Altitude and picking period affect the quality of Lushan Yunwu tea: Insights from sensory and metabolomic analysis

Abstract

Lushan Yunwu tea (LYT) is recognized as one of China's top ten famous teas, with a long-standing reputation. However, the relationship between LYT quality at different altitudes and picking periods remains unclear. Hence, this study systematically explored the synergistic effects of these two factors on LYT quality. The results revealed significant differences in the taste and aroma profiles of LYT across different altitudes and picking periods. This study demonstrated that the first-picked LYT from medium-to-high altitudes exhibited superior quality with distinct characteristics at different elevations. In the first pick, teas from medium to high altitudes contained more umami and sweet amino acids, whereas those from higher altitudes exhibited higher levels of aromatic compounds, contributing to intense floral, woody, and fruity flavors. Furthermore, the caffeine, theobromine, catechin, and gallic acid contents declined with increasing altitude in the first-picked LYT. In contrast, the contents of these four components were significantly higher in the second-picked LYT from medium-to-high altitudes than in the first-picked LYT. Finally, a multi-parameter flavor wheel was developed for LYT quality, incorporating nine key taste-active and 13 key aroma-active compounds. The findings demonstrated that altitude and picking period act as interdependent drivers of tea quality, which jointly shape its characteristics through their combined effects on temperature and light exposure. These results provide a theoretical basis for understanding the mechanism of LYT quality formation and offer practical guidance for the cultivation and processing of high-quality LYT.

Highlights

• •Altitude and picking periods are key factors affecting LYT quality.
• •First-pick LYT at mid-to-high altitude exhibits superior quality to second-pick.
• •High-altitude first-pick LYT has more sweet amino acids and complex aroma.
• •Second-pick LYT has more catechins, caffeine & theobromine.
• •Middle-altitude first-pick LYT has more sweet-taste and umami taste amino acids.

1. Introduction

As a variety of green tea, Lushan Yunwu tea (LYT) possesses unique taste and quality characteristics, primarily influenced by the cloudy, fog-enshrouded, and cool climate of Lushan Mountain. LYT is characterized by its “mellow taste, vibrant color, fragrant aroma, and clear infusion,” which is persistently pursued by consumers (Liu et al., 2025). Lushan Mountain is located in the northern part of Jiangxi Province, China (Sun, Wu, et al., 2024), and features a subtropical humid mountain climate characterized by four distinct seasons, abundant rainfall, significant daily temperature fluctuations, and continuously changing clouds and fogs throughout the year. The annual average temperature at Lushan Mountain, at an altitude of 1164.5 m, is 11.9 °C, which is 5.7 °C lower than that at an altitude of 37.1 m. The average temperature decreases by approximately 0.5 °C for every 100 m increase in altitude. The unique climate, altitude, and other ecological factors of the Lushan Mountain contribute to the distinctive flavor profile of LYT (Liu et al., 2025; Yan et al., 2022).

Tea (Camellia sinensis) is a subtropical, shade-tolerant, perennial plant. Its yield and quality are closely related to the ecological environment. The microclimate of tea-growing regions, characterized by abundant cloud cover, precipitation, and sunlight, is crucial for enhancing the concentration of quality compounds, such as catechins (Cs) and amino acids, thereby improving its flavor profile. Elevation of tea plantations is a critical factor influencing tea quality. Previous studies have shown that higher elevations can significantly enhance tea quality (Han et al., 2017; Nicole et al., 2018). This elevation affects the biochemical components of tea (Wang, Hua, et al., 2021) and influences the development of aroma (Jiang et al., 2021; Wang, Cao, et al., 2021). Tea produced at higher altitudes typically exhibits superior freshness and sweetness, along with reduced astringency and bitterness (Kfoury et al., 2018; Wang, Du, et al., 2022). Furthermore, the enhanced aroma profile at high altitudes is likely attributable to the increased synthesis of volatile organic compounds, such as linalool and geraniol, under cooler stress conditions (Wang, Li, et al., 2022).

Multiple factors influence the chemical composition of tea leaves, with the picking period being a crucial determinant that leads to significant variations in tea quality (Chen et al., 2024; Ma et al., 2023). Green tea infusions from different picking periods exhibit distinct characteristics, including color, aroma, and flavor. Spring brings abundant rainfall, and after enduring prolonged winter dormancy, tea plants accumulate a wealth of nutrients in the preceding season (Kang et al., 2023; Sun, Yu, et al., 2024). Moreover, the freshness of tea leaves is a vital factor affecting tea quality. One criterion for harvesting tea leaves is that the buds and leaves must be tender. Tea leaves harvested during the early germination or late growth stages are tender, nutrient-rich, and of high quality, whereas those harvested during the mid-growth period tend to be older, with reduced content and lower quality (Kang et al., 2023; Wang et al., 2024).

The foundation of this field was established by early studies that reached a consensus: both high-altitude cultivation and early spring picking are associated with superior tea quality (Han et al., 2017). Subsequent studies have further refined this understanding, reporting higher amino acid content in high-altitude teas (Sun, Wu, et al., 2024) and distinct volatile profiles in the first-picked leaves (Kang et al., 2023). However, most existing studies have examined only the isolated effects of individual factors (e.g., altitude or picking time) on a limited range of chemical components, such as aroma and taste compounds. Comprehensive investigations that systematically explore how altitude and picking time synergistically regulate LYT quality, integrating sensory, taste, and aroma profiles, remain scarce.

This study was designed to comprehensively analyze the relationships among aroma compounds, flavor substances, and LYT quality across various altitudes and multiple picking periods. Eighteen LYT samples from different altitudes and picking periods were used for sensory evaluation. In addition, high-performance liquid chromatography (HPLC), ultra-performance liquid chromatography (UPLC), and headspace solid-phase microextraction gas chromatography–mass spectrometry (HS-SPME-GC–MS) were used to investigate the aroma compounds and flavor substances present in LYT. This study enhances our understanding of the influence of altitude and different picking periods on tea metabolites and quality.

2. Materials and methods

2.1. Sample collection

A total of 18 LYT samples were collected from a local cultivar grown at three different altitudes on Lushan Mountain (29°33′34″N, 115°59′36″E): 100–300 m (low altitude), 600–800 m (medium altitude), and 1000–1200 m (high altitude) (Table S1). All tea plants were grown using the same cultivation practices. The picking standards for fresh leaf samples consisted of one bud and one leaf, and the samples were prepared in accordance with the standardized LYT processing guidelines (GB/T22109–2008, Code of Practice for Lushan Yunwu Green Tea Processing). At each altitude, two picking periods were conducted; the second picking period involved buds and leaves that developed after the first picking. All the tea samples were collected in triplicate.

