Integrated Liquid Chromatography‐Tandem Mass Spectrometry and Headspace Solid‐Phase Microextraction With Gas Chromatography‐Mass Spectrometry‐based Profiling Reveals Developmental Metabolic Dynamics of Ligusticum striatum DC.

ABSTRACT

Ligusticum striatum DC. (Ligusticum chuanxiong Hort. or Ligusticum wallichii) is a traditional medicinal herb in East Asia used for cardiovascular, neurological, and inflammatory disorders, but developmental phytochemical changes remain unclear. Here, targeted liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) and untargeted headspace solid‐phase microextraction with gas chromatography‐MS were applied to examine five bioactive compounds and volatile organic compounds (VOCs) in aerial and root tissues across seven growth periods. Five compounds, including ferulic acid, icariside F2, ligusticoside A, N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid, and ligustiphenol, were quantified with excellent linearity, sensitivity, precision, and accuracy. VOC profiling identified 33 and 32 compounds in aerial parts and roots, respectively, showing clear period‐ and tissue‐specific differences. Chemometrics analysis revealed distinct clustering by growth stage, indicating dynamic metabolic shifts. Overall, roots served as reservoirs of phenolic acids, while aerial parts were enriched in phthalides and sesquiterpenes. These findings provide a basis for harvest optimization, quality control, and standardization of L. striatum, while novel compounds in Vietnamese herbal medicines expand its phytochemical diversity and pharmacological potential.

A complementary liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) and headspace solid‐phase microextraction coupled with gas chromatography‐MS platform revealed coordinated changes in primary volatile and bioactive metabolites throughout Ligusticum striatum DC. development, providing biomarkers for quality control and harvest optimization.

1. Introduction

The genus Ligusticum belongs to the Apiaceae family and includes 66 recognized species. These species are widely distributed across Asia, Europe, and North America, many of which hold significant ethnopharmacological value [1, 2, 3]. Among those various species, Ligusticum striatum DC. (frequently associated with Ligusticum chuanxiong Hort., or Ligusticum wallichii)—also known as Chuanxiong—is extensively used in traditional medicine for treating cardiovascular and neurological disorders, promoting blood circulation, relieving pain, and treating amenorrhea, including pain management and menstrual irregularities [1, 4, 5, 6].

L. striatum contains a diverse chemical pool that contributes to its special medicinal properties. The major chemical components identified include essential oils, alkaloids, phenolic acids, phthalide lactones, and other compounds, many of which exhibit vasorelaxation and antioxidant activities [5, 6]. Specifically, phenolic acids, alkaloids, and terpenes are widely used for cardiovascular disorders, which have gained strong clinical and research interest in L. striatum [7, 8]. Polyphenols, which include phenolic acids, flavonoids, and simple phenols, represent a substantial proportion of the identified compounds in L. striatum [9, 10]. The primary active compounds in L. striatum, particularly senkyunolide I and senkyunolide H, are recognized for their various therapeutic effects, including anti‐migraine, neuroprotective, and anti‐inflammatory activities, as well as their roles in protecting red blood cells and improving blood flow and vascular function. These compounds are often used as chemical markers in the analysis of Chuanxiong [11, 12]. Tetramethylpyrazine and ferulic acid are representative constituents of L. chuanxiong with complementary, rather than identical, pharmacological profiles: Tetramethylpyrazine is mainly associated with vascular, antithrombotic, endothelial, and neuroprotective effects, while ferulic acid primarily contributes antioxidant and anti‐inflammatory activities relevant to ischemic and neurodegenerative injury [9, 10, 13, 14].

L. striatum is also known for an abundant amount of volatile organic compounds (VOCs), which play an important role in its specific aroma. VOCs can also serve as biomarkers for quality assessment, authentication, and differentiation among closely related species or ecotypes​. Aroma is a complex mixture of various VOCs that not only impart a distinctive fragrance but also play essential roles in the ecological adaptability of plants, such as attracting pollinators and deterring pathogens [15, 16]. Strong aromatic scents are often indicators of high quality. However, these unique aromas can vary significantly and are often difficult to distinguish from one another [13]. Therefore, it is also important to elucidate VOC profiles according to harvest conditions in herbal medicines. Traditional extraction methods of VOCs are steam distillation and solvent extraction, which involve high temperatures or aggressive solvents that may alter or degrade thermolabile compounds, thereby affecting the native VOC profile [17, 18]. Meanwhile, headspace solid‐phase microextraction gas chromatography‐mass spectrometry (HS‐SPME‐GC/MS) is a highly effective analytical technique for detecting volatile and semi‐volatile compounds in complex matrices [19]. Several studies have used HS‐SPME‐GC/MS to analyze VOCs in L. Striatum due to its high sensitivity and solvent‐free extraction ​ [4, 20, 21]. These findings support HS‐SPME‐GC/MS as a valuable tool for species differentiation and chemotaxonomic studies. However, most studies focused on chemical profiling of mature rhizomes, overlooking key biosynthetic and metabolic transitions that occur at different growth stages. For example, Zhanga et al. compared L. chuanxiong from Gansu and Sichuan but only analyzed harvest stage samples, missing VOC changes over time. Studying L. striatum across different growth stages is essential to understand how VOC composition evolves during plant development [22]. In addition, Huang et al. collected samples during their respective harvesting periods to compare VOCs among four herbs of L. striatum in China and Japan (Chuanxiong, Japanese Chuanxiong, Fuxiong and Jinxiong) [4]. Xu et al. gathered samples at harvest time by selecting fully extended, mature leaves from cultivation areas in China [21].

