Qianlin cha (QLC), a traditional Taoist herbal tea derived from Camellia cuspidata, is prized for its health benefits, but its bitter taste is obvious and has a herbal flavor. In order to reduce the bitterness in QLC, enhance the fragrance of florals, and develop new products. The purpose of this study is to reduce the bitterness and astringency of QLC and improve the fragrance of florals through the application of yellowing process. Comprehensive assessments, including sensory evaluation, color analysis, partial least squares discriminant analysis (PLS-DA) of physicochemical parameters, headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS), and gas chromatography-olfactometry (GC-O), were employed to identify key determinants of QLC's sensory appeal. The yellowing-treated QLC (QLC-Y) exhibited significantly improved sensory scores, marked color transformation toward desirable yellow hues with reduced a and b values, and enhanced levels of amino acids and soluble sugars (P < 0.05), contributing to a sweeter taste profile. In contrast, bitter and astringent ester catechins decreased notably, indicating superior physicochemical characteristics. Aroma analysis indicated the elevated aroma indices (P < 0.05), leading to the identification of four aroma-active compounds by GC-O: linalool, nonanal, sulcatone, and (E,E)-2,4-heptadienal. These results indicated that the yellowing treatment alters the sensory profile of QLC from herbaceous and bitter notes to a sweeter, more floral character by modifying its volatile compounds. This study provides preliminary mechanistic evidence suggesting that yellowing treatment associated with improvements in Camellia cuspidata tea quality, which could offer a scientific basis for premium herbal tea production.

This study systematically investigates the regulatory role of processing technology in the aroma differentiation of Fuding Dabai tea (Camellia sinensis). Using an integrated sensomics approach combining quantitative descriptive analysis and GC × GC-TOF-MS, we deciphered aroma formation in green (GT), white (WT), black (BT), and dark (DT) teas. Among 187 volatiles detected, WT exhibited the highest VOC content (2349.42 μg/L) and the most key odorants (30 of 36). Multivariate statistical modeling identified fermentation degree as the primary factor driving aroma divergence, clearly discriminating fermented (BT/DT) from non/light-fermented (GT/WT) teas. OPLS-DA selected 12 marker compounds (VIP > 1), predominantly alcohols and aldehydes. Sweet aroma exhibited strong correlations with benzeneacetaldehyde (r = 0.91) and (E)-2-hexenal (r = 0.92), while aged aroma correlated strongly with (E,E)-2,4-heptadienal (r = 0.92) (all p < 0.001). We demonstrate that processing reconfigures aroma profiles through enzymatic inhibition, oxidative conversion, and microbial fermentation pathways. These results provide a biochemical basis for aroma-oriented optimization in tea processing and establish the superior suitability of Fuding Dabai for white tea production.

Background: Roasting conditions significantly influence the sensory profile of Hubei strip-shaped green tea (HSSGT). Methods: This study examined the effects of roast processing on the sensory attributes, color qualities, physicochemical properties, and key aroma compounds of HSSGT. Sensory evaluation, color qualities determination, principal component analysis of physicochemical components (PCA), HS-SPME (headspace solid-phase microextraction) coupled with GC-MS (gas chromatography–mass spectrometry), relative odor activity value (ROAV), gas chromatography–olfactometry (GC-O), and absolute quantification analysis were employed to identify the critical difference in compounds that influence HSSGT desirability. Results: The results indicated that HSSGT roasted at 110 °C for 14 min achieved the highest sensory scores, superior physicochemical qualities, and an enhanced aroma index, which was attributed to shifting the proportion of chestnut to floral volatile compounds. Additionally, sensory-guided ROAV, GC-O, and absolute quantification revealed that linalool, octanal, nonanal, and hexanal were the most significant volatile compounds. The variations in these four critical compounds throughout the roasting process were further elucidated, showing that the ideal roasting conditions heightened floral aromas while diminishing the presence of less desirable green odors. These findings offer technical guidance and theoretical support for producing HSSGT with a more desirable balance of chestnut and floral aroma characteristics.