2.2. Sensory evaluation

The sensory evaluation of LYT was conducted in accordance with relevant national standards, specifically “Methodology for Sensory Evaluation of Tea” (GB/T 23776–2018) and “Tea Vocabulary for Sensory Evaluation” (GB/T 14487–2017). A tea sample weighing 3.0 g was placed in an evaluation cup, followed by the addition of 150 mL of boiling water. The cup was then covered with a lid, and the tea infusion was filtered after 4 min. A blinded assessment was performed by a panel of three qualified tea evaluation experts. The results were scored on a 100-point scale. The overall score of the final sensory evaluation was calculated using the following weighted formula: Total score = appearance × 25 % + soup color × 10 % + aroma × 25 % + flavor × 30 % + leaf bottom × 10 %.

The scores were subjected to significance testing using analysis of variance, followed by Duncan and Tukey's HSD test.

2.3. Determination of amino acid composition

The contents of 18 amino acids were determined using UPLC according to a validated method (Jin et al., 2021; Liu et al., 2025) with minor modifications. Chemicals for UPLC were provided in Table S2. Briefly, the tea samples were extracted using ultrapure water, vortexed, ultrasonicated, and centrifuged. The supernatant was filtered through a 0.22-μm membrane before UPLC analysis. Chromatographic separation was performed using a C18 column (100 × 2.1 mm, 1.7 μm) maintained at 35 °C. Details of the mobile phase composition and elution gradient are provided in the Supplementary Materials (Supplementary Method 1). All samples were analyzed in triplicate (n = 3) with randomized injection orders to reduce analytical bias.

2.4. Determination of Cs, theobromine (TB), gallic acid (GA), and caffeine (CAF) composition

HPLC was used to analyze Cs, GA, TB, and CAF components, including catechin (C), epicatechin (EC), gallocatechin (GC), catechin gallate (CG), epigallocatechin (EGC), epicatechin gallate (ECG), gallocatechin gallate (GCG), epigallocatechin gallate (EGCG), CAF, TB, and GA (Jin et al., 2021; Liu et al., 2025), with minor modifications. Chemicals for HPLC were provided in Table S2. Briefly, tea samples were extracted with 70 % methanol in a 70 °C water bath with periodic vortexing. The extracts were centrifuged and filtered before analysis. Separation was performed on a Thermo Hypersil GOLD Phenyl column (250 × 4.6 mm, 5 μm) at 35 °C, with detection at 278 nm. Details of the mobile phase composition and elution gradient were provided in the Supplementary Materials. All samples were analyzed in triplicate (n = 3), and the injection order was fully randomized to minimize the instrument drift.

2.5. Analysis of volatile metabolites

LYT volatile compounds were extracted using HS-SPME-GC–MS, as described in our previous studies (Gao et al., 2024; Liu et al., 2025). The chemicals used for HS-SPME-GC–MS were listed in Table S2. Volatile compounds were extracted using HS-SPME with a DVB/CAR/PDMS fiber (50/30 μm, 1 cm; Bellefonte, PA). Separation and detection were performed using a Thermo TSQ 8000 GC–MS system (TriPlus RSH autosampler) equipped with a 30 m × 0.25 mm, 0.25 μm TG-5MS column (Thermo Fisher).

2.6. Data analysis

Excel 2019 was used for preliminary data processing. Significance testing and hierarchical cluster analysis (HCA) were performed using Metware Cloud (https://cloud.metware.cn). Data were analyzed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) on the MetaboAnalyst platform (Liu et al., 2025; Sun, Wu, et al., 2024; https://www.metaboanalyst.ca/). Heat maps were generated using TBtools version 1.120. The validity and reliability of the discriminant model were assessed using 100 random permutation tests, with a variable importance projection (VIP) threshold set at >1 for selecting significant variables. The taste activity value (TAV) and odor activity value (OAV) were calculated as previously described (Gao et al., 2024; Liu et al., 2025).

3. Results

3.1. Sensory evaluation analysis

Sensory evaluation revealed that the combined scores for liquor color, dry tea leaf appearance, tea soup aroma, taste, and infused leaf morphology ranged from 86.90 to 92.50 (Table S3), with significant differences observed among the six LYTs according to Duncan's and Tukey's HSD test (P < 0.05). The HT1 (high altitude, first picking) received the highest score, followed by MT1 (medium altitude, first picking), LT1 (low altitude, first picking), HT2 (high altitude, second picking), MT2 (medium altitude, second picking), and LT2 (low altitude, second picking). Tea samples of LYT grown at different altitudes exhibited diverse characteristics in flavor, liquor color, and infused leaf morphology. Liquor color analysis indicated that the low-altitude samples were predominantly yellowish-green, whereas those from medium and high altitudes were primarily green. Notably, the higher the altitude, the darker the liquor color. Taste analysis revealed that MT1, HT1, and HT2 had a sweet aftertaste. The higher the altitude and the earlier the picking time, the fresher and sweeter the taste. The analysis of the appearance of the dry tea leaves revealed that HT1, MT1, and LT1 were wiry, blooming, and slightly tippy, whereas HT2, MT2, and LT2 were slightly wiry, slightly blooming, and moderately tippy. All the samples exhibited a clean and refreshing aroma, with HT1 and MT1 demonstrating floral aromas. Furthermore, the aroma persisted for a longer duration at higher altitudes than at lower ones. At the same altitude, samples from the first picking period were cleaner, more refreshing, and had a longer-lasting aroma than those from the second picking period. LYT samples from different picking times exhibited distinct and mesh appearances in their dry tea leaves; the first-harvest samples were slightly tippy, whereas the second-harvest samples were more tippy. These findings indicate that altitude and picking time are significant factors influencing tea quality, leading to variations in the appearance, aroma, and taste of tea.

