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.

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.

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.

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.

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.

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.

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.

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.

Visualizing chemical indicators: Spatial and temporal quality formation and distribution during black tea fermentation.

Fermentation is a key black tea processing step and makes an important contribution to quality formation. Current approaches to fermentation monitoring are costly or laboratory-based. Here, we first evaluated the potential of at-line computer vision for detecting fermentation quality in a tea factory. A self-built industrial camera was used to collect tea samples at various fermentation durations. The correlations of color variables that were extracted from the images with key quality indicators in the tea samples were verified. Subsequently, partial least-squares regression models based on the color variables showed high prediction accuracy with residual prediction deviation values of 4.13, 3.53, and 3.39 for catechins, theaflavins and chlorophylls, respectively. Finally, the spatial and temporal distributions of indicators during fermentation were mapped to visualize the fermentation quality. This study realized low-cost, at-line and real-time detection for black tea fermentation, which provides technical support for the industrial and intelligent production of black tea.

Cost-effective and sensitive indicator-displacement array (IDA) assay for quality monitoring of black tea fermentation.

Herein, a new indicator-displacement array (IDA) sensor was developed for the quality evaluation of black tea fermentation. On the principle of the reversible covalent binding of phenylboronic acid and catechol, phenylboronic acids were selected as acceptors for targeted binding to polyphenols. Pyrocatechol violet and alizarin red S were used as indicators of the reaction. The IDA sensors have sensitive differential responses to fermented tea samples, achieving an assessment of the fermentation degree with accuracies of 80.39-88.00% by support vector machine (SVM). In addition, the key polyphenol components of the fermentation process were accurately predicted by the IDA and SVM regression with ratio of prediction to deviation values of 1.55-1.72, 2.03-2.21, and 2.03-2.08 for total polyphenols, total catechins, and epigallocatechin-3-O-gallate, respectively. In conclusion, the developed IDA sensor is capable of the in-situ quality monitoring of black tea fermentation, with the advantages being cost-effectiveness, sensitivity, and rapidity.

Analysis of volatile metabolite variations in strip green tea during processing and effect of rubbing degree using untargeted and targeted metabolomics.

Strip green tea (SGT) is widely distributed in China owing to its unique appearance and aroma but the evolution and formation mechanisms of volatile metabolites (VMs) during SGT processing, and especially in the unique process of rubbing, remain unclear. In this study, based on untargeted metabolomics, 217 VMs (8 categories) were identified, and fixation and rubbing processes were found to be key for SGT aroma formation. Moreover, targeted metabolomics was applied to obtain 38 differential VMs and their related substances, of which fatty acid-derived volatiles (14 VMs) and glycoside-derived volatiles (8 VMs) showed significant contributions to SGT aroma, and their derivation laws during SGT manufacturing were clarified. Furthermore, the effect of rubbing degree on volatile metabolite formation was explored, and 11 key differential VMs were screened by variable importance in projection, and odor activity value analyses. Appropriate rubbing promoted the loss of grassy VMs (such as 1-octanol and 2-pentyl-furan) and enrichment of floral/fruity VMs (such as trans-ß-ionone, nonanal, geraniol, citral, (Z)-3,7-dimethyl-2,6-octadien-1-ol, and (Z)-hexanoic acid, 3-hexenyl ester). Our study not only enriches the chemical theory of green tea processing but also provides technical support for the precision directional processing of high-quality SGT.

Evaluation of the effects of solar withering on nonvolatile compounds in white tea through metabolomics and transcriptomics.

The mechanism through which solar withering (SW) affects the quality of white tea is unclear. To address this gap in the literature, in this study, we used metabolomics and transcriptomics to investigate the effect of SW on the quality of WT. WT that underwent SW was slightly more bitter and astringent than WT that underwent natural withering (control group). Specifically, SW considerably increased the concentration of astringent flavonoids and flavone glycosides in WT. This increase was mainly attributed to the upregulated expression of key genes in the shikimic acid, phenylpropanoid, and flavonoid biosynthesis pathways, such as shikimate kinase, chalcone synthase, and flavonol synthase. In addition, SW experienced considerable heat and light stress. The levels of glycerophosphatidylcholine and carbohydrates increased in response to the stress, which also affected the taste of WT. The results of this study indicate the mechanism through which SW affects the quality of WT.

Effects of Microbial Action and Moist-Heat Action on the Nonvolatile Components of Pu-Erh Tea, as Revealed by Metabolomics.

