Volatilome-mediated defence response in Acorus calamus under Tetranychus urticae infestation

Volatilome-mediated defence response in Acorus calamus under Tetranychus urticae infestation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Volatilome-mediated defence response in Acorus calamus under Tetranychus urticae infestation Pallavi Nautiyal, Vijay Laxmi Trivedi, Marco Landi, M C Nautiyal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9198391/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Acorus calamus L. is a medicinal wetland species whose leaves and rhizomes are rich in bioactive phenylpropanoids and terpenoids, yet its biochemical defence responses to herbivores remain poorly understood. This study investigated the impact of Tetranychus urticae infection on volatile metabolism of A. calamus by infestation assessment, GC–MS-based profiling, metabolite class enrichment, and pathway impact analysis. Infested plants grown hydroponically showed a strong downward-to-upward gradient in mite density, with basal leaves reaching 25.64 ± 2.76 mites cm⁻² and 36.55 ± 2.43% leaf area damage, whereas non-infected soil-grown plants had no detectable mites or damage. GC–MS analysis identified 28 volatile metabolites across treatments. Infected plants were dominated by phenylpropanoids and monoterpenoids, with β-asarone (33.55 ± 1.52%), α-asarone (8.98 ± 0.12%), α-pinene, β-pinene, 3-carene, and camphene significantly increased, along with stress-associated volatiles such as [Z]-ocimene, nonanal, and α-phellandrene. Non-infected plants showed higher production of amino acids, organic acids, and other nitrogen-rich primary metabolites. Enrichment analysis revealed strong domination of monoterpenoids, anisoles, heteroaromatics, and carbonyls in infected plants, while amino acids and α-keto acids were enriched in non-infected plants. Pathway impact analysis further showed higher activation of monoterpenoid, methoxy-phenylpropanoid, sesquiterpenoid, and lipoxygenase-mediated fatty-acid volatile biosynthesis pathways in infected plants. These results indicate that T. urticae infestation suppresses primary nitrogen metabolism and redirects rhizome biochemistry toward defense-oriented volatile pathways, providing new insight into belowground chemical defense strategies in A. calamus. Acorus calamus Biosynthesis pathways Tetranychus urticae Monoterpenoids Phenylpropanoids sesquiterpenoids Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Acorus calamus L. is a medicinal and aromatic wetland species valued for its rhizome-derived phenylpropanoids, terpenoids, and methoxy-substituted compounds that contribute to its antimicrobial, insecticidal, and therapeutic properties (Sarker et al., 2017 ; Lee et al., 2020 ). Beyond their pharmacological importance, these metabolites play essential ecological roles, especially in chemical defense against herbivores and environmental stress (Sati et al., 2025 ). Among major herbivores, the two-spotted spider mite Tetranychus urticae is a highly polyphagous pest (Chen et al., 2025 ) known to infest essential-oil-rich medicinal plants (Ali et al., 2025 ), inducing metabolic disruption (Ruffatto et al., 2024 ), chlorosis (Pavan et al., 2025 ), oxidative stress (Erb & Reymond, 2019 ), and shifts in volatile organic compound biosynthesis (Bergman et al., 2025 ). Recent studies on aromatic herbs such as Mentha piperita, Ocimum basilicum, Citrus sinensis , and Solanum lycopersicum indicated that spider mite feeding strongly upregulates terpenoid, phenylpropanoid, and lipoxygenase-derived volatiles as part of herbivore-induced plant volatile (HIPV) production (Blaazer et al., 2018 ). However, despite extensive literature on the phytochemistry of A. calamus , no investigation has examined how the chemical composition of its responds metabolically to herbivore attack. Metabolomics study has provided insights into plant–herbivore interactions by identifying stress-associated changes in primary and secondary metabolites and linking these responses to defense signaling pathways (Fiallo-Olivé et al., 2020 ; Hu et al., 2021). GC–MS-based volatile profiling, along with enrichment and pathway impact analysis, has proved especially effective in identifying changes in biochemical networks during biotic stress (Dinh et al., 2020 ). Although a clear research gap is present regarding rhizome-specific responses of plants, particularly on the balance between constitutive and induced metabolites under spider mite infestation. Most studies examine only the leaves, even though underground parts like rhizomes often store the highest levels of defense-related compounds (Erb & Reymond, 2019 ; Huang et al., 2020 ). Therefore, a comparative analysis of the metabolites of the infected and non-infected A. calamu s plants is still lacking. The present study addresses this research gap by, GC–GC-MS-based metabolite profiling, enrichment, and pathway impact analysis. The objectives were to quantify infestation severity; characterize differences in volatile chemical composition between infected and non-infected plants; identify enriched biochemicals; and activate major metabolic pathways. We hypothesized that spider mite infestation would induce a significant metabolic change in metabolites. By elucidating these biochemical shifts, this study contributes to a deeper understanding of chemical defence responses in A. calamus and indicates future studies on plant–herbivore interactions and stress signaling in medicinal plants. Materials and Methods Infected and non-infected plants of A. calamus were used for this study. The affected group consisted of plants grown under hydroponic conditions, which exhibited visible stress symptoms. The control group comprised healthy plants cultivated under soil-based conditions. Both cultivation conditions were maintained under similar environmental conditions. Samples from both cultivation systems were used for further analysis. Plants were maintained in well-drained loamy soil (pH 6.5–7.0; organic matter 2.1%). All plants were grown under natural light (12 h photoperiod), temperature 25 ± 2°C, and 60–70% relative humidity. Leaf samples from basal and apical positions were excised (1 cm² area) and examined under a stereomicroscope (40×) to quantify mite density (mites cm⁻²). Leaf damage was measured as the percentage leaf area affected using ImageJ software (NIH, USA) (Collins et al. 2007). Damage severity was scored on a 0–5 scale: Rhizome tissues were washed, shade-dried, and ground to a fine powder. A total of 100 mg of the powdered material was extracted in a 1:1 mixture of HPLC-grade methanol and HPLC-grade chloroform (1 mL + 1 mL) using sonication for 30 min. The extracts were centrifuged at 10,000 rpm for 10 min, and the resulting supernatant was filtered through a 0.22 µm PTFE membrane filter before GC–MS analysis. GC–MS analysis of extracts Volatile metabolites in leaf extracts of infected and non-infected A. calamus were analysed using a GC–MS system (Agilent, equipped with a single quadrupole mass analyser) fitted with an HP-5MS capillary column (30 m × 0.25 mm i.d., 0.25 μm film thickness). Helium was used as the carrier gas at a constant flow rate of 1.0 mL min⁻¹. The injector temperature was maintained at 250 °C and samples (1 μL) were injected in split mode (split ratio 20:1). The oven temperature programme was: initial temperature 50 °C (held for 2 min), followed by a ramp of 4 °C min⁻¹ to 280 °C, with a final isothermal hold of 5 min. The transfer line temperature was set at 280 °C. Mass spectra were recorded in electron-impact (EI) mode at 70 eV over an m/z range of 40–550. The ion source and quadrupole temperatures were maintained at 230°C and 150°C, respectively. Compounds were tentatively identified based on (i) retention time, (ii) comparison of mass spectra with NIST 14 and Wiley 09 libraries (similarity index ≥ 80 %), and (iii) comparison of calculated retention indices with literature values using a homologous series of n-alkanes (C₈–C₂₄) analysed under identical conditions. Relative abundances of individual metabolites were obtained using peak-area normalization and expressed as a percentage of the total ion chromatogram for each sample (McLafferty & Tureček, 2009) Metabolite class enrichment analysis Identified metabolites were classified into major biochemical groups (monoterpenoids, phenylpropanoids, benzenoids, aldehydes, fatty acids, etc.). Metabolite class enrichment was performed using the DNEA R package (version 2.2.4) (Patsalis et al. 2024), with a hypergeometric test (p < 0.05). A pathway impact analysis was conducted using the PlantCyc metabolic pathway database (PlantCyc, 2024). Results were visualized using bar-type enrichment plots and bubble plots to represent class significance and enrichment ratios. Result Mite density and damage severity Mite infestation was detected only in infected plants, with no mites observed in non-infected samples across both basal and apical leaf positions (Table 1). In infected plants, the basal leaves showed significantly higher mite density (25.64 ± 2.76 mites cm⁻²) compared to apical leaves (5.86 ± 1.37 mites cm⁻²). Leaf damage followed a similar pattern, with basal leaves showing a higher percentage of damaged area (36.55 ± 2.43%) than apical leaves (12.85 ± 2.22%). Correspondingly, the