3.2. Content and contribution value of amino acid compounds at different altitudes and picking periods of LYT

3.2.1. Content of amino acid components

The flavor of tea is predominantly influenced by its amino acids (Mao et al., 2018; Yue et al., 2023). A comprehensive analysis identified 18 distinct amino acids in all LYT samples using HPLC. The total ion chromatogram (TIC) is shown in Fig. S1. Among these amino acids, L-theanine (The) exhibited the highest concentration (12.19 ± 0.13 to 19.44 ± 0.49 mg·g⁻¹), whereas glycine (Gly) exhibited the lowest (0.03 ± 0.00 to 0.34 ± 0.04 mg·g⁻¹). During the first picking period, significant variations in total amino acid content were observed among the three altitudes: LT1 (25.363 ± 0.316 mg·g⁻¹), MT1 (39.409 ± 1.195 mg·g⁻¹), and HT1 (33.382 ± 1.269 mg·g⁻¹). In the second picking period, the total amino acid content did not differ significantly between LT2 (31.679 ± 1.011 mg·g⁻¹) and MT2 (32.294 ± 1.745 mg·g⁻¹); however, both were significantly higher than HT2 (27.048 ± 0.453 mg·g⁻¹) (Fig. S2). Notable variations in amino acid levels were also observed between the two picking periods at the same altitude.

Amino acids contribute to various taste profiles, including sweetness, umami, sourness, and bitterness, and are widely recognized as key determinants of tea flavor (Mao et al., 2018; Yue et al., 2023). Analysis of taste-active amino acids revealed that umami-tasting amino acids ranged from 17.457 ± 0.308 to 25.99 ± 0.732 mg·g⁻¹, sweet-tasting amino acids from 2.767 ± 0.037 to 6.771 ± 0.254 mg·g⁻¹, and bitter-tasting amino acids from 4.648 ± 0.081 to 7.508 ± 0.417 mg·g⁻¹ (Fig. S2). The umami-tasting amino acid content exhibited distinct altitude- and harvest-dependent patterns. In the first picking, MT1 exhibited significantly higher levels of umami-tasting amino acids than HT1 and LT1, which were comparable (Fig. S2). Conversely, LT2 and HT2 contained significantly more umami amino acids than MT2 in the second picking. Interestingly, the umami content increased at low altitude from the first to the second picking, whereas the opposite trend was observed at medium and high altitudes. For the bitter-tasting amino acid, levels first increased and then decreased with altitude in the first picking, but consistently increased with altitude in the second harvest. Both medium- and high-altitude LYT demonstrated significantly higher sweet-tasting amino acid levels than those at low altitude (Figs. 1, S2). Significant variations in sweet-tasting amino acids were observed between the picking periods at different altitudes. Meanwhile, the bitter-tasting amino acid content increased from the first to the second picking period at low and medium altitudes but decreased at high altitudes (Figs. 1, S2).

Fig. 1.

The total content of amino acid. Duncan's multiple range test, following analysis of variance (P < 0.05), assigned differing superscript letters to significant contrasts. The abbreviations LT, MT, and HT represent low, medium, and high altitude, respectively. The numbers following these abbreviations correspond to the picking period.

3.2.2. Comparative analysis of amino acid components

PCA of the 18 amino acids across LYT from various altitudes and picking periods revealed that the PCA model extracted two PCs with a fitting index of R² = 0.9865. This suggests that the model possesses robust explanatory power, stability, and predictive capability. The results indicated that LYT samples from the same altitude and picking period clustered together, whereas those from different altitudes and picking periods dispersed in the PCA model. The cumulative variance explained by the first two PCs was 75.9 %, with PC1 contributing 44.4 % and PC2 contributing 31.5 % (Fig. 2a). In addition, PC3 accounted for 13.7 % and PC4 for 7.4 % (Fig. S3-A). These findings demonstrate that the first two PCs adequately represented the 18 amino acids in all 18 LYT samples. The PCA biplot (Fig. 2c) illustrated that MT1 was strongly correlated with umami and sweet amino acids (such as The, Gly, Ala, Glu, etc.) in the positive PC1 axis region, whereas MT2 and LT2 exhibited strong correlations with bitter amino acids (such as Tyr, Ser, Leu, Val, Ile, Phe, etc.) in the negative PC1 axis region. Our PCA results revealed clear segregation among the tea samples processed at different picking periods and altitudes.

Fig. 2.

PCA, PLS-DA, and HCA analyses of amino acids. (a) PCA plot; (b) PLS-DA plot; (c); PCA biplot; (d) PLS-DA biplot; (e) VIP values; (f) HCA plot. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

Previous studies have demonstrated that PLS-DA can minimize within-group variation while maximizing between-group separation, thereby enhancing the discriminative power for characterizing sample differences (Sun, Wu, et al., 2024). To further identify the differential amino acid components of LYT, a PLS-DA model was constructed based on the amino acid content of the 18 LYT samples (Fig. 2b). R² represents the explanatory power of the PLS-DA model, whereas the predictive ability is indicated by Q², with values close to 1 indicating greater model efficacy. The R² value from the five-fold cross-validation was 0.9995, and the Q² value was 0.9986 (Fig. S4-A), indicating that this model could effectively distinguish LYT samples from different altitudes and picking periods. The PLS-DA results revealed that PC1 (42 %) and PC2 (22.5 %) together explained 64.5 % of the total variability, categorizing the 18 LYT samples into four groups: MT1, HT1, HT2-LT1, and LT2-MT2. The PLS-DA biplot further confirmed that MT1 was enriched in umami and sweet amino acids, whereas MT2 and LT2 contained higher levels of bitter amino acids (Fig. 2d).

In the PLS-DA model, the VIP values of the amino acids reflected their contribution to the classification of different altitudes and picking periods. A higher VIP value indicates greater differences in amino acid components across varying altitudes and picking periods. As shown in Fig. 2e, ten key amino acid components—methionine (Met), tyrosine (Tyr), serine (Ser), isoleucine (Ile), phenylalanine (Phe), valine (Val), leucine (Leu), aspartic acid (Asp), threonine (Thr), and arginine (Arg) —exhibited VIP values >1 (Tables 1, S4). This indicates that these ten amino acids exhibited significant differences among the various altitudes and picking periods, contributing substantially to the PLS-DA model.

Table 1.

Flavor substances with both VIP and TAV greater than 1 at different altitudes and picking periods.