Astringency is crucial in determining the taste quality of matcha, primarily influenced by flavonoids. However, the specific impact of cultivars and processing techniques on flavonoid composition remains unclear. This study employs quantitative descriptive analysis, multivariate statistical analysis, dose over threshold (Dot) values, and sensory verification to comprehensively analyze changes in flavonoid profiles during the processing of two cultivars (Longjing 43 and Zhongcha 108) and their effects on matcha's astringency. 679 flavonoid metabolites were identified, predominantly comprising flavones and flavonols. Longjing 43 fresh leaves predominantly contain glycosylated flavonoids, whereas Zhongcha 108 has a higher proportion of O-methylated modifications. Drying is a critical process, significantly boosting flavonoid glycoside content. Cultivar emerges as the primary and most influential factor determining matcha astringency, with processing techniques exerting a lesser impact. Furthermore, by utilizing Dot values and sensory verification, it was determined that quercetin-3-O-glucoside, kaempferol-3-O-rutinoside, (-)-epigallocatechin gallate, and kaempferol-3-O-glucoside are pivotal components of matcha's astringency.

γ-Aminobutyric acid (GABA), a four-carbon non-protein amino acid functions as a key signaling molecule in plants. As a signature bioactive compound in tea, GABA plays a crucial role in determining both flavor profile and health-promoting properties. Despite its importance, the molecular regulation of GABA accumulation in tea plants-especially its metabolic crosstalk with key quality determinants like flavonoids-remains elusive. While amino acid transporters are known to mediate source-sink allocation in plants, the functional characterization of GABA transporters in Camellia sinensis has been lacking. In this study, we identified and functionally characterized the bidirectional amino acid transporter CsBAT in tea plants. Through a comprehensive multiplatform validation system encompassing yeast heterologous expression, Arabidopsis genetic transformation, and tea transgenic system, we revealed that CsBAT shows vascular-specific expression and facilitates directional amino acid transport from source (mature leaves) to sink (young shoots), thereby significantly boosting GABA accumulation in buds and young leaves. Importantly, we discovered that CsBAT functionally interacts with key flavonoid biosynthetic enzymes (LAR, 4CL, C4H) within secondary metabolic networks. Our findings provide the first mechanistic link between CsBAT-mediated amino acid transport and tea quality formation, establishing both theoretical frameworks and practical tools for molecular breeding of premium tea cultivars.

This study systematically investigates lipid dynamics and their role in aroma formation during Qingzhuan tea (QZT) processing. Using UHPLC-MRM-MS/MS and GC-MS, we analyzed fatty acids (FAs) and oxidized fatty acids (OFAs) across seven processing stages, identifying 31 FAs and 55 OFAs. Polyunsaturated fatty acids (PUFAs), particularly α-linolenic acid (C18:3) and linoleic acid (C18:2), dominated the lipid profiles (43.7 %-60.1 %), exhibiting biphasic dynamics: a 5.3-fold increase during pile fermentation and natural aging (RT → A12) followed by oxidative degradation (30.0 % reduction in QZT). Multivariate analysis revealed 76 differential lipids correlating with 22 key volatiles, including (E,E)-2,4-heptadienal and (E)-2-octenal. Metabolic pathway analysis mapped lipoxygenase/cyclooxygenase (LOX/COX)-mediated oxidation of C18:3/C18:2 to hydroperoxides, which were then cleaved by lyases into aldehydes. Isotope labeling confirmed cross-pathway interactions between linoleic and arachidonic acid metabolism, while modeling experiments validated enzymatic generation of C6-C9 aldehydes from lipid precursors. This work elucidates the biochemical basis of QZT's aged aroma, providing actionable insights for flavor modulation in fermented teas.

