Integrated phytochemical and bioactivity profiling of Xanthium strumarium fruits from Korea and China: Implications for origin‐specific quality specification

Abstract

BACKGROUND

Geographic origin influences the phytochemical composition and biological activities of medicinal plant resources. Xanthium strumarium L. (XS) fruit is widely used in East Asian traditional medicine. However, current pharmacopeial standards primarily recognize Chinese‐derived material, despite the availability and traditional use of XS in Korea. To address this gap and support origin‐informed quality specification, we compared fruits from Korea (XS‐K) and China (XS‐C) using chloroplast genome sequencing, targeted phytochemical profiling (high‐performance liquid chromatography (HPLC) for selected phenolics and gas chromatography‐flame ionization detection (GC‐FID) for fatty acids and phytosterols, and multivariate chemometric analysis.

RESULTS

Chloroplast genome analysis revealed high overall similarity but localized divergence around the rpoC2 locus and a greater mutation burden in XS‐C, supporting origin‐associated genomic differentiation. Phytochemical profiling revealed distinct origin‐dependent metabolic signatures. XS‐K showed higher levels of phytosterols, chlorogenic acid, 4,5‐dicaffeoylquinic acid (4,5‐DCQ), and xanthatin was detected only in XS‐K, whereas XS‐C exhibited greater abundance of total fatty acids, particularly oleic acid. Unsupervised clustering and log₂ fold‐change ranking confirmed clear compositional separation, and variable importance in projection (VIP) analysis identified chlorogenic acid, β‐sitosterol, oleic acid, 4,5‐DCQ, and xanthatin as major discriminators between origins. Bioactivity assays demonstrated that XS‐K exerted stronger antioxidant effects in ABTS, DPPH and FRAP assays, stronger skin‐related enzyme inhibition, and greater antibacterial activity against Staphylococcus aureus, consistent with its enriched phenolic and sterol profile.

CONCLUSION

Together, chloroplast sequence variation, targeted metabolite quantification, and screening bioassays consistently distinguished XS‐K from XS‐C. These findings support the use of candidate markers for the origin‐based authentication and quality control of XS fruit‐derived ingredients. © 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

INTRODUCTION

Natural products, diverse secondary metabolites produced by plants, play essential ecological roles, including defense against pathogens and herbivores, chemical communication, and adaptation to environmental stresses. Many of these compounds exhibit bioactivities beneficial to humans and have been widely utilized in foods, cosmetics, and pharmaceuticals. ¹ Herbal medicines are widely used worldwide as part of traditional and complementary healthcare practices, and interest in plant‐based bioactive compounds remains strong for the development of functional ingredients and therapeutic leads. ² Notably, crude plant extracts often show synergistic biological activities beyond those of purified single compounds isolated from plant materials, supporting their continued relevance in natural product‐based applications. ¹

Recent studies increasingly combine analytical profiling with bioactivity evaluation to provide more comprehensive evidence for natural products, including liquid chromatography–mass spectrometry (LC–MS)‐based constituent characterization and related integrative approaches. ³ In parallel, recent reviews and translational studies have emphasized the importance of interpreting phytochemical diversity together with functional evidence and, where relevant, pharmacokinetic considerations. In this context, quality control (QC)‐oriented marker panels remain useful for routine screening and origin‐based quality assessment, although their limited chemical coverage should be recognized.^{4, 5}

The genus Xanthium (Asteraceae) encompasses several species with a long history of medicinal use, among which Xanthium strumarium L. (XS) is widely applied across Asia for inflammatory and respiratory conditions. ⁶ In Chinese contexts, Xanthium sibiricum, prevalent in that region, is taxonomically treated as a synonym of XS. ⁷ The medicinal application of XS fruits has been documented in classical Asian medical texts such as the ShenNong BenCaoJing (ShenNong's Classic of Materia Medica, first–second century ce) and Donguibogam (Mirror of Eastern Medicine, 1613) for headache, skin disorders, and rheumatic inflammation. ⁸ Despite the domestic availability of XS in Korea, only Chinese‐derived materials have undergone formal standardization, underscoring the need for comparative quality evaluation between the two origins.

