key volatile compounds in AT were screened using SPME-GC-MS and SPE-GC-MS analytical techniques in combination with odor activity value (OAV) and flavor dilution factor (FD). The results showed that with the increase of storage time the stale and woody aromas were revealed. Esters, acids and hydrocarbons are the main types of volatile compounds in AT, and their content accounts for 52.69 %-61.29 % of the total volatile compounds. The key volatile compounds with stale and woody aromas during AT storage were obtained by OAV value and FD value, namely ketoisophorone (flavor dilution factor, FD = 64), linalool oxide C (FD = 64), 1-octen-3-ol (OAV > 1, FD = 32), 1,2-dimethoxybenzene (FD = 16), naphthalene (OAV > 1, FD = 32), 3,4-dimethoxytoluene (FD = 16), and 1,2,3-trimethoxybenzene (FD = 8). Our research provides a scientific basis and insights for the improvement of quality during the storage of dark tea.

Rapid detection of multiple colorant adulteration in Keemun black tea based on hemp spherical AgNPs-SERS.

This study synthesized stable and sensitive hemp spherical AgNPs as the SERS substrate for the simultaneous and rapid detection of sunset yellow, lemon yellow, carmine and erythrosine adulteration in black tea. With R6G as the probe molecule, the AgNPs were determined to have satisfactory stability over 60 days with an enhancement factor of 108. The effects of three variable screening methods on model performance were compared. Among them, CARS-PLS exhibited superior performance for the quantification of all the four colorants, with prediction set correlation coefficients of 0.95, 0.97, 0.99 and 0.88, respectively. The differentiation of the mixed colorants was also achieved, with recoveries ranging from 91.87 % to 106.5 % with RSD value <1.97 %, demonstrating the high accuracy and precision of the proposed method. The results indicate that AgNPs-based SERS is an effective method and has substantial potential for application in the identification and quantification of colorant in tea.

Monitoring green tea fixation quality by intelligent sensors: comparison of image and spectral information.

BACKGROUND: Intelligent monitoring of fixation quality is a prerequisite for automated green tea processing. To meet the requirements of intelligent monitoring of fixation quality in large-scale production, fast and non-destructive detection means are urgently needed. Here, smartphone-coupled micro near-infrared spectroscopy and a self-built computer vision system were used to perform rapid detection of the fixation quality in green tea processing lines. RESULTS: Spectral and image information from green tea samples with different fixation degrees were collected at-line by two intelligent monitoring sensors. Competitive adaptive reweighted sampling and correlation analysis were employed to select feature variables from spectral and color information as the target data for modeling, respectively. The developed least squares support vector machine (LS-SVM) model by spectral information and the LS-SVM model by image information achieved the best discriminations of sample fixation degree, with both prediction set accuracies of 100%. Compared to the spectral information, the image information-based support vector regression model performed better in moisture prediction, with a correlation coefficient of prediction of 0.9884 and residual predictive deviation of 6.46. CONCLUSION: The present study provided a rapid and low-cost means of monitoring fixation quality, and also provided theoretical support and technical guidance for the automation of the green tea fixation process. © 2022 Society of Chemical Industry.