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 explore the effects of different withering methods on the quality of Congou black tea, this study focused on five different withering methods: natural withering, warm-air withering, sun–natural combined withering, sun withering, and shaking withering. Gas chromatography‒mass spectrometry (GC‒MS), high-performance liquid chromatography (HPLC), and ion-exchange chromatography techniques were used to analyze the nonvolatile and volatile components and composition of the tea. The results revealed significant differences (p < 0.05) in the contents of nonvolatile constituents including caffeine, polyphenols, soluble sugars, free amino acids and their components, theaflavins, thearubigins, and catechins among the five different withering methods, with varying degrees of correlation between these components. A total of 227 aroma compounds were detected, and significant differences in the contents of alcohols, aldehydes, and ketones were observed. A relative odor activity value (ROVA) analysis of the aroma compounds revealed that 19 compounds had an ROVA > 1. Among them, benzylaldehyde, trans-2-decenal, decanal, benzaldehyde, nonanal, hexanal, trans-linalool, and geraniol from the shaking withering method had significantly higher ROVA values than those from the other withering methods, which may be the reason for the prominent floral and fruity aroma of shaking withering. This study revealed the impact of different withering methods on the quality of Congou black tea, providing a scientific basis for the development of Congou black tea with different flavors and the improvement of Congou black tea processing techniques.

To investigate the variation in flavonoids content in ancient tree sun–dried green tea under abiotic stress environmental conditions, this study determined the flavonoids content in ancient tree sun−dried green tea and analyzed its correlation with corresponding factors such as the age, height, altitude, and soil composition of the tree. This study uses two machine−learning models, Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression, to build a predictive model based on the selection of effective variables. During the process, bootstrap was used to expand the dataset for single−factor and multi−factor comparative analyses, as well as for model validation, and the goodness−of−fit was assessed using the Akaike information criterion (AIC). The results showed that pH, total potassium, nitrate nitrogen, available phosphorus, hydrolytic nitrogen, and ammonium nitrogen have a high accuracy in predicting the flavonoids content of this model and have a synergistic effect on the production of flavonoids in the ancient tree tea. In this prediction model, when the flavonoids content was >6‰, the area under the curve of the training set and validation set were 0.8121 and 0.792 and, when the flavonoids content was >9‰, the area under the curve of the training set and validation set were 0.877 and 0.889, demonstrating good consistency. Compared to modeling with all significantly correlated factors (p < 0.05), the AIC decreased by 32.534%. Simultaneously, a visualization system for predicting flavonoids content in ancient tree sun−dried green tea was developed based on a nomogram model. The model was externally validated using actual measurement data and achieved an accuracy rate of 83.33%. Therefore, this study offers a scientific theoretical foundation for explaining the forecast and interference of the quality of ancient tree sun−dried green tea under abiotic stress.

To explore the changes in epigallocatechin gallate (EGCG) content in tea under abiotic stress conditions, we collected tea samples, along with corresponding soil and altitude data, and utilized the measured data for single-factor analysis. At the same time, the LASSO regression method, which is rarely used in agriculture, was employed to screen modeling factors, a prediction model was established, and the Akaike information criterion (AIC) was introduced to compare the goodness of fit. The results show that LASSO screening reduced the AIC value of the model by 13.8%. The average area under the curve of the training set and the validation set was 0.81 and 0.76, respectively, and the calibration curve also showed good consistency. Based on the nomogram model, a visual prediction system was developed, and the content prediction curve was introduced for detailed soil evaluation. The accuracy rate reached 75% after external verification. This study provides a theoretical basis for elucidating the prediction and intervention of Pu’er tea quality under abiotic stress conditions.

Tea (Camellia sinensis) is consumed worldwide for its numerous benefits and China lead the world production. In March 2023, leaf spots were observed on approximately 10% of tea plants in a 50-ha commercial tea plantation in Menghai (21°46'13"N, 100°30'6"E), Yunnan, China. Initial symptoms appeared as small spots, which progressively expanded and spread over the entire leaf surface. Subsequently, pale pink mold layers developed from the lesions (Fig. S1). To isolate the pathogen, small leaf pieces (3 × 3 mm) were cut from the margins of the lesions, sterilized with 75% ethanol for 30 sec and 0.5% NaClO for another 30 sec, and rinsed three times with sterile water. The pieces were placed on acidified potato dextrose agar (PDA) plates and incubated in darkness at 28°C. A total of 15 fungal isolates with identical morphologies were collected. The colonies appeared pale pink with white mycelia initially then turned orange-pink at the center and light white at the edges. After 10-15 days, exhibiting a powdery texture and concentric rings with uniform edges. Conidia were found at the apex peduncle and were inverted pear-shaped or oval, either non-septate (15.3 ± 2 × 7.8 ± 1.8 μm in size, n = 60) or septate, with a slightly constricted spore base featuring papillary projecvtions (14.8 ± 1.5 × 7.4 ± 0.7 μm in size, n = 60). The morphology closely resembled Trichoderma roseum (Oh et al. 2014). To confirm the species, the strain CYB5 was selected for identification by sequencing the ribosomal internal transcribed spacer (ITS) and large subunit (LSU) genes using polymerase chain reaction (PCR) (White et al.1990). The ITS (GenBank accession OR889657) and LSU (PQ270526) gene sequences exhibited 98% similarity with the Trichoderma roseum sequence KP317992 from NCBI database. A phylogenetic tree was constructed using MEGA 11 (Felsenstein 1981) based on the concatenated sequences (ITS and LSU) of the strain CYB5 and reference strains (Fig. S2). The analysis confirmed that CYB5 is T. roseum (Inácio et al. 2011). Pathogenicity tests were conducted on detached healthy tea leaves placed on wet filter paper in petri dishes. Micro-wounds were made on leaves using a sterilized needle, followed by inoculation with a 6-mm plug of CYB5. Control leaves were inoculates with fungus-free agar disks. The dishes were incubated at 25°C in the dark for 7 days. The leaves inoculated with CYB5 developed reddish brown to dark brown lesions around the inoculated sites, while control leaves remained asymptomatic. The fungus was reisolated from the lesion, and the isolates were morphologically identical to the original cultures. A second pathogenicity test was conducted on potted tea plants of the cultivar 'Yunkang No. 10.' Three plants scratched with a needle and three non-wounded plants were inoculated by spraying 20 ml of a spore suspension (105 spores/ml) of CYB5. Plants sprayed with sterile water served as controls. All plants were maintained in a growth chamber at 28°C, and 70% relative humidity. The lesions developed three days post-inoculation, and typical symptoms appeared after 10 days on spore-inoculated plants only. T. roseum was reisolated and reidentified based on the morphology and molecular analyses, thus fulfilling Koch's postulates. To our best knowledge, this is the first report of T. roseum causing tea leaf rot in China.