The aroma profile of sun-dried black tea (SBT) was identified by headspace solid–phase microextraction (HS–SPME) coupled with gas chromatography–mass spectrometry (GC–MS) and gas chromatography–olfactometry (GC–O). A total of 37 scents were captured by using the GC–O technique, and 35 scents with odor intensities ranging from 1.09 ± 1.93 to 9.91 ± 0.29 were identified. Twenty-one compounds were further identified as key odor-active compounds with odor activity values (OAVs) greater than or equal to one. These key odor-active compounds were restructured with their detected concentrations, and the aroma profile of the selected SBT sample was successfully imitated to a certain extent. An omission test was performed by designing 25 models and confirmed that (E)-β-damascenone, β-ionone, dihydro-β-ionone, linalool, and geraniol were the key odor-active compounds for the aroma profile of SBT. Meanwhile, phenylethyl alcohol, (E)-2-decenal, hexanal, and methyl salicylate were also important to the aroma profile of SBT. This study can provide theoretical support for the improvement of the aroma quality of sun-dried black tea.

The contents of secondary metabolites such as tea polyphenols, amino acids, caffeine, and volatile metabolites in fresh tea leaves are key factors determining the unique flavor and health attributes of finished tea products. However, differences in varieties, cultivation practices, and environmental conditions often lead to variations in these metabolites among fresh tea leaves, thereby affecting tea quality. In order to clarify the various internal and external factors that influence the formation of the quality of fresh tea leaves and their mechanism of action. This article mainly reviews the research on fresh leaf quality in the past decade. Firstly, it clarifies the molecular basis of metabolic differences among varieties. Then, it summarizes the regulatory mechanisms of underground (soil, microorganisms) and above-ground (light, temperature, humidity) environments on key metabolic pathways, and focuses on evaluating the effects of intercropping, fertilization, and other cultivation measures on improving tea quality. This review found that the specific gene expression of varieties, the transmission of environmental signals, and cultivation interventions jointly drive the synthesis and accumulation of tea polyphenols, amino acids, caffeine, and aroma substances. However, no one has ever systematically reviewed it. Therefore, it provides certain theoretical references for improving the quality of fresh leaves.

China’s Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. In external validation, the mAP of the model outperforms other deep learning networks such as Faster-RCNN, SSD, and the original YOLOv8n, with improvements of 14.34%, 8.85%, and 2.18%, respectively. In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science.

Post-fermented Pu-erh tea (PFPT) is a microbial fermented tea characterized by unique sensory attributes and multiple health benefits. Aspergillus niger is the dominant fungus involved in the fermentation process and plays a significant role in imparting the distinct characteristics of PFPT. To investigate the role of Aspergillus niger in the fermentation of Pu-erh tea, this study inoculated unsterilized sun-dried green tea with Aspergillus niger isolated from Pu-erh tea to enhance the fermentation process. Metabolites and microbial communities in sun-dried green tea (CK), fortified fermented tea (TF), and naturally fermented tea (NF) were analyzed using non-targeted metabolomics, 16S rDNA, and internal transcribed spacer sequencing. Non-targeted metabolomics revealed that Aspergillus niger significantly altered the metabolite profile of the tea samples, identifying a total of 200 different metabolites, with 95 showing significant increases and 105 significant decreases, predominantly enriched in metabolic pathways associated with amino acid biosynthesis and degradation. High-throughput sequencing revealed that although the relative abundance of the fungal community remained largely unchanged, the inoculation of Aspergillus niger significantly increased the abundance of Bacillales and Pseudomonas within the bacterial community, thereby influencing the dynamic balance of the microbial ecosystem. Collectively, the inoculation of Aspergillus niger altered the composition of the microbial community and metabolic activities, resulting in changes to the content of amino acid-dominated metabolites, thereby enhancing the flavor profile and overall quality of Pu-erh tea. These findings provide important insights for optimizing the production processes of Pu-erh tea and the application of microorganisms in other fermented foods.

To investigate the flavour evolution mechanism of raw Pu-erh tea (RPT) during storage, the volatile and non-volatile compounds of RPT with different storage years (1–10 years) from the same raw material origin, manufacturer, and storage location in Wenshan Prefecture, Yunnan Province, were systematically analysed by HPLC, HS-SPME-GC-MS, and OAV. The results showed that both cluster analyses based on non-volatile and volatile compounds could classify RPT of different storage years into three ageing cycles, with key turning points in the third and eighth years of storage, which is also accompanied by the colour changing from green to orange or brown, the aroma changing from a faint scent to woody and ageing, the astringency diminishing, and the sweet and mellow increasing. Theophylline was identified as the potential marker of RPT stored 1–3 years, while (−)-catechin gallate, (−)-gallocatechin gallate, quercetin, and rutin as those for a storage of 9–10 years. The volatile compounds indicate a general trend of an initial increase followed by a decrease. Forty-four key aroma compounds (OAV ≥ 1) were identified. Eucalyptol, β-Caryophyllene, 2-Amylfuran, Copaene, Estragole, and α-Terpinene originated as potential markers for RPT stored 1–3 years, while (Z)-Linalool oxide (furanoid), α-Terpineol, Terpinen-4-ol, and cis-Anethol were for RPT stored 8–10 years. This study revealed the flavour characteristics and quality changes of RPT over the course of storage, and constructed a sensory flavour wheel, providing theoretical underpinnings for the quality control and assessment of RPT.

To elucidate the regional flavor characteristics of sun-dried green tea (SDT) and their underlying influencing factors, a comprehensive analysis was conducted using metabolomics and flavoromics approaches. This study systematically examined SDT samples and their corresponding tea garden soils from 13 distinct regions in Yunnan Province. The results revealed that the SDT samples could be classified into two distinct groups based on their flavor profiles. Compared to the regions of Pa Sha (PS), Bang Dong (BD), Dong Ban Shan (DBS), Dong Guo (DG), Su Hu (SH), Gua Feng Zhai (GFZ), and Wu Liang Shan (WLS), the regions of Xin Nong (XN), Ba Ka Nuan (BKN), Mang Ang (MA), Man Nuan (MN), Bing Dao (BDao), and Bin Shan (BS) exhibited a significant upregulation of the tea polyphenols (TP)/free amino acids (FAA) ratio. The former group was characterized by a sweet mellow taste, while the latter displayed a stronger taste profile. Furthermore, the analysis of volatile compounds demonstrated that geraniol and linalool were significantly upregulated in the PS, BD, DBS, DG, BS, and BDao regions, which were associated with tender and floral aromas. In contrast, isophorone, 2-pentyl furan, 1-octanol, D-limonene, and benzaldehyde were markedly enriched in the XN, BKN, MA, MN, SH, GFZ, and WLS regions, contributing to sweet and honey-like aromatic profiles. Altitude and mineral element phosphorus are potential key factors affecting the regional flavor differences in SDT. Specifically, SDT cultivated at higher altitudes and in soils with elevated available phosphorus content exhibited a greater likelihood of accumulating sweet mellow and floral compounds. This study provides scientific evidence for understanding the characteristic flavor profiles of SDT across different regions, offering valuable insights into the factors contributing to regional flavor differentiation in tea production.