Chemical profiling of L. striatum at different growth stages is crucial because secondary metabolite production is highly stage‐dependent. Key compounds such as ferulic acid, ligustilides, and phthalides could accumulate at specific phases. Therefore, to evaluate pharmacological potential properly, periodic chemical profiling should be considered. Stage‐specific profiles can also clarify metabolite functions since early stages often produce defense‐related VOCs, while later stages favor storage metabolites like phenolic acids. Such analyses could improve quality control (QC) in traditional medicine by establishing quality markers and optimal harvest times, ensuring reproducibility in clinical use. In addition, the analysis of two new compounds, which are ligusticoside A and N‐3‐(3‐methoxy‐4‐hydroxyphenyl)allyl pipecolic acid, also expands the chemical diversity and pharmacological prospects. For cultivation and industry, analysis of herbal medicines with different harvest periods would suggest an optimal method of harvest timing and processing to maximize therapeutic efficacy and economic value.

This study integrates untargeted HS‐SPME‐GC/MS and targeted liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) analyses to characterize phytochemical variation in L. striatum across seven different harvest periods, which were cultivated in Vietnam. VOC profiles of aerial and root parts were tracked with chemometric analyses identifying stage‐specific biomarkers. This study also quantified five pharmacologically important compounds using LC–MS/MS, including ferulic acid, icariside F2, and ligustiphenol, which have been previously reported for their bioactivities. In addition, two structurally distinct compounds, ligusticoside A and N‐3‐(3‐methoxy‐4‐hydroxyphenyl)allyl pipecolic acid, were detected in Vietnamese L. striatum samples [23, 24, 25, 26]. N‐3‐(3‐methoxy‐4‐hydroxyphenyl)allyl pipecolic acid represents a structurally novel metabolite, while ligusticoside A, previously reported only in L. chuanxiong from China, is reported here for the first time in Vietnamese material [27, 28].

2. Materials and Methods

2.1. Standards and Materials

For HPLC analysis, 5 standards including N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid, ferulic acid, icariside F2, ligusticoside A, and ligustiphenol were isolated from L. striatum [28]. Standard solutions of n‐alkanes C7–C30 for GC‐MS were purchased from Sigma‐Aldrich (St. Louis, MO, USA). HPLC‐grade methanol, acetonitrile, and water were purchased from J. T. Baker (Phillipsburg, NJ, USA). Each standard was prepared as a stock solution by dissolving the mixture in 80% methanol.

2.2. Sample Collection

L. striatum was planted on February 15, 2024. For chemical profiling, Lao Cai province populations of L. striatum were collected at the beginning of each month from June to December 2024 at a sampling site located around N22.353230, E103.859520, at an elevation of approximately 1350 m above sea level, in northern Vietnam. A voucher herbarium specimen (NKB0824) has been deposited at the Institute of Chemistry, VAST in Hanoi, Vietnam. The whole plants were carefully harvested and separated into two distinct parts: the aerial part and the root part at each time point. This separation allowed for a detailed investigation of compound distribution across different plant parts during the growth period. Harvesting was conducted when the plants were fully developed with completely formed leaves and well‐established root systems, ensuring that both vegetative organs had reached a stable stage of growth and metabolite accumulation. After collection, the fresh plant materials were cleaned to remove impurities and chopped into small pieces. The chopped materials were then dried at 50°C using a dry oven before being ground into powder and passed through a 1680 µm sieve to obtain a uniform particle size. The powdered samples were stored at room temperature until extraction. For each sampling time point, three technical replicates were prepared and analyzed to evaluate analytical reproducibility.

2.3. Extraction Method Development

2.3.1. Ultrasonic‐assisted Extraction

An aliquot of each precisely weighed sample (500 mg) was extracted in a 50 mL centrifuge tube with 10 mL of 80% methanol for each extraction, performed in triplicate. The samples were then sonicated for 30 min at 40°C. Following sonication, the extracts were centrifuged at 15 000 rcf for 10 min at 4°C. The resulting supernatants were evaporated to dryness using a rotary evaporator. The dried residues were reconstituted in 80% methanol and transferred to a 10 mL volumetric flask. Then, the solution was diluted fivefold to achieve a final concentration of 10 mg/mL and filtered through a 0.2 µm syringe filter for LC‐MS/MS analysis. A QC sample was prepared by pooling equal portions of powder from all 42 samples. This QC sample was used for method development, validation, and monitoring system stability throughout the whole analysis.