Compound	Taste Characteristic	VIP values	Threshold (mg·g−1)	TAV
				LT1	LT2	MT1	MT2	HT1	HT2
Arg	Bitter	1.47	0.60	2.13	3.13	5.72	5.75	2.93	2.29
Asp	Umami	1.08	1.00	2.24	3.36	2.89	2.61	2.20	2.01
CAF	Bitter	1.29	1.00	41.11	41.04	39.63	47.45	35.36	40.82
CG	Astringent	1.24	0.12	1.40	1.37	1.24	1.75	1.02	1.38
EGC	Bitter, Astringent	1.13	0.11	119.88	116.93	104.49	183.86	94.29	128.33
GCG	Bitter, Astringent	1.38	0.03	26.84	27.04	21.45	35.46	13.06	18.65
TB	Bitter	1.24	0.30	12.84	12.72	11.02	15.06	5.25	11.67

We performed HCA to determine the relationships between the data points. The results indicated that the 18 LYT samples were categorized into four distinct clusters (Fig. 2f). Cluster 1 comprised MT1, cluster 2 comprised HT1, cluster 3 included LT1 and HT2, and cluster 4 included MT2 and LT2. These findings revealed significant variations in the amino acid profiles of LYT across different altitudes and picking periods, underscoring the critical influence of these factors on amino acid composition.

3.2.3. Key amino acid compounds identified by TAV

TAV comprehensively considers both the concentration of taste compounds and their taste thresholds, thereby avoiding the misconception that taste contribution can be determined solely by concentration. A TAV >1 indicates that a compound significantly contributes to taste quality, whereas a higher TAV corresponds to a greater contribution of a compound to the overall taste profile (Liu et al., 2025; Sun, Wu, et al., 2024). Based on the amino acid content of LYT samples from various altitudes and harvesting periods, and by referencing the taste thresholds of these compounds from the relevant literature (Liu et al., 2025), a taste contribution analysis was conducted on the analyzed samples (Tables 1, S4). Eight amino acids exhibited a TAV >1, including Arg, Asp, Glutamic acid (Glu), Histidine (His), Lysine (Lys), Met, The, and Val. They exhibited the highest TAV, ranging from 203.10 to 323.95, indicating that they were the most dominant taste-active compounds in the samples. Val showed TAV >1 only in MT2 and LT2, suggesting that it significantly contributes to taste perception in these specific groups. Conversely, Lys in LT1 exhibited TAV <1. When combined with a VIP >1 (Table 1), four key amino acids, Arg, Asp, Val, and Met, were identified as the primary taste-active compounds across the 18 samples.

3.3. Qualitative analysis of GA, CAF, TB, and Cs components at different altitudes and picking periods of LYT

3.3.1. Content of GA, CAF, TB, and Cs

CAF, GA, TB, and Cs are the primary contributors to the bitter taste of green tea (Zou et al., 2018; Li et al., 2022). Eight Cs were identified in all LYT samples: GCG, EC, EGC, EGCG, GC, ECG, C, and CG (Fig. S5). Among these Cs (Fig. S6), EGCG exhibited the highest content (78.3 ± 1.62 to 129.84 ± 0.72 mg·g⁻¹), followed by ECG (19.33 ± 1.45 to 27.44 ± 0.13 mg·g⁻¹) and EGC (10.47 ± 0.45 to 20.41 ± 0.24 mg·g⁻¹). The lowest content was observed for CG (0.12 ± 0 to 0.20 ± 0 mg·g⁻¹). At low altitudes, the total C content during the different picking periods showed no significant variations (P > 0.05). However, at medium and high altitudes, the total amount of Cs increased (MT2 > MT1 and HT2 > HT1). Moreover, the total CAF content decreased with increasing altitude during the first-picking period. In the second picking period, the total Cs initially increased and then decreased with increasing altitudes (Fig. 3). During the first picking period, CAF, TB, and GA levels were not significantly different between the low and medium altitudes (P > 0.05) but were significantly lower at high altitudes than at lower altitudes (P < 0.05). Compared with MT2, the TB and GA contents in HT2 and LT2 were significantly higher, with no significant difference between HT2 and LT2 (P > 0.05). In contrast, the CAF content exhibited an opposite trend during the second-picking period. In summary, the total CAF, GA, TB, and Cs contents had a limited influence on the taste of tea harvested during different periods at low altitudes, whereas these factors significantly influenced the taste of tea at medium and high altitudes.

Fig. 3.

The total content of CAF, Cs, TB, and GA. Duncan's multiple range test, following analysis of variance (P < 0.05), assigned differing superscript letters to significant contrasts. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

3.3.2. Comparative analysis of GA, CAF, TB, and Cs components

PCA was conducted on the GA, CAF, TB, and Cs content of the LYT samples collected from various altitudes and picking periods. The model (Fig. 4a) extracted two PCs with a fitting index of R² = 0.9955, demonstrating strong explanatory power, stability, and predictive ability. The two PCs accounted for 88.9 % of the cumulative variance, with PC1 and PC2 contributing 75.6 % and 13.3 %, respectively (Fig. S3—B). The PCA results revealed that HT2 and LT2 clustered together, suggesting that they shared similar Cs, TB, CAF, and GA compositions. In contrast, LT1, HT1, MT2, and MT1 were distinctly separated in the PCA model, indicating differences in their Cs, TB, CAF, and GA contents. The PCA biplot illustrated that LT1, LT2, MT2, and HT2 contained relatively higher levels of CAF, CG, C, GCG, EC, EGCG, TB, EGC, GC, and ECG (Fig. 4c).

Fig. 4.

PCA, PLS-DA, and HCA analyses of Cs, GA, and CAF. (a) PCA plot; (b) PLS-DA plot; (c); PCA biplot; (d) PLS-DA biplot; (e) VIP values; (f) HCA plot. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

To further investigate the differential biochemical components in LYT across various altitudes and picking periods, a PLS-DA model was used, followed by a randomized permutation test on the data. The model yielded R² = 0.9925 and Q² = 0.9752, confirming its stability and strong predictive performance (Fig. S4—B). The PLS-DA results demonstrated a clear separation of LYT samples from different altitudes and picking periods, with better discrimination than that of PCA. PC1 and PC2 accounted for 74.5 % and 10.3 % of the variance, respectively, resulting in a cumulative variance of 84.8 % (Fig. 4b). The PLS-DA biplot further illustrated that LT1, LT2, MT2, and HT2 were rich in CAF, CG, C, GCG, EC, EGCG, TB, EGC, GC, and ECG (Fig. 4d). Based on the VIP >1 criterion, five differential biochemical markers were identified: GCG, TB, CAF, CG, and EGC (Fig. 4e).