Phytochemical profiles of medicinal plants are strongly influenced by geographical origin due to genetic, ecological, and environmental factors.^{9, 10, 11} Structural variation in the chloroplast genome may also contribute to differences in metabolic output and phytochemical accumulation.^{12, 13} Previous studies have shown that compounds such as phenolic acids, sesquiterpene lactones, volatiles, and fatty acids can vary significantly across plant ecotypes.^{14, 15, 16} However, few studies have jointly examined chloroplast genome variation with targeted multi‐platform chemical profiling (phenolics, phytosterols, and fatty acids), bioactivity screening, and chemometric integration for origin‐aware quality specification of XS fruits.

Accordingly, this study presents an integrative, origin‐aware workflow that combines chloroplast genome analysis with targeted phytochemical profiling and functional bioactivity assays, and chemometric analysis. Similar comparative workflows integrating component profiling with multivariate analysis have been used to differentiate botanical materials across sources and conditions, supporting the rationale for our integrative design.^{17, 18} Using principal component analysis (PCA), partial least squares discriminant analysis (PLS‐DA), hierarchical clustering, and correlation analysis, we compare XS fruits sourced from Korea (XS‐K) and China (XS‐C) to assess their potential interchangeability and to prioritize candidate origin‐informed quality markers within the targeted panel. Through this integrated design, we aim to support evidence‐based selection and routine quality specification of XS fruit‐derived ingredients for industrial applications.^{9, 17, 19}

MATERIALS AND METHODS

Plant material and extraction

XS‐K and XS‐C were obtained from Hyunjin Pharmaceutical Co. (Seoul, Korea). Voucher specimens were authenticated and deposited at Myongji University under accession numbers MJU‐01‐HWANG‐XS‐K and MJU‐01‐HWANG‐XS‐C.

Dried fruits were pulverized and extracted with 70% ethanol for 6 h. The resulting extracts were filtered, evaporated at 40 °C, and then freeze‐dried. The extraction yields were 5.77 ± 0.49% for XS‐K and 5.84 ± 0.35% for XS‐C. Unless otherwise stated, the 70% ethanol extracts were used for high‐performance liquid chromatography (HPLC)‐based phenolic quantification, phytosterol analysis (Phytosterol composition section), and in vitro bioassays. Fatty acid analysis (Fatty acid analysis section) was performed using dried fruit powder, independent of the ethanol extracts.

Chloroplast genome analysis

Genomic DNA was extracted from XS‐K and XS‐C, and its purity and concentration were assessed using spectrophotometry and fluorometry. DNA integrity was evaluated using an Agilent 4200 TapeStation (Agilent Technologies, Santa Clara, CA, USA), yielding DNA Integrity Number (DIN values) of 7.0 (XS‐K) and 6.4 (XS‐C). Sequencing libraries were prepared using the TruSeq Nano DNA Sample Prep Kit (350 bp) (Illumina, San Diego, CA, USA) according to the manufacturer's protocol, and sequencing was performed to generate paired‐end reads (R1.Fastq.gz and R2.Fastq.gz). Raw data quality metrics (Q20 and Q30) were approximately 97% and 92%, respectively. Reference‐based analysis was performed using the chloroplast genome assembly NC_072298.1, with MH473582 used as a reference. ²⁰

Fatty acid analysis

Fatty acids were prepared from dried fruit powder, independently of the 70% ethanol extracts described in Plant material and extraction section, converted to fatty acid methyl esters (FAMEs) and analyzed by gas chromatography with flame ionization detection (GC‐FID) (Agilent Technologies) equipped with a DB‐23 column (60 m × 0.25 mm × 0.25 μm). Identification and quantification were performed using the Supelco 37 Component FAME Mix (Sigma‐Aldrich, Burlington, MA, USA) as calibration standards, following the method of Garcés and Mancha. ²¹

Phytosterol composition

Phytosterols were quantified from freeze‐dried 70% ethanol extracts prepared in Plant material and extraction section, following sequential acid and alkaline hydrolysis, and analyzed by GC‐FID as previously described. ²² Method accuracy for the phytosterol analysis was validated using Standard Reference Material (SRM) 3251 (saw palmetto, Serenoa repens) obtained from the National Institute of Standards and Technology (NIST, Gaithersburg, MD, USA). Recovery rates for stigmasterol and β‐sitosterol ranged from 93.3% to 96.3%, indicating excellent accuracy. For reporting on a dry‐fruit weight (DW) basis, phytosterol contents determined in the ethanol extracts were converted using the extraction yield of each origin. Specifically, values measured per gram of freeze‐dried extract were multiplied by the extraction yield (in g extract g⁻¹ DW).

