Next Article in Journal
Reference Genes in Plant–Pathogen Interaction: A Bibliometric Analysis
Previous Article in Journal
Optimization of Agro-Residue Substrates for Sustainable Cultivation of Pleurotus giganteus in Hainan, China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Aroma Characterization and Key Volatile Identification in Wuyi Rock Tea Prepared from Wuyi Mingcong Tea Plant Varieties

1
College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
Tea Engineering Research Center of Fujian Higher Education, College of Tea and Food Sciences, Collaborative Innovation Center of Chinese Oolong Tea Industry, Wuyi University, Wuyishan 354300, China
3
State Key Laboratory of Tea Plant Germplasm Innovation and Resource Utilization, Anhui Agricultural University, Hefei 230036, China
4
iPhenome Biotechnology (Dalian) Inc., Dalian 116000, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(12), 1414; https://doi.org/10.3390/horticulturae11121414
Submission received: 8 October 2025 / Revised: 16 November 2025 / Accepted: 18 November 2025 / Published: 21 November 2025
(This article belongs to the Special Issue Sustainable Practices in Tea Plantations)

Abstract

Wuyi Mingcong (WYMC) is a distinctive tea germplasm resource from Wuyi Mountain, known for its unique aroma and quality characteristics. However, the aroma quality of WYMC has been insufficiently studied. In this study, the aroma profiles of seven characteristic tea plant resources WYMC tea samples were characterized using sensory evaluation combined with headspace solid-phase microextraction and gas chromatography–mass spectrometry (HS-SPME-GC-MS). The results revealed that “floral,” “fruity,” “clean and refreshing,” “woody,” and “sweet” were the main aroma characteristics. A total of 37 volatile compounds were found to contribute significantly to the aroma profiles of the seven WYMC tea samples, with dihydrolinalool and (E)-β-ionone likely being the key contributors to their floral and fruity notes. Ten key volatile markers were identified as responsible for aroma differences between the Fujian Shuixian (SX) and seven WYMC tea samples. Phenylethyl alcohol, cis-3-hexenyl benzoate, δ-cadinene, nerol, and β-myrcene may be critical for the formation of WYMC’s characteristic aroma. cis-3-hexenyl benzoate and nerol may act as “broad-spectrum” aroma contributors, enhancing the overall intensity or layered nature of WYMC’s scent. The results of this study enrich the understanding of the aroma characteristics of WYMC and provide a theoretical foundation for the development and utilization of tea germplasm resources in the Wuyi Mountain.

1. Introduction

Tea is one of the most popular beverages globally, including black tea, green tea and oolong tea, etc. [1]. In China, Wuyi Mountain is one of the major producing areas of oolong tea, and the oolong tea produced here is often referred to as ‘Wuyi rock tea (WRT)’. The common tea plant varieties used for ‘Wuyi rock tea’ processing include the ‘Fujian Shuixian (SX)’ tea plant and ‘Rougui (RG)’ tea plant, which are currently the two largest tea plant germplasms in terms of planting area at the Wuyi Mountain [2,3]. Wuyi Mountain is also an important treasure trove of tea plant germplasm resources. According to incomplete statistics, Wuyi Mountain has over a hundred natural tea plant germplasm resources [2,4]. Some elite varieties, selected from these Wuyi Mountain local germplasm resources, were called ‘Wuyi Mingcong (WYMC)’ such as, ‘Dahongpao (DHP)’, RG, and ‘Shuijingui (SJG)’ [2].
The flavor characteristics of WRT are shaped by multiple factors [5,6,7]. Extensive studies have used transcriptomic and metabolomic approaches to investigate how different regions and processing techniques influence the formation of its quality traits, exploring changes in both volatile and nonvolatile compounds [8,9,10,11]. Additionally, WRT produced from different tea plant varieties typically exhibits distinct flavor qualities and, especially, aroma characteristics. For example, RG-WRT is noted for a cinnamon-like aroma, while SX-WRT features a floral aroma with woody notes [12]. Previous research analyzed 16 WRT samples from different oolong tea plant varieties to explore their aroma profiles [13]. However, most of these varieties were not ‘WYMC’ types; WYMC is a characteristic tea plant resource of Wuyi Mountain, and the aroma characteristics of WRT derived from different ‘WYMC’ tea plant varieties remain unclear.
In this study, the aroma components of eight WRT samples of seven characteristic ‘WYMC‘ tea varieties within a certain planting area of Wuyi Mountain and one national-level cultivar ‘SX‘ were compared and analyzed. The sensory evaluation, in combination with quantitative descriptive analysis (QDA), headspace solid-phase microextraction gas chromatography-mass spectrometry (HS–SPME–GC–MS), and molecular docking experiments, was used to investigate the contribution of different aroma volatiles to the aroma profiles of WYMC-WRT samples and the aromatic distinctions between WYMC and SX. The findings are expected to offer a theoretical basis for future efforts aimed at promoting and breeding WYMC varieties.

2. Materials and Methods

2.1. Tea Sample Collection

The test samples were collected in the spring of 2023 from tea cultivars (Camellia sinensis var. sinensis) grown on the tea germplasm plantation of Wuyi University (Wuyishan City, Fujian Province, China, 27° 73′ N, 118° 00′ E). Their planting land is flat, and the altitude (213 m), soil type (yellow loam), climate (annual average temperature of about 18.0 °C, annual average rainfall of about 2000 mm, and annual average relative humidity of about 80%), irrigation, and fertilization management measures are consistent. After preliminary investigation, the growth potential of the selected seven WYMC tea varieties was excellent, and the quality of WRT was good. Therefore, we selected seven tea varieties as the experimental group, including “Rogui (RG)”, “Hongdujuan (HDJ)”, “Honghaitang (HHT)”, “Mujinluohan (MJLH)”, “Zuiguifei (ZGF)”, “Zhengtaiyin (ZTY)”, and “Guoshanlong (GSL)”. “Fujian Shuixian (SX)” was selected as the control group.
In this study, a total of 90 tea plants were randomly selected from each tea cultivar, and every 30th plant was a replicate, so each cultivar had three replicates of tea samples. The fresh leaves of the three and four leaves of each cultivar were picked as raw materials for the traditional production process of Wuyi rock tea, which involves withering, shaking (six times), fixing, twisting, drying, and roasting. The post-harvested tea leaves were spread under sunlight and withered (24–26 °C, 65–70% relative humidity, 2–3 cm thickness, withering to soft leaves, leaf edge slightly curled, green gas decreased, fragrance revealed as moderate, and time of 30 min)→green-making (hand-made green, the first shaking 10–15 turns, spread for 30 min, the second shaking 20–30 turns, spread for 60 min, the third shaking 30–40 turns, spread for 80 min, the fourth 40–50 turns, spread for 90 min, the fifth shaking 50–60 turns, spread for 120 min, the sixth shaking 52–60 turns, and spread for 120 min; the thickness of the spread leaves was thickened step by step, until the leaves achieved a bright-yellow surface, a “tortoise-back” curl, the signature “three-red-seven-green” coloration with cinnabar-red edges, and a balanced floral-fruity aroma, time of 8 h)→fixing (manual fixing, pot temperature 220~240 °C, and the amount of leaves per pot is about 0.75 kg; the appropriate standard for fixing was that the leaves became soft and sticky, turned dark, developed a fragrance, and had no green odor; process lasted 6~8 min)→rolling (the leaves were rolled for 7–10 min until tea juice exuded and they formed tight strips)→drying (baking machine drying, gross fire temperature 120 °C, time of 30 min, airing for 2 h and then full fire, full fire temperature 80 °C, time of 120 min)→picking→redrying (baking machine drying, temperature 110~120 °C, time of 40 min). After the eight tea samples were prepared, the impurities were removed, and the samples were sealed for future use.

2.2. Sensory Evaluation

The sensory evaluation team consisted of thirteen trained evaluators (seven females and six males, aged 25–40 years; all had the qualification of senior tea evaluator). The sensory quality (appearance, liquor color, aroma, taste, and infused leaves) of Wuyi rock tea (WRT) was evaluated according to the standards of China in GB/T 23776-2018 [14]. Before the sensory evaluation, each tea sample was labeled with codes and randomly arranged in the process of sensory evaluation and quantitative descriptive analysis to improve the accuracy of the sensory quality evaluation of the tea samples. During the evaluation process, 5 g of each uniformly mixed WRT sample was placed in an independent lidded teacup. Then 110 mL of boiling water was added to the cup. The tea samples were brewed three times, and the first bubble (2 min), the second bubble (3 min), the third bubble (5 min), and each tea soup was subjected to sensory evaluation. The aroma characteristics and intensity of the tea leaves were recorded by evaluators, with the aroma descriptors referencing Guo et al. [15]. The evaluators agreed that the aroma of the tea samples could be described in terms of five attributes: namely, “floral”, “fruity”, “sweet”, “woody”, and “clean and refreshing”.
The quantitative descriptive analysis (QDA) method [13,16,17,18] was used to quantitatively evaluate the aroma intensity of the samples. Before quantitative evaluation, 13 evaluators were tested for WRT aroma recognition, evaluation, description and perception, and flavor analysis ability. The scores were all >80%, indicating that the 13 evaluators had the ability to perform QDA quantitative analysis. The scores of each attribute in QDA quantitative analysis ranged from 0 to 10. The higher the score, the stronger the intensity; 0 = no intensity or no perceived intensity, 3 = weak intensity, 5 = moderate intensity, 7 = high intensity, and 10 = extremely high intensity. The first cup was used to assess the type of aroma; the second cup was used to determine the intensity of the aroma; and the third cup was used to reassess the aroma and aroma persistence. Each evaluator evaluated each sample three times and all data are expressed as averages.