damage severity score was greater in basal leaves (score 4) compared to apical leaves (score 2). No damage or severe symptoms were recorded in non-infected plants (score 0). GC–MS profiling of metabolites GC–MS analysis identified 28 metabolites across infected and non-infected samples, spanning monoterpenes, phenolics, sesquiterpenes, fatty acids, and aldehydes (Table 2 and Figure 1). The relative abundance of most compounds was higher in infected plants compared to non-infected plants. Among all detected compounds, β-asarone was the most dominant metabolite in both conditions, with significantly higher abundance in infected plants (33.55 ± 1.52%) compared to non-infected plants (18.98 ± 1.59%). Similarly, α-asarone showed a marked increase in infected plants (8.98 ± 0.12%) relative to non-infected plants (2.32 ± 0.02%). Caryophyllene also showed higher levels in infected plants (4.33 ± 0.03%) than in non-infected plants (3.54 ± 0.01%). Monoterpenes such as α-pinene, β-pinene, and camphene were consistently higher in infected plants, with α-pinene increasing from 2.11 ± 0.08% to 3.05 ± 0.15%, β-pinene from 0.22 ± 0.03% to 0.54 ± 0.07%, and camphene from 0.12 ± 0.05% to 0.47 ± 0.07%. Similarly, aromatic compounds, including guaiacol, vanillin, and eugenol, showed higher concentrations in infected plants. Several compounds were detected exclusively in infected plants, including limonene, α-phellandrene, [Z]-ocimene, butylbenzene, hexanol, and nonanal, whereas no compounds were uniquely detected in non-infected plants. In contrast, β-myrcene and decanal showed slightly higher abundance in non-infected plants (0.44 ± 0.03% and 0.53 ± 0.01%, respectively) compared to infected plants. The metabolite profile of infected plants was characterized by increased abundance and diversity of volatile compounds, whereas non-infected plants exhibited comparatively lower concentrations and the absence of several volatile metabolites. Classification of metabolites In infected plants, the metabolite profile was dominated by monoterpenoids (28%), followed by carbonyl compounds (16%), methoxyphenols (12%), anisoles (12%), and sesquiterpenoids (8%) (Figure 2). Minor contributions were observed from fatty acids and conjugates (4%), fatty alcohols (4%), benzenediols (4%), alcohols and polyols (4%), styrenes (4%), and heteroaromatic compounds (4%). These classes corresponded to compounds such as (+)-limonene, α-pinene, β-pinene, camphene, decanal, 2-furancarboxaldehyde, guaiacol, vanillin, γ-asarone, trans-isoasarone, β-caryophyllene, cis-vaccenic acid, 1-hexanol, and 4-hydroxystyrene (Table 2). In contrast, non-infected plants showed a markedly different distribution, with amino acids, peptides, and analogues accounting for 57% of total metabolites. Other classes included pyrrolidinylpyridines (5%), hydroxycinnamic acids and derivatives (5%), benzenes (5%), alpha-keto acids and derivatives (5%), phenylpyruvic acid derivatives (5%), dicarboxylic acids and derivatives (5%), carboxylic acids (5%), short-chain keto acids and derivatives (4%), and amines (4%). Representative compounds included β-alanine, glycine, L-tyrosine, phenylalanine, serine, L-valine, pyruvic acid, phenylpyruvic acid, fumaric acid, caffeic acid, benzene, acetoacetic acid, propionic acid, and cotinine. No amino acid or peptide derivatives were detected in infected plants, whereas volatile classes such as monoterpenoids, anisoles, styrenes, and heteroaromatic compounds were minimally represented in non-infected plants. Comparative metabolites enrichment Enrichment analysis showed a clear difference between infected and non-infected plants (Figure 3A). Infected plants showed higher enrichment of volatile metabolite classes, whereas non-infected plants were enriched in nitrogen-containing and organic acid derivatives. Heteroaromatic compounds showed the highest enrichment ratio in infected plants, followed by monoterpenoids and anisoles. The bubble plot (Figure 3B) showed higher –log10(p-values) and larger bubble sizes for these classes, indicating stronger statistical significance and enrichment. In non-infected plants, alpha-keto acids and derivatives showed the highest enrichment ratio, while amino acids, peptides, and analogues exhibited the highest –log10(p-values). Metabolic pathway impact assessment Pathway impact analysis revealed differences in metabolic pathway activation between infected and non-infected plants (Figure 4). Both conditions shared similar pathways; however, pathway impact and statistical significance were higher in infected plants. In infected plants, monoterpenoid biosynthesis (PWY-5073) showed the highest pathway impact and –log10(p-value), followed by lipoxygenase-mediated fatty-acid volatile biosynthesis (PWY-5139), methoxy-phenylpropanoid biosynthesis (PWY-5973), and sesquiterpenoid biosynthesis (PWY-7209). Lower pathway impact values were observed for general phenylpropanoid biosynthesis (PWY-5010), eugenol biosynthesis (PWY-5021), and vanillin biosynthesis (PWY-5387). In non-infected plants, the same pathways were present but showed lower pathway impact and lower –log10(p-values). Monoterpenoid biosynthesis remained the highest-impact pathway, followed by lipoxygenase-mediated fatty-acid volatile biosynthesis, methoxy-phenylpropanoid biosynthesis, and sesquiterpenoid biosynthesis. General phenylpropanoid, eugenol, and vanillin biosynthesis pathways were also detected with lower impact values. Discussion Spatial gradient of mite infestation and density-dependent leaf damage in Acorus calamus Mite distribution showed a pronounced spatial gradient, with higher colonization and damage localized to basal leaves, indicating preferential feeding on older tissues. This pattern is consistent with the feeding ecology of Tetranychus urticae , which preferentially exploits mature leaves characterized by reduced defensive capacity, increased cellular permeability, and enhanced nutrient leakage (Sarr et al., 2018 ). The substantially greater mite density and associated damage observed in basal leaves therefore reflect a susceptibility gradient within the plant canopy (Diaz-Marquina et al., 2019). The strong correspondence between mite density and foliar damage further suggests a density-dependent escalation of physiological injury. Elevated infestation levels are known to disrupt chloroplast integrity, induce oxidative stress, and accelerate chlorosis and necrosis, thereby amplifying tissue degradation (Sethi et al., 2022). Similar density–damage relationships have been reported across host systems, including Lycopersicon esculentum and medicinal plant species, where increasing herbivore pressure proportionally intensifies structural and biochemical impairment (Santamaría et al., 2020 ). In contrast, the complete absence of mites and damage in non-infected plants confirms that the observed physiological disruption is directly attributable to herbivory rather than background environmental variation (Marques-Batista et al., 2021 ). These findings indicate that spatial heterogeneity in leaf age and defense status governs mite colonization patterns, while infestation intensity acts as a key determinant of damage severity in Acorus calamus . Infestation-induced changes of volatile metabolome in Acorus calamus GC–MS profiling revealed a pronounced reconfiguration of the volatile metabolome in response to infestation, characterized by both qualitative emergence of stress-related compounds and quantitative amplification of key defense-associated metabolites. The marked accumulation of phenylpropanoid derivatives, particularly β-asarone and α-asarone, indicates strong activation of secondary metabolic pathways under herbivore pressure. These compounds are well recognized as bioactive constituents of A. calamus , and their elevated abundance suggests an induced chemical defense response, consistent with herbivory-driven upregulation of phenylpropanoid biosynthesis (War et al., 2020 ). Alongside the enhanced levels of monoterpenes, including α-pinene, β-pinene, camphene, and 3-carene, further support the activation of volatile-mediated defense signaling. Monoterpenoids are key components of herbivore-induced plant volatiles (HIPVs), functioning in direct toxicity, deterrence, and indirect defense via signaling cascades (Riedlmeier et al., 2017 ; Erb & Reymond, 2019 ). Their increased abundance aligns with previous observations of T. urticae -induced volatile emissions in aromatic plants, indicating that A. calamus exhibits a comparable inducible defense strategy (Su et al., 2022 ; Blaazer et al., 2018 ). The detection of compounds such as ocimene, phellandrene, hexanol, and nonanal in infected plants highlights the induction of stress-specific metabolic pathways. These volatiles are closely linked to jasmonate-mediated defense signaling and lipoxygenase-driven lipid peroxidation, processes commonly associated with herbivore-induced oxidative stress (Song et al., 2018; Sarde et al., 2019 ). Their presence suggests that infestation triggers membrane disruption and downstream volatile aldehyde formation, reinforcing the role of oxidative pathways in defense activation (Deng et al., 2021; Liang et al., 2022 ). In contrast, the higher abundance of β-myrcene and decanal in non-infected plants reflects a constitutive metabolic state, associated