Polyphenols and antioxidant‐related constituents

Selected phenolics [chlorogenic acid, caffeic acid, cynarin, ferulic acid, 4,5‐dicaffeoylquinic acid (4,5‐DCQ), quercetin, kaempferol, and xanthatin] were quantified via HPLC, following the method of Fan et al. ⁸ Total phenolic content (TPC), total flavonoid content (TFC), and total antioxidant capacity (TAC) were determined using standard colorimetric assays, according to Marinova et al. ²³ and Shabbir et al. ²⁴ Phenolic profiling was conducted as a targeted, QC‐oriented panel using HPLC, prioritizing compounds with routine applicability for origin‐aware screening.

Antioxidant assays

Antioxidant activities were assessed using ABTS, DPPH, and FRAP assays, following previously established protocols.^{25, 26, 27} Results were expressed as half‐maximal inhibitory concentration (IC₅₀) values (in mg mL⁻¹) for radical scavenging assays and iron(II) ion (Fe²⁺) equivalents (in mg Fe2⁺ mL⁻¹) for FRAP.

Enzyme inhibitory assays

Tyrosinase inhibition was evaluated following the method of Ishihara et al. ²⁸ Collagenase and elastase inhibitory activities were determined using the FALFPA and SALAPN substrates, respectively, as described by Pintus et al. ²⁹ Arbutin and epigallocatechin gallate (EGCG) were used as positive controls for tyrosinase and collagenase/elastase assays, respectively.

Antimicrobial activity

Antimicrobial activity was assessed using the agar well diffusion method against Staphylococcus aureus (ATCC 25923), following the procedure described by Nguyen et al. ³⁰ The inhibition clear zone (ICZ, in millimeters) was measured after 24 h of incubation. Antibacterial activity against Escherichia coli O157 (KCTC 9637) was evaluated under the same conditions. For interpretation, inhibition zone diameters were used to categorize the strength of growth inhibition in the agar diffusion: ICZ > 18 mm (sensitive), 12–18 mm (moderately sensitive), and ICZ < 12 mm or no zone (resistant/insensitive). These categories describe relative inhibition in this diffusion assay and are not intended to indicate clinical antibiotic susceptibility.

Chemometric and multivariate analysis

Chemometric analyses were conducted using integrated datasets from HPLC‐quantified phenolics and GC‐FID‐derived fatty acids and phytosterols. All analyses were performed in R (version 4.4.3). Prior to multivariate analysis, metabolite variables were mean‐centered and scaled to unit variance. Unsupervised analysis was conducted using PCA to explore sample distribution and clustering patterns. Supervised classification was performed using PLS‐DA via the mixOmics package, and variable importance in projection (VIP) scores were computed to rank discriminant metabolites contributing to origin‐based separation.

Statistical analysis

All experiments were performed in triplicate, and data are expressed as mean ± standard deviation (SD). One‐way analysis of variance (ANOVA) followed by Tukey's honestly significant difference (HSD) test was conducted using GraphPad Prism 9. For multiple comparisons in metabolite profiling, Benjamini–Hochberg false discovery rate (FDR) correction was applied. A P‐value < 0.05 or FDR < 0.05 was considered statistically significant.

RESULTS

Comparative chloroplast genome analysis of XS‐K and XS‐C

Comparison of chloroplast genomes indicated a high level of overall similarity between XS‐K and XS‐C, while also revealing origin‐dependent differences in sequence variation patterns (Supporting Information, Fig. S1). A localized divergence signal was observed in the large single‐copy (LSC) region near the rpoC2 locus. In addition, XS‐C exhibited a higher reference‐based variant burden, with more single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) relative to the same chloroplast reference genome, compared with XS‐K. Collectively, these results suggest that although XS‐K and XS‐C are closely related at the chloroplast genome level, distinct origin‐associated polymorphisms are clearly detectable and may support origin‐aware authentication and traceability.