HCA grouped 18 LYT samples into four distinct clusters (Fig. 4f). Cluster 1 (C1) comprised MT2; C2 included HT1; C3 contained MT1; and C4 encompassed LT1, HT2, and LT2. These findings were consistent with the results obtained from the PCA (Fig. 4a) and PLS-DA (Fig. 4b).

3.3.3. TAV analysis of GA, CAF, TB, and Cs components

The TAV values of GA, CAF, TB, and Cs in LYT across various altitudes and picking periods (Tables 1, S4) indicated that all LYT samples of GA, CAF, TB, and Cs exhibited TAVs >1, demonstrating their significant influence on the flavor profile of the LYT. EGCG exhibited the highest TAV values, ranging from 797.51 (HT1) to 1338.59 (MT2). Using PLS-DA, five compounds that exceeded both the VIP and OAV thresholds (both >1) were identified as the key components across the three altitudes and during the two picking periods of LYT: GCG, TB, CAF, CG, and EGC (Table 1).

3.4. Content and contribution value of volatile components at different altitudes and picking periods of LYT

3.4.1. Content of volatile components

HS-SPME-GC–MS was used to investigate the effects of altitude and picking period on the aroma profile of LYT. The total ion chromatograms are shown in Fig. S7. A total of 50 aroma compounds were detected in LT1, 46 in LT2, 45 in MT1, 49 in MT2, and 49 in HT1 and HT2 (Tables S5, S6). Among the identified aroma compounds, there were 18 alcohols, 2 aldehydes, 12 alkanes, 5 esters, 1 indole, 2 ketones, 1 phenol, and 12 terpenoids. Significant differences were observed in the types and concentrations of aroma substances in tea samples from different altitudes and picking periods. In LT1, HT1, and HT2, alcohols constituted the highest proportion of compounds, accounting for 42.32 %, 51.96 %, and 46.78 %, respectively (Fig. 5a, e, and f). This was followed by alkanes (31.17 %, 28.83 %, and 28.98 %) and terpenoids (11.93 %, 8.80 %, and 9.62 %). In LT2, MT1, and MT2, alkanes were the most abundant compounds, comprising 47.03 %, 57.56 %, and 49.14 %, respectively (Fig. 5b, c, d), followed by alcohols at 32.19 %, 25.77 %, and 35.01 %, respectively, and terpenoids at 12.33 %, 7.03 %, and 7.16 %, respectively. Esters were the fourth most abundant aroma substances in LT1, MT1, MT2, and HT2, whereas aldehydes and indoles were the fourth most prevalent compounds in LT2 and HT1, respectively.

Fig. 5.

Categories and percentages of volatile components at different altitudes and picking periods. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

Moreover, the results indicated that the pronounced enrichment of aroma compounds in HT1 cultivated LYT underscores altitude as a critical determinant of tea fragrance potential (Fig. 6, Table S6). Linalool, a major contributor to the aroma of green tea, imparts a floral and fresh aroma. Its concentration was significantly elevated in the high-altitude LYT (HT1 and HT2) groups. Similarly, linalool oxide significantly increased with altitude, suggesting enhanced oxidation metabolism under high-altitude conditions. Geraniol, known for its floral and sweet aroma, is another important component of green tea's fragrance. The geraniol content was significantly higher in the high-altitude samples (HT1 and HT2). Furthermore, the concentration of benzyl alcohol was significantly increased in the high-altitude samples, whereas phenethyl alcohol levels were elevated in HT1. These aroma-active compounds exhibit dual floral-fruity characteristics, which substantially define the scent profile of the green tea. The cadinene content was significantly increased in the high-altitude LYT, and α-terpineol also showed higher levels in HT1. These compounds possess woody and floral aromas that potentially enhance the aromatic complexity of green tea. Additionally, the concentrations of 2,6,11-trimethyldodecane and 4,6-dimethyldodecane were significantly higher in the high-altitude samples. Although alkanes typically have weak odors, they may serve as precursors for aroma compounds or act synergistically with other substances.

Fig. 6.

Cluster heatmap visualization of volatile compound compositions. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

3.4.2. Comparative analysis of volatile components

The PCA results (Fig. 7a) extracted two PCs with a fitting index of R² = 0.9979, indicating excellent stability and predictive capability. The PC1 score was 78.4 %, the PC2 score was 10.0 %, and the total score was 88.4 % (Fig. 7a). These results demonstrate that the first two PCs effectively represented the 53 volatile compounds detected in the 18 LYTs samples. The PCA results demonstrated a clear separation between HT1, HT2 and MT2, MT1, LT1, and LT2, indicating significant differences in the aromatic compound composition. The PCA biplot revealed that HT1 contained the most aroma compounds at significantly higher concentrations, including linalool, E-nerolidol, benzyl alcohol, δ-cadinene, geraniol, phenylethyl alcohol, α-terpineol, 2,6,11-trimethyldodecane, dodecane,4,6-dimethyl-, etc. HT2 exhibited relatively higher levels of α-cedrene and trans-2-hexenylcaproate, whereas LT1 exhibited increased levels of phytol, methyl salicylate, and humulene (Fig. 7c).

Fig. 7.

PCA, PLS-DA, and HCA analyses of aroma substances. (a) PCA plot; (b) PLS-DA plot; (c); PCA biplot; (d) PLS-DA biplot; (e) VIP values; (f) HCA plot. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

PLS-DA modeling was further applied to evaluate the combined effects of altitude and picking period on the volatile fingerprints of LYT. The results (Fig. 7b) indicated that the R² value from the five-fold cross-validation was 0.9922, and the Q² value was 0.9722 (Fig. S4—C), demonstrating that the model was reliable and suitable for the discriminatory analysis of the 53 volatile components in the 18 LYT samples. The six tea samples were clearly separated in the PLS-DA score plot. The first two PCs explained 88.1 % of the variance, with PC1 being the primary contributor at 77.4 %, compared with PC2 at 10.8 % Fig. S3—C). This indicates that the first two PCs effectively captured the compositional characteristics of the 53 aroma compounds in the six LYT samples. Furthermore, the separation effect of PLS-DA was superior to that of PCA. The PLS-DA biplot results were consistent with those of the PCA biplot (Fig. 7d), demonstrating significant differences in the aromatic compound profiles of LYT at different altitudes and picking periods.