with basal volatile production and normal fatty acid turnover rather than stress-induced responses (Kundu et al., 2021 ; Liang et al., 2022 ). These findings reveal a clear metabolic shift from constitutive to inducible defense chemistry, where infestation drives the preferential synthesis of phenylpropanoids and terpenoids while restructuring the overall volatile profile of A. calamus . Herbivory-mediated metabolic reallocation from primary to volatile secondary pathways in Acorus calamus Metabolite classification revealed a clear shift in metabolic organization under infestation, characterized by the predominance of volatile secondary metabolites in infected plants and nitrogen-rich primary metabolites in non-infected plants. The dominance of monoterpenoids, phenolic derivatives, and related volatile classes in infected tissues indicates a coordinated activation of secondary metabolic pathways associated with plant defense (Erb & Reymond, 2019 ). These compounds are widely recognized as key components of herbivore-induced plant volatiles, contributing to direct toxicity, deterrence, and signaling functions during arthropod attack (Song et al., 2018; Guo et al., 2020 ). In contrast, the metabolite profile of non-infected plants was largely dominated by amino acids, organic acids, and related nitrogen-containing compounds, reflecting an active primary metabolism linked to growth, protein synthesis, and energy turnover (Kundu et al., 2021 ). This metabolic configuration is typical of unstressed plants, where resources are preferentially allocated toward biomass accumulation and physiological maintenance (Fiallo-Olivé et al., 2020 ). The complete absence of amino acid–related metabolites in infected plants suggests a strong suppression of primary nitrogen metabolism, likely driven by resource reallocation toward defense-associated pathways (Kundu et al., 2021 ). Such metabolic trade-offs are a well-established feature of plant responses to herbivory, where carbon and nitrogen skeletons are diverted from growth processes toward the biosynthesis of phenylpropanoids and terpenoids (Sethi et al., 2022). This reprogramming reflects a strategic shift from constitutive metabolism to inducible defense, prioritizing survival over growth under biotic stress (Schwachtje & Baldwin, 2020). Additionally, the near absence of monoterpenoids, anisoles, and heteroaromatic volatiles in non-infected plants reinforces their inducible nature. These metabolite classes are typically synthesized in response to herbivore attack and remain at low baseline levels under non-stress conditions, consistent with the dynamics of HIPV production (Bui et al., 2018; Dicke & Lucas, 2020). The observed metabolic divergence highlights a tightly regulated defense strategy in A. calamus , where infestation triggers a systemic reallocation of metabolic flux toward volatile secondary pathways while downregulating primary metabolic processes. Herbivory-driven metabolic reprogramming and pathway activation in Acorus calamus Metabolite enrichment and pathway analyses revealed a clear reorganization of plant metabolism under mite infestation, characterized by the preferential activation of volatile secondary metabolites and suppression of primary metabolic processes. Infected plants showed strong enrichment of heteroaromatic compounds, monoterpenoids, and anisoles, which also exhibited higher statistical significance and enrichment strength. These metabolite classes are widely associated with herbivore-induced plant volatiles and are known to play roles in direct defense, deterrence, and inter-plant signaling during biotic stress (Erb & Reymond, 2019 ; Guo et al., 2020 ). The high enrichment of heteroaromatic and carbonyl compounds further suggests activation of oxidative lipid degradation pathways. Such compounds are commonly produced through membrane lipid peroxidation and are considered biochemical markers of herbivore-induced oxidative stress (Deng et al., 2021). This indicates that mite feeding may disrupt cellular membranes, triggering lipid-derived volatile production and reinforcing defense signaling (Liang et al., 2022 ). In contrast, non-infected plants were enriched in nitrogen-containing metabolites, particularly amino acids and alpha-keto acids, which showed the highest statistical significance. This metabolic profile reflects a growth-oriented physiological state, where primary metabolism supports protein synthesis, energy production, and development (Fiallo-Olivé et al., 2020 ). The absence of enrichment of volatile secondary metabolites in these plants further indicates the lack of stress-induced metabolic activation (Kundu et al., 2021 ). Pathway impact analysis provided additional insight into the underlying biochemical mechanisms. Monoterpenoid biosynthesis (PWY-5073) emerged as the most significantly impacted pathway in infected plants, followed by lipoxygenase-mediated fatty-acid volatile biosynthesis (PWY-5139), methoxy-phenylpropanoid biosynthesis (PWY-5973), and sesquiterpenoid biosynthesis (PWY-7209). The activation of these pathways is consistent with herbivore-induced metabolic reprogramming, where terpenoid and phenylpropanoid pathways are upregulated to produce defense-related compounds (Dudareva et al., 2013; Wasternack & Feussner, 2018). The strong impact of the lipoxygenase pathway further highlights the role of oxylipin-mediated signaling and oxidative stress responses during infestation. Lipoxygenase-derived metabolites are known to regulate jasmonate signaling pathways and contribute to defense responses against herbivores (Deng et al., 2021; Liang et al., 2022 ). Similarly, enhanced phenylpropanoid and sesquiterpenoid biosynthesis aligns with previous studies demonstrating their involvement in chemical defense and stress adaptation in medicinal plants (Marques-Batista et al., 2021 ; Goura et al., 2025 ). In contrast, although similar pathways were present in non-infected plants, their lower pathway impact and reduced statistical significance indicate basal metabolic activity without active defense induction (Su et al., 2022 ). This supports the concept that plants maintain constitutive levels of secondary metabolism, which are rapidly upregulated upon herbivore attack (Guo et al., 2020 ). These findings revealed a coordinated metabolic shift in A. calamus , where infestation induces a transition from primary metabolism toward volatile secondary metabolism. This reprogramming enhances the production of terpenoids, phenylpropanoids, and lipid-derived volatiles, reflecting a dynamic and tightly regulated biochemical defense strategy against herbivore stress. Conclusions This study provides the metabolomic comparison of plant from spider mite–infested and non-infested A. calamus plants. The study reveals significant biochemical changes under herbivore stress. Infested plants showed a significant change from non-infected, including monoterpenoid, methoxy-phenylpropanoid, sesquiterpenoid, and lipoxygenase-mediated fatty-acid biosynthesis. Elevated levels of β-asarone, α-asarone, α-pinene, β-pinene, 3-carene, and stress-related aldehydes showed induction of herbivore-induced volatile production. In contrast, non-infected plants were dominated by amino acids, organic acids, and other primary metabolites. These findings highlighted that A. calamus possess a potential chemical composition against mite infestation. The study also provides a current understanding of belowground defence responses and provides a groundwork for future research on stress signaling and metabolomic resilience in medicinal plants. Declarations Funding information Funding information is not available. Ethics approval Not applicable Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this study. Author contribution PN: Writing—original draft, Visualization, Validation, Methodology, Investigation, Data curation, and Conceptualization. VLT: Writing—review and editing, Formal analysis, Supervision, Resources, Project administration, ML & MCN: Writing—review and editing, Supervision. Data availability statement Data will be made available on request. 