2.3.2. Headspace SPME

For the extraction, 0.5 g of powders were stored in a 10 mL headspace vial with a crimp‐type cap and PTFE/silicone septum to prevent the leakage of volatile compounds. Then, the vials with samples were heated using an oven at 70°C for 60 min.

Four types of fiber coating were tested, including polydimethylsiloxane (PDMS) with 100 µm thickness, PDMS/divinylbenzene (PDMS/DVB) with 65 µm thickness, carboxen/PDMS (CAR/PDMS) with 75 µm thickness, and DVB/CAR/PDMS with 50/30 µm thickness for method optimization. Before the samples were extracted, all the above fibers were conditioned using their recommended temperature and duration: PDMS, 250°C for 30 min; PDMS/DVB, 250°C for 30 min; CAR/PDMS, 300°C for 30 min; DVB/CAR/PDMS, 270°C for 60 min.

2.4. Instrumental Analysis

2.4.1. LC‐MS/MS Analysis

Samples were analyzed by a Shimadzu LCMS‐8040 system (Kyoto, Japan). Electrospray ionization (ESI) MS was performed at the interface voltage of −3.5 kV for the negative mode and at 4.5 kV for the positive mode. The parameters of optimized ionization conditions are as follows: drying gas, 15 L/min; desolvation line temperature, 250°C; heat block temperature, 400°C; nebulizing gas, 3 L/min. Target compounds were separated using a Gemini C18 (150 x 4.6 mm, 5 µm; Phenomenex, Torrance, CA, USA). The mobile phases consisted of water (A) and acetonitrile (B) at a flow rate of 0.4 mL/min: 0–8 min, 10% B; 8–18 min, 30% B; 18–22 min, 30% B, 22–27 min, 50%B; 27–35 min, 80% B; 35–40 min, 100% B; 40–46 min, 10% B. The injection volume was 20 µL. Multiple reaction monitoring (MRM) was applied for the quantitation of five compounds and corresponding retention times, and MRM transition parameters are presented in Table 1.

TABLE 1.

Name, structure, and mass spectral parameters of five components.

Name	MW (g/mol)	Chemical formula	Retention time (min)	MS polarity	Structure	Precursor ion (m/z)	Product ion (m/z)	Collision Energy (V)
N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid	291.34	C16H21O4	11.55	Positive		292.15	131.00	−19.0
							163.10	−8.0
							103.10	−38.0
Ferulic acid	194.18	C10H10O4	31.32	Negative		193.1	133.90	14
							177.80	15
							148.85	14
Icariside F2	402.39	C18H26O10	11.98	Negative		401.1	269.05	18
							160.95	22
							100.95	27
Ligusticoside A	402.4	C18H26O10	13.12	Negative		401.1	293.05	13
							106.95	47
							88.95	23
Ligustiphenol	264.32	C15H20O4	23.09	Negative		263.0	106.90	30
							59.00	16
							150.90	16

2.4.2. GC‐MS Analysis

The GC‐MS analysis was performed using an Agilent 7890B gas chromatograph connected to an Agilent 5977 mass spectrometric detector (GC/MSD; Agilent Technologies, Santa Clara, CA, USA). A DB‐5MS capillary column (30 m length, 0.25 mm inner diameter, 0.25 µm film thickness; J&W Scientific, Palo Alto, CA, USA) was used for separation of VOCs with helium as a carrier gas with a flow rate of 1.0 mL min⁻¹.

The temperatures at the inlet and ion source were kept constant at 270°C and 230°C. GC oven temperature was programmed at 50°C for 1 min, increased to 180°C by 4°C min⁻¹, held for 3 min and finally increased to 250°C by 35°C min⁻¹ and held for 3 min. Total run time was 41.5 min, and full scan mode was used for the MSD.

VOCs were identified by comparing the mass spectra to the data system library (NIST). The linear retention index (LRI) was determined using a homologous series of C7–C30 n‐alkanes, and the results were compared with values reported in the literature for similar chromatographic columns. The percentage of individual peaks was obtained by normalizing the measured peak area without correction factors.

2.5. Method Validation

Before applying the developed method for the quantification of five components, it was validated by ICH guidelines. To assess linearity, calibration curves were constructed using six different concentrations. All analytes exhibited correlation coefficients (R ²) greater than 0.99, indicating satisfactory linearity.

To determine the limits of detection (LOD) and quantification (LOQ), a series of diluted mixed reference standard solutions was prepared from stock solutions and analyzed using LC‐MS/MS. The LOD and LOQ were defined as the analyte amounts corresponding to signal‐to‐noise (S/N) ratios of 3 and 10, respectively.