To determine the effects of microbial proteins on Qingzhuan tea sensory quality during tea pile fermentation, tea leaf metabolomic and microorganism proteomic analyses were performed. In total, 1835 differential metabolites and 443 differentially expressed proteins of the microorganisms were identified. Correlation analysis between metabolomics and proteomics data revealed that the levels of microbial proteins EG II and CBH I cellulase may play important roles in cell wall construction and permeability, which were crucial for the interaction between tea leaves and microorganisms. Microbial proteins heat shock proteins (HSP), alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), and CuAO related to detoxification and stress responses showed a positive correlation with tea theanine, glutamine, gamma-aminobutyric acid, glutamic acid, catechin, (-)-gallocatechin gallate, and (-)-catechin gallate, suggesting their effects on tea characteristic compound accumulation, thus affecting Qingzhuan tea sensory quality.

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Volatile constituents are critical to the flavor of tea, but the changes in Enshi Yulu tea during the processing have not been clearly understood. Using headspace solid phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) techniques, we analyze the aroma components of Enshi Yulu tea and changes in them during the processing stages. In total, 242 volatile compounds were identified. From fresh leaves to the shaping process in tea production, there are significant decreases in overall aroma substances, followed by increases after drying. Linalool is the dominant aroma component in Enshi Yulu tea, with a proportion of 12.35%, followed by compounds such as geraniol (7.41%), 2,6-dimethyl-5-heptene (6.93%), phenylmethanol (5.98%), isobutyl acetate (4.16%), hexan-1-ol (3.95%), 2-phenylacetaldehyde (3.80%), and oct-1-ene-3-ol (3.34%). The number of differential volatile components varied by production stage, with 20 up- and 139 down-regulated after steaming, 24 down-regulated after rolling, 60 up- and 51 down-regulated after shaping, and 68 up- and 13 down-regulated after drying. Most variation in expression occurred because of steaming, and the least during the rolling stage. PLS-DA analysis revealed significant differences in aroma components throughout processing and the identification of 100 compounds with higher relative contents, with five distinct change trends. Phenylmethanol, phenylacetaldehyde, (2E)-non-2-enal, oct-1-ene-3-ol, and cis-3-hexenyl hexanoate could exert a profound influence on the overall aroma quality of Enshi Yulu tea during processing. The results offer a scientific foundation and valuable insights for understanding the volatile composition of Enshi Yulu tea and its changes during the processing.

This paper applies near-infrared spectroscopy (NIRS) and multiple chemometrics to efficiently distinguish the origins of fresh tea leaves. The key components were obtained using the partial least squares discriminant analysis (PLS-DA) method. PLS, synergy interval PLS (siPLS), principal component analysis (PCA), genetic algorithm (GA), and their combination methods were used to establish NIRS non-destructive discrimination models. Then, the practical application was examined using external samples. The study identified nine key components (variable importance for the projection (VIP) > 1): epigallocatechin, epicatechin, total sugar, water extracts, total catechins, gallocatechin gallate, tea polyphenols, gallocatechin, and epigallocatechin gallate. Of the six NIRS models, the siPLS-GA model that used 37 spectral data points produced the best results (Rp2 = 0.9706, RMSEP = 0.0772, RPD = 6.59). This model had a prediction accuracy of 96.67% for the prediction set samples and 93.33% for the external samples. It offers a rapid, precise, and non-invasive approach to monitor and regulate the illicit trade of fresh tea leaves, thereby guaranteeing the authenticity of Enshi Yulu products from the processing source and fostering the long-term prosperity and stability of the Enshi Yulu tea industry.

为进一步降低某款现役青砖茶专用液压机的制造费用,利用有限元法对该液压机上横梁进行受力和形变分析,评估了安装孔特征对分析结果的影响程度.采用命令流形式建立了上横梁结构的数学模型,依据建模时布尔运算增加或减少体积对模型中13个尺寸参数进行分组,按照不分组和分组两种形式以子迭代方式进行尺寸优化.结果显示,优化后横梁应力处在25～100 MPa范围的区域相比优化前有所增大,而最大应力发生位置没有改变,均处于立柱筒与横梁对角筋板交接的下表面.优化后横梁形变的过渡区域更大,而最大形变发生位置没有改变,均处于油缸与上横梁安装基准面.液压机横梁应力应变的分布更加趋于合理,且分组优化过程收敛更快,目标值更优.相较于原有的设计尺寸,上横梁质量由1 294 kg下降至975.8 kg,可节约24.6%材料,有效降低了设备的制造成本.