2.3. Electronic Nose Detection

The aroma characteristics of Wuyi rock tea were assessed using the PEN3 electronic nose from AIRSENSE, which is equipped with ten sensors (all sensors are sensitive to a large class of substances, rather than a single substance). These sensors include the following: W1C for aromatic ingredients and benzene; W5S for nitrogen oxide; W3C for ammonia and aromatic components; W6S for hydrogen; W5C for short-chain alkanes and aromatic components; W1S for methyl groups; W1W for inorganic sulfides and terpenes; W2S for alcohols, ethers, aldehydes, and ketones; W2W for aromatic components and organic sulfides; and W3S for long-chain alkanes (the performance descriptions of sensors were provided by the electronic nose manufacturer, and the specific description is shown in Table S1). Prior to the experiment, the electronic nose system was preheated for 30 min to achieve stability. The system was then flushed, and the sensor array was continuously purged until all sensor signals reached stable baseline values. For each measurement, 1.0 g of a tea sample was placed in a 100 mL beaker, which was sealed with double layers of cling film and equilibrated at 80 °C for 5 min after standing for 30 min at room temperature. The detection time for each sample was 120 s, with the sample injecting speed of 400 mL/min; after each experiment, the flush time was selected as 120 s to ensure the accuracy and reliability of the results. Each sample was tested three times.

2.4. Analysis of Volatile Aroma Components in Tea Samples

Volatile aroma components extraction: 1.0 g of tea sample was weighed into a 20 mL headspace vial with 2.5 mL saturated NaCl solution and 10 μL (50 μg/mL) methyl 2-hydroxybenzoate-d4 (dissolved in n-hexane) as isotope labeled internal standard. Each sample was mixed in equal amounts to make quality control (QC) samples, and a QC sample was added every eight times to detect the stability of the experiment. The ion flow diagrams of different QC quality control samples are shown in the attached Figure S1. Each sample was subsequently heated to static equilibrium at 80 °C for 20 min [19]. Then, the 120 μm DVB/CWR/PDMS fibrehead (Agilent Technologies, Santa Clara, CA, USA) was inserted into a headspace vial for 40 min, followed by desorption at 250 °C for 5 min.
GC-MS analysis: The identification and quantification of volatile components were carried out using an Agilent Model 8890 GC and a 7000D mass spectrometer (Agilent) equipped with a 30 m × 0.25 mm × 0.25 μm DB-5MS (Agilent J&W Scientific, Folsom, CA, USA). The injector temperature was set at 250 °C, and the sample was fed without a shunt. The initial temperature was held at 40 °C for 1 min, then increased to 280 °C at a rate of 5 °C/min and held for 5 min. High-purity helium (purity > 99.999%) was used as carrier gas at constant flow rate of 1 mL/min. Then, 50~500 m/z mass spectra were recorded in electron impact (EI) ionization mode at 70 eV with an ion source, and with interface temperatures set at 230 °C, and 250 °C, respectively. Biology determination was repeated three times for each rock tea sample (Metware Biotechnology Co., Ltd., Wuhan, China).
The metabolites in the samples were identified by comparing the mass spectrum with the data system library (MWGC and NIST 20, MWGGG is a self-built database of volatile metabolome of Metware Biotechnology Co., Ltd., Wuhan, China), the linear retention index (RI, calculated from n-alkanes C7–C40), and using match score > 75% [20] (Metware Biotechnology Co., Ltd., Wuhan, China). The quantification process included a comparison of the peak areas of the internal standard (IS) to calculate the contents of the aroma components (μg/g). The concentrations of volatile compounds were estimated by using a semi-quantitative method, through normalizing the peak area of each identified volatile compound to the internal standard [21].

2.5. Characterization and OAV Calculation of Volatile Compounds

The odor activity values (OAVs) were determined as the ratios of the relative contents to their odor thresholds in water for each volatile compound to assess the impacts of volatile compounds [22]. The formula for calculating the OAV is as follows:
OAV   = C i O T i
where Ci (µg/g) is the relative content of volatile component and OTi (µg/g) is the aroma threshold of the volatile components in water. The thresholds were taken from the previous literature [13,23,24,25,26,27,28].

2.6. Molecular Docking of the Binding Interactions Between the Aroma Active Compounds and the Olfactory Receptors

Five-dimensional structural models of the compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov, accessed on 10 September 2025). Three-dimensional structural models of the olfactory receptors were obtained from UniProt (https://www.uniprot.org, accessed on 10 September 2025). Proteins (receptors) and aroma compounds (ligands) were then hydrogenated and charged using CB-Dock2 (https://cadd.labshare.cn/cb-dock2/php/index.php, accessed on 11 September 2025) [29].

2.7. Statistical Analysis

A radar map was generated using Origin 2021. Unsupervised principal component analysis (PCA) was performed using the statistics function prcomp within the R package stats 3.5.1. A heatmap was generated using the R package complexheatmap 2.12.0. Flavor wheel plots were drawn using the R package ggplot2. OPLS-DA was performed using the R package MetaboAnalystR. Bar charts were drawn using GraphPad Prism9. The one-way analysis of variance (ANOVA) was performed using IBM SPSS Statistics 25 to assess differences in volatile content among different tea plant varieties. When ANOVA results were significant (p < 0.05), Duncan’s multiple range test (DMRT) was used for post-hoc multiple comparisons.

3. Results and Discussion

3.1. Sensory Evaluation of SX and WYMC Teas

The flavor characteristics of WRT vary depending on the tea plant germplasm. To assess quality differences, SX and seven WYMC tea samples (RG, ZGF, MJLH, ZTY, HDJ, HHT, and GSL) underwent sensory evaluation by an expert panel. The results of the sensory evaluation showed that most samples had a sturdy, tight shape with a greenish-auburn and black bloom appearance (Figure 1 and Table S2). Tea broths of these samples were predominantly orange and bright (Figure 1 and Table S2). All the samples presented significant floral, fruity, or clean and refreshing aromas, with HDJ tea and SX tea also displaying woody notes. In terms of taste, these teas were characterized by a strong, thick, mellow, brisk, and sweet aftertaste, with a distinctive “Yan” flavor (Table S2). The infused leaves were yellow-green, soft, bright, and even, with a distinctive red edge, which is typical of WRT (Figure 1 and Table S2). Overall, sensory results indicated that all selected teas possessed typical WRT characteristics.

3.2. Aroma Characterization of SX and WYMC Teas

The electronic nose is mainly used to identify and compare the overall volatile odor of tea [30]. In order to further explore the aroma characteristics of WYMC and reveal its aroma profile, the aroma attributes of the eight WRT samples were analyzed using an electronic nose, and the results are displayed in a radar diagram (Figure 1b). The radargrams showed significant similarity in aroma attributes across the samples, with variations only in response values. All the samples presented relatively high response values for the sensor W5S and showed fluctuations in the sensor W2. W2W is mainly sensitive to aromatic components with floral and fruity aroma, and W5S is mainly sensitive to nitrogen oxides. This result was also consistent with the WYMC sensory evaluation of the overall flower and fruit aroma. Although there are some similarities in the overall profile of aroma, there are also significant differences between different samples from the fluctuation of response values of sensors W5S and W2W.
Oolong teas produced by different varieties usually exhibit different flavors, known as “varieties flavor” [12]. As shown in Figure 2a, the odor types of SX and seven WYMC teas were described as “floral”, “fruity”, “clean and refreshing”, “woody”, and “sweet”, with varying intensities among the eight tea plant varieties. SX tea has high-intensity sweet and floral odors, RG tea has a high-intensity floral odor, ZGF tea has high-intensity clean and refreshing and floral odors, ZTY tea has a high-intensity clean and refreshing odor, HDJ tea has a high-intensity fruity odor, HHT tea has high-intensity clean and refreshing and floral odors, GSL tea has a high-intensity fruity odor (scores ≥ 7), MLJH tea has moderate intensity clean and refreshing and sweet odors, and SX tea and HDJ tea also have woody odors.
The results of the electronic nose and QDA revealed that the eight samples overall exhibited characteristic floral and fruity aromas. While their general aroma profiles were similar, differences were observed, allowing each sample to demonstrate unique aromatic characteristics. However, aroma perception is a complex outcome, likely influenced by the composition, concentration, and proportional balance of aromatic substances in the samples. Therefore, it is necessary to further identify the key aroma-active compounds that contribute to these specific aroma profiles and their differences.