Accuracy was assessed through recovery experiments using both standard‐spiked and matrix‐matched samples. Blank samples were spiked with mixed standards at three concentration levels (low, medium, and high), and recovery percentages were calculated.

Intra‐day precision was evaluated by analyzing six replicates at each concentration level within the same day, while inter‐day precision was assessed by analyzing the same sample on three consecutive days. Repeatability was examined to assess the stability of the HPLC system during continuous sample injections. Precision and repeatability were expressed as relative standard deviation (RSD).

2.6. Statistical Analysis

Statistical analysis of LC‐MS/MS data was performed in MetaboAnalyst 6.0 [29]. After normalization by sum, log₁₀ transformation, and autoscaling (mean‐centering and division by the standard deviation of each variable, PCA provided an unsupervised overview of metabolic variation. Key metabolites were visualized in a heat map to show relative abundance patterns across samples.

GC‐MS data were processed using MS‐DIAL software version 4.9 [30]. Identification was performed with comparison to the NIST 17 mass spectral library. Multivariate statistical analyses, including PCA, VIP score computation, ANOVA and heatmap generation, were conducted using MetaboAnalyst 6.0. Compounds with VIP scores greater than 1.0 and p‐values <0.05 based on ANOVA were identified as potential biomarkers for distinguishing between different growth stages.

3. Results and Discussion

3.1. LC‐MS/MS Analysis of L. striatum Species

3.1.1. Method Development and Validation

Five major bioactive compounds in L. striatum were successfully identified by LC‐MS/MS, including N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid, ferulic acid, Icariside F2, ligusticoside A, and ligustiphenol. The chromatographic peaks of each compound were confirmed based on their corresponding retention time, and precursor and product ions (Table 1; Figure S1). Quantitative results showed that all compounds exhibited excellent linearity with correlation coefficients above 0.9990, and the method demonstrated high sensitivity with LODs ranging from 0.05 to 2 ng/g and LOQs between 0.1 and 10 ng/g (Table S1). Precision evaluation indicated that intra‐day RSD values were below 4.8% and inter‐day RSDs were below 11.4%, confirming good repeatability and reproducibility (Table S2). Recovery experiments at three spiking levels further supported method accuracy, with average recoveries ranging from 90.0% to 113.5%. Among the analytes, ligustiphenol showed slightly higher variability (RSD 6.4%) at low concentration, while other compounds maintained consistent recovery values near 90‐102% (Table S3). Overall, the developed LC‐MS/MS method is robust and reliable for simultaneous detection and quantification of the five targeted metabolites in L. striatum.

3.1.2. Variation of Bioactive Compounds Across Different Growth Stages of L. striatum

The LC‐MS/MS analysis of L. striatum revealed clear tissue‐specific and stage‐dependent variations in bioactive compound accumulation (Figure 1 and Table 2). In the aerial parts, the icariside F2 content temporarily decreased in the second month (7.50 ± 6 µg/g) and increased again in the fourth month (20.37 ± 5 µg/g), followed by a gradual decline during the subsequent sampling, and it peaked with the highest concentration in the seventh month (23.2 ± 1 µg/g). Similarly, ligusticoside A remained low during early growth and gradually rose with plant development. Ferulic acid exhibited a pronounced peak in the fifth month (199.77 ± 6 µg/g) before declining in later stages. This variation indicates that the temporal changes in ferulic acid levels are unlikely to occur by random variation and are closely associated with plant developmental processes. Meanwhile, N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid accumulated moderately, reaching 1.81 ± 1 µg/g in the third month, while ligustiphenol fluctuated, with a sharp rise observed in the sixth month (5.91 ± 1 µg/g). By comparison, the root part displayed a distinct metabolite profile, with ferulic acid being the dominant constituent throughout development, progressively increasing from 524.75 ± 38 µg/g in the first month to 1040.03 ± 32 µg/g in the seventh month, far exceeding levels in the aerial parts. When compared with previously reported contents of L. chuanxiong, where ferulic acid ranged from 0.16 to 0.25 mg/g of dried material, the present results fall within a comparable range, confirming that ferulic acid is consistently the major phenolic compound in roots across different samples of L. striatum [31]. The pronounced accumulation of ferulic acid in L. striatum may be associated with environmental and physiological factors influencing secondary metabolism. During mid‐growth stages, favorable environmental conditions such as optimal temperature, precipitation, and enhanced photosynthetic activity may stimulate the phenylpropanoid pathway in the aerial part, leading to transient accumulation of ferulic acid [32].

FIGURE 1.

Content of five bioactive compounds across different growth stages of (a) aerial part and (b) root part of L. striatum.

TABLE 2.

Contents of five compounds in different growth stages of aerial part and root part (µg/g).