Microbial action and moist-heat action are crucial factors that influence the piling fermentation (PF) of Pu-erh tea. However, their effects on the quality of Pu-erh tea remain unclear. In this study, the effects of spontaneous PF (SPPF) and sterile PF (STPF) on the chemical profile of Pu-erh tea were investigated for the first time, and sun-dried green tea was used as a raw material to determine the factors contributing to the unique quality of Pu-erh tea. The results indicated that the SPPF-processed samples had a stale and mellow taste, whereas the STPF-processed samples had a sweet and mellow taste. Through metabolomics-based analysis, 21 potential markers of microbial action (including kaempferol, quercetin, and dulcitol) and 10 potential markers of moist-heat action (including ellagic acid, ß-glucogallin, and ascorbic acid) were screened among 186 differential metabolites. Correlation analysis with taste revealed that metabolites upregulated by moist-heat and microbial action were the main factors contributing to the staler mellow taste of the SPPF-processed samples and the sweeter mellow taste of the STPF-processed samples. Kaempferol, quercetin, and ellagic acid were the main active substances formed under microbial action. This study provides new knowledge regarding the quality formation mechanism of Pu-erh tea.

Sensomics analysis of the effect of the withering method on the aroma components of Keemun black tea.

Withering is a key process that affects the aroma of Keemun black tea (KBT). In this study, the aroma composition of KBT through natural withering, sun withering, and warm-air withering was analysed using gas chromatography-mass spectrometry. The results revealed significant differences in the three samples. Gas chromatography-olfactometry and aroma extract dilution analysis were performed with screening through a relative odour activity value (rOAV) > 1. In total, 11 aroma-active compounds (geraniol, (Z)-4-heptenal, 1-octen-3-ol, (E)-ß-ionone, 3-methylbutanal, linalool, ß-damascenone, (E, E)-2,4-decadienal, methional, (E, E)-2,4-nonadienal, and (E)-2-nonenal) were found to be responsible for the differences in aroma caused by different withering methods. Linalool (rOAV, 161) and geraniol (rOAV, 785) were responsible for the higher flowery and fruity aromas when sun withering was applied, whereas methional (rOAV, 124) contributed to the intense roasty aroma when warm-air withering was employed. Moreover, our results were verified by quantitative descriptive analysis and addition experiments.

High-speed identification system for fresh tea leaves based on phenotypic characteristics utilizing an improved genetic algorithm.

BACKGROUND: High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera. RESULTS: The influence of combinations of morphology, color, and custom corner-point morphological features on the classification results were investigated, and the necessary dimensionality of the model was tested. After feature selection and combination, the classification performance of the Naive Bayes, k-nearest neighbor, and support vector machine algorithms were compared. The recognition time of Naive Bayes was the shortest, whereas the accuracy of support vector machine had the best classification accuracy at approximately 97%. The support vector machine algorithm with only three feature dimensions (equivalent diameter, circularity, and skeleton endpoints) can meet production requirements with an accuracy rate reaching 92.5%. The proposed algorithm was tested by using the Swedish leaf and Flavia data sets, on which it achieved accuracies of 99.57% and 99.44%, respectively, demonstrating the flexibility and efficiency of the recognition scheme detailed in the present study. CONCLUSION: This research provides an efficient tea leaves recognition system that can be applied to production lines to reduce manual picking costs. © 2022 Society of Chemical Industry.

Improving the flavor of summer green tea (Camellia sinensis L.) using the yellowing process.

Summer green tea (SGT) has poor flavor due to its high levels of bitterness and astringency. The present study aimed to improve the flavor of SGT using the yellowing process. The results showed that after the yellowing process, the sweetness and overall acceptability increased, and the content of gallated catechins and flavonol glycosides decreased by 30.2% and 27.4%, respectively, as did the bitterness and astringency of SGT. Yellowing caused a decrease in the concentration of some aroma compounds, such as (z)-3-hexen-1-ol, 1-hexanol, pentanal, heptanal and 1-octanol, which caused grassy, floral and fruity aromas. In contrast, the concentrations of 1-octen-3-ol, benzene acetaldehyde and ß-ionone increased, which have mushroom and sweet aromas. Meanwhile, the sweetness and umami of SGT were enhanced by the addition of selected aroma compounds (1-octen-3-ol, benzene acetaldehyde and ß-ionone), demonstrating that the yellowing process improves the flavor of SGT through odor-taste interactions.