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Plant Physiol 178:1640–1653 Steinbrenner AD, Gómez S, Osorio S, Fernie AR, Orians CM (2011) Herbivore-induced changes in tomato (Solanum lycopersicum) primary metabolism: a whole plant perspective. J Chem Ecol 37:1294–1303 Su Q, Wang R, Ding X et al (2022) Tetranychus urticae triggers HIPV production in aromatic plants. Pest Manag Sci 78:1102–1114 War AR, Paulraj MG, Ahmad T, Buhroo AA, Hussain B, Ignacimuthu S, Sharma HC (2020) Mechanisms of plant defense against insect herbivores. Plant Signal Behav 15:1784025 Tables Table 1- Mite density and damage severity in Acorus calamus S. No. Sample leaf position sampled Mean mite density (Mites/cm 2 ) Leaf area damaged (%) Damage severity score (0-5) 1 Infected Basal 25.64±2.76 36.55±2.43 4 2 Infected Apical 5.86±1.37 12.85±2.22 2 3 Non-infected Basal 0 0 0 4 Non-infected Apical 0 0 0 Table 2- GC-MS -profile of volatile metabolites in Acorus calamus S. No. RT (min) Compound name Infected (%) Non-infected (%) 1 5.87 α - Pinene 3.05±0.15 2.11±0.08 2 5.92 Guaiacol 0.47±0.02 0.26±0.06 3 5.96 4-vinylphenol 0.88±0.01 0.65±0.01 4 6.54 Eugenol 0.39±0.04 0.24±0.01 5 6.73 Vanillin 0.73±0.09 0.42±0.01 6 10.54 2-Pentanone 0.54±0.33 0.31±0.15 7 10.87 β-curcumene 0.64±0.02 0.59±0.01 8 11.16 Isobutanol 0.45±0.08 0.27±0.04 9 12.17 β - pinene 0.54±0.07 0.22±0.03 10 12.18 3-Carene 1.69±0.03 1.49±0.01 11 14.57 Camphene 0.47±0.07 0.12±0.05 12 16.28 β- Asarone 33.55±1.52 18.98±1.59 13 16.34 Elemicin 0.22±0.02 0.13±0.03 14 16.84 Caryophyllene 4.33±0.03 3.54±0.01 15 17.29 Resorcinol 0.87±0.87 0.12±0.68 16 17.96 α- Asarone 8.98±0.12 2.32±0.02 17 22.3 Limonene 0.13±0.01 ND 18 23.12 α-phellandrene 0.17±0.001 ND 19 24.35 β - Myrcene 0.28±0.03 0.44±0.03 20 24.56 cis-Vaccenic acid 0.26±0.08 0.20±0.02 21 24.67 β-Copaene 0.56±0.07 0.52±0.01 22 24.82 2-Pentylfuran 1.58±0.06 1.35±0.01 23 25.11 [Z]-Ocimene 2.98±0.04 ND 24 30.37 Butylbenzene 0.37±0.03 ND 25 33.48 Hexanol 0.16±0.07 ND 26 35.94 Nonanal 0.22±0.06 ND 27 40.5 Furfural 0.43±0.05 0.34±0.01 28 42.97 Decanal 0.28±0.07 0.53±0.01 Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Editor assigned by journal 26 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9198391","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623548556,"identity":"c2e6c25f-f123-4c7e-b834-5554f49f7880","order_by":0,"name":"Pallavi Nautiyal","email":"","orcid":"","institution":"Hemvati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"Pallavi","middleName":"","lastName":"Nautiyal","suffix":""},{"id":623548557,"identity":"79b01b0d-0fac-404e-845b-53a7d56b1456","order_by":1,"name":"Vijay Laxmi Trivedi","email":"","orcid":"","institution":"Hemvati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"Vijay","middleName":"Laxmi","lastName":"Trivedi","suffix":""},{"id":623548558,"identity":"01ffbdef-387a-40f7-afaa-f96722c0a9f1","order_by":2,"name":"Marco Landi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYPACCyBObHzAwCDBwMbA2ECMFgmQlmYDqJZGYvSAtCSwSUB5+K3RbT/78MMHBgl5c/bktmreHRZ5fAzM7Q/waTE7k24sOYNBwnBnz8O227xnJIoJOszsQBobMw+DBOOGG4lALW0SiW0EtZx/BtZiD9JSTJyWGxBbEkFamInU8oxZcoaBRPKGMw+bJee2Af3CzNg4A7/D0hg/fKiwsd1wPP3hh7dtdXny7e0PPuDTAgEGCGYCAzNh9agggVQNo2AUjIJRMPwBAPlHRRl+gjCoAAAAAElFTkSuQmCC","orcid":"","institution":"Università di Pisa: Universita degli Studi di Pisa","correspondingAuthor":true,"prefix":"","firstName":"Marco","middleName":"","lastName":"Landi","suffix":""},{"id":623548559,"identity":"5f2dfe79-9ae3-4af8-95b4-941ed0e534e2","order_by":3,"name":"M C Nautiyal","email":"","orcid":"","institution":"Hemvati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"C","lastName":"Nautiyal","suffix":""}],"badges":[],"createdAt":"2026-03-23 09:26:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9198391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9198391/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107637449,"identity":"6b2f4886-ee3f-41d5-8b51-a43b71bce08a","added_by":"auto","created_at":"2026-04-23 12:46:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":110263,"visible":true,"origin":"","legend":"\u003cp\u003eComparative GC–MS profiling of volatile metabolites in infected [A] and healthy [B] \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9198391/v1/e1c5a26b29488e0052b6c7cb.png"},{"id":107707381,"identity":"0710d7ad-0f2b-47b7-a5ef-8188999037b0","added_by":"auto","created_at":"2026-04-24 09:20:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":188843,"visible":true,"origin":"","legend":"\u003cp\u003eClassification of metabolites in infected [A] and healthy [B] \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9198391/v1/d21c66945adb055908f2ef7b.png"},{"id":107637451,"identity":"1c8e4f41-4f88-4152-9e54-06f13157a388","added_by":"auto","created_at":"2026-04-23 12:46:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":174587,"visible":true,"origin":"","legend":"\u003cp\u003eComparative chemical class enrichment analysis of infected and non-infected \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9198391/v1/cf26e94c1654d9637fa7e14e.png"},{"id":107707284,"identity":"f6b6c40f-e8fd-462d-a6c7-889a5af69e00","added_by":"auto","created_at":"2026-04-24 09:19:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":226250,"visible":true,"origin":"","legend":"\u003cp\u003eComparative pathway impact assessment of infected and non-infected \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9198391/v1/116dd2204658c054944b26d1.png"},{"id":107709414,"identity":"5908da73-662a-4ea2-b9f6-c1b389ea0c92","added_by":"auto","created_at":"2026-04-24 09:35:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":927173,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9198391/v1/bb37b84b-b322-4448-a07b-66dee8595741.pdf"}],"financialInterests":"","formattedTitle":"Volatilome-mediated defence response in Acorus calamus under Tetranychus urticae infestation","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eAcorus calamus\u003c/em\u003e L. is a medicinal and aromatic wetland species valued for its rhizome-derived phenylpropanoids, terpenoids, and methoxy-substituted compounds that contribute to its antimicrobial, insecticidal, and therapeutic properties (Sarker et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Beyond their pharmacological importance, these metabolites play essential ecological roles, especially in chemical defense against herbivores and environmental stress (Sati et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among major herbivores, the two-spotted spider mite \u003cem\u003eTetranychus urticae\u003c/em\u003e is a highly polyphagous pest (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) known to infest essential-oil-rich medicinal plants (Ali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), inducing metabolic disruption (Ruffatto et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), chlorosis (Pavan et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), oxidative stress (Erb \u0026amp; Reymond, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and shifts in volatile organic compound biosynthesis (Bergman et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Recent studies on aromatic herbs such as \u003cem\u003eMentha piperita, Ocimum basilicum, Citrus sinensis\u003c/em\u003e, and \u003cem\u003eSolanum lycopersicum\u003c/em\u003e indicated that spider mite feeding strongly upregulates terpenoid, phenylpropanoid, and lipoxygenase-derived volatiles as part of herbivore-induced plant volatile (HIPV) production (Blaazer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, despite extensive literature on the phytochemistry of \u003cem\u003eA. calamus\u003c/em\u003e, no investigation has examined how the chemical composition of its responds metabolically to herbivore attack.\u003c/p\u003e \u003cp\u003eMetabolomics study has provided insights into plant\u0026ndash;herbivore interactions by identifying stress-associated changes in primary and secondary metabolites and linking these responses to defense signaling pathways (Fiallo-Oliv\u0026eacute; et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hu et al., 2021). GC\u0026ndash;MS-based volatile profiling, along with enrichment and pathway impact analysis, has proved especially effective in identifying changes in biochemical networks during biotic stress (Dinh et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although a clear research gap is present regarding rhizome-specific responses of plants, particularly on the balance between constitutive and induced metabolites under spider mite infestation. Most studies examine only the leaves, even though underground parts like rhizomes often store the highest levels of defense-related compounds (Erb \u0026amp; Reymond, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Huang et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, a comparative analysis of the metabolites of the infected and non-infected \u003cem\u003eA. calamu\u003c/em\u003es plants is still lacking. The present study addresses this research gap by, GC\u0026ndash;GC-MS-based metabolite profiling, enrichment, and pathway impact analysis. The objectives were to quantify infestation severity; characterize differences in volatile chemical composition between infected and non-infected plants; identify enriched biochemicals; and activate major metabolic pathways. We hypothesized that spider mite infestation would induce a significant metabolic change in metabolites. By elucidating these biochemical shifts, this study contributes to a deeper understanding of chemical defence responses in \u003cem\u003eA. calamus\u003c/em\u003e and indicates future studies on plant\u0026ndash;herbivore interactions and stress signaling in medicinal plants.