	Name compounds	Months
		1st	2nd	3rd	4th	5th	6th	7th
Aerial part (µg /g)	N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid	0.09 ± 0	0.85 ± 1	1.81 ± 1	0.87 ± 1	2.62 ± 1	2.24 ± 0	1.32 ± 0
	Ferulic acid	8.79 ± 13	26.80 ± 9	67.47 ± 19	53 ± 20	199.77 ± 6	162.08 ± 16	80.63 ± 17
	Icariside F2	11.54 ± 4	7.50 ± 6	10.92 ± 7	20.37 ± 5	16.79 ± 6	15.81 ± 5	23.2 ± 1
	Ligusticoside A	0.88 ± 0	0.40 ± 0	0.74 ± 0	1.42 ± 1	1.32 ± 1	1.88 ± 1	2.23 ± 0
	Ligustiphenol	1.85 ± 1	2.61 ± 0	3.63 ± 2	3.94 ± 0	3.67 ± 0	5.91 ± 1	11.8 ± 2
Root part (µg/g)	N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid	4.25 ± 1	2.41 ± 1	2.89 ± 2	3.69 ± 2	4.65 ± 2	7.20 ± 2	8.49 ± 3
	Ferulic acid	524.75 ± 38	609.61 ± 41	636.35 ± 40	712.61 ± 36	740.66 ± 10	958.14 ± 19	1040.03 ± 32
	Icariside F2	40.54 ± 7	38.44 ± 16	33.94 ± 9	33.91 ± 16	32.80 ± 8	42.54 ± 18	38.51 ± 10
	Ligusticoside A	15.61 ± 5	11.62 ± 5	11.93 ± 7	8.09 ± 3	10.59 ± 1	15.25 ± 4	11.32 ± 5
	Ligustiphenol	34.87 ± 5	43.15 ± 9	28.65 ± 5	41.32 ± 3	17.39 ± 3	19.69 ± 6	19.91 ± 6

The bar chart (Figure 1) illustrates distinct tissue‐specific and developmental variations in the five major metabolites of L. striatum. In the aerial part (Figure 1a), ferulic acid peaked at late stages (A5 and A7), while ligustiphenol showed a marked increase and reached its maximum at A7. Icariside F2 and ligusticoside A were present at relatively lower levels, with only moderate fluctuations. Ferulic acid was also the most abundant compound and showed a clear increasing trend from R1 to R7 in Figure 1b, reaching the highest level at the final stage. N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid also increased gradually during root development, particularly from R4 to R7. In contrast, icariside F2 remained relatively stable across the sampling stages, with only minor fluctuations. Ligusticoside A was detected at low to moderate levels, but its abundance was slightly higher in the root parts than in the aerial parts. Ligustiphenol was relatively abundant in the roots during the early to middle stages (R1–R4), followed by a marked decrease from R5 to R7.

The PCA score plots of the aerial (Figure 2a) and root (Figure 2b) parts of L. striatum clearly illustrate distinct clustering patterns across different growth stages, indicating dynamic metabolic variation during development. In the aerial part, PC1 accounted for 71.3% of the total variance, while PC2 explained 17.9%, capturing nearly 90% of the variation. Samples of the first and the fifth month (A1, A5) formed separate clusters from the others, indicating notable shifts in metabolite composition during these specific growth stages. The loading plot showed that ferulic acid and N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid contributed strongly to the positive PC1 direction, whereas icariside F2, ligusticoside A, and ligustiphenol were associated with the negative PC1 direction. Similarly, in the root tissues, PC1 (70.9%) and PC2 (22.3%) explained over 93% of the variance, with well‐defined clusters corresponding to different developmental periods. Roots in the first month (R1) clustered apart from the second month to the fourth month (R2‐R4) and the fifth to the seventh month (R5‐R7), consistent with the gradual accumulation of ferulic acid and other metabolites observed in quantitative analysis. The loading plot indicated that N‐3‐(3‐methoxy‐4‐hydroxyphenyl) allyl pipecolic acid, ligusticoside A, and icariside F2 were major contributors to sample discrimination, while ferulic acid and ligustiphenol were positioned in opposite loading directions. The tight clustering within each stage also highlights good reproducibility of the LC‐MS/MS data. Overall, the PCA results emphasize that both aerial and root parts undergo marked metabolomic transitions during growth, with roots showing stronger stage‐dependent differentiation compared to aerial tissues.

FIGURE 2.

Principal component analysis (PCA) score plot of (a) aerial part and (b) root part of L. striatum.