Steamed green tea has unique characteristics that differ from other green teas. However, the alteration patterns of non-volatile metabolites during steamed green tea processing are not fully understood. In this study, a widely targeted metabolomic method was employed to explore the changes in non-volatile metabolites during steamed green tea processing. A total of 735 non-volatile compounds were identified, covering 14 subclasses. Of these, 256 compounds showed significant changes in at least one processing step. Most amino acids, main catechins, caffeine, and main sugars were excluded from the analysis. The most significant alterations were observed during steaming, followed by shaping and drying. Steaming resulted in significant increases in the levels of most amino acids and their peptides, most phenolic acids, most organic acids, and most nucleotides and their derivates, as well as some flavonoids. Steaming also resulted in significant decreases in the levels of most lipids and some flavonoids. Shaping and drying caused significant increases in the levels of some flavonoids, phenolic acids, and lipids, and significant decreases in the levels of some amino acids and their peptides, some flavonoids, and some other compounds. Our study provides a comprehensive characterization of the dynamic alterations in non-volatile metabolites during steamed green tea manufacturing.

Changes in key odorants and aroma profiles of three types of green tea during storage and after baking treatment were determined using headspace solid-phase microextraction–gas chromatography–mass spectrometry/olfactometry, odor activity value (OAV) and orthogonal partial least-squares discriminant analysis. As the stale odor developed during storage, the content of aldehydes decreased, whereas the contents of ketones and heterocycles (furans, pyrroles, etc.) increased. Key odorants, including (E,E)-2,4-heptadienal, α-terpineol, (E,E)-2,4-nonadienal and (E,E)-2,4-decadienal, appeared to be mainly responsible for the stale odor. After baking treatment, the stale odor was significantly improved, the contents of aldehydes and heterocycles were significantly increased and the content of alcohols was significantly decreased. Of these, 2-pentylfuran, hexanal, nonanal and limonene, which increased after baking, contribute the green, fruity and roasted aromas of green tea, because of their high OAVs, aroma intensities and variable importance in projection values. This study has improved understanding of the chemical changes resulting in stale odor development in green tea during storage and improvements arising from baking treatment, as well as providing a theoretical basis for the improvement of storage conditions and green tea flavor.

Fresh leaves of Echa 1 were fixed by roller, steam/hot air and light-wave, and the effects of the three fixation methods on the chemical characteristics of straight-shaped green teas (GTs) were studied by widely targeted metabolomic analysis. 1001 non-volatile substances was identified, from which 97 differential metabolites were selected by the criteria of variable importance in projection (VIP) > 1, p < 0.05, and |log2(fold change)| > 1. Correlation analysis indicated that 14 taste-active metabolites were the major contributors to the taste differences between differently processed GTs. High-temperature fixation induces protein oxidation or degradation, γ-glutamyl peptide transpeptidation, degradation of flavonoid glycosides and epimerization of cis-catechins, resulting in the accumulation of amino acids, peptides, flavonoids and trans-catechins, which have flavor characteristics such as umami, sweetness, kokumi, bitterness and astringency, thereby affecting the overall taste of GTs. These findings provided a scientific basis for the directional processing technology of high-quality green tea.

In order to analyze the changes in the microbial community structure during the pile fermentation of Qingzhuan tea and their correlation with the formation of quality compounds in Qingzhuan tea, this study carried out metagenomic and metabolomic analyses of tea samples during the fermentation process of Qingzhuan tea. The changes in the expression and abundance of microorganisms during the pile fermentation were investigated through metagenomic assays. During the processing of Qingzhuan tea, there is a transition from a bacterial dominated ecosystem to an ecosystem enriched with fungi. The correlation analyses of metagenomics and metabolomics showed that amino acids and polyphenol metabolites with relatively simple structures exhibited a significant negative correlation with target microorganisms, while the structurally complicated B-ring dihydroxy puerin, B-ring trihydroxy galloyl puerlin, and other compounds showed a significant positive correlation with target microorganisms. Aspergillus niger, Aspergillus glaucus, Penicillium in the Aspergillaceae family, and Talaromyces and Rasamsonia emersonii in Trichocomaceae were the key microorganisms involved in the formation of the characteristic qualities of Qingzhuan tea.