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eInfected and non-infected plants of \u003cem\u003eA. calamus\u003c/em\u003e were used for this study. The affected group consisted of plants grown under hydroponic conditions, which exhibited visible stress symptoms. The control group comprised healthy plants cultivated under soil-based conditions. Both cultivation conditions were maintained under similar environmental conditions. Samples from both cultivation systems were used for further analysis. Plants were maintained in well-drained loamy soil (pH 6.5\u0026ndash;7.0; organic matter 2.1%). All plants were grown under natural light (12 h photoperiod), temperature 25 \u0026plusmn; 2\u0026deg;C, and 60\u0026ndash;70% relative humidity. Leaf samples from basal and apical positions were excised (1 cm\u0026sup2; area) and examined under a stereomicroscope (40\u0026times;) to quantify mite density (mites cm⁻\u0026sup2;). Leaf damage was measured as the percentage leaf area affected using ImageJ software (NIH, USA) (Collins et al. 2007). Damage severity was scored on a 0\u0026ndash;5 scale:\u003c/p\u003e\n\u003cp\u003eRhizome tissues were washed, shade-dried, and ground to a fine powder. A total of 100 mg of the powdered material was extracted in a 1:1 mixture of HPLC-grade methanol and HPLC-grade chloroform (1 mL + 1 mL) using sonication for 30 min. The extracts were centrifuged at 10,000 rpm for 10 min, and the resulting supernatant was filtered through a 0.22 \u0026micro;m PTFE membrane filter before GC\u0026ndash;MS analysis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1776947699.png\" width=\"1022\" height=\"85\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGC\u0026ndash;MS analysis of extracts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVolatile metabolites in leaf extracts of infected and non-infected \u003cem\u003eA. calamus\u003c/em\u003e were analysed using a GC\u0026ndash;MS system (Agilent, equipped with a single quadrupole mass analyser) fitted with an HP-5MS capillary column (30 m \u0026times; 0.25 mm i.d., 0.25 \u0026mu;m film thickness). Helium was used as the carrier gas at a constant flow rate of 1.0 mL min⁻\u0026sup1;. The injector temperature was maintained at 250 \u0026deg;C and samples (1 \u0026mu;L) were injected in split mode (split ratio 20:1). The oven temperature programme was: initial temperature 50 \u0026deg;C (held for 2 min), followed by a ramp of 4 \u0026deg;C min⁻\u0026sup1; to 280 \u0026deg;C, with a final isothermal hold of 5 min. The transfer line temperature was set at 280 \u0026deg;C. Mass spectra were recorded in electron-impact (EI) mode at 70 eV over an m/z range of 40\u0026ndash;550. The ion source and quadrupole temperatures were maintained at 230\u0026deg;C and 150\u0026deg;C, respectively. Compounds were tentatively identified based on (i) retention time, (ii) comparison of mass spectra with NIST 14 and Wiley 09 libraries (similarity index \u0026ge; 80 %), and (iii) comparison of calculated retention indices with literature values using a homologous series of n-alkanes (C₈\u0026ndash;C₂₄) analysed under identical conditions. Relative abundances of individual metabolites were obtained using peak-area normalization and expressed as a percentage of the total ion chromatogram for each sample (McLafferty \u0026amp; Tureček, 2009)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolite class enrichment analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIdentified metabolites were classified into major biochemical groups (monoterpenoids, phenylpropanoids, benzenoids, aldehydes, fatty acids, etc.). Metabolite class enrichment was performed using the DNEA R package (version 2.2.4) (Patsalis et al. 2024), with a hypergeometric test (p \u0026lt; 0.05). A pathway impact analysis was conducted using the PlantCyc metabolic pathway database (PlantCyc, 2024). Results were visualized using bar-type enrichment plots and bubble plots to represent class significance and enrichment ratios.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cstrong\u003eMite density and damage severity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMite infestation was detected only in infected plants, with no mites observed in non-infected samples across both basal and apical leaf positions (Table 1). In infected plants, the basal leaves showed significantly higher mite density (25.64 \u0026plusmn; 2.76 mites cm⁻\u0026sup2;) compared to apical leaves (5.86 \u0026plusmn; 1.37 mites cm⁻\u0026sup2;). Leaf damage followed a similar pattern, with basal leaves showing a higher percentage of damaged area (36.55 \u0026plusmn; 2.43%) than apical leaves (12.85 \u0026plusmn; 2.22%). Correspondingly, the damage severity score was greater in basal leaves (score 4) compared to apical leaves (score 2). No damage or severe symptoms were recorded in non-infected plants (score 0).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGC\u0026ndash;MS profiling of metabolites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGC\u0026ndash;MS analysis identified 28 metabolites across infected and non-infected samples, spanning monoterpenes, phenolics, sesquiterpenes, fatty acids, and aldehydes (Table 2 and Figure 1). The relative abundance of most compounds was higher in infected plants compared to non-infected plants. Among all detected compounds, \u0026beta;-asarone was the most dominant metabolite in both conditions, with significantly higher abundance in infected plants (33.55 \u0026plusmn; 1.52%) compared to non-infected plants (18.98 \u0026plusmn; 1.59%). Similarly, \u0026alpha;-asarone showed a marked increase in infected plants (8.98 \u0026plusmn; 0.12%) relative to non-infected plants (2.32 \u0026plusmn; 0.02%). Caryophyllene also showed higher levels in infected plants (4.33 \u0026plusmn; 0.03%) than in non-infected plants (3.54 \u0026plusmn; 0.01%). Monoterpenes such as \u0026alpha;-pinene, \u0026beta;-pinene, and camphene were consistently higher in infected plants, with \u0026alpha;-pinene increasing from 2.11 \u0026plusmn; 0.08% to 3.05 \u0026plusmn; 0.15%, \u0026beta;-pinene from 0.22 \u0026plusmn; 0.03% to 0.54 \u0026plusmn; 0.07%, and camphene from 0.12 \u0026plusmn; 0.05% to 0.47 \u0026plusmn; 0.07%. Similarly, aromatic compounds, including guaiacol, vanillin, and eugenol, showed higher concentrations in infected plants. Several compounds were detected exclusively in infected plants, including limonene, \u0026alpha;-phellandrene, [Z]-ocimene, butylbenzene, hexanol, and nonanal, whereas no compounds were uniquely detected in non-infected plants. In contrast, \u0026beta;-myrcene and decanal showed slightly higher abundance in non-infected plants (0.44 \u0026plusmn; 0.03% and 0.53 \u0026plusmn; 0.01%, respectively) compared to infected plants. The metabolite profile of infected plants was characterized by increased abundance and diversity of volatile compounds, whereas non-infected plants exhibited comparatively lower concentrations and the absence of several volatile metabolites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClassification of metabolites\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn infected plants, the metabolite profile was dominated by monoterpenoids (28%), followed by carbonyl compounds (16%), methoxyphenols (12%), anisoles (12%), and sesquiterpenoids (8%) (Figure 2). Minor contributions were observed from fatty acids and conjugates (4%), fatty alcohols (4%), benzenediols (4%), alcohols and polyols (4%), styrenes (4%), and heteroaromatic compounds (4%). These classes corresponded to compounds such as (+)-limonene, \u0026alpha;-pinene, \u0026beta;-pinene, camphene, decanal, 2-furancarboxaldehyde, guaiacol, vanillin, \u0026gamma;-asarone, trans-isoasarone, \u0026beta;-caryophyllene, cis-vaccenic acid, 1-hexanol, and 4-hydroxystyrene (Table 2). In contrast, non-infected plants showed a markedly different distribution, with amino acids, peptides, and analogues accounting for 57% of total metabolites. Other classes included pyrrolidinylpyridines (5%), hydroxycinnamic acids and derivatives (5%), benzenes (5%), alpha-keto acids and derivatives (5%), phenylpyruvic acid derivatives (5%), dicarboxylic acids and derivatives (5%), carboxylic acids (5%), short-chain keto acids and derivatives (4%), and amines (4%). Representative compounds included \u0026beta;-alanine, glycine, L-tyrosine, phenylalanine, serine, L-valine, pyruvic acid, phenylpyruvic acid, fumaric acid, caffeic acid, benzene, acetoacetic acid, propionic acid, and cotinine. No amino acid or peptide derivatives were detected in infected plants, whereas volatile classes such as monoterpenoids, anisoles, styrenes, and heteroaromatic compounds were minimally represented in non-infected plants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparative metabolites enrichment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnrichment analysis showed a clear difference between infected and non-infected plants (Figure 3A). Infected plants showed higher enrichment of volatile metabolite classes, whereas non-infected plants were enriched in nitrogen-containing and organic acid derivatives. Heteroaromatic compounds showed the highest enrichment ratio in infected plants, followed by monoterpenoids and anisoles. The bubble plot (Figure 3B) showed higher \u0026ndash;log10(p-values) and larger bubble sizes for these classes, indicating stronger statistical significance and enrichment. In non-infected plants, alpha-keto acids and derivatives showed the highest enrichment ratio, while amino acids, peptides, and analogues exhibited the highest \u0026ndash;log10(p-values).