Based on VIP > 1, 30 key components were identified from the model (Fig. 7e). These components included cedrol, cadalene, cedrene, trans-geranylacetone, 3,7-octadiene-2,6-diol,2,6-dimethyl-, 2,6,10-trimethyltridecane, cadine-1,4-diene, methyl jasmonate, trans-β-ionone, α-copaene, geraniol, hexanoic acid, 3-hexenyl ester, (Z)-caryophyllene, 2,4-di-tert-butylphenol, trans-linalool oxide (pyranoid), α-cubebene, cis-linalool oxide (furanoid), benzyl alcohol, δ-cadinene, τ-muurolol, cis-geraniol, (E)-linalool oxide (furanoid), phenylethyl alcohol, α-terpineol, indole, epicubebol, linalool, E-nerolidol, pentadecane, and heptadecane.

The HCA result divided the six LYT samples into four distinct clusters (Fig. 7f): G1 included HT1; G2 consisted of HT2; G3 comprised MT1 and MT2; and G4 included LT1 and LT2. This clustering pattern indicates differences in the aroma compounds of LYT at various picking periods at high altitudes, whereas the differences were less pronounced at low and medium altitudes. Additionally, the aroma compounds of LYT varied significantly with the altitude.

3.4.3. Key aroma compounds identified by OAV

The sensory profile of tea is mechanistically determined by the OAVs of aroma-active volatiles (Gao et al., 2024; Liu et al., 2025). Generally, compounds with OAVs >1 significantly contribute to the aromatic characteristics of tea. Therefore, OAVs were calculated for the aroma compounds in the six LYT samples, which represented distinct altitudes and picking periods. By combining these results with VIP >1, 14 odorants that defined the fragrance profile of HT1 were identified (Table 2). These included trans-β-ionone, linalool, δ-cadinene, α-terpineol, geraniol, cedrol, methyl jasmonate, indole, hexanoic acid,3-hexenyl ester,(Z)-, benzyl alcohol, E-nerolidol phenylethyl alcohol, (E)-linalool oxide (furanoid), cis-β-farnesene, etc. Ten key aroma compounds were identified in HT2 (except for E-nerolidol, phenylethyl alcohol, (E)-linalool oxide (furanoid), and cis-β-farnesene, where the OVA was <1 in all other cases). Nine compounds were found in LT1 (excluding E-nerolidol, phenylethyl alcohol, (E)-linalool oxide (furanoid), indole, and cis-β-farnesene, with the OAV being <1 in all other instances. Eight key aroma compounds were identified in LT2 (excluding E-nerolidol, phenylethyl alcohol, (E)-linalool oxide (furanoid), indole, methy jasmonate, and cis-β-farnesene, where the OAV was <1 in all other cases), as well as in MT2 (excluding E-nerolidol, phenylethyl alcohol, (E)-linalool oxide (furanoid), indole, benzyl alcohol, and cis-β-farnesene, with the OAV being <1 in all other cases. Seven key aroma compounds were identified in MT1 (except for linalool, cedrol, benzyl alcohol, E-nerolidol, phenylethyl alcohol, (E)-linalool oxide (furanoid), and cis-β-farnesene, where the OAV was <1 in all other cases). The highest OAV was observed for trans-β-ionone from HT1, reaching 14,578.28 μg·kg ⁻¹, followed by linalool from HT1 (11,570.73 μg·kg ⁻¹). The aroma compounds in HT1 exhibited the highest OAV. Furthermore, the OAV of aroma compounds at low and medium altitudes was consistently lower than that at high altitudes (Table 2).

Table 2.

Aroma compounds with OVA >1 identified at different altitudes and picking periods.

Compounds	Odor threshold (μg·kg−1)	LT1	LT2	MT1	MT2	HT1	HT2
trans-β-Ionone	0.007	5112.86	5034.55	3364.71	4227.98	14,578.28	6384.38
Linalool	0.22	1185.60	1595.77	0.00	2035.61	11,570.73	2219.71
δ-Cadinene	1.5	79.46	113.24	57.93	69.07	477.55	110.91
α-Terpineol	1.5	17.29	24.85	15.00	35.57	222.61	53.21
Geraniol	6.6	22.46	28.00	21.14	16.59	92.08	32.46
Cedrol	0.5	23.64	24.47	0.00	15.59	76.46	52.02
Methy jasmonate	3	10.81	0.00	6.24	2.74	70.08	20.26
Indole	40	0.91	0.00	1.49	0.03	19.03	1.66
Hexanoic acid, 3-hexenyl ester, (Z)-	16	8.53	1.85	9.13	5.05	16.36	15.14
Benzyl alcohol	100	1.29	1.24	0.67	0.43	9.96	1.28
E-Nerolidol	250	0.33	0.00	0.55	0.09	5.09	0.45
Phenylethyl alcohol	390	0.23	0.14	0.24	0.12	1.53	0.24
(E)-Linalol oxide (furanoid)	190	0.19	0.17	0.24	0.27	1.35	0.45
cis-β-Farnesene	87	0.29	0.17	0.61	0.03	1.07	0.18

4. Discussion

4.1. Amino acid contents in response to altitude and picking period variation

Amino acids are the primary contributors to umami taste and serve as important precursors of aroma formation (Wang et al., 2021a). The analysis revealed distinct accumulation patterns of taste-related amino acids across the samples. The is the most abundant and plays a crucial role in determining quality due to its pronounced umami character (Jia et al., 2018). Consistent with previous studies (Liu et al., 2025; Sun, Yu, et al., 2024), our results also identified The as the most abundant amino acid (Fig. S2). Notably, The and Glu, the key contributors to umami taste, were the most abundant in MT1 samples (Fig. S2), with The recognized as a quality marker of premium tea (Sun, Yu, et al., 2024). Similarly, Ohno et al. (2011) reported that black tea produced in high-altitude regions of Sri Lanka contained higher concentrations of The. Moreover, sweet-tasting amino acids such as Gly, GABA, His, and Ala were significantly higher in MT1, whereas bitter-tasting amino acids, including Arg, Tyr, Val, and Ile, predominated in MT2, and Leu and Phe were enriched in LT2. Overall, the first-picked LYT from medium and high altitudes exhibited greater levels of umami and sweet amino acids, whereas the second-picked LYT from low and medium altitudes contained higher levels of bitter amino acids (Fig. 1). This trend mirrors that observed in Congou black tea, where early spring teas exhibit superior taste quality compared to late-spring Congou black tea (Yu et al., 2025). These findings collectively demonstrate that the amino acid composition is strongly influenced by both altitude and picking period, with first-picked teas from medium-to high-altitude regions showing enhanced freshness and umami quality, in agreement with previous studies (Sun, Wu, et al., 2024; Xiao et al., 2023).