3.2. GC‐MS Analysis of L. striatum Species

3.2.1. Optimization HS‐SPME Condition

To establish a reliable HS‐SPME‐GC/MS method, SPME extraction conditions for L. striatum were optimized. Extraction efficiency was evaluated based on the intensities of 10 representative VOCs commonly detected in L. striatum. Fiber coating selection was a critical step in SPME method optimization, as extraction efficiency strongly depends on the distribution constant between the fiber coating and the sample matrix [33]. Four different SPME fibers were tested under identical conditions: 30 min extraction at 70°C (Figure S2). The results indicated that CAR/PDMS and PDMS fibers exhibited poor extraction performance for VOCs in L. striatum, whereas DVB/CAR/PDMS and PDMS/DVB showed better efficiency. Although PDMS/DVB is typically used for detecting alcohol and amines in polar matrices, DVB/CAR/PDMS was selected due to its superior extraction capability. This fiber can effectively adsorb a broad range of compounds, particularly C3‐C20 volatiles. Given that plant aroma consists of a complex mixture of species‐specific volatile compounds [34], the DVB/CAR/PDMS fiber was deemed most suitable for this study.

To determine the optimal sample amount, four different weights (0.1, 0.3, 0.5, and 0.7 g) of L. striatum powder were analyzed in headspace vials. In addition to comparing the peak intensities of 10 representative VOCs, the untargeted GC‐MS dataset was also evaluated by counting the total number of detected metabolites under each condition by MS‐Dial. The number of detected compounds increased from 138 at 0.1 g to 143 at 0.3 g and reached the highest value of 151 at 0.5 g, followed by a slight decrease to 148 at 0.7 g. Notably, certain compounds such as butylphthalide, senkyunolide, and ligustilide in the 0.5 g samples were more abundant compared to others (Figure 3a). Consequently, 0.5 g was selected as the optimal sample amount for further analysis.

FIGURE 3.

Optimization of headspace solid‐phase microextraction (HS‐SPME) conditions: (a) sample amount, (b) extraction temperature, and (c) extraction time.

Furthermore, the optimal extraction temperature and time for the DVB/CAR/PDMS fiber were systematically evaluated to enhance VOC analysis in L. striatum. To determine the most effective extraction temperature, three different conditions 30, 50, and 70°C were tested. Generally, increasing the extraction temperature enhances the volatility of analytes, leading to a greater concentration of VOCs in the headspace and thus improving extraction efficiency. However, excessively high temperatures may result in reduced recovery due to the potential degradation of thermally labile compounds or decreased fiber adsorption efficiency [35]. In the present study, evaluation of the full untargeted GC‐MS dataset showed that the number of detected compounds increased with extraction temperature, from 117 compounds at 30°C to 144 compounds at 50°C and 158 compounds at 70°C. In addition, the extraction performed at 70°C yielded significantly higher concentrations of key volatile constituents, including butylphthalide, butylidenephthalide, and senkyunolide (Figure 3b). These compounds exhibited a notable increase in peak intensity compared to extractions at lower temperatures. Therefore, 70°C was selected as the optimal extraction temperature for VOC profiling in L. striatum, providing the best balance between volatilization and fiber adsorption.

As a critical parameter in SPME method development, the optimal extraction time was determined by evaluating three different conditions: 20, 40, and 60 min. Extraction time significantly influences extraction efficiency, reproducibility, and analytical sensitivity. In general, shorter extraction times are more suitable for highly volatile compounds, while longer durations enhance the recovery of less volatile constituents. Evaluation of the full untargeted GC‐MS dataset showed that the number of detected compounds increased with extraction time, from 127 compounds at 20 min to 138 compounds at 40 min and 153 compounds at 60 min. As shown in Figure 3c, the concentrations of key volatiles such as butylphthalide and senkyunolide increased progressively with longer extraction times. Among the tested conditions, 60 min yielded the highest peak intensities, indicating the most efficient extraction.

Finally, the HS‐SPME extraction conditions for VOC profiling in L. striatum were optimized as follows: 0.5 g of powdered sample, extracted using a DVB/CAR/PDMS fiber at 70°C for 60 min. These parameters provided the most comprehensive and efficient recovery of volatile compounds in this study.