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolic pathway impact assessment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePathway impact analysis revealed differences in metabolic pathway activation between infected and non-infected plants (Figure 4). Both conditions shared similar pathways; however, pathway impact and statistical significance were higher in infected plants. In infected plants, monoterpenoid biosynthesis (PWY-5073) showed the highest pathway impact and \u0026ndash;log10(p-value), followed by lipoxygenase-mediated fatty-acid volatile biosynthesis (PWY-5139), methoxy-phenylpropanoid biosynthesis (PWY-5973), and sesquiterpenoid biosynthesis (PWY-7209). Lower pathway impact values were observed for general phenylpropanoid biosynthesis (PWY-5010), eugenol biosynthesis (PWY-5021), and vanillin biosynthesis (PWY-5387). In non-infected plants, the same pathways were present but showed lower pathway impact and lower \u0026ndash;log10(p-values). Monoterpenoid biosynthesis remained the highest-impact pathway, followed by lipoxygenase-mediated fatty-acid volatile biosynthesis, methoxy-phenylpropanoid biosynthesis, and sesquiterpenoid biosynthesis. General phenylpropanoid, eugenol, and vanillin biosynthesis pathways were also detected with lower impact values.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eSpatial gradient of mite infestation and density-dependent leaf damage in\u003c/b\u003e \u003cb\u003eAcorus calamus\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMite distribution showed a pronounced spatial gradient, with higher colonization and damage localized to basal leaves, indicating preferential feeding on older tissues. This pattern is consistent with the feeding ecology of \u003cem\u003eTetranychus urticae\u003c/em\u003e, which preferentially exploits mature leaves characterized by reduced defensive capacity, increased cellular permeability, and enhanced nutrient leakage (Sarr et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The substantially greater mite density and associated damage observed in basal leaves therefore reflect a susceptibility gradient within the plant canopy (Diaz-Marquina et al., 2019). The strong correspondence between mite density and foliar damage further suggests a density-dependent escalation of physiological injury. Elevated infestation levels are known to disrupt chloroplast integrity, induce oxidative stress, and accelerate chlorosis and necrosis, thereby amplifying tissue degradation (Sethi et al., 2022). Similar density\u0026ndash;damage relationships have been reported across host systems, including \u003cem\u003eLycopersicon esculentum\u003c/em\u003e and medicinal plant species, where increasing herbivore pressure proportionally intensifies structural and biochemical impairment (Santamar\u0026iacute;a et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, the complete absence of mites and damage in non-infected plants confirms that the observed physiological disruption is directly attributable to herbivory rather than background environmental variation (Marques-Batista et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These findings indicate that spatial heterogeneity in leaf age and defense status governs mite colonization patterns, while infestation intensity acts as a key determinant of damage severity in \u003cem\u003eAcorus calamus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInfestation-induced changes of volatile metabolome in\u003c/b\u003e \u003cb\u003eAcorus calamus\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGC\u0026ndash;MS profiling revealed a pronounced reconfiguration of the volatile metabolome in response to infestation, characterized by both qualitative emergence of stress-related compounds and quantitative amplification of key defense-associated metabolites. The marked accumulation of phenylpropanoid derivatives, particularly β-asarone and α-asarone, indicates strong activation of secondary metabolic pathways under herbivore pressure. These compounds are well recognized as bioactive constituents of \u003cem\u003eA. calamus\u003c/em\u003e, and their elevated abundance suggests an induced chemical defense response, consistent with herbivory-driven upregulation of phenylpropanoid biosynthesis (War et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Alongside the enhanced levels of monoterpenes, including α-pinene, β-pinene, camphene, and 3-carene, further support the activation of volatile-mediated defense signaling. Monoterpenoids are key components of herbivore-induced plant volatiles (HIPVs), functioning in direct toxicity, deterrence, and indirect defense via signaling cascades (Riedlmeier et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Erb \u0026amp; Reymond, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their increased abundance aligns with previous observations of \u003cem\u003eT. urticae\u003c/em\u003e-induced volatile emissions in aromatic plants, indicating that \u003cem\u003eA. calamus\u003c/em\u003e exhibits a comparable inducible defense strategy (Su et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Blaazer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe detection of compounds such as ocimene, phellandrene, hexanol, and nonanal in infected plants highlights the induction of stress-specific metabolic pathways. These volatiles are closely linked to jasmonate-mediated defense signaling and lipoxygenase-driven lipid peroxidation, processes commonly associated with herbivore-induced oxidative stress (Song et al., 2018; Sarde et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their presence suggests that infestation triggers membrane disruption and downstream volatile aldehyde formation, reinforcing the role of oxidative pathways in defense activation (Deng et al., 2021; Liang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, the higher abundance of β-myrcene and decanal in non-infected plants reflects a constitutive metabolic state, associated with basal volatile production and normal fatty acid turnover rather than stress-induced responses (Kundu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings reveal a clear metabolic shift from constitutive to inducible defense chemistry, where infestation drives the preferential synthesis of phenylpropanoids and terpenoids while restructuring the overall volatile profile of \u003cem\u003eA. calamus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHerbivory-mediated metabolic reallocation from primary to volatile secondary pathways in\u003c/b\u003e \u003cb\u003eAcorus calamus\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMetabolite classification revealed a clear shift in metabolic organization under infestation, characterized by the predominance of volatile secondary metabolites in infected plants and nitrogen-rich primary metabolites in non-infected plants. The dominance of monoterpenoids, phenolic derivatives, and related volatile classes in infected tissues indicates a coordinated activation of secondary metabolic pathways associated with plant defense (Erb \u0026amp; Reymond, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These compounds are widely recognized as key components of herbivore-induced plant volatiles, contributing to direct toxicity, deterrence, and signaling functions during arthropod attack (Song et al., 2018; Guo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, the metabolite profile of non-infected plants was largely dominated by amino acids, organic acids, and related nitrogen-containing compounds, reflecting an active primary metabolism linked to growth, protein synthesis, and energy turnover (Kundu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This metabolic configuration is typical of unstressed plants, where resources are preferentially allocated toward biomass accumulation and physiological maintenance (Fiallo-Oliv\u0026eacute; et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The complete absence of amino acid\u0026ndash;related metabolites in infected plants suggests a strong suppression of primary nitrogen metabolism, likely driven by resource reallocation toward defense-associated pathways (Kundu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Such metabolic trade-offs are a well-established feature of plant responses to herbivory, where carbon and nitrogen skeletons are diverted from growth processes toward the biosynthesis of phenylpropanoids and terpenoids (Sethi et al., 2022). This reprogramming reflects a strategic shift from constitutive metabolism to inducible defense, prioritizing survival over growth under biotic stress (Schwachtje \u0026amp; Baldwin, 2020). Additionally, the near absence of monoterpenoids, anisoles, and heteroaromatic volatiles in non-infected plants reinforces their inducible nature. These metabolite classes are typically synthesized in response to herbivore attack and remain at low baseline levels under non-stress conditions, consistent with the dynamics of HIPV production (Bui et al., 2018; Dicke \u0026amp; Lucas, 2020). The observed metabolic divergence highlights a tightly regulated defense strategy in \u003cem\u003eA. calamus\u003c/em\u003e, where infestation triggers a systemic reallocation of metabolic flux toward volatile secondary pathways while downregulating primary metabolic processes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHerbivory-driven metabolic reprogramming and pathway activation in\u003c/b\u003e \u003cb\u003eAcorus calamus\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMetabolite enrichment and pathway analyses revealed a clear reorganization of plant metabolism under mite infestation, characterized by the preferential activation of volatile secondary metabolites and suppression of primary metabolic processes. Infected plants showed strong enrichment of heteroaromatic