While these chloroplast polymorphisms do not establish a direct mechanistic basis for the observed phytochemical and bioactivity differences, they provide stable origin‐associated genomic signatures that are consistent with the compositional separation identified by targeted metabolite profiling and chemometric analysis. In this context, the chloroplast data are best interpreted as complementary evidence for origin‐aware authentication and traceability, rather than as direct determinants of the measured functional traits.

Quantitative profiling of major phytochemicals

Targeted quantification revealed origin‐dependent differences in fatty acids, phytosterols, and phenolic constituents (Table 1). Total fatty acid content was higher in XS‐C than in XS‐K (74.3 versus 53.8 mg g⁻¹ DW), with oleic acid being the dominant fatty acid in both origins (Table 1). In contrast, several sterols and phenolic markers showed higher abundance in XS‐K, including higher total phytosterol content (50.4 versus 43.8 mg (100 g)⁻¹ DW), primarily driven by β‐sitosterol and stigmasterol (Table 1). Among phenolic constituents, chlorogenic acid and 4,5‐DCQ were detected in both origins, whereas xanthatin was only detected in XS‐K (reported as not detected (ND) in XS‐C) (Table 1). The total quantified phenolics were higher in XS‐K than in XS‐C (51.2 versus 46.6 mg g⁻¹ DW).

Table 1.

Quantitative profiles of major phytochemicals in Xanthium strumarium L. fruits from Korea (XS‐K) and China (XS‐C)

	Compound	XS‐K	XS‐C	log2FC
Fatty acid (mg g−1 DW)	C14:0	3.10 ± 0.15 (5.8)	2.01 ± 0.13 (2.7)	0.62
	C17:0	1.55 ± 0.02 (2.9)	2.94 ± 0.05 (4.0)	−0.92
	C18:0	5.90 ± 0.09 (11.0)	15.28 ± 0.27 (20.6)	−1.37
	C18:1n9c	42.25 ± 0.55 (78.5)	51.63 ± 0.91 (69.5)	−0.29
	C18:2n6c	0.23 ± 0.00 (0.4)	0.12 ± 0.01 (0.2)	0.89
	C18:3n6	0.10 ± 0.00 (0.2)	0.12 ± 0.00 (0.2)	−0.29
	C18:3n3	ND	0.10 ± 0.00 (0.1)
	C20:4n6	0.55 ± 0.01 (1.0)	0.60 ± 0.01 (0.8)	−0.13
	C22:2n6	0.16 ± 0.00 (0.3)	0.13 ± 0.00 (0.2)	0.32
	C22:6n3	ND	1.45 ± 0.53 (2.0)
	Total fatty acid	53.83 ± 1.56	74.28 ± 1.56
Phytosterol (mg (100 g)−1 DW)	β‐Sitosterol	45.5 ± 1.67	42.0 ± 0.43**	0.12
	Stigmasterol	4.97 ± 0.09	1.77 ± 0.06***	1.49
	Total phytosterols	50.4 ± 1.76	43.8 ± 0.49
Polyphenol (mg g−1 DW)	Chlorogenic acid	48.6 ± 0.94	44.9 ± 0.53***	0.13
	4,5‐DCQ	1.74 ± 0.03	1.72 ± 0.06	0.02
	Xanthatin	0.87 ± 0.04	ND
	Total phenolics	51.2 ± 0.09	46.6 ± 0.05

Note: Data are expressed as mean ± standard deviation (n = 3). Log₂FoldChange (FC) values were calculated as log₂(XS‐K/XS‐C); positive values indicate higher levels in XS‐K. Log₂FC values are reported only for metabolites quantified in both origins; metabolites not detected (ND) in either origin were excluded from FC analysis and statistical testing. Values in parentheses indicate relative abundance (% of total fatty acids) in each origin (XS‐K and XS‐C). DW, dry weight; 4,5‐DCQ, 4,5‐dicaffeoylquinic acid.

Chemometric discrimination and marker prioritization

Unsupervised chemometric analyses supported origin‐dependent compositional differentiation. A heatmap with hierarchical clustering based on the scaled metabolite matrix showed that biological replicates clustered consistently within each origin, exhibiting contrasting abundance patterns across fatty acids, phytosterols, and phenolic markers (Fig. 1(A)). PCA further supported this trend, showing clear separation of XS‐K and XS‐C primarily along principal component one (PC1) (Fig. 1(B)), indicating that origin‐related variation was detectable without supervised modeling.