3.2.2. Chemometric Analysis of VOCs in the Aerial Part and Root Part Across Developmental Stages of L. striatum

HS‐SPME‐GC/MS was employed to comprehensively profile VOCs in the aerial and root parts of L. striatum across different growth stages. Based on mass spectral matching with the NIST library and comparison of calculated LRI with literature values, 33 and 32 VOCs were putatively annotated in the aerial and root parts, respectively (Tables S4 and S5). The heatmap analysis (Figure 4) clearly illustrates the dynamics in VOC composition during the seven developmental stages in both plant parts. At the earliest stage (A1), several compounds with reported biological activities, including 1,4a‐Dimethyl‐7‐(prop‐1‐en‐2‐yl)‐1,2,3,4,4a,5,6,7‐octahydronaphthalene, 3‐Methyl‐6‐(6‐methylhept‐5‐en‐2‐yl)cyclohex‐2‐enone, 2‐Methyl‐6‐(4‐methylenecyclohex‐2‐en‐1‐yl)hept‐2‐en‐4‐one were particularly abundant in the aerial parts. Previous studies have reported that 1,4a‐Dimethyl‐7‐(prop‐1‐en‐2‐yl)‐1,2,3,4,4a,5,6,7‐octahydronaphthalene showed only a weak activity against M. intracellulare [36]. Additionally, 3‐Methyl‐6‐(6‐methylhept‐5‐en‐2‐yl)cyclohex‐2‐enone exhibits significant antidermatophytic activity, while 2‐Methyl‐6‐(4‐methylenecyclohex‐2‐en‐1‐yl)hept‐2‐en‐4‐one demonstrates strong antioxidant effects, including inhibition of lipid peroxidation, along with marked anti‐inflammatory activity [37, 38]. In addition, in the fifth month (A5), butylidenephthalide became prominent. This compound, which can be isolated from Ligusticum porteri, has been reported to be potentially useful for the development of new antidiabetic, antiobesity, and antiviral agents [39]. As the plant matured, 1,8‐Dimethyl‐4‐(prop‐1‐en‐2‐yl)spiro[4.5]dec‐7‐ene became the predominant volatile at the final stage (A7). This pattern further underscores the temporal specificity of VOC production in L. striatum.

FIGURE 4.

Heatmap for the volatile organic compounds (VOCs) of (a) aerial part and (b) root part among the seven different growth stages.

Meanwhile, in the root, the earliest developmental stage was characterized by high levels of compounds such as benzene, 1‐methyl‐3‐(1‐methylethenyl)‐, bisabolone, 2‐Isopropenyl‐4a,8‐dimethyl‐1,2,3,4,4a,5,6,8a‐octahydronaphthalene and 2‐Methyl‐6‐(4‐methylenecyclohex‐2‐en‐1‐yl)hept‐2‐en‐4‐one, a compound known for its strong antioxidant activity, including inhibition of lipid peroxidation, as well as notable anti‐inflammatory properties [38, 40]. As the plant progressed to the fifth month (R5), compounds such as 2‐Cyclohexen‐1‐one, 3‐methyl‐6‐(1‐methylethylidene)‐, 2,4‐di‐tert‐butylphenol (a potent natural CSK9 inhibitor), and muurolene showed significant changes in concentration [41]. By the late stage, no single compound predominated, suggesting a more balanced and dynamically regulated VOC composition in the root over time.

Peak areas of the major VOCs that aligned by MS‐Dial showed clear tissue‐ and stage‐dependent variation in L. striatum (Figure 5). In the aerial parts (Figure 5a), butylphthalide reached its maximum at A6. Senkyunolide, which is recognized for its therapeutic effects including alleviation of asthma, cholestatic liver fibrosis, and reduction of lipid accumulation in hyperlipidemic hepatocytes, also showed the highest peak area at A6 [42, 43, 44]. Butylidenephthalide and 1‐(2‐hydroxy‐5‐methylphenyl)‐ethanone reached their highest level at A5. In the root parts (Figure 5b), butylphthalide was also the dominant volatile and peaked at R2. Senkyunolide and butylidenephthalide showed the highest peak area at R3. Overall, these results indicate dynamic developmental regulation of VOC biosynthesis, with distinct accumulation patterns between aerial and root parts during plant growth.

FIGURE 5.

Bar chart of the content of main volatile substances in (a) aerial part and (b) root part of L. striatum species.

PCA revealed clear stage‐dependent variation in VOC profiles of both aerial and root parts of L. striatum (Figure 6). In the aerial part (Figure 6a), PC1 and PC2 explained 46.6 and 16.8% of the total variance, respectively. The early developmental stages (A1 and A2) were clearly separated from the later stages along PC1. Samples from A3‐A4 were positioned between these two groups (A1 and A2), indicating a transitional metabolic phase. A5 formed a distinct independent cluster, while A6‐A7 clustered closely together, highlighting two broad metabolic phases: A1‐A4 and A5–A7. In the root part (Figure 6b), PC1 (28.8%) and PC2 (25.6%) distinguished R1 as a distinct metabolic profile at the early root development stage. R5 was distinctly separated, reflecting pronounced metabolic changes during this stage. In contrast, the other stages (R2–R4 and R6 and R7) exhibited overlap and clustering, indicating more gradual metabolic variation. Overall, PCA clearly demonstrated distinct developmental regulation of VOC profiles in both aerial and root parts of L. striatum, while also highlighting marked metabolic differences between the two parts. The aerial part exhibited sharper stage‐dependent separation, indicating rapid metabolic shifts across development, whereas the root part showed more gradual transitions with partial overlap among later stages. These results highlight the importance of PCA in reducing complex VOC datasets into interpretable metabolic patterns.

FIGURE 6.