compounds, monoterpenoids, and anisoles, which also exhibited higher statistical significance and enrichment strength. These metabolite classes are widely associated with herbivore-induced plant volatiles and are known to play roles in direct defense, deterrence, and inter-plant signaling during biotic stress (Erb \u0026amp; Reymond, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Guo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The high enrichment of heteroaromatic and carbonyl compounds further suggests activation of oxidative lipid degradation pathways. Such compounds are commonly produced through membrane lipid peroxidation and are considered biochemical markers of herbivore-induced oxidative stress (Deng et al., 2021). This indicates that mite feeding may disrupt cellular membranes, triggering lipid-derived volatile production and reinforcing defense signaling (Liang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, non-infected plants were enriched in nitrogen-containing metabolites, particularly amino acids and alpha-keto acids, which showed the highest statistical significance. This metabolic profile reflects a growth-oriented physiological state, where primary metabolism supports protein synthesis, energy production, and development (Fiallo-Oliv\u0026eacute; et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The absence of enrichment of volatile secondary metabolites in these plants further indicates the lack of stress-induced metabolic activation (Kundu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Pathway impact analysis provided additional insight into the underlying biochemical mechanisms. Monoterpenoid biosynthesis (PWY-5073) emerged as the most significantly impacted pathway in infected plants, followed by lipoxygenase-mediated fatty-acid volatile biosynthesis (PWY-5139), methoxy-phenylpropanoid biosynthesis (PWY-5973), and sesquiterpenoid biosynthesis (PWY-7209). The activation of these pathways is consistent with herbivore-induced metabolic reprogramming, where terpenoid and phenylpropanoid pathways are upregulated to produce defense-related compounds (Dudareva et al., 2013; Wasternack \u0026amp; Feussner, 2018). The strong impact of the lipoxygenase pathway further highlights the role of oxylipin-mediated signaling and oxidative stress responses during infestation. Lipoxygenase-derived metabolites are known to regulate jasmonate signaling pathways and contribute to defense responses against herbivores (Deng et al., 2021; Liang et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, enhanced phenylpropanoid and sesquiterpenoid biosynthesis aligns with previous studies demonstrating their involvement in chemical defense and stress adaptation in medicinal plants (Marques-Batista et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Goura et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In contrast, although similar pathways were present in non-infected plants, their lower pathway impact and reduced statistical significance indicate basal metabolic activity without active defense induction (Su et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This supports the concept that plants maintain constitutive levels of secondary metabolism, which are rapidly upregulated upon herbivore attack (Guo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These findings revealed a coordinated metabolic shift in \u003cem\u003eA. calamus\u003c/em\u003e, where infestation induces a transition from primary metabolism toward volatile secondary metabolism. This reprogramming enhances the production of terpenoids, phenylpropanoids, and lipid-derived volatiles, reflecting a dynamic and tightly regulated biochemical defense strategy against herbivore stress.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides the metabolomic comparison of plant from spider mite\u0026ndash;infested and non-infested \u003cem\u003eA. calamus\u003c/em\u003e plants. The study reveals significant biochemical changes under herbivore stress. Infested plants showed a significant change from non-infected, including monoterpenoid, methoxy-phenylpropanoid, sesquiterpenoid, and lipoxygenase-mediated fatty-acid biosynthesis. Elevated levels of β-asarone, α-asarone, α-pinene, β-pinene, 3-carene, and stress-related aldehydes showed induction of herbivore-induced volatile production. In contrast, non-infected plants were dominated by amino acids, organic acids, and other primary metabolites. These findings highlighted that \u003cem\u003eA. calamus\u003c/em\u003e possess a potential chemical composition against mite infestation. The study also provides a current understanding of belowground defence responses and provides a groundwork for future research on stress signaling and metabolomic resilience in medicinal plants.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding information is not available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePN: Writing\u0026mdash;original draft, Visualization, Validation, Methodology, Investigation, Data curation, and Conceptualization. VLT: Writing\u0026mdash;review and editing, Formal analysis, Supervision, Resources, Project administration, ML \u0026amp; MCN: Writing\u0026mdash;review and editing, Supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAli M, Muhammad A, Lin Z, He H, Zhang Y (2025) Exploring Lamiaceae-derived bioactive compounds as nature\u0026rsquo;s arsenal for sustainable pest management. Phytochem Rev 24:1989\u0026ndash;2013\u003c/li\u003e\n \u003cli\u003eBergman ME, Huang XQ, Baudino S, Caissard JC, Dudareva N (2025) Plant volatile organic compounds: emission and perception in a changing world. Curr Opin Plant Biol 85:102706\u003c/li\u003e\n \u003cli\u003eBlaazer CJH, Villacis-Perez EA, Chafi R, Van Leeuwen T, Kant MR, Schimmel BC (2018) Why do herbivorous mites suppress plant defenses? 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Plant Cell Rep 40:1213\u0026ndash;1230\u003c/li\u003e\n \u003cli\u003eSong GC, Ryu CM (2018) The LOX pathway and jasmonate-dependent volatile production in herbivore defense. Plant Physiol 178:1640\u0026ndash;1653\u003c/li\u003e\n \u003cli\u003eSong GC, Ryu CM (2018) The LOX pathway and jasmonate-dependent volatile production in herbivore defense. Plant Physiol 178:1640\u0026ndash;1653\u003c/li\u003e\n \u003cli\u003eSteinbrenner AD, G\u0026oacute;mez S, Osorio S, Fernie AR, Orians CM (2011) Herbivore-induced changes in tomato (Solanum lycopersicum) primary metabolism: a whole plant perspective. J Chem Ecol 37:1294\u0026ndash;1303\u003c/li\u003e\n \u003cli\u003eSu Q, Wang R, Ding X et al (2022) Tetranychus urticae triggers HIPV production in aromatic plants. Pest Manag Sci 78:1102\u0026ndash;1114\u003c/li\u003e\n \u003cli\u003eWar AR, Paulraj MG, Ahmad T, Buhroo AA, Hussain B, Ignacimuthu S, Sharma HC (2020) Mechanisms of plant defense against insect herbivores. Plant Signal Behav 15:1784025\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1- Mite density and damage severity in \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eleaf position sampled\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean mite density (Mites/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeaf area damaged (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDamage severity score (0-5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 42px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 96px;\"\u003e\n \u003cp\u003eInfected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 92px;\"\u003e\n \u003cp\u003eBasal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 145px;\"\u003e\n \u003cp\u003e25.64\u0026plusmn;2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 98px;\"\u003e\n \u003cp\u003e36.55\u0026plusmn;2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 133px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 42px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 96px;\"\u003e\n \u003cp\u003eInfected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 92px;\"\u003e\n \u003cp\u003eApical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 145px;\"\u003e\n \u003cp\u003e5.86\u0026plusmn;1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 98px;\"\u003e\n \u003cp\u003e12.85\u0026plusmn;2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 133px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 42px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 96px;\"\u003e\n \u003cp\u003eNon-infected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 92px;\"\u003e\n \u003cp\u003eBasal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 96px;\"\u003e\n \u003cp\u003eNon-infected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 92px;\"\u003e\n \u003cp\u003eApical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2- GC-MS -profile of volatile metabolites in \u003cem\u003eAcorus calamus\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"587\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS. No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRT (min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompound name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfected (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-infected (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026alpha; - Pinene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e3.05\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2.11\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eGuaiacol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.47\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.26\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e4-vinylphenol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.88\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.65\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eEugenol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.39\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.24\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eVanillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.73\u0026plusmn;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.42\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e2-Pentanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.54\u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.31\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026beta;-curcumene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.64\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.59\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e11.