Figure 1.

Origin‐dependent metabolite patterns and unsupervised chemometric separation of Xanthium strumarium L. fruits from Korea (XS‐K) and China (XS‐C). (A) Hierarchical clustering heatmap of quantified metabolites across XS‐K and XS‐C. (B) PCA score plot showing separation of XS‐K and XS‐C samples based on the same dataset.

To prioritize candidate markers, a supervised PLS‐DA model was applied to derive VIP scores (Supporting Information, Fig. S3 and Table S1). Given the small sample size (n = three samples per origin), PLS‐DA outputs were interpreted descriptively and used primarily for marker prioritization rather than predictive performance claims. VIP ranking (averaged across components 1 and 2) highlighted metabolites contributing most strongly to origin‐based separation, summarized as the top‐ranked features in Fig. 2(B) and reported comprehensively in Table S1.

Figure 2.

Integrated summary of discriminatory importance, effect direction, and statistical significance. (A) Bubble plot combining VIP scores, log₂FC, and FDR. Only metabolites with VIP > 1 and FDR < 0.05 were labeled. Positive log₂FC values indicate higher abundance in XS‐K, whereas negative values indicate higher abundance in XS‐C. Bubble size corresponds to –log₁₀(FDR). (B) Corresponding bar plot for the top 15 VIP‐ranked metabolites derived from the PLS‐DA model.

To integrate discriminant importance with directional and statistical context, VIP scores were combined with log₂FoldChange (log₂FC) and FDR in a summary bubble plot (Fig. 2(A)). In this plot, the x‐axis represents log₂FC (XS‐K/XS‐C), the y‐axis represents VIP score, and bubble size reflects –log₁₀(FDR). Log₂FC was defined as log₂(XS‐K/XS‐C), where positive values indicate higher abundance in XS‐K and negative values indicate higher abundance in XS‐C (Table 1, Figs 2(A) and S2). Metabolites not detected in either origin were excluded from log₂FC calculation and statistical testing and reported as ND. The corresponding absolute concentrations for VIP‐ranked metabolites are shown in Fig. 2(B), and a comprehensive log₂FC overview across all detected metabolites is provided in Fig. S2.

Antioxidant‐related constituents, antioxidant activity, and correlation patterns

Antioxidant‐related constituents differed significantly between the two origins (Table 2). XS‐K showed significantly higher TPC (94.31 versus 71.79 μg GAE g⁻¹ DW), TFC (1.14 versus 0.52 μg QE g⁻¹ DW), and TAC (19.65 versus 16.62 μg ASCE g⁻¹ DW) compared to XS‐C. Consistent with these compositional differences, antioxidant activities also varied distinctly between origins. XS‐K exhibited lower IC₅₀ values in both the ABTS (0.37 versus 0.58 mg mL⁻¹) and DPPH (0.03 versus 0.14 mg mL⁻¹) assays, along with higher FRAP reducing capacity (1.31 versus 0.63 mg  Fe²⁺ mL⁻¹).

Table 2.

Antioxidant contents and activities in Xanthium strumarium L. fruits from Korea (XS‐K) and China (XS‐C)

	TPC (μg GAE g−1 DW) a	TFC (μg QE g−1 DW) b	TAC (μg ASCE g−1 DW) c	ABTS (IC50, mg mL−1) d	DPPH (IC50, mg mL−1) d	FRAP (mg Fe2+ mL−1) e
XS‐K	94.31 ± 2.25	1.14 ± 0.05	19.65 ± 0.41	0.37 ± 0.03	0.03 ± 0.00	1.31 ± 0.10
XS‐C	71.79 ± 1.10***	0.52 ± 0.09***	16.62 ± 1.22	0.58 ± 0.03*	0.14 ± 0.00	0.63 ± 0.06

^a Total phenolic content, microgram of gallic acid equivalent per gram dry weight.

^b Total flavonoid content, micrograms of quercetin equivalent per gram dry weight.

^c Total antioxidant capacity, micrograms of ascorbic acid equivalent per gram dry weight.

