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Tea, one of the most popular beverages worldwide, is produced from the tender leaves of Camellia sinensis through complex chemical processes. Tea quality is largely determined by its aroma and color, which are influenced by the tea’s manufacturing process and cultivar. However, limited research has explored the combined effects of processing methods and tea cultivars on tea infusion color. This study compared the effects of semi-fermented oolong tea and fully fermented black tea processing on infusion color using Taiwan Tea Experiment Station (TTES) No. 18 and Chin-shin cultivars. The results revealed that oolong tea processing minimized polyphenol oxidase activity and preserved catechins, resulting in a lighter infusion color. In contrast, black tea processing enhanced theaflavin production, deepening the yellow-orange color of the tea infusion. TTES No. 18, with higher catechin content, exhibited a darker tea color compared to Chin-shin. This study highlights the significant influence of processing methods and tea cultivar on infusion color. Oolong tea processing maintains catechin levels and a lighter color, while black tea processing intensifies theaflavin content and deepens the color. These findings provide insights into optimizing tea production to enhance the visual quality of tea infusions.

Tea aroma is one of the most important factors affecting the character and quality of tea. Here we describe the practical application of methyl jasmonate (MeJA) to improve the aroma quality of teas. The changes of selected metabolites during crucial tea processing steps, namely, withering, fixing and rolling, and fermentation, were analyzed. MeJA treatment of tea leaves (12, 24, 48, and 168 h) greatly promotes the aroma quality of green, oolong, and black tea products when comparing with untreated ones (0 h) and as confirmed by sensory evaluation. MeJA modulates the aroma profiles before, during, and after processing. Benzyl alcohol, benzaldehyde, 2-phenylethyl alcohol, phenylacetaldehyde, and trans-2-hexenal increased 1.07- to 3-fold in MeJA-treated fresh leaves and the first two maintained at a higher level in black tea and the last two in green tea. This correlates with a decrease in aromatic amino acids by more than twofold indicating a direct relation to tryptophan- and phenylalanine-derived volatiles. MeJA-treated oolong tea was characterized by a more pleasant aroma. Especially the terpenoids linalool and oxides, geraniol, and carvenol increased by more than twofold.

Tea’s chemical composition is influenced by cultivar, harvest maturity, and growing environment; however, processing remains the dominant factor shaping final quality. Despite the diversity of Taiwanese native teas, systematic comparisons of functional components across multiple manufacturing stages remain limited. In this study, nine representative Taiwanese teas were evaluated at four key processing stages—green tea (G), enzymatic fermentation (oxidative fermentation, F), semi-finished tea prior to roasting (S), and completed tea (C)—to clarify how enzymatic oxidation, rolling, and roasting alter major bioactive constituents. Green-tea-stage samples exhibited clear cultivar-dependent profiles: large-leaf cultivars contained higher catechins and gallic acid, whereas bud-rich small-leaf teas showed elevated caffeine and amino acids, with amino acids further enhanced at higher elevations. Fermentation intensity governed the major chemical transitions, including catechin depletion, gallic acid formation, accumulation of early stage catechin-derived paired oxidative polymerization compounds (POPCs), and pronounced increases in theasinensins in heavily fermented teas. L-theanine decreased most markedly in teas subjected to prolonged withering. Roasting further reduced amino acids but had minimal influence on caffeine, while rolling effects varied by tea type. Overall, this study provides the first stage-resolved chemical map of Taiwanese native teas, offering practical insights for optimizing processing strategies to enhance functional phytochemical profiles.

Fruity-floral black tea quality is co-determined by both cultivar and processing. Jinlong No. 1 (JL1), a newly released high-aroma cultivar, lacked identified quantitative aroma markers. To elucidate the aroma characteristics of the newly released high-aroma cultivar 'Jinlong No.1' (JL1), three black teas were analyzed through GC-MS/MS-based volatile metabolomics, sensory evaluation, and relative odor activity value analysis. These included JL1 fruity-floral black tea (JL1B), JL1 conventional black tea (JL1S), and 'Huangdan' fruity-floral black tea (HDB). JL1B achieved the highest overall aroma score (8.2 ± 0.8). Comparative analysis revealed 340 differential volatiles between the two fruity-floral teas, predominantly esters (18%) and ketones (16%). Key upregulated compounds in JL1B included hexyl butanoate and hexyl 2-methylbutanoate, while ( )-2-nonenal and 1-nonen-3-ol were notably downregulated. Further comparison between the two JL1 teas identified 536 differential volatiles, with terpenoids (20%) and esters (18%) as the most abundant classes. Seventeen metabolites were commonly altered across comparisons, including the aforementioned esters. These findings establish specific quantitative targets for the precision processing and cultivar-directed breeding of premium fruity-floral black teas.

Tea winnowing is a key process in tea processing. At present, tea winnowing parameters are adjusted by manual observation of tea leaves. This results in the uncertainty of winnowing quality. In this work, we propose a new tea winnowing method based on deep learning for the characteristics of white tea. Firstly, the YOLOv11 model is improved by introducing ACmix and EUCB. The recognition accuracy of the improved YOLO-AE model is improved by 2.1%, and the detection time is shortened by 40%, which significantly improves the detection performance and shortens the inference time. The region segmentation and convolution neural network algorithm are used to distinguish the proportion parameters of each grade in tea in real time, and the accurate wind selection parameters are obtained by combining the winnowing theory. The recognition accuracy of the verification set of the recognition model attains 94%. The MAP (0.5:0.95) is 0.93. A test on the tea winnowing parameter control test bench reveals that the identification accuracy of tea materials with different proportions is consistent. Additionally, the difference between the two batches of high-quality white tea is less than 3%. The winnowing scheme proposed in this study can provide the basic theory and technical support for the design of tea precision winnowing equipment.