In this study, near-infrared spectroscopy (NIRS) combined with a variety of chemometrics methods was used to establish a fast and non-destructive prediction model for the purchase price of fresh tea leaves. Firstly, a paired t-test was conducted on the quality index (QI) of seven quality grade fresh tea samples, all of which showed statistical significance (p < 0.05). Further, there was a good linear relationship between the QI, quality grades, and purchase price of fresh tea samples, with the determination coefficient being greater than 0.99. Then, the original near-infrared spectra of fresh tea samples were obtained and preprocessed, with the combination (standard normal variable (SNV) + second derivative (SD)) as the optimal preprocessing method. Four spectral intervals closely related to fresh tea prices were screened using the synergy interval partial least squares (si-PLS), namely 4377.62 cm−1–4751.74 cm−1, 4755.63 cm−1–5129.75 cm−1, 6262.70 cm−1–6633.93 cm−1, and 7386 cm−1–7756.32 cm−1, respectively. The genetic algorithm (GA) was applied to accurately extract 70 and 33 feature spectral data points from the whole denoised spectral data (DSD) and the four characteristic spectral intervals data (FSD), respectively. Principal component analysis (PCA) was applied, respectively, on the data points selected, and the cumulative contribution rates of the first three PCs were 99.856% and 99.852%. Finally, the back propagation artificial neural (BP-ANN) model with a 3-5-1 structure was calibrated with the first three PCs. When the transfer function was logistic, the best results were obtained (Rp2 = 0.985, RMSEP = 6.732 RMB/kg) by 33 feature spectral data points. The detection effect of the best BP-ANN model by 14 external samples were R2 = 0.987 and RMSEP = 6.670 RMB/kg. The results of this study have achieved real-time, non-destructive, and accurate evaluation and digital display of purchase prices of fresh tea samples by using NIRS technology.

In order to explore the differences of flavor characteristics among different cultivars (strains) of large-leaf yellow tea, the main tea tree varieties (strains) in Hubei Province were used as materials to process large-leaf yellow tea. The differences in sensory quality, taste and aroma components were anaylzed, and chemometrics analysis was used to explore the relationship between taste-characteristic attributes and chemical compositions. The results showed that large-leaf yellow tea of B6-1 and 07-7-44 strains had the best total sensory scores with long-lasting roasting aroma and sweet floral fragrance, the large-leaf yellow tea of D12 and B6-1 strains had the higher contents of non-ester catechins and amino acids, while large-leaf yellow tea of D12, B6-1 and 07-7-44 strains had the lower ratio of tea polyphenols/amino acids, showed the characteristics of mellow and sweet aftertaste. Correlation analysis showed that taste score and total sensory score were significantly positively correlated with the contents of water extracts, amino acids and soluble sugars (P<0.01), while significantly negatively correlated with the contents of flavonoids, the ratio of tea polyphenols/amino acids and the ratio of ester catechins/non-ester catechins (P<0.01). The contents of linalool and its oxides, 1-ethyl-2-formylpyrrole, methyl salicylate, furfural and other substances in large-leaf yellow tea produced by B6-1 and 07-7-44 strains were higher, components such as linalool and its oxides, methyl salicylate presented floral, sweet flavor, meanwhile, furfural and 1-ethyl-2-formylpyrrole have the aroma of baking, nutty or caramel, which together constituted the material basis of unique baking fragrance, sweet and floral flavor. In conclusion, the B6-1 and 07-7-44 strains had certain advantages for processing high-quality large-leaf yellow tea. The research results provided an important theoretical basis for the selection, processing and comprehensive utilization of suitable varieties of large-leaf yellow tea.