^d IC₅₀, half‐maximal inhibitory concentration.

^e Ferric reducing antioxidant power, milligrams iron(II) ion equivalents per milliliter.

To explore metabolite–activity relationships, Pearson correlation analysis was performed (Fig. 3). In addition, inter‐assay correlations among the antioxidant methods (ABTS, DPPH, and FRAP) were assessed across biological replicates (Table S2). ABTS and DPPH IC₅₀ values were strongly positively correlated, whereas both IC₅₀‐based assays showed strong negative correlations with FRAP, consistent with the opposite reporting directions. The antioxidant assays used in this study reflect related but not identical aspects of redox activity, and their consistent trends across XS‐K and XS‐C strengthen the interpretation of origin‐associated bioactivity divergence.

Figure 3.

Correlation matrix linking quantified metabolites with antioxidant‐related measures. Heatmap showing Pearson correlation coefficients (r) between key metabolites and antioxidant indices (TPC, TFC, TAC, ABTS, DPPH, FRAP). Red indicates positive correlations (r > 0) and blue indicates negative correlations (r < 0); color intensity indicates the magnitude of the correlations (|r|), with the scale ranging −1 to +1. Asterisks denote statistical significance (*P < 0.05, **P < 0.01, ***P < 0.001).

Overall, antioxidant‐related indices (TPC, TFC, TAC, ABTS, DPPH, and FRAP) showed a coherent correlation structure with several phenolic and sterol compounds, supporting an association between compositional variation and antioxidant‐related outcomes across the dataset (Fig. 3). In XS‐K, chlorogenic acid, 4,5‐DCQ, and xanthatin showed strong positive correlations with TFC and with all three antioxidant assays (r > 0.95), indicating potential coordinated contributions to antioxidant capacity. In contrast, XS‐C exhibited its strongest associations between chlorogenic acid, 4,5‐DCQ, and TPC (r ≈ 0.997–0.998). Despite these origin‐specific differences, both XS‐K and XS‐C demonstrated consistently positive correlations across the antioxidant‐related indices (TPC, TFC, TAC, ABTS, DPPH, and FRAP), supporting a shared alignment between phenolic composition and antioxidant activity.

Skin‐related bioactivities encompassing enzyme inhibition and antibacterial effects

Both XS‐K and XS‐C exhibited dose‐dependent inhibitory activities against key skin‐aging enzymes, including tyrosinase, collagenase, and elastase (Fig. 4(A)–(C)). Across all concentrations (1.25–10 mg mL⁻¹), inhibitory activities were consistently observable for both origins, with quantitative differences between XS‐K and XS‐C depending on the enzyme and concentration (Fig. 4(A)–(C)). In particular, collagenase inhibition reached 58.3% for XS‐K and 47.6% for XS‐C at 5 mg mL⁻¹. Elastase inhibition also showed a stronger effect in XS‐K, suggesting enhanced anti‐wrinkle and skin‐firming potential. A similar trend was observed for tyrosinase, with XS‐K showing slightly higher activity at lower doses.

Figure 4.

Skin‐related enzyme inhibitory and antibacterial activities of Xanthium strumarium L. fruits from Korea (XS‐K) and China (XS‐C). (A) Tyrosinase inhibitory activity. (B) Collagenase inhibitory activity. (C) Elastase inhibitory activity. (D) Antibacterial activity against Staphylococcus aureus. (E) Inhibition zone diameters (mm) for XS‐K, XS‐C, and streptomycin (200 μg mL⁻¹). Data are expressed as mean ± SD (n = 3); *P < 0.05, **P < 0.01, ***P < 0.001.

Antibacterial testing revealed activity only against S. aureus, while no detectable inhibition was observed for E. coli O157 at concentrations up to 100 mg mL⁻¹ (Fig. 4(D),(E)). Consistent with its stronger enzymatic inhibition, XS‐K produced larger inhibition zones than XS‐C. At 100 mg mL⁻¹, the inhibition zone diameter of XS‐K corresponded to 84.7% of the streptomycin control, whereas XS‐C reached around 44%.

Collectively, these results suggest that XS‐K exhibits numerically greater enzyme inhibitory and antibacterial activity than XS‐C, in line with its higher levels of key phenolic and phytosterol markers and superior antioxidant performance.