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eIsobutanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.45\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.27\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e12.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026beta; - pinene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.54\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e12.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e3-Carene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.69\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.49\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e14.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eCamphene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.47\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e16.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026beta;- Asarone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e33.55\u0026plusmn;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e18.98\u0026plusmn;1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e16.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eElemicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.22\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.13\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e16.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eCaryophyllene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e4.33\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e3.54\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e17.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eResorcinol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e17.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026alpha;- Asarone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e8.98\u0026plusmn;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e2.32\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eLimonene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.13\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e23.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026alpha;-phellandrene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.17\u0026plusmn;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026beta; - Myrcene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.28\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n 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style=\"width: 159px;\"\u003e\n \u003cp\u003e\u0026beta;-Copaene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.56\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.52\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e2-Pentylfuran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e1.58\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e1.35\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e25.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003e[Z]-Ocimene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e2.98\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e30.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eButylbenzene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.37\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e33.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eHexanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.16\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e35.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eNonanal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.22\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eFurfural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.43\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.34\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 86px;\"\u003e\n \u003cp\u003e42.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 159px;\"\u003e\n \u003cp\u003eDecanal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0.28\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 118px;\"\u003e\n \u003cp\u003e0.53\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-physiologiae-plantarum","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acpp","sideBox":"Learn more about [Acta Physiologiae Plantarum](http://link.springer.com/journal/11738)","snPcode":"11738","submissionUrl":"https://www.editorialmanager.com/acpp/default2.aspx","title":"Acta Physiologiae Plantarum","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Acorus calamus, Biosynthesis pathways, Tetranychus urticae, Monoterpenoids, Phenylpropanoids, sesquiterpenoids","lastPublishedDoi":"10.21203/rs.3.rs-9198391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9198391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eAcorus calamus\u003c/em\u003e L. is a medicinal wetland species whose leaves and rhizomes are rich in bioactive phenylpropanoids and terpenoids, yet its biochemical defence responses to herbivores remain poorly understood. This study investigated the impact of \u003cem\u003eTetranychus urticae\u003c/em\u003e infection on volatile metabolism of \u003cem\u003eA. calamus\u003c/em\u003e by infestation assessment, GC\u0026ndash;MS-based profiling, metabolite class enrichment, and pathway impact analysis. Infested plants grown hydroponically showed a strong downward-to-upward gradient in mite density, with basal leaves reaching 25.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76 mites cm⁻\u0026sup2; and 36.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.43% leaf area damage, whereas non-infected soil-grown plants had no detectable mites or damage. GC\u0026ndash;MS analysis identified 28 volatile metabolites across treatments. Infected plants were dominated by phenylpropanoids and monoterpenoids, with β-asarone (33.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52%), α-asarone (8.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12%), α-pinene, β-pinene, 3-carene, and camphene significantly increased, along with stress-associated volatiles such as [Z]-ocimene, nonanal, and α-phellandrene. Non-infected plants showed higher production of amino acids, organic acids, and other nitrogen-rich primary metabolites. Enrichment analysis revealed strong domination of monoterpenoids, anisoles, heteroaromatics, and carbonyls in infected plants, while amino acids and α-keto acids were enriched in non-infected plants. Pathway impact analysis further showed higher activation of monoterpenoid, methoxy-phenylpropanoid, sesquiterpenoid, and lipoxygenase-mediated fatty-acid volatile biosynthesis pathways in infected plants. These results indicate that \u003cem\u003eT. urticae\u003c/em\u003e infestation suppresses primary nitrogen metabolism and redirects rhizome biochemistry toward defense-oriented volatile pathways, providing new insight into belowground chemical defense strategies in \u003cem\u003eA. calamus.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Volatilome-mediated defence response in Acorus calamus under Tetranychus urticae infestation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 12:46:02","doi":"10.21203/rs.3.rs-9198391/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-04-16T13:14:38+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T09:46:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T05:14:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Physiologiae Plantarum","date":"2026-03-24T10:18:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-physiologiae-plantarum","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acpp","sideBox":"Learn more about [Acta Physiologiae Plantarum](http://link.springer.com/journal/11738)","snPcode":"11738","submissionUrl":"https://www.editorialmanager.com/acpp/default2.aspx","title":"Acta Physiologiae Plantarum","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8f5ddde6-d6a4-412b-8bbc-459d23e6a644","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T12:46:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 12:46:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9198391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9198391","identity":"rs-9198391","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}