为了提高茉莉绿碎茶产品品质,以现行窨花工艺为对照,比较分析不同工艺流程处理所制样品的感官得分、色泽品质、理化成分、香气组分和生产成本,采用感官分析、化学计量法、顶空固相微萃取(HS-SPME)结合气相色谱-质谱联用技术(GC-MS)和气相色谱-嗅觉测量方法(GC-O)技术,对比筛选了不同窨花工艺对茉莉绿碎茶理化品质和香气组分的影响.结果表明,经过增加窨花次数和增加提花工艺后,所制的茉莉绿碎茶感官得分明显提高了1.92～4.25分;干茶亮度提高了4.05％～5.20％(p<0.01),干茶和叶底色泽变红(p<0.01);儿茶素苦涩味指数降低了2.35％～8.87％,综合理化品质得到升高;同时鉴定得到了茉莉绿碎茶中20种呈香成分,其中苯甲酸甲酯、芳樟醇、乙酸苯甲酯和水杨酸甲酯的呈香强度≥3.综合来看,"一窨一提"工艺所制茉莉绿碎茶的品质符合商品要求,成本相对较低,更适合实际生产的技术需要.

In order to explore the correlation between mineral elements content and quality ingredients of flat green tea, ten representative flat green tea samples from five production areas (Dawu County, Hubei Province, Pan'an County, Zhejiang Province, She County, Anhui Province, Meitan County, Guizhou Province and Emeishan City, Sichuan Province) were collected. The content of nine mineral elements (Mg, K, Ca, P, Al, Mn, Fe, Zn, B) and five quality ingredients (water extracts, tea polyphenols, free amino acids, total soluble sugars, caffeine) were determined. Results showed that the mineral elements influenced each other and existed with synergistic or antagonistic effects. The water extracts content was significantly negatively correlated with the B content (P<0.05), the tea polyphenol content was extremely negatively correlated with Fe content (P<0.01), the total soluble sugar content was significantly positive to the B content (P<0.05), but negatively correlated with Mg and Ca content (P<0.05), Fe and Mn had a negative effect on caffeine content. The principal component analysised exhibited that the first three principal components explained 89.00% of the cumulative variance contribution, Mg, Ca, Zn, Al and P were considered as characteristic elements of flat green tea, water extracts content and free amino acids content were considered as important physicochemical indicators to evaluate the quality of flat green tea. Cluster analysis showed that samples from the same producing area were grouped together, and samples from different producing areas were clearly separated, indicated that the quality of flat green tea showed distinct regional distribution characteristics.

Tea polyphenols are one of the most important ingredients in Qingzhuan tea. Usually, a chemical method is used to determine tea polyphenols content, but it was time-consuming and laborious. This paper attempted to use near infrared spectroscopy (NIRS) technology combined with three partial least squares methods to predict tea polyphenols content quickly and nondestructively. The partial least squares (PLS), synergy interval PLS (siPLS) and genetic algorithm based PLS (gaPLS) were used to establish prediction models, the performance of the final model was showed by root mean square error of prediction (RMSEP) and determination coefficient (Rp2) in prediction set. The best spectral preprocessing method was multivariate scattering correction (MSC); the RMSEP and Rp2 of PLS model were 0.145% and 0.8974, respectively; the siPLS model was established with four spectral regions (4377.6 cm-1-4751.7 cm-1, 4755.6 cm-1-5129.7 cm-1, 6262.7 cm-1-6633.9 cm-1 and 7386 cm-1-7756.3 cm-1), whose RMSEP and Rp2 were 0.0652% and 0.9235, respectively; the gaPLS model was established with 36 spectra dada points and showed the best performance (RMSEP=0.0624%, Rp2=0.9769) compared with the PLS and si-PLS models. Therefore, the application of near infrared technology combined with the gaPLS method could predict tea polyphenols content in Qingzhuan tea more accurately and rapidly.