3.3. Analysis of the Aroma Components of SX and WYMC Teas Using HS-SPME-GC-MS

As shown in Figure S1, the total ion chromatogram (TIC) profiles of volatile compounds detected in QC samples exhibited highly overlapping curves, with consistent retention times and peak intensities, demonstrating stable instrument performance and the reliability of the HS-SPME-GC-MS analytical methodology employed in this study. A total of 192 aroma volatile compounds were identified, including 10 alcohols (2.44–5.02 μg/g), 19 ketones (2.90–5.63 μg/g), 55 terpenoids (23.30–46.60 μg/g), 38 esters (14.83–29.31 μg/g), 14 heterocyclic compounds (8.67–22.05 μg/g), 27 hydrocarbons (4.10–7.74 μg/g), 11 aromatics (0.47–1.85 μg/g), 12 aldehydes (0.44–0.89 μg/g), 3 phenols (0.89–2.46 μg/g), 2 nitrogen compounds (0.22–4.98 μg/g), and 1 acid (0.00–0.01 μg/g); the classification results of the 192 aroma volatile compounds are shown in Table S3. The contents of terpenoids and esters ranked first and second, respectively, among the eight tea samples, indicating that these two types of compounds are the primary contributors to the aroma of the eight tea samples. The classifications, abundances, and percentages of the different volatile compounds in the eight tea samples were illustrated in Figure 2b–d.
Among these tea samples, aromas’ volatile concentrations varied significantly: HDJ tea, SX tea, and HHT tea showed the highest levels at 118.90 μg/g, 108.96 μg/g, and 104.89 μg/g, respectively. The total aroma volatile contents of the other five samples were lower, with values as follows: MJLH tea (79.08 μg/g), RG tea (77.87 μg/g), GSL tea (73.05 μg/g), ZTY tea (66.77 μg/g), and ZGF tea (65.98 μg/g). Notably, HDJ tea had the highest total aroma volatile content across all samples. Specifically, its terpenoid and ester contents were 45.80 μg/g and 30.67 μg/g, respectively. These two components made up more than half of its total volatile content and were significantly higher than those in SX tea. These results thus suggest that HDJ tea plant could be a suitable variety for producing WRT with high aroma quality.
In this study, terpenoids were the most abundant aroma components across all eight tea samples, with concentrations exceeding 20 μg/g in all samples (Figure 2c). This result corroborates findings by Yue et al. [13], suggesting that terpenoids play a crucial role in the aroma quality and are closely related to tea aroma intensity. Terpenoids are mainly synthesized via the methylerythritol phosphate (MEP) pathway or the mevalonate (MVA) pathway [31]. Key terpenoids such as linalool, geraniol, (E)-β-ionone, and trans-nerolidol were present in high concentrations in eight tea samples, contributing floral and woody aromas. Geraniol and linalool are monoterpenes formed by the hydrolysis of glycosides, which play a role in the floral and fruity aroma of tea [23,32]. At the same time, short-term sunlight-induced withering significantly upregulated key genes involved in terpenoid metabolic pathways, increasing aroma formation during oolong tea manufacturing [33]. Esters are the primary source of sweet, floral, and fruity tea aromas, and extracellular lipids can be broken down and converted into aromatic compounds during the production process, which is an important factor affecting the aroma of oolong tea [34,35]. In this study, esters accounted for the second largest pro-portion of the aroma substance content of these eight tea samples. cis-3-hexenyl hexanoate, a key aroma compound formed during rolling, contributes floral and fruity notes [36], and was highly concentrated in all eight tea samples. Previous studies have shown that ester content gradually increases during SX processing, playing a key role in shaping its aroma intensity and odor characteristics [37]. Notably, cis-jasminalactone showed the highest relative content in SX tea, highlighting its significance in the aroma profile of this variety. Heterocyclic compounds also play an important role in the aroma formation of oolong tea. The heterocyclic compound indole has the highest concentration in eight tea samples, which is an important substance affecting the floral aroma of oolong tea [38], and indole is also a key substance constituting the basic aroma characteristics of jasmine tea and the chestnut aroma of green tea [8,39]. The results of volatile component analysis showed that abundant terpenoids and esters were the main material basis for the characteristic aroma of the flower and fruit aromas of the eight Wuyi rock tea varieties. This is also consistent with the results of the previous sensory evaluation, identifying floral and fruity odors.

3.4. Identification of Key Aroma Volatile Compounds in the WYMC Tea Samples

In tea, among the many aroma components, only a few play a dominant role in determining the characteristic aroma of the tea [40]. Notably, the concentration of aroma components does not directly reflect the tea’s characteristic aroma. For this reason, previous studies have employed the odor activity value (OAV) to assess the contribution of individual aroma components to the overall aroma of tea. Specifically, an OAV > 1 indicates that the compound exerts some influence on the tea’s aroma, while an OAV > 10 means the compound is regarded as making a significant contribution to the aroma [41,42,43]. By calculating the OAV based on the reported thresholds of volatile substances, this study screened 37 important volatile compounds that contribute to the aroma of seven WYMC samples. The aroma wheel for the seven WYMC samples was constructed based on OAV > 1, as shown in Figure 3 and Table 1.
Analysis of the 37 key volatile compounds revealed that dihydrolinalool and (E)-β-ionone had OAVs > 2000, making these the top two compounds in terms of OAV ranking among the important volatile components. Previous studies have shown that dihydrolinalool is a key compound in forming the aroma of beauty tea [24], and (E)-β-ionone is a key factor in enhancing the floral aroma of green tea [10,44]. According to our results and these previous studies, dihydrolinalool and (E)-β-ionone may be the main contributors to the floral and fruity aromas of these seven WYMC tea samples. This is also consistent with our sensory evaluation results.
A comparison revealed that in HDJ, the OAV of linalool (sweet, fresh, and floral) [45], 2-pentyl-furan (fruity) [46], β-ocimene (citrus, and green) [44], and jasmone (jasmine) [25] were significantly higher than those of the other six WYMC samples. This could contribute to the more pronounced floral and fruity aroma characteristics of HDJ. In ZGF, (+)-α-pinene (herbaceous) [9] had an OAV > 90, indicating that it might significantly contribute to ZGF’s fresh aroma. In ZTY, the OAV of (E)-β-ionone (violet) [25] was greater than 10,000, the highest among all compounds, indicating its important contribution to ZTY’s aroma characteristics. δ-Cadinene (thyme, herbal, woody, and dry) [47] is an active ingredient in the volatile oils of some herbaceous plants. In GSL, its OAV > 180, significantly higher than in other WYMC samples, which may contribute to GSL’s aroma characteristics.
In summary, the aroma characteristics of tea are the result of the synergistic effect of multiple compounds. Notably, key compounds with high OAVs were identified as major contributors to the shared aroma profile of the eight WRT samples. Dihydrolinalool and (E)-β-ionone contribute to the floral and fruity notes, and δ-cadinene to the woody character. This result was also consistent with the previous sensory evaluation results of floral, fruity, and woody fragrances. However, the ‘varietal flavor’ exhibited by SX and WYMC depends on a few key aroma components and can be used as a marker for the chemical differentiation of the seven WYMCs. Therefore, it is necessary to find the key aroma markers to distinguish the seven WYMCs.

3.5. Differential Analysis of Volatile Compounds Between SX and WYMC Teas

In this study, we employed principal component analysis (PCA) to examine the relative contents of aroma components in SX and seven WYMC tea samples. As shown in Figure 4a, the eight tea samples clustered into distinct regions; among them, MJLH, RG, ZGF, ZTY, and GSL are clustered closer together, while HHT, HDJ, and SX form separate clusters. The first two principal components accounted for over 60% of the variance. In general, good separation is indicated when the cumulative contribution of the PCA model reaches 60% [48]. The results of PCA suggested that the eight tea samples exhibited significant differences in terms of their volatile compounds. The clustering heatmap (Figure 4b) reveals that HDJ formed an isolated cluster, while SX, MJLH, and RG were grouped together, and the remaining WYMC samples formed another group, suggesting that HDJ differs from the other samples in terms of its aromas’ volatile contents.
To further explore the differences between SX and the seven WYMC samples, an OPLS-DA model was constructed to screen for key metabolites that differed significantly. The OPLS-DA score plot (Figure 4c) and the 200 random permutation tests (Figure 4d) showed a model fit of R2Y = 0.989 and a predictive ability of Q2 = 0.97, indicating that the model was reliable. The OPLS-DA score plot clearly distinguished SX from the seven WYMC samples, and 65 key differential volatile compounds (DVCs) were identified based on VIP > 1. The classification results of the 65 DVCs are shown in Table S4 and Figure 5.