PurposeThis study aims to investigate the suitability of summer-plucked fresh tea leaves (FTL-GT) for green tea production, challenging the common experience-based claim of their unsuitability. It seeks scientific evidence to support or refute this claim.Design/methodology/approachThe study comprehensively analyzes the taste properties of green tea (GT) made from FTL-GT, including non-volatiles like polyphenols, caffeine, free amino acids, total sugar and L-theanine. Various indices during processing, such as dose-over-threshold (Dot) factors, catechin quality index (CQI), phenol/amino ratio (PAR) and non-esterified/esterified catechins ratio (NER). Additionally, sensory evaluation is conducted.FindingsFTL-GT exhibits high CQI (256.38) and NER (0.58) and low PAR (5.37), indicating its suitability for producing high-quality GT. Green tea made from FTL-GT contains high catechin content and exhibits strong, mellow and umami-like tastes. EGCG, caffeine and L-theanine with high Dot factors of 680.47, 250.89 and 16.69, respectively, are identified as key contributors to the astringent, bitter and umami-like tastes in GT. Cysteine, with a Dot factor of 6.55, is the primary compound responsible for the sweet taste.Research limitations/implicationsThis study primarily focuses on the taste properties of green tea made from summer-plucked fresh tea leaves but does not explore potential variations in other quality attributes such as aroma or appearance. Additionally, the study was conducted using a specific set of tea leaves and processing methods, limiting the generalizability of the findings. Implications for the tea industry include the potential to expand production seasons and improve the quality of green tea by utilizing summer-plucked leaves.Practical implicationsThe study suggests that tea producers can consider using summer-plucked fresh tea leaves for green tea production, potentially expanding their production seasons and increasing yield. This could lead to more sustainable tea farming practices and higher quality green tea products. Additionally, the identified taste-active compounds and indices can guide tea processors in optimizing production methods to enhance the taste profiles of green tea.Social implicationsBy demonstrating the suitability of summer-plucked fresh tea leaves for green tea production, this study could contribute to the economic development of tea-growing regions by providing farmers with an additional source of income. Furthermore, the promotion of high-quality green tea made from these leaves could enhance cultural appreciation and consumption of tea, fostering a deeper connection to traditional tea practices and encouraging healthy lifestyles among consumers.Originality/valueThe originality of this study lies in its comprehensive analysis of the taste properties of green tea made with summer-plucked fresh tea leaves, which challenges the commonly held belief based on experience that these leaves are not suitable for green tea production. The study provides scientific evidence to support the suitability of FTL-GT for green tea production and reveals the taste profiles of summer green tea. This information serves as a valuable reference for the tea industry and researchers interested in optimizing green tea production and quality.

This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.

Mulberry (Morus alba L.) leaves from two cultivars, Yai-Burirum (YB) and Khunphai (KP), were prepared into green tea (GT) and black tea (BT). Compared to fresh leaf (FL) extract, GT and BT extracts were evaluated for their total phenolic and total flavonoid contents. Total phenolic content (TPCs) in all samples ranged between 129.93 and 390.89 mg GAE/g extract. The processing of tea decreased the levels of TPC when compared to FL extracts in both cultivars. The total flavonoid content (TFCs) in all samples was found in the range of 10.15–39.09 mg QE/g extract and TFCs in GT and BT extracts were higher than FL extracts. The change in tryptophan, melatonin, phenolic and flavonoid contents was investigated by liquid chromatography–mass spectroscopy (LC-MS). The results exhibited that tryptophan contents in all samples were detected in the range 29.54–673.72 µg/g extract. Both GT and BT extracts increased tryptophan content compared to FL extracts. BT extracts presented the highest amounts of tryptophan among others in both cultivars. Phenolic compounds were found in mulberry leaf extracts, including gallic acid, caffeic acid, gentisic acid, protocatechuic acid and chlorogenic acid. Chlorogenic acid presented the highest amount in all samples. Almost all phenolic acids were increased in the processed tea extracts except chlorogenic acid. Rutin was the only flavonoid that was detected in all extracts in the range 109.48–1009.75 mg/g extract. The change in phenolic and flavonoid compounds during tea processing resulted in the change in antioxidant capacities of the GT and BT extracts. All extracts presented acetylcholinesterase enzyme (AChE) inhibitory activity with IC50 in the range 146.53–165.24 µg/mL. The processing of tea slightly increased the AChE inhibitory effect of GT and BT extracts. In conclusion, processed tea from mulberry leaves could serve as a new alternative functional food for health-concerned consumers because it could be a promising source of tryptophan, phenolics and flavonoids. Moreover, the tea extracts also had antioxidative and anti-AChE activities.

This paper addresses the low level of intelligence in tea processing equipment in Enshi Prefecture by designing an intelligent withering control system based on the STMicroelectronics 32-bit Microcontroller (STM32). This control system can achieve real-time monitoring of the withering environment and automate the control of heating and ventilation dehumidification modules. By integrating IoT technology, relevant users can view the tea production process via mobile devices, enabling intelligent and remote production operations. Application results show that the system operates stably, accurately measures temperature and humidity in the withering environment, and achieves a control precision of % through a fuzzy control algorithm. It effectively meets the needs of tea processing in Enshi Prefecture. The system not only optimizes traditional processing workflows, enhancing processing efficiency and tea quality, but also provides new technological means for tea processing enterprises, contributing to the development and upgrading of the local tea industry.