4.2. Cs, TB, GA, and CAF contents in response to altitudes and picking period variation

The astringent properties of green tea are primarily attributed to CAF, Cs, and TB, as demonstrated in previous studies (Xu et al., 2021). In this study, the concentrations of Cs, TB, GA, and CAF during the first picking period decreased with increasing altitude (Fig. 3), which is consistent with previous findings (Han et al., 2017; Sun, Wu, et al., 2024; Wang, Cao, et al., 2021). This reduction explains the pronounced bitter and astringent characteristics observed in lowland tea products (Sun, Wu, et al., 2024). In contrast, during the second picking period of LYT, the concentrations of Cs, TB, and CAF initially increased, followed by a decline along the elevational gradient, peaking at a medium altitude (Fig. 3). Similarly, Chen et al. (2010) found that oolong tea cultivated at an altitude of 500 m exhibited significantly higher levels of EGCG, CG, and total Cs than that grown at lower altitudes (350 m). A similar phenomenon has been observed in Turkish black tea (ÖZDEMİR et al., 2018). Moreover, Sri Lankan high-altitude black tea has been reported to contain higher CAF levels (Ohno et al., 2011), consistent with our results for the second-picked LYT samples. EGCG contributes significantly to the astringency of tea infusions (Deng et al., 2022; Zhang et al., 2020). In this study, EGCG was present at the highest concentration, accounting for 67.84 % to 72.17 % of the total Cs content. EGCG is the most abundant catechin in both oolong and black teas (Chen et al., 2010; Ohno et al., 2011). Furthermore, our analysis revealed that the second-picked LYT contained significantly elevated levels of CAF, Cs, and TB compared with those of the first-picked LYT. This pattern can be attributed to prolonged daylight exposure and higher light intensity, which are known  to enhance the biosynthesis of CAF, Cs, and TB in tea leaves (Liu, Li, et al., 2023; Sun, Yu, et al., 2024; Xiao et al., 2023).

4.3. Aroma compounds in response to altitudes and picking period variation

Aroma, primarily composed of volatile compounds, has long been recognized as a key quality attribute of tea (Liao et al., 2020). Our results demonstrated that the high-altitude LYT exhibited a more intense aroma than that from low-altitude regions. This was associated with the markedly elevated content of volatile compounds. This finding corroborates the observations of Sun, Wu, et al. (2024). Liu, Shen, et al. (2023) identified 1-hexanol, linalool, linalool oxide, 2-methylpropanal, geraniol, (E)-β-ionone, and isoamyl acetate as key aromatic components that impart signature floral notes to green tea. Xie et al. (2023) identified seven volatile compounds, including geraniol, heptanal, linalool, phenylethyl alcohol, trans-β-ionone, phenylacetaldehyde, and hexanal, as essential aroma compounds in green tea. Consistent with these findings, our analysis revealed that trans-β-Ionone, linalool, δ-cadinene, α-terpineol, geraniol, cedrol, methyl jasmonate, indole, hexanoic acid,3-hexenyl ester (Z)-, and benzyl alcohol were the key aromatic components of LYT. Linalool, a monoterpenoid alcohol widely present in plants, imparts floral and citrus-like aromas and is one of the most significant contributors to tea aroma (Yang et al., 2016). Ketone compounds typically exhibit floral and fruity aromas. β-ionone, characterized by its violet-like scent, is primarily generated through the oxidative degradation and thermal oxidative degradation of carotenoids and serves as a significant aromatic component in green tea (Zhu et al., 2018). Geraniol has a distinctive rose-like aroma, characterized by sweet floral notes that evoke the scent of fresh rose petals. A unique orchid-like floral fragrance is regarded as a vital attribute of premium green tea (Feng et al., 2020). Methyl jasmonate has been identified as a key volatile compound responsible for imparting orchid fragrance to high-quality green tea (Feng et al., 2020). δ-Cadinene, known for its herbaceous and woody aromas, is a crucial aroma-active compound in Xinyang Maojian green tea (Yin et al., 2022). Indole plays a significant role in shaping the floral aroma profile of Oolong tea (Yang et al., 2021). In this study, the aroma components of high-altitude LYT, including methyl jasmonate, linalool, β-ionone, δ-cadinene, and geraniol, were significantly enriched, resulting in complex floral, woody, and fruity aromas.

4.4. Possible mechanisms underlying the effects of altitude and picking period on LYT quality

Changes in altitude cause significant variations in environmental factors, such as temperature, light intensity, and light quality. Air temperature decreases by approximately 0.5 °C per 100 m increase in elevation, rendering high-altitude tea plants more susceptible to low-temperature stress. Low temperatures have been shown to downregulate the expression of genes involved in Cs biosynthesis, such as CsC4H, CsANS, CsANR1, and CsANR2, thereby reducing the accumulation of Cs in tea plants (Tian et al., 2024). The synthesis of EGCG is influenced by 1-O-galloyl-β-d-glucose O-galloyltransferase (ECGT). The activity of ECGT is relatively high within the temperature range of 20–50 °C, with an optimal temperature of 30 °C. As temperature decreases with increasing altitude, ECGT activity also decreases, leading to a lower EGCG content in high-altitude regions (Chen et al., 2014). In addition, low temperatures suppress shoot growth by reducing the expression of growth-related genes, such as CsTCP1, CsTCP6, and CsAFR5, thereby affecting the accumulation of Cs, TB, GA, and CAF (Xiang et al., 2020). Conversely, tea plants exposed to cold stress may enhance the release of volatile compounds, such as nerolidol, geraniol, linalool, and methyl salicylate, through the C-repeat binding factor (CBF)-dependent pathway (Zhao et al., 2020).

Light influences tea quality by regulating the synthesis of secondary metabolites (Liu et al., 2025; Wang, Yang, et al., 2022). High-altitude environments typically experience higher rainfall, which reduces light intensity and sunlight duration. This reduction contributes to lower Cs, TB, GA, and CAF content while simultaneously enhancing umami and sweet amino acids in high-altitude tea plants. This finding is consistent with Liu et al. (2025), who reported that ecological shading significantly decreased Cs, CAF, and TB, whereas it increased amino acid accumulation. Furthermore, Wang et al. (2022) demonstrated that stimulating temperature and light conditions in high-altitude regions led to elevated amino acid and aroma compound levels in tea leaves.