3.6. Potential Key Volatile Markers Responsible for the Different Fragrances of SX and WYMC Teas

The above studies found that the aroma characteristics, volatile compound concentration, and odor intensity of SX and 7 WYMC were significantly different. In order to better understand the differences in key characteristic compounds and aroma-active compounds between SX and WYMC aroma types, we screened ten key volatile markers leading to aroma differences based on VIP > 1, OAV > 1, and FC > 1.5, and the results are shown in Table 2 and Figure 6. The ten key volatile markers are produced from three main precursors: carotenoids, lipids, and amino acids/carbohydrates [49]. The relative contents of indole, cis-Jasminlactone, 6-methyl-5-hepten-2-one, hexyl 2-methylbutyrate, and dihydrolinalool in SX were all significantly (p < 0.05) higher than the average relative contents of the seven WYMC tea samples. In contrast, the average relative contents of phenylethyl alcohol, cis-3-hexenyl benzoate, δ-cadinene, nerol, and β-myrcene in the seven WYMC samples were significantly (p < 0.05) higher than those in SX, so they were hypothesized to be the key volatiles for the aroma characteristics of the seven WYMC samples. The content of β-myrcene in HDJ exceeded 1 μg/g, significantly higher than that in SX, suggesting it may be an important substance in shaping the aroma characteristics of HDJ. Additionally, although nerol, δ-cadinene, and cis-3-hexenyl benzoate accounted for relatively small proportions in the seven WYMC samples, their contents were significantly higher than those in SX. Notably, the relative content of phenylethyl alcohol was significantly higher in all seven WYMC samples compared to SX. It is speculated that phenylethyl alcohol may play an important role in the formation of WYMC aroma characteristics.
Indole has been confirmed as a characteristic volatile compound in oolong tea, mainly formed during processing [50]. cis-Jasminlactone, providing fruity and sweet floral aromas, is primarily produced by lipid degradation during the “turning-over” process [51]. In addition, 6-methyl-5-hepten-2-one has been identified as a key characteristic aroma compound in DHP [52], and these compounds may explain the unique floral aroma of SX. Dihydrolinalool has a fresh floral and fruity aroma, which has previously been shown to have an important relationship with the aroma quality of beauty tea [53]. Some studies have shown that β-myrcene is an important substance affecting the floral and fruity aroma of tea [54], and that cis-3-hexenyl benzoate exhibits sweet floral and fruity aroma, which affects the aroma characteristics of black tea [36], and that nerol and δ-cadinene are mainly expressed as a floral, woody fragrance, and these compounds further influence the formation of the aroma characteristics of WYMC. Phenylethyl alcohol imparts a pleasant floral aroma and has three main synthetic pathways in tea: the phenylacetaldehyde (PAld) pathway, the phenylpyruvic acid (PPA) plus PAld pathway, and the (E/Z)-phenylacetaldoxime ((E/Z)-PAOx) plus PAld pathway [55,56]. Previous studies indicate that phenylethyl alcohol is associated with the aroma quality of white tea, Guangdong black tea, and Weishan yellow tea [25,35,57]. The higher content of phenylethyl alcohol in WYMC compared to SX suggests that this compound may be a key contributor to the characteristic aroma of WYMC germplasm resources. To further investigate the mechanisms behind the aroma formation of WYMC, subsequent analysis can be conducted based on the transformation of precursor substances during the processing.

3.7. Molecular Docking Analysis of the Interaction Between the Potential Key Volatile Markers of WYMC and Human Olfactory Receptors

The results demonstrated that ten key volatile markers were effectively able to discriminate the aroma profiles between SX and the seven WYMC teas. Among these, five compounds were significantly more abundant in WYMC than in SX. To elucidate their roles in shaping the characteristic WYMC aroma, molecular docking was employed to simulate the binding interactions between these five key aroma compounds and human olfactory receptor proteins, thereby evaluating their potential contribution to aroma perception. In molecular docking studies, the binding energy between a ligand and its receptor protein is inversely correlated with the likelihood of their interaction; a lower binding energy indicates a higher probability of stable interaction and a binding energy threshold of ≤−5.0 kcal/mol is generally recognized as indicative of strong binding affinity [58,59,60,61,62,63]. To investigate the role of five potential key volatile markers in shaping the aroma characteristics of Wuyi Mingcong (WYMC) tea, we performed molecular docking analyses between these volatiles and four common human olfactory receptors (ORs), specifically OR1G1, OR5M3, OR7D4, and OR8D1 [17,59]. The docking results (Figure 7) revealed distinct binding patterns: cis-3-hexenyl benzoate and nerol exhibited spontaneous binding to all four olfactory receptors, with binding energies consistently ≤−5.0 kcal/mol, indicating robust affinity across multiple ORs. Phenylethyl alcohol and β-myrcene showed selective yet strong binding to OR1G1, OR5M3, and OR7D4, also meeting the ≤−5.0 kcal/mol threshold. Notably, δ-cadinene displayed high specificity for OR5M3 and OR8D1, with exceptionally low binding energies of −7.7 kcal/mol and −7.0 kcal/mol, respectively, suggesting particularly stable interactions with these receptors.
These molecular docking results provide critical insights into the potential sensory mechanisms underlying WYMC tea’s unique aroma. The strong binding affinities (≤−5.0 kcal/mol) observed for all five volatiles with at least one olfactory receptor support their role as key contributors to WYMC’s aroma profile—their ability to stably interact with human ORs suggests they are likely perceived as integral components of the tea’s sensory characteristics.
The differential binding specificities further illuminate the complexity of WYMC’s aroma. For instance, cis-3-hexenyl benzoate and nerol, which bound to all four ORs, may act as “broad-spectrum” aroma contributors, enhancing the overall intensity or layered nature of WYMC’s scent. In contrast, δ-cadinene’s high selectivity for OR5M3 and OR8D1—coupled with its exceptionally low binding energies—implies it may play a specialized role in shaping a distinct note within WYMC’s aroma bouquet, potentially contributing to woody or earthy undertones often associated with Wuyi rock teas. Moreover, these findings bridge chemical composition and sensory perception: phenylethyl alcohol (linked to floral and sweet notes) and nerol (a known floral volatile) exhibited strong interactions with multiple ORs, aligning with the sensory evaluation results highlighting “floral” and “sweet” as dominant aroma descriptors of WYMC. This consistency between chemical binding affinity and sensory attributes strengthens the argument that these volatiles are indeed critical to WYMC’s aroma quality.
In summary, the perceived aroma of tea arises from the synergistic interaction of multiple volatile compounds acting on the human olfactory system. Molecular docking results aligned with the sensory evaluation—particularly floral, fruity, and woody notes—observed in the tea samples. These findings were further supported by GC-MS analysis, which showed the presence of five characteristic compounds associated with WYMC. The convergence of molecular docking and GC-MS results lends additional support to the role of these compounds as fundamental contributors to the aroma of WYMC.

4. Conclusions

This study primarily analyzed the aroma characteristics and their volatiles of seven WYMC tea samples and the national variety SX, using QDA combined with electronic nose and HS-SPME-GC-MS. The results revealed typical floral and fruity notes with terpenoids and esters as the dominant volatile compounds. Dihydrolinalool and (E)-β-ionone ranked in the top two for OAV, suggesting that these two compounds may be the primary contributors to the floral and fruity aroma of the seven WYMC samples. Ten key volatile markers were identified that distinguish seven WYMC teas from SX. Among these, phenylethyl alcohol, cis-3-hexenyl benzoate, δ-cadinene, nerol, and β-myrcene may be the key volatiles in the formation of WYMC aroma characteristics. The results of molecular docking experiments showed that the five potential key volatile markers affecting the aroma characteristics of WYMC had strong binding affinity with four common human olfactory proteins. Future work will explore the quality characteristics of these cultivars across different years, seasons, and geographical conditions. This systematic investigation aims to elucidate the varietal effects more comprehensively, thereby providing a robust foundation for expanding the cultivation and utilization of WYMC.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11121414/s1. Table S1: The name and performance of sensors in the electronic nose. Table S2: Results of the sensory evaluation. Table S3. The classification results of the 192 aroma volatile compounds. Table S4: The differential content of aroma volatile compounds with VIP > 1 in SX and WYMC samples. Figure S1: Ion chromatogram of the quality control (QC) sample.