Volatile organic compounds (VOCs) analysis in L. striatum species at different growth stages with PCA score plots of (a) aerial part and (b) root part.

The variable importance in projection (VIP) score indicates how much each compound contributes to distinguishing sample groups [45]. In this study, compounds with VIP values greater than 1 and statistical significance (p < 0.05) were selected as key differential markers (Figure S4; Tables S6 and S7). Based on these criteria, 17 significant volatile biomarkers were identified in the aerial parts (Table S6), and 11 in the root parts (Table S7) of L. striatum. The stage‐specific VOC markers listed in Tables S6 and S7 may have functional significance, as several of these compounds belong to bioactive chemical classes that have been previously reported in Ligusticum species and other aromatic medicinal plants. Among these compounds, phthalide/lactone derivatives, including butylidenephthalide and senkyunolide, have been reported to exhibit various therapeutic activities. Several terpenoid markers, including caryophyllene, copaene, muurolene, calamenene, carotol, and ionone, may contribute to the characteristic aroma of L. striatum and may also be involved in plant defense and stress responses. Caryophyllene has been widely reported as a bioactive dietary sesquiterpene with anti‐inflammatory and antioxidant effects, while ionone and related apocarotenoids are known plant volatiles involved in aroma formation, ecological signaling, and stress responses [46, 47]. Caryophyllene has been reported as a dietary sesquiterpene with antioxidant and anti‐inflammatory activities, partly associated with CB2 receptor‐related mechanisms, while β‐ionone and related ionone derivatives are well‐known aroma compounds with reported anti‐inflammatory, antimicrobial, antioxidant, and plant ecological functions [46, 48, 49, 50]. Aromatic and phenolic VOCs, including benzeneacetaldehyde, 3‐allyl‐6‐methoxyphenol, and ethyl mandelate, may also contribute to the sensory and bioactive properties of L. striatum. Benzeneacetaldehyde‐related volatiles are important floral/honey like aroma contributors, while 3‐allyl‐6‐methoxyphenol belong to phenylpropanoid‐type aroma compounds with reported antioxidant and anti‐inflammatory relevance [51, 52]. Therefore, although the VOCs in this study were putatively annotated by HS‐SPME‐GC/MS rather than confirmed with authentic standards, these markers may serve as useful indicators for harvest optimization, quality assessment, and future bioactivity‐guided studies. These compounds serve as reliable indicators for differentiating developmental stages of the plant. Importantly, the identification of these stage‐specific VOC markers provides valuable guidance for determining optimal harvest times. By targeting periods when key bioactive compounds are most abundant, harvest strategies can be optimized to enhance the quality and efficacy of plant‐derived products.

4. Conclusion

This study presents the first comprehensive analysis of L. striatum across various developmental stages, utilizing both LC‐MS/MS and HS‐SPME‐GC/MS techniques. Five key bioactive compounds were quantified with high accuracy and sensitivity. Among the quantified metabolites, ferulic acid exhibited the most pronounced accumulation, particularly in the root part at later developmental stages, highlighting its role as a major phenolic constituent of L. striatum. This stage‐dependent enrichment suggests that ferulic acid may serve as an important biochemical marker for assessing the quality and optimal harvest time of the species. On the other hand, volatile profiling revealed different parts and stage‐specific metabolite accumulation. Chemometric analyses further demonstrate dynamic metabolite shifts during growth, with roots serving as reservoirs of phenolic acids and aerial parts enriched in phthalides and sesquiterpenes at specific stages. These findings underscore the importance of growth‐stage monitoring for optimizing harvest periods, ensuring consistent therapeutic quality, and supporting the standardization of L. striatum in traditional and modern medicine.

However, several limitations should be acknowledged. First, the samples analyzed in this study were collected from a single cultivation area in Lao Cai Province, Vietnam, during one growing season. Therefore, the metabolic patterns observed here may partly reflect local environmental, climatic, and cultivation‐related conditions. Additionally, although several marker compounds were identified and quantified, the pharmacological relevance of newly detected or less studied constituents remains to be confirmed through further biological and mechanistic studies.

Moreover, the identification of novel compounds in Vietnamese‐grown L. striatum expands its known phytochemical diversity and highlights its potential for future pharmacological exploration. Following this work, future research will extend the quantitative analysis of these five bioactive compounds and VOCs profiling to L. striatum populations from Vietnam, Korea, and China using the same HS‐SPME‐GC/MS methodology. Such cross‐regional comparisons will enable the evaluation of environmental, climatic, and genetic influences on metabolite production, offering deeper insights into chemotypic variation and enhancing the species value in both medicinal and agricultural applications.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (RS‐2022‐NR070856) and the Ministry of Education (RS‐2025‐25397599).

Supporting information

Supporting File 1: jssc70502‐sup‐0001‐SuppMat.docx.

Supporting File 2: jssc70502‐sup‐0002‐Data.zip.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.