• Light-wave and conventional fixation methods for green tea were compared. • Light-wave-dried tea leaves (LWL) exhibited jade green leaves, fresh and mellow taste. • Fixation produces more amino acids, peptides, flavonoids and trans-catechins. • The fresh and mellow taste of LWL is related to its high level of γ-glutamyl peptides. • Pinocembrin, phloretin and bitter peptides caused the bitterness of roller-dried tea.

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.

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 (R_p² = 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.