The picking period is another key factor influencing tea quality (Chen et al., 2024; Ma et al., 2022). Seasonal progression results in rising temperatures, longer daylight hours, and stronger light intensity, which accelerate shoot growth and promote the development of mechanical tissues, such as cellulose and lignin, in the leaves. This physiological change leads to increased accumulation of Cs, CAF, TB, and GA, but a decline in aromatic compounds and amino acid content in the tea leaves. Previous research has demonstrated that spring tea contains higher amino acid levels but lower Cs and tea polyphenol concentrations than summer and autumn teas. This is consistent with the elevated expression of genes associated with flavonoid and lignin biosynthesis during the summer and autumn seasons (Ma et al., 2022). In summary, altitude and picking period are key determinants of LYT quality, primarily acting through temperature- and light-mediated regulation of secondary metabolite biosynthesis.

5. Conclusion and perspectives

In this study, HPLC, UPLC, HS-SPME-GC–MS, and sensory evaluation were used to comprehensively analyze the taste- and aroma-related metabolites in LYT tea samples from different altitudes and picking periods. In total, 18 amino acids, eight Cs, one GA, one CAF, one TB, and 53 aromatic components were detected in the LYT. Using multivariate statistical analyses (PCA, PLS-DA, and HCA), a multi-parametric characteristic wheel of LYT quality was developed for the first time, highlighting nine key taste-active compounds and 13 aroma-active compounds (Fig. 8). The findings of this study demonstrate that the first-picked LYT from mid-to-high altitudes exhibited superior overall quality. Specifically, the first-picked LYT from middle-altitude contained higher levels of sweet- and umami-tasting amino acids. In contrast, the second-picked LYT showed elevated Cs, CAF, and TB. In addition, the first-picked LYT from high altitudes exhibited a more intense floral, fruity, and woody aroma.

Fig. 8.

Key flavor compounds in LYT. Abbreviations of the LT1, LT2, MT1, MT2, HT1, and HT2 are the same as those given in Fig. 1.

Overall, our findings demonstrate that LYT quality is fundamentally influenced by altitude and picking period, primarily through variations in temperature and light. Therefore, in low-altitude tea gardens, ecological shading can be applied to simulate the temperature and light environments of medium-to-high altitudes. This practice can effectively reduce the field temperature and light intensity, thereby decreasing the accumulation of bitter and astringent compounds, enhancing the amino acid and aromatic contents, and improving the sensory quality of LYT. Furthermore, tea harvested from different altitudes and picking periods, characterized by higher bitterness and astringency, may require targeted processing adjustments.

This study elucidated how altitude and picking period influence the content and metabolic mechanisms of LYT. These findings are expected to provide a theoretical foundation for future research and practical guidance for the targeted cultivation and processing of LYT to enhance its overall aroma quality. However, our study examined altitude and picking period independently, without fully addressing the synergistic effects of key environmental factors, such as temperature, light, and humidity, along the altitudinal gradient.

CRediT authorship contribution statement

Gui-Zhen Chen: Writing – original draft. Wen-Gang Liu: Data curation. Jie Huang: Data curation. Ting Deng: Resources. Yan Chen: Methodology. Yang-Ling Zhang: Resources. Ji-Gang Huang: Methodology. Hong-Fei Wei: Resources. Yin-Xiang Gao: Writing – review & editing. Xin-Feng Jiang: Writing – review & editing.

Informed consent statement

Ethical approval for the sensory evaluation involving five participants was obtained from the Ethics Committee of Jiujiang University. And all sensory evaluators agreed to participate and signed the in-formed consent form.

Institutional review board statement

The sensory evaluation protocol, including data collection and usage, was approved by the Jiujiang University Human Ethics (Approval ID: JJUM20240090; Date: 7 April 2024).

Declaration of competing interest

The authors declare no competing financial interests or personal relationships that could influence this work.

Appendix A. Supplementary data

Supplementary Method 1: Detailed UPLC Procedure for Amino Acid Analysis.

Supplementary Method 2: Detailed HPLC Procedure for Cs, TB, GA, and CAF analysis.

Table S1. Characteristics of LYT samples.

Table S2. The chemicals used in this study.

Table S3. Sensory evaluation results of six LYT samples.

Table S4. VIP and TAV Values of flavor substances at different altitudes and picking periods.

Table S5. Identification of volatile compounds identified at different altitudes and picking periods.

Table S6. Relative quantification of volatile compounds identified at different altitudes and picking periods. Note: Values are means ± standard deviation from triplicate analyses.

Fig. S1. TIC of six different altitudes and picking time of LYT by HPLC. Abbreviations of the 6 tea samples (i.e., LT1, LT2, MT1, MT2, HT1, and HT2) are the same as those given in Table S1.

Fig. S2. Significance test for amino acid content. Data are reported as mean ± standard deviation (n = 3). Duncan's multiple range test, following analysis of variance (P < 0.05), assigned differing superscript letters to significant contrasts. Abbreviations of the 6 tea samples (i.e., LT1, LT2, MT1, MT2, HT1, and HT2) are the same as those given in Table S1.

Fig. S3. PCA screen of six different altitudes and picking periods of LYT. A, amino acid; B, GA, CAF, TB, and Cs; C, aroma compounds.

Fig. S4. Five-fold cross-testing of the PLS-DA model of LYT from six different altitudes and picking periods.

Fig. S5. TIC of six different altitudes and picking time of LYT by UPLC. LT1 represents the low-altitude first-picking LYT; LT2 represents the low-altitude second-picking LYT; MT1 represents the medium-altitude first-picking LYT; MT2 represents the medium-altitude second-picking LYT; HT1 represents the high-altitude first-picking LYT; and HT2 represents the high-altitude second-picking LYT.

Fig. S6. Significance test of C, GA, and CAF contents. Data are presented as mean ± standard deviation of three replicates. Different lowercase letters indicate statistically significant differences based on analysis of variance at P < 0.05, followed by Duncan's test.

Fig. S7. TIC of 6 different altitudes and picking time of LYT by HS-SPME-GC-MS. LT1 represents the low-altitude first-picking LYT; LT2 represents the low-altitude second-picking LYT; MT1 represents the medium-altitude first-picking LYT; MT2 represents the medium-altitude second-picking LYT; HT1 represents the high-altitude first-picking LYT; and HT2 represents the high-altitude second-picking LYT.

Data availability

Data will be made available on request.