Author Contributions

Conceptualization, R.L. and H.F.; methodology, R.L. and H.F.; software, R.L. and Y.W.; formal analysis, R.L., H.F., Y.L. and Y.Z.; resources, B.Z., Y.S. and C.N.; data curation, Q.G. and Z.W.; writing—original draft preparation, R.L. and H.F.; writing—review and editing, F.W. and S.L.; supervision, F.W. and S.J.; project administration, F.W.; funding acquisition, F.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Project of Science and Technology Plan of Nanping city (N2024Z007), the Open Fund of Collaborative Innovation Center of Chinese Oolong Tea Industry (2025W 01), the Project of Science and Technology Plan of Fujian Province (2023N5013, 2024N3013, 2022N0030), the Scientific Research Fund of Wuyi University (2021L3058, 2024-WHFW-011, 2019N0023), and the Special Funds for Colleges and Universities in Fujian Province to Improve the Level of Running Schools (No.77 [2022]).

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Zeming Wu was employed by the company iPhenome Biotechnology (Dalian) Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
WYMCWuyi Mingcong
HS-SPME-GC-MSHeadspace solid-phase microextraction and gas chromatography–mass spectrometry
WRTWuyi rock tea
QDAQuantitative descriptive analysis

References

  1. Zeng, L.; Zhou, X.; Su, X.; Yang, Z. Chinese oolong tea: An aromatic beverage produced under multiple stresses. Trends Food Sci. Technol. 2020, 106, 242–253. [Google Scholar] [CrossRef]
  2. Chen, S.; Li, M.; Zheng, G.; Wang, T.; Lin, J.; Wang, S.; Wang, X.; Chao, Q.; Cao, S.; Yang, Z.; et al. Metabolite Profiling of 14 Wuyi Rock Tea Cultivars Using UPLC-QTOF MS and UPLC-QqQ MS Combined with Chemometrics. Molecules 2018, 23, 104. [Google Scholar] [CrossRef] [PubMed]
  3. Shang, H.; Zhu, C.; Sun, W. Widely targeted metabolomics analysis of different Wuyi Shuixian teas and association with taste attributes. Heliyon 2023, 9, e18891. [Google Scholar] [CrossRef]
  4. Peng, Y.; Zheng, C.; Guo, S.; Gao, F.; Wang, X.; Du, Z.; Gao, F.; Su, F.; Zhang, W.; Yu, X.; et al. Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea. NPJ Sci. Food 2023, 7, 7. [Google Scholar] [CrossRef] [PubMed]
  5. Huang, S.; Yu, Y.; Cui, J.; Luo, Z.; Luo, L.; Song, C.; Liao, H. Organic fertilizer substitution optimizes aroma metabolites in Wuyi Rock tea. Front. Plant Sci. 2025, 16, 1581120. [Google Scholar] [CrossRef] [PubMed]
  6. Liu, Z.; Chen, F.; Sun, J.; Ni, L. Dynamic changes of volatile and phenolic components during the whole manufacturing process of Wuyi Rock tea (Rougui). Food Chem. 2022, 367, 130624. [Google Scholar] [CrossRef]
  7. Zhang, Q.; Jia, X.; Chen, M.; Wang, Y.; Lin, S.; Pan, Y.; Cheng, P.; Li, M.; Zhang, Y.; Luo, Z.; et al. Effect of different degrees of withering on gene expression and metabolite content of Wuyi rock tea leaves. LWT 2023, 189, 115462. [Google Scholar] [CrossRef]
  8. Liu, N.; Shen, S.; Huang, L.; Deng, G.; Wei, Y.; Ning, J.; Wang, Y. Revelation of volatile contributions in green teas with different aroma types by GC-MS and GC-IMS. Food Res. Int. 2023, 169, 112845. [Google Scholar] [CrossRef]
  9. Schulze, L.J.; Schafer, U.; Beier, R.; Hartmann, B.; Wust, M.; Krammer, G.E. Molecular-Sensory Decoding of the Citrus latifolia Aroma. J. Agric. Food Chem. 2024, 72, 14874–14886. [Google Scholar] [CrossRef]
  10. Wang, Y.; Deng, G.; Huang, L.; Ning, J. Sensory-directed flavor analysis reveals the improvement in aroma quality of summer green tea by osmanthus scenting. Food Chem. X 2024, 23, 101571. [Google Scholar] [CrossRef]
  11. Song, X.; Wu, Z.; Liang, Q.; Ma, C.; Cai, P. Prediction of storage years of Wuyi rock tea Shuixian by metabolites analysis. Food Sci. Nutr. 2024, 12, 7166–7176. [Google Scholar] [CrossRef]
  12. Zhao, F.; Lin, H.T.; Zhang, S.; Lin, Y.F.; Yang, J.F.; Ye, N.X. Simultaneous determination of caffeine and some selected polyphenols in Wuyi Rock tea by high-performance liquid chromatography. J. Agric. Food Chem. 2014, 62, 2772–2781. [Google Scholar] [CrossRef]
  13. Yue, C.; Cao, H.; Zhang, S.; Hao, Z.; Wu, Z.; Luo, L.; Zeng, L. Aroma characteristics of Wuyi rock tea prepared from 16 different tea plant varieties. Food Chem. X 2023, 17, 100586. [Google Scholar] [CrossRef]
  14. GB/T 23776-2018; Methodology of Sensory Evaluation of Tea. Standardization Administration of the People’s Republic of China: Beijing, China, 2018.
  15. Guo, X.; Sch, W.; Ho, C.-T.; Song, C.; Wan, X. Characterization of the aroma profiles of oolong tea made from three tea cultivars by both GC–MS and GC-IMS. Food Chem. 2022, 376, 131933. [Google Scholar] [CrossRef]
  16. Wang, Z.; Gan, S.; Sun, W.; Chen, Z. Quality Characteristics of Oolong Tea Products in Different Regions and the Contribution of Thirteen Phytochemical Components to Its Taste. Horticulturae 2022, 8, 278. [Google Scholar] [CrossRef]
  17. Liang, Y.; Wang, Z.; Zhang, L.; Dai, H.; Wu, W.; Zheng, Z.; Lin, F.; Xu, J.; Huang, Y.; Sun, W. Characterization of volatile compounds and identification of key aroma compounds in different aroma types of Rougui Wuyi rock tea. Food Chem. 2024, 455, 139931. [Google Scholar] [CrossRef]
  18. Guo, X.; Ho, C.-T.; Wan, X.; Zhu, H.; Liu, Q.; Wen, Z. Changes of volatile compounds and odor profiles in Wuyi rock tea during processing. Food Chem. 2021, 341, 128230. [Google Scholar] [CrossRef] [PubMed]
  19. Zeng, J.; Lv, S.; Zeng, R.; Lin, J.; Jiang, J.; Shen, Q.; Ma, Y.; Fang, W.; Tian, J.; Zhu, X. Floral aroma improvement via solar withering and shaking in summer green tea: Sensory and analytical insights. Food Chem. X 2025, 29, 102833. [Google Scholar] [CrossRef] [PubMed]
  20. Wang, F.; Feng, H.; Zheng, Y.; Liu, R.; Dong, J.; Wu, Y.; Chen, S.; Zhang, B.; Wang, P.; Yan, J. Aroma analysis and biomarker screening of 27 tea cultivars based on four leaf color types. Food Res. Int. 2025, 201, 115681. [Google Scholar] [CrossRef]
  21. Zhu, Y.; Dong, J.; Jin, J.; Liu, J.; Zheng, X.; Lu, J.; Liang, Y.; Ye, J. Roasting process shaping the chemical profile of roasted green tea and the association with aroma features. Food Chem. 2021, 353, 129428. [Google Scholar] [CrossRef] [PubMed]
  22. Chen, G.; Zhu, G.; Xie, H.; Zhang, J.; Huang, J.; Liu, Z.; Wang, C. Characterization of the key differential aroma compounds in five dark teas from different geographical regions integrating GC–MS, ROAV and chemometrics approaches. Food Res. Int. 2024, 194, 114928. [Google Scholar] [CrossRef]
  23. Qin, D.; Wang, Q.; Jiang, X.; Ni, E.; Fang, K.; Li, H.; Wang, Q.; Pan, C.; Li, B.; Wu, H. Identification of key volatile and odor-active compounds in 10 main fragrance types of Fenghuang Dancong tea using HS-SPME/GC-MS combined with multivariate analysis. Food Res. Int. 2023, 173, 113356. [Google Scholar] [CrossRef]
  24. Li, M.; Zhang, Y.; Chen, C.; Zhong, S.; Li, M.; Xu, K.; Zhu, Y.; Li, P.; You, S.; Jin, S. Chemical and Quality Analysis of Beauty Tea Processed from Fresh Leaves of Tieguanyin Variety with Different Puncturing Degrees. Foods 2023, 12, 1737. [Google Scholar] [CrossRef]
  25. Ma, L.; Sun, Y.; Wang, X.; Zhang, H.; Zhang, L.; Yin, Y.; Wu, Y.; Du, L.; Du, Z. The characteristic of the key aroma-active components in white tea using GC-TOF-MS and GC-olfactometry combined with sensory-directed flavor analysis. J. Sci. Food Agric. 2023, 103, 7136–7152. [Google Scholar] [CrossRef]
  26. Liu, H.; Xu, Y.; Wu, J.; Wen, J.; Yu, Y.; An, K.; Zou, B. GC-IMS and olfactometry analysis on the tea aroma of Yingde black teas harvested in different seasons. Food Res. Int. 2021, 150, 110784. [Google Scholar] [CrossRef] [PubMed]
  27. Wang, M.; Ma, W.; Shi, J.; Zhu, Y.; Lin, Z.; Lv, H. Characterization of the key aroma compounds in Longjing tea using stir bar sorptive extraction (SBSE) combined with gas chromatography-mass spectrometry (GC–MS), gas chromatography-olfactometry (GC-O), odor activity value (OAV), and aroma recombination. Food Res. Int. 2020, 130, 108908. [Google Scholar] [CrossRef] [PubMed]
  28. Zhai, X.; Zhang, L.; Granvogl, M.; Ho, C.T.; Wan, X. Flavor of tea (Camellia sinensis): A review on odorants and analytical techniques. Compr. Rev. Food Sci. Food Saf. 2022, 21, 3867–3909. [Google Scholar] [CrossRef] [PubMed]
  29. Liu, Y.; Yang, X.; Gan, J.; Chen, S.; Xiao, Z.-X.; Cao, Y. CB-Dock2: Improved protein-ligand blind docking by integrating cavity detection, docking and homologous template fitting. Nucleic Acids Res. 2022, 50, W159–W164. [Google Scholar] [CrossRef]
  30. Guo, X.; Schwab, W.; Ho, C.T.; Song, C.; Wan, X. Characterization of the changes of aroma profiles in large-leaf yellow tea during processing using GC–MS and electronic nose analysis. Food Chem. X 2025, 27, 102507. [Google Scholar] [CrossRef]