DISCUSSION

This study presents a comparative, origin‐aware framework for characterizing XS‐K and XS‐C by integrating chloroplast genome comparison, targeted chemical profiling (fatty acids, phytosterols, and phenolic compounds), chemometric analyses, and functional bioassays relevant to antioxidant capacity and skin‐related applications. Such multi‐layered integration is increasingly adopted to support botanical quality specification, traceability, and standardization, particularly in contexts where compositional heterogeneity associated with genotype and environment may affect functional consistency.^{9, 10, 19} Accordingly, the current study emphasizes a practical, marker‐based strategy that may be extended to industrial QC and origin authentication.

From a QC perspective, the main utility of the chemical dataset is the identification of a reproducible multi‐target marker signature, rather than attributing origin effects to any single compound. Multivariate chemometric tools provide a structured way to summarize coordinated variation across metabolite classes and to prioritize candidate markers suitable for routine screening.^{9, 19} In this study, VIP‐based ranking served as an exploratory ranking approach, while FC direction and FDR‐adjusted significance values provided complementary statistical support within this dataset for selecting candidate QC markers.^{10, 31} This combined strategy is consistent with established practices in botanical standardization, where multi‐compound marker panels often provide more reliable traceability than single‐marker approaches.^{17, 19}

Chloroplast genome alignment showed high overall similarity between the two origins, while highlighting a localized divergence signal near rpoC2 in the LSC region. XS‐C also showed a higher reference‐based SNP and InDel burden than XS‐K. Comparable levels of intraspecific chloroplast variation and origin‐associated polymorphism have been reported in diverse crop and medicinal plant species, reflecting underlying geographic structure and/or lineage history.^{16, 32, 33} Because chloroplast‐encoded genes contribute to photosynthesis and the biosynthesis of key metabolic precursors, sequence‐level variation may plausibly be associated with downstream compositional divergence. ³⁴ However, direct mechanistic linkage between specific chloroplast loci and metabolite differences cannot be inferred from the present dataset, and would require broader population‐level sampling and experimental validation.^{10, 34}

The functional assays used in this study provide application‐relevant context but should be interpreted as screening‐level evidence rather than definitive validation. Phenolic compounds are well‐established contributors to antioxidant behavior, including electron donation and radical scavenging, in complex plant matrices,^{25, 26} and mixture‐driven effects are common in crude extracts. ²⁷ In more detail, ABTS and DPPH assays are reported as IC₅₀, so lower IC₅₀ values indicate stronger radical scavenging activity, whereas FRAP reflects reducing power, with higher values indicating stronger reducing capacity. Inter‐assay correlation analysis among ABTS, DPPH, and FRAP showed strong method‐to‐method coherence across biological replicates. ABTS and DPPH were strongly positively correlated, and both IC₅₀‐based assays were inversely correlated with FRAP, consistent with their opposite reporting directions. For enzyme inhibition, tyrosinase‐, collagenase‐, and elastase‐targeted assays provide screening‐level evidence relevant to pigmentation and extracellular‐matrix turnover. The consistently stronger inhibition observed for XS‐K across concentrations suggests that origin‐associated compositional differences are functionally detectable under these in vitro conditions, although mixture‐driven and potentially synergistic effects are likely in crude extracts. For antibacterial screening, inhibition zone diameters in the agar diffusion assay reflect the strength of growth inhibition rather than clinical susceptibility. In this study, the inhibition zone against S. aureus fell within the < 12 mm category, indicating weak inhibition under the tested conditions, while no inhibition was observed against E. coli O157.

Key limitations of this study include single‐batch sourcing per origin, the targeted nature of the chemical dataset based on routine quantitative platforms, and the small sample size (n = three per origin), which together limit the generalizability of supervised modeling and preclude predictive claims.^{7, 14, 15} Because the chemical space was intentionally restricted to a targeted QC‐oriented panel, these candidate markers should be interpreted within the scope of the quantified compounds rather than as comprehensive markers. Future studies could expand chemical coverage using untargeted LC–MS‐ or GC–MS‐based metabolomics, whereas the present study focused on establishing a robust and routinely applicable QC marker panel using HPLC and GC‐FID. Although in silico analyses could provide mechanistic insight into the observed bioactivities, they were not included in the present study because the current phytochemical profiling was targeted rather than untargeted.^{17, 29, 35} In vivo validation using both origins would further strengthen the translational relevance of the present findings and should be considered in future studies.