  31. Chen, S.; Xie, P.; Li, Y.; Wang, X.; Liu, H.; Wang, S.; Han, W.; Wu, R.; Li, X.; Guan, Y.; et al. New Insights into Stress-Induced β-Ocimene Biosynthesis in Tea (Camellia sinensis) Leaves during Oolong Tea Processing. J. Agric. Food Chem. 2021, 69, 11656–11664. [Google Scholar] [CrossRef]
  32. Wang, C.; Lv, S.; Wu, Y.; Gao, X.; Li, J.; Zhang, W.; Meng, Q. Oolong tea made from tea plants from different locations in Yunnan and Fujian, China showed similar aroma but different taste characteristics. SpringerPlus 2016, 5, 576. [Google Scholar] [CrossRef]
  33. Deng, H.; Chen, S.; Zhou, Z.; Li, X.; Chen, S.; Hu, J.; Lai, Z.; Sun, Y. Transcriptome analysis reveals the effect of short-term sunlight on aroma metabolism in postharvest leaves of oolong tea(Camellia sinensis). Food Res. Int. 2020, 137, 109347. [Google Scholar] [CrossRef] [PubMed]
  34. Huang, F.; Yang, P.; Bai, S.; Liu, Z.; Li, J.; Huang, J.; Xiong, L. Lipids: A noteworthy role in better tea quality. Food Chem. 2024, 431, 137071. [Google Scholar] [CrossRef] [PubMed]
  35. Shi, Y.; Wang, M.; Dong, Z.; Zhu, Y.; Shi, J.; Ma, W.; Lin, Z.; Lv, H. Volatile components and key odorants of Chinese yellow tea (Camellia sinensis). LWT 2021, 146, 111512. [Google Scholar] [CrossRef]
  36. Chen, Q.; Yu, P.; Li, Z.; Wang, Y.; Liu, Y.; Zhu, Y.; Fu, H. Re-Rolling Treatment in the Fermentation Process Improves the Aroma Quality of Black Tea. Foods 2023, 12, 3702. [Google Scholar] [CrossRef] [PubMed]
  37. Ye, J.; Wang, Y.; Lin, S.; Hong, L.; Kang, J.; Chen, Y.; Li, M.; Jia, Y.; Jia, X.; Wu, Z.; et al. Effect of processing on aroma intensity and odor characteristic of Shuixian (Camellia sinensis) tea. Food Chem. X 2023, 17, 100616. [Google Scholar] [CrossRef]
  38. Yang, J.; Zhou, X.; Wu, S.; Gu, D.; Zeng, L.; Yang, Z. Involvement of DNA methylation in regulating the accumulation of the aroma compound indole in tea (Camellia sinensis) leaves during postharvest processing. Food Res. Int. 2021, 142, 110183. [Google Scholar] [CrossRef]
  39. Zhao, Y.; Li, S.; Du, X.; Xu, W.; Bian, J.; Chen, S.; He, C.; Xu, J.; Ye, S.; Feng, D.; et al. Insights into momentous aroma dominating the characteristic flavor of jasmine tea. Food Sci. Nutr. 2023, 11, 7841–7854. [Google Scholar] [CrossRef]
  40. Song, H.; Liu, J. GC-O-MS technique and its applications in food flavor analysis. Food Res. Int. 2018, 114, 187–198. [Google Scholar] [CrossRef]
  41. Ni, H.; Jiang, Q.; Lin, Q.; Ma, Q.; Wang, L.; Weng, S.; Huang, G.; Li, L.; Chen, F. Enzymatic hydrolysis and auto-isomerization during beta-glucosidase treatment improve the aroma of instant white tea infusion. Food Chem. 2021, 342, 128565. [Google Scholar] [CrossRef]
  42. Wang, Z.; Su, D.; Ren, H.; Lv, Q.; Ren, L.; Li, Y.; Zhou, H. Effect of different drying methods after fermentation on the aroma of Pu-erh tea (ripe tea). LWT 2022, 171, 114129. [Google Scholar] [CrossRef]
  43. Zhu, L.; Wang, X.; Song, X.; Zheng, F.; Li, H.; Chen, F.; Zhang, Y.; Zhang, F. Evolution of the key odorants and aroma profiles in traditional Laowuzeng baijiu during its one-year ageing. Food Chem. 2020, 310, 125898. [Google Scholar] [CrossRef] [PubMed]
  44. Zhang, J.; Xia, D.; Li, T.; Wei, Y.; Feng, W.; Xiong, Z.; Huang, J.; Deng, W.W.; Ning, J. Effects of different over-fired drying methods on the aroma of Lu’an Guapian tea. Food Res. Int. 2023, 173, 113224. [Google Scholar] [CrossRef] [PubMed]
  45. Zhang, L.; Ni, H.; Zhu, Y.; Yang, Y.; Li, L.; Jiang, Z.; Zheng, F.P.; Chen, F. Characterization of aromas of instant oolong tea and its counterparts treated with two crude enzymes from Aspergillus niger. J. Food Process. Preserv. 2017, 42, e13500. [Google Scholar] [CrossRef]
  46. Kang, S.; Yan, H.; Zhu, Y.; Liu, X.; Lv, H.; Zhang, Y.; Dai, W.; Guo, L.; Tan, J.; Peng, Q.; et al. Identification and quantification of key odorants in the world’s four most famous black teas. Food Res. Int. 2019, 121, 73–83. [Google Scholar] [CrossRef]
  47. Guo, Y.; Shen, Y.; Hu, B.; Ye, H.; Guo, H.; Chu, Q.; Chen, P. Decoding the Chemical Signatures and Sensory Profiles of Enshi Yulu: Insights from Diverse Tea Cultivars. Plants 2023, 12, 3707. [Google Scholar] [CrossRef]
  48. Wu, Z.; Chen, L.; Wu, L.; Xue, X.; Zhao, J.; Li, Y.; Ye, Z.; Lin, G. Classification of Chinese Honeys According to Their Floral Origins Using Elemental and Stable Isotopic Compositions. J. Agric. Food Chem. 2015, 63, 5388–5394. [Google Scholar] [CrossRef]
  49. Ho, C.; Zheng, X.; Li, S. Tea aroma formation. Food Sci. Hum. Wellness 2015, 4, 9–27. [Google Scholar] [CrossRef]
  50. Zeng, L.; Zhou, Y.; Gui, J.; Fu, X.; Mei, X.; Zhen, Y.; Ye, T.; Du, B.; Dong, F.; Watanabe, N.; et al. Formation of Volatile Tea Constituent Indole During the Oolong Tea Manufacturing Process. J. Agric. Food Chem. 2016, 64, 5011–5019. [Google Scholar] [CrossRef]
  51. Zeng, L.; Zhou, Y.; Fu, X.; Liao, Y.; Yuan, Y.; Jia, Y.; Dong, F.; Yang, Z. Biosynthesis of Jasmine Lactone in Tea (Camellia sinensis) Leaves and Its Formation in Response to Multiple Stresses. J. Agric. Food Chem. 2018, 66, 3899–3909. [Google Scholar] [CrossRef]
  52. Wang, J.; Li, M.; Wang, H.; Huang, W.; Li, F.; Wang, L.; Ho, C.T.; Zhang, Y.; Zhang, L.; Zhai, X.; et al. Decoding the Specific Roasty Aroma Wuyi Rock Tea (Camellia sinensis: Dahongpao) by the Sensomics Approach. J. Agric. Food Chem. 2022, 70, 10571–10583. [Google Scholar] [CrossRef]
  53. Li, M.; Zhang, Y.; Yan, J.; Ding, F.; Chen, C.; Zhong, S.; Li, M.; Zhu, Y.; Yue, P.; Li, P.; et al. Comparative Metabolomic Analysis Reveals the Differences in Nonvolatile and Volatile Metabolites and Their Quality Characteristics in Beauty Tea with Different Extents of Punctured Leaves by Tea Green Leafhopper. J. Agric. Food Chem. 2023, 71, 16233–16247. [Google Scholar] [CrossRef] [PubMed]
  54. Wu, Z.; Jiao, Y.; Jiang, X.; Li, C.; Sun, W.; Chen, Y.; Yu, Z.; Ni, D. Effects of Sun Withering Degree on Black Tea Quality Revealed via Non-Targeted Metabolomics. Foods 2023, 12, 2430. [Google Scholar] [CrossRef]
  55. Yao, H.; Su, H.; Ma, J.; Zheng, J.; He, W.; Wu, C.; Hou, Z.; Zhao, R.; Zhou, Q. Widely targeted volatileomics analysis reveals the typical aroma formation of Xinyang black tea during fermentation. Food Res. Int. 2023, 164, 112387. [Google Scholar] [CrossRef]
  56. Zeng, L.; Tan, H.; Liao, Y.; Jian, G.; Kang, M.; Dong, F.; Watanabe, N.; Yang, Z. Increasing Temperature Changes Flux into Multiple Biosynthetic Pathways for 2-Phenylethanol in Model Systems of Tea (Camellia sinensis) and Other Plants. J. Agric. Food Chem. 2019, 67, 10145–10154. [Google Scholar] [CrossRef] [PubMed]
  57. Wang, Q.; Qin, D.; Jiang, X.; Fang, K.; Li, B.; Wang, Q.; Pan, C.; Ni, E.; Li, H.; Chen, D.; et al. Characterization of the Aroma Profiles of Guangdong Black Teas Using Non-Targeted Metabolomics. Foods 2023, 12, 1560. [Google Scholar] [CrossRef] [PubMed]
  58. Huang, Z.; Du, X.; Ma, C.; Zhang, R.; Gong, W.L.; Liu, F. Identification of Antitumor Active Constituents in Polygonatum sibiricum Flower by UPLC-Q-TOF-MSE and Network Pharmacology. ACS Omega 2020, 5, 29755–29764. [Google Scholar] [CrossRef]
  59. Zheng, Y.; Zhang, Y.; Ou, X.; Li, Q.; Huang, H.; Zhang, J.; Wang, F.; Shi, Y.; Hao, Z.; Zhang, B.; et al. The New Aristocrat of Wuyi Rock Tea: Chemical Basis of the Unique Aroma Quality of “Laocong Shuixian”. Foods 2025, 14, 1706. [Google Scholar] [CrossRef]
  60. Wei, Z.; Jinan, W.; Ziyin, W.; Chao, H.; Aiping, L.; Yonghua, W. Systems pharmacology exploration of botanic drug pairs reveals the mechanism for treating different diseases. Sci. Rep. 2016, 6, 36985. [Google Scholar] [CrossRef]
  61. Liu, H.; Wang, J.; Zhou, W.; Wang, Y.; Yang, L. Systems approaches and polypharmacology for drug discovery from herbal medicines: An example using licorice. J. Ethnopharmacol. 2013, 146, 773–793. [Google Scholar] [CrossRef]
  62. Tao, W.; Xu, X.; Wang, X.; Li, B.; Wang, Y.; Li, Y.; Yang, L. Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J. Ethnopharmacol. 2013, 145, 1–10. [Google Scholar] [CrossRef] [PubMed]
  63. Li, X.; Xu, X.; Wang, J.; Yu, H.; Wang, X.; Yang, H.; Xu, H.; Tang, S.; Li, Y.; Yang, L.; et al. A system-level investigation into the mechanisms of Chinese Traditional Medicine: Compound Danshen Formula for cardiovascular disease treatment. PLoS ONE 2018, 7, e43918. [Google Scholar] [CrossRef] [PubMed]
Figure 1. (a) The shape, infusion, leaves, and aroma of SX and WYMC tea samples used in this study, and the infusion color of the first brewed cup were recorded. (b) The aroma attributes of SX and WYMC tea samples were analyzed by using electronic nose (note: the name and performance of the sensor in the electronic nose are shown in Table S1).
Figure 1. (a) The shape, infusion, leaves, and aroma of SX and WYMC tea samples used in this study, and the infusion color of the first brewed cup were recorded. (b) The aroma attributes of SX and WYMC tea samples were analyzed by using electronic nose (note: the name and performance of the sensor in the electronic nose are shown in Table S1).
Horticulturae 11 01414 g001
Figure 2. (a) Scores of different aroma characteristics of eight tea samples. (b) Classification of different volatile compounds classes in the eight tea samples. (c) The relative content of the different volatile compound classes of the eight tea samples. (d) The percentage of the different volatile compound classes of the eight tea samples.
Figure 2. (a) Scores of different aroma characteristics of eight tea samples. (b) Classification of different volatile compounds classes in the eight tea samples. (c) The relative content of the different volatile compound classes of the eight tea samples. (d) The percentage of the different volatile compound classes of the eight tea samples.
Horticulturae 11 01414 g002
Figure 3. The aroma wheels for the WYMC tea samples were constructed based on 37 volatiles with OAV > 1.
Figure 3. The aroma wheels for the WYMC tea samples were constructed based on 37 volatiles with OAV > 1.
Horticulturae 11 01414 g003
Figure 4. (a) The PCA score plot of eight tea samples using all aroma volatile compounds. (b) Cluster heatmap analysis of aroma volatile compounds of eight tea samples (the vertical axis presents the results of unsupervised hierarchical clustering of the GC-MS-detected volatile compounds). (c) The OPLS-DA score plot of SX and WYMC tea samples. (d) The OPLS-DA model after 200 randomized permutation experiments.
Figure 4. (a) The PCA score plot of eight tea samples using all aroma volatile compounds. (b) Cluster heatmap analysis of aroma volatile compounds of eight tea samples (the vertical axis presents the results of unsupervised hierarchical clustering of the GC-MS-detected volatile compounds). (c) The OPLS-DA score plot of SX and WYMC tea samples. (d) The OPLS-DA model after 200 randomized permutation experiments.
Horticulturae 11 01414 g004
Figure 5. Heat map of the differential content of volatile compounds with VIP > 1 in SX and WYMC tea samples: (a) terpenoids; (b) esters and acid; (c) hydrocarbons; (d) ketones; (e) alcohol; and (f) phenol, aromatics, aldehydes, heterocyclic compounds.
Figure 5. Heat map of the differential content of volatile compounds with VIP > 1 in SX and WYMC tea samples: (a) terpenoids; (b) esters and acid; (c) hydrocarbons; (d) ketones; (e) alcohol; and (f) phenol, aromatics, aldehydes, heterocyclic compounds.
Horticulturae 11 01414 g005
Figure 6. (a) The aroma volatiles, more abundant in WYMC teas than in SX tea. (b) The aroma volatiles, more abundant in SX tea than in WYMC teas (note: different letters indicate significant differences among group means at p < 0.05).
Figure 6. (a) The aroma volatiles, more abundant in WYMC teas than in SX tea. (b) The aroma volatiles, more abundant in SX tea than in WYMC teas (note: different letters indicate significant differences among group means at p < 0.05).
Horticulturae 11 01414 g006
Figure 7. Molecular docking results of five key volatile markers in WYMC.
Figure 7. Molecular docking results of five key volatile markers in WYMC.
Horticulturae 11 01414 g007aHorticulturae 11 01414 g007b
Table 1. The 37 aroma volatile compounds with OAV > 1 in eight samples.
Table 1. The 37 aroma volatile compounds with OAV > 1 in eight samples.
CompoundsOdor DescriptionCASThreshold
(μg/g)
SXRGZGFMJLHZTYHDJHHTGSL
Alcohols
1-Octen-3-olmushroom, floral, and hay3391-86-40.001349.56240.04182.00332.89 282.25 329.18 213.32 242.11
Phenylethyl alcoholsoft, and lasting rose60-12-80.147.80 22.19 18.22 18.38 9.18 22.46 26.51 18.80
(E)-3-Hexen-1-olclean, and fresh928-97-20.111.60 1.12 2.63 4.53 2.43 6.03 2.27 1.94
Ketones
6-Methyl-5-hepten-2-onefruity, and fresh110-93-00.0533.25 20.27 8.33 15.15 17.05 15.42 18.27 10.05
2,2,6-Trimethyl-cyclohexanonepungent, honey, and herbal2408-37-90.00011263.251314.711143.291780.441516.46 1197.041144.501311.46
Jasmoneelegant jasmine488-10-80.00790.46 41.04 52.83 37.11 74.12 294.82 137.83 97.33
Geranylacetonefresh rose3796-70-10.0610.28 8.99 8.81 10.22 9.71 7.84 7.71 6.85
Terpenoids
Nerolrose106-25-20.0491.31 1.68 3.23 2.26 1.37 4.69 1.25 2.05
β-Myrcenesweet orange, and balsamic123-35-30.01528.86 28.09 57.76 57.23 36.29 77.47 24.86 42.97
γ-Terpinenecitrus, and lemon99-85-40.00242.82 65.68 21.99 28.56 24.45 43.35 35.03 29.48
β-Ocimenecitrus, and green13877-91-30.006792.90 47.44 73.64 81.59 63.21 196.67 68.98 70.11
Linaloolsweet, and floral78-70-60.006253.85 166.52 141.70 199.61 176.34 596.10 200.51 264.00
2,6-Dimethyl-2,4,6-octatrienefloral673-84-70.0340.64 0.50 0.66 0.81 0.56 1.01 0.38 0.58
Safranalwoody, and herbal116-26-70.00322.91 31.90 21.76 27.77 23.39 24.01 18.65 22.95
β-Cyclocitralsaffron, herbal, sweet, and fruity432-25-70.00348.74 43.77 34.21 50.11 53.94 32.45 34.90 31.49
Geraniolmild, and sweet rose106-24-10.0066268.98 173.30 808.52 530.10 337.00 916.28 219.13 515.91
(+)-α-Pineneherbaceous7785-70-80.005312.09 7.68 96.13 5.06 74.63 26.79 22.29 3.15
α-Iononewarm, woody, and violet127-41-30.0004813.18 698.14 299.13 542.75 872.44 359.90 829.71 359.11
cis-β-Farnesenegreen28973-97-90.08737.64 38.34 17.42 33.10 33.13 41.38 76.01 30.82
(E)-β-Iononeviolet79-77-60.00028718.50 7529.17 6229.88 8498.84 10269.65 6375.36 5939.87 6096.80
δ-Cadinenethyme, and woody483-76-10.001524.53 23.29 57.97 64.21 37.04 64.16 73.56 183.90
trans-Nerolidolwoody, floral, and fruity40716-66-30.2534.83 32.86 18.97 29.29 27.70 43.16 60.83 33.04
trans-Linalool oxide (furanoid)floral34995-77-20.193.41 1.82 4.79 6.04 1.81 10.96 7.88 6.59
Dihydrolinaloolfloral, and fruity29957-43-50.000656425.26 8288.17 2624.28 2426.63 2376.62 4362.25 5333.76 4057.73
Esters
Methyl salicylatestrong wintergreen119-36-80.0415.22 5.77 21.45 23.62 8.46 28.83 16.53 17.09
cis-3-Hexenyl valerategreen apple35852-46-10.0611.93 8.16 7.64 9.37 4.91 12.52 11.10 8.17
Hexyl 2-methylbutyratefruity10032-15-20.02228.78 25.22 12.79 11.58 5.63 16.67 19.25 16.59
cis-3-Hexenyl hexanoatesweet, and apple-pear31501-11-80.7817.39 7.24 7.85 9.52 5.96 11.90 7.35 6.40
Dihydroactinidiolidewoody, and floral17092-92-10.0021244.68 187.02 127.09 204.60 281.29 122.27 183.30 128.53
cis-3-Hexenyl benzoategreen, floral, and balsamic25152-85-60.50.72 1.38 1.60 1.33 0.77 1.52 1.42 1.13
Hexyl benzoatewoody, balsamic, and fruity6789-88-40.0732.94 7.30 3.28 2.20 1.41 2.86 3.75 4.00
Methyl jasmonatestrong floral, and green1211-29-60.074.62 1.45 1.91 1.99 2.54 10.30 3.85 3.03
cis-Jasminlactonecoconut, fruity, and jasmine25524-95-224.10 1.06 1.20 1.56 1.31 2.12 2.46 0.57
Heterocyclic compounds
2-Pentyl-furanfruity, and vegetal3777-69-30.006150.84 134.56 64.97 163.67 128.00 205.32 108.34 104.65
Indolelight floral, orange, and jasmine120-72-90.04509.19 110.42 191.14 218.06 236.70 328.48318.96185.46
Aldehydes
Decanalgreen, spicy, citrus, and rose112-31-20.0001323.24 443.87 179.50 316.67 241.98 290.09 222.78189.48
Benzaldehydebitter almond100-52-70.350.67 1.07 0.38 0.66 0.41 0.57 0.67 0.31
Table 2. Ten key marker volatiles distinguish SX and WYMC.
Table 2. Ten key marker volatiles distinguish SX and WYMC.
CompoundsOdor DescriptionVIPOAVPrecursorStructural Formula
6-Methyl-5-hepten-2-onefruity, and fresh2.11 8.33~33.25CarotenoidsHorticulturae 11 01414 i001
Phenylethyl alcoholsoft, and lasting rose2.06 7.8~26.51Amino acidsHorticulturae 11 01414 i002
Indolelight floral, orange, and jasmine2.05 110.42~509.19Amino acids/
Carbohydrates
Horticulturae 11 01414 i003
cis-Jasminlactonecoconut, fruity, and jasmine2.02 1.06~4.1Fatty AcidsHorticulturae 11 01414 i004
cis-3-hexenyl benzoategreen, floral, and balsamic1.96 0.5~1.6Fatty AcidsHorticulturae 11 01414 i005
Hexyl 2-methylbutyratefruity1.49 5.63~28.78Fatty AcidsHorticulturae 11 01414 i006
δ-Cadinenethyme, and woody1.35 23.29~183.9CarotenoidsHorticulturae 11 01414 i007
Dihydrolinaloolfloral, and fruity1.16 2376.62~8288.17CarotenoidsHorticulturae 11 01414 i008
Nerolrose1.13 1.25~4.69CarotenoidsHorticulturae 11 01414 i009
β-Myrcenesweet orange, and balsamic1.01 24.86~77.47CarotenoidsHorticulturae 11 01414 i010
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Liu, R.; Feng, H.; Wu, Y.; Lin, S.; Zheng, Y.; Liu, Y.; Zhang, B.; Shi, Y.; Nie, C.; Guo, Q.; et al. Aroma Characterization and Key Volatile Identification in Wuyi Rock Tea Prepared from Wuyi Mingcong Tea Plant Varieties. Horticulturae 2025, 11, 1414. https://doi.org/10.3390/horticulturae11121414