Geographical origin significantly influences the compositional and bioactivity profiles of XS fruits, underscoring its importance in selecting industrial raw materials for herbal preparations, functional ingredients, or cosmeceutical formulations. The observed origin‐dependent patterns across fatty acids, phytosterols, and phenolic constituents were reflected in chemometric discrimination and in vitro bioactivity outcomes related to antioxidant capacity, enzyme inhibition, and antibacterial screening. Our QC‐oriented profiling and chemometric prioritization strategy is consistent with recent comparative component studies that use multivariate analysis for sample discrimination and marker prioritization.^{17, 18} From a QC perspective, the integration of chloroplast variation, origin‐informative metabolites, and chemometric models provides a practical framework for origin authentication and for defining robust, origin‐specific quality markers. This framework may also be extended to other medicinal plant systems facing similar challenges in compositional variability and bioactivity standardization. While current assays provide preliminary screening‐level insight, further studies should validate the functional relevance in biologically relevant models and/or formulated product settings.

CONCLUSION

This comparative study demonstrates that geographical origin is associated with measurable differences in chloroplast sequence variation, targeted metabolite composition, and in vitro bioactivity profiles of XS fruit extracts. Using a consistent definition of log₂FC (log₂(XS‐K/XS‐C)), the integrated profiling and chemometric analysis identified origin‐informative candidate markers, supported by FC ranking and FDR‐adjusted statistics. Bioactivity assays indicated origin‐dependent differences in antioxidant capacity and skin‐related enzyme inhibition, broadly reflecting variation in phenolic‐ and sterol‐related constituents. Antibacterial activity against S. aureus was observed under the tested conditions. However, these functional assays should be interpreted as screening‐level evidence.

Collectively, these findings provide integrated genomic–chemical–bioactivity evidence for origin‐informed quality specification and support origin‐specific quality markers. This origin‐informed approach may also be adapted to other botanical systems facing challenges in standardization and traceability.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

Supporting information

Method S1. Plant material and extraction.

Method S2. Chloroplast genome pipeline.

Method S3. Lipid fraction preparation for GC‐FID.

Method S4. Sterol hydrolysis for GC‐FID.

Method S5. HPLC conditions.

Method S6. Antioxidant assays.

Method S7. Enzyme inhibition assays.

Method S8. Antimicrobial assay.

Figure S1. Chloroplast genome alignment and localized sequence variation between XS‐K and XS‐C. Global alignment of the XS‐K and XS‐C chloroplast genomes revealed high overall sequence similarity, with a distinct divergence localized in the large single‐copy (LSC) region near the rpoC2 locus (highlighted). Sequence variants (SNPs and InDels) were called independently for each origin by mapping reads to the same chloroplast reference under identical filters. XS‐C showed a higher reference‐based variant burden than XS‐K, reflecting origin‐associated polymorphism patterns.

Figure S2. Volcano plot of metabolite differences between XS‐K and XS‐C. The x‐axis represents log₂ foldchange (log₂FC), calculated as log₂(XS‐K/XS‐C), where negative values indicate higher abundance in XS‐C. The y‐axis represents –log₁₀(FDR) based on Benjamini–Hochberg correction. Dashed vertical lines denote |log₂FC| = 1, and the horizontal line denotes FDR = 0.05. Metabolites that passed both thresholds are highlighted and labeled.

Figure S3. PLS‐DA score plot based on targeted metabolite profiling. Partial least squares discriminant analysis (PLS‐DA) was performed using the integrated quantified metabolite dataset (n = 3 per origin). Each point represents an individual replicate of XS‐K and XS‐C. The supervised model showed origin‐dependent separation consistent with the PCA pattern; however, due to the small sample size, the PLS‐DA result is presented as an exploratory visualization rather than for predictive performance modeling.

Table S1. Complete VIP ranking of metabolites from PLS‐DA.

Table S2. Inter‐assay Pearson correlations among antioxidant assays.

DATA AVAILABILITY STATEMENT

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