AMA Style

Liu R, Feng H, Wu Y, Lin S, Zheng Y, Liu Y, Zhang B, Shi Y, Nie C, Guo Q, et al. Aroma Characterization and Key Volatile Identification in Wuyi Rock Tea Prepared from Wuyi Mingcong Tea Plant Varieties. Horticulturae. 2025; 11(12):1414. https://doi.org/10.3390/horticulturae11121414

Chicago/Turabian Style

Liu, Ruihua, Hua Feng, Yao Wu, Shijia Lin, Yucheng Zheng, Yiting Liu, Bo Zhang, Yutao Shi, Chuanpeng Nie, Qi Guo, and et al. 2025. "Aroma Characterization and Key Volatile Identification in Wuyi Rock Tea Prepared from Wuyi Mingcong Tea Plant Varieties" Horticulturae 11, no. 12: 1414. https://doi.org/10.3390/horticulturae11121414

APA Style

Liu, R., Feng, H., Wu, Y., Lin, S., Zheng, Y., Liu, Y., Zhang, B., Shi, Y., Nie, C., Guo, Q., Wu, Z., Wang, F., & Jin, S. (2025). Aroma Characterization and Key Volatile Identification in Wuyi Rock Tea Prepared from Wuyi Mingcong Tea Plant Varieties. Horticulturae, 11(12), 1414. https://doi.org/10.3390/horticulturae11121414

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop