Salicylic Acid-mediated Modulation of Biochemical Parameters in Aged Tomato Seeds

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Mohanty, C. Patra, S. Dash, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6906482/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigated the influence of salicylic acid (SA) priming on the physiological and biochemical attributes of aged tomato seeds (Solanum lycopersicum L., variety BT-10, Utkal Kumari). Seeds were subjected to priming with varying concentrations of SA (0 mM, 0.1 mM, 0.25 mM, 0.5 mM, 0.75 mM, and 1.0 mM) for 24 hours, followed by drying under controlled conditions. The experiment was conducted using a completely randomized design (CRD) with five trials and three replications per treatment. Key physiological parameters evaluated included germination percentage, seed vigour index (SVI), seedling length, speed of germination, and moisture content. Biochemical analyses focused on changes in electrical conductivity, dehydrogenase activity, superoxide dismutase (SOD), peroxidase (POD), catalase, alpha-amylase activity, and protein content. Results demonstrated that a moderate concentration of SA (0.5 mM) significantly improved both physiological and biochemical seed quality. Higher concentrations showed inhibitory effects. These findings highlight the potential of SA priming to support robust early growth in aged tomato seeds. Biological sciences/Biochemistry Biological sciences/Chemical biology Biological sciences/Physiology Salicylic acid Biochemical analyses Seed Vigour Index Modulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION One of the most significant widely grown horticultural crops, the tomato ( Solanum lycopersicum L .) is rated second globally in terms of production and consumption (Singh and Prajapati, 2018 ). According to FAOSTAT (FAOSTAT 2019 ), the world currently produces over 182.3 million tons of fresh tomato, with most of that output originating from nations that are primarily situated between temperate and subtropical zones. Based on IBGE's 2020 data, Brazil ranks among the top ten producers of tomato, with an annual production of 4.08 million tons. The tomato species is a tropical plant; yet environmental stress is still the key factor limiting tomato quality and potential yield (Ronga et al., 2020 ). According to George et al. (George et al. 2013 ), most tomato varieties are vulnerable to drought stress, particularly in the early stages of growth, which include seed germination and seedling growth. Crops are significantly affected by abiotic stresses restraining yield (Lalarukh et al., 2022 ). Major abiotic stresses include heat, drought, and salt stress, which reduce plant growth and ultimately affect harvest (Hussain et al., 2021). Among these, heat stress causes serious losses in crops like tomato by shortening the growth period, causing wilting, poor fruit set, and early maturity from May onwards in Punjab. Central Punjab, the study area, experiences scorching, semi-arid summers with temperatures above 40°C, often exceeding 45°C (Syed et al., 2021 ), worsening under climate change. There is a key role of salicylic acid in several plant physiological and biochemical processes, helpful for maintaining growth and yield (Arberg, 1981). Foliar application of salicylic acid in wheat increased chlorophyll contents (Hayat et al., 2005 ); chlorophyll content increment is a direct indication of increased photosynthesis in plants, as reported in the literature (Ghai et al., 2002; Fariduddin et al., 2003 ) in Brassica juncea and B. napus. In soybean and corn, foliar application improved transpiration, increased leaf area, and accelerated carbon assimilation (Khan et al., 2003 ). Exogenous salicylic acid application improved wheat yield by increasing plant height, leaf numbers, leaf area, stem diameter, and dry mass (Hussein et al., 2007 ). Reduced metabolism leads to lesser growth and yield (Ramagopal, 1987 ) but improves with SA (Shakirova, 2007 ). SA application also enhanced root systems (Sandoval-Yapiz, 2004 ; Gutierrez-Coronada et al., 1998), flowering and fruit set (Martin-Mex et al., 2005 ), increasing yield in tomato and cucumber (Larque-Saavedra & Martin-Mex, 2007 ). A phenolic molecule called salicylic acid (SA) controls how plants grow, develop, and react to both biotic and abiotic stressors (Raskin, 1992 ; Khan et al., 2012 , 2013 ; Miura and Tada, 2014 ). Under abiotic stress circumstances, salicylic acid can also have a major impact on plant water relations (Barkosky and Einhelling, 1993). In response to both biotic and abiotic stress, plants create proteins, and many of these proteins are triggered by phytohormones such as salicylic acid (Hoyos and Zhang, 2000 ) and ABA (Jin et al., 2000 ). SA protects plants against abiotic stresses by regulating key physiological processes in plants, including photosynthesis, nitrogen metabolism, proline metabolism, GA production, antioxidant defence system, and plant-water relations under stress (Khan et al., 2010 , 2012 a, b, c, 2013b, 2014; Nazar et al., 2011 ; Miura and Tada, 2014 ). SA enhances tolerance to metal, salinity, osmotic, drought, and heat stress. This study aims to explore the growth effects of SA priming on different doses of aged tomato seed. MATERIAL & METHODS One-year-old tomato seeds (BT 10) were gathered from AICRP on Vegetable Crops to conduct the experiment. Laboratory work was done at the Department of Seed Science & Technology, College of Agriculture, and Dr. G.V. Chalam Seed Testing Research Laboratory, OUAT, Bhubaneswar. Time span of experiment M0 10-month-old M1 11-month-old M2 12-month-old M3 13-month-old M4 14-month-old Number of Treatment Treatment Salicylic acid concentration T1 0.10 mM T2 0.25 mM T3 0.50 mM T4 0.75 mM T5 1.00 mM T6 Control Statistical analysis The experiment was planned under randomized complete block design WITH three replications Biochemical parameters: 1. Dehydrogenase: The seeds were positioned in a test tube after a 12-hour soaking period. Each tube was administered 20 ml of a 0.05% tetrazolium chloride solution prior to incubation for 4 hours at 32°C in darkness. After incubation, the sample was rinsed with distilled water, and surplus solution discarded. Then, 20 ml of methyl cellosolve was added and left for 9 hours with intermittent shaking. Colour intensity was evaluated at 470 nm. 2. EC: Eight grams of seeds were introduced into a 100 ml beaker containing 40 ml of distilled water and maintained at 27 °C for 12 hours. Conductivity was quantified in dS/m. 3. Alpha-amylase: The estimation of alpha-amylase activity using a citrate buffer with iodine-potassium iodide method is based on the principle that alpha-amylase breaks down starch, reducing blue-black complex intensity, thus allowing estimation of enzyme activity through colour change and compare with alpha amylase standard graph ( Graph 1 ) Graph 1: Alpha amylase standard graph 4. SOD: A seed sample weighing about 1.0 g was macerated in 2 ml of 50 M potassium phosphate buffer at pH 7.8. The homogenate was centrifuged at 10,000 rpm for 10 minutes at 4 °C in a refrigerated centrifuge. Each of the two test tubes (one for dark and one for light) included 0.1 ml of supernatant, 1.5 ml of potassium phosphate buffer, 0.2 ml of methionine, 0.1 ml of EDTA, 0.1 ml of NBT, 0.1 ml of riboflavin, and 0.9 ml of water. NBT was used without a sample to establish a blank, whereas another blank was prepared without NBT and the sample. Test tubes were exposed to a 400 W bulb for 15 minutes. The activity was identified by suppression of the riboflavin-NBT interaction in presence of methionine. Measurement was made at 560 nm and recorded. Enzyme activity was quantified as U/mg of protein. 5. POD: A seed sample weighing about 1.0 g was macerated in 2 ml of 50 M sodium phosphate buffer using a pestle and mortar. The homogenate was centrifuged at 10,000 rpm for 10 minutes at 4 °C in a refrigerated centrifuge. 0.1 ml of supernatant, 1.5 ml of sodium phosphate buffer, 0.1 ml of guaiacol, 0.9 ml of water, and 0.5 ml of hydrogen peroxide were added to two test tubes immediately before measurement. A reference was established using guaiacol without a test sample and a blank devoid of guaiacol. Test tubes were exposed to a 400 W bulb for 15 minutes. Absorbance readings were taken at 0, 1, 2, and 3 minutes, with peak absorbance at 470 nm. POD activity was quantified as U/ml. 6. Catalase: Grind the sample (0.1g) with 0.1M phosphate buffer, pH 7.0 in a prechilled mortar and pestle. Centrifuge at 15,000g for 30min at 4 degree C Utilize the supernatant as a source of enzymes. 7. Protein: The technique outlined by Lowry et al. (1951) was used to assess the protein content in seed samples. A 0.2 g seed sample was homogenized in 10 ml of TCA solution. After that, the sample was centrifuged at 5000 revolutions per minute for 10 minutes. The supernatant was removed. After adding 10 milliliters of 1N NaOH and thoroughly mixing, the mixture was centrifuged for ten more minutes at 10,000 rpm. Protein quantitation was done using the supernatant. 0.2 ml of 1N NaOH was added after pipetting standard solutions of 0, 0.2, 0.4, 0.6, 0.8, and 1.0 ml into each test tube. Two additional test tubes were pipetted with 0.1 and 0.2 milliliters of the sample extract, respectively, and filled with one milliliter of water. A blank is a tube filled with one milliliter of water. After mixing, 5 ml of Reagent C and then 0.5 ml of Reagent D were added. Measurement was taken at 660 nm and protein expressed as mg/g or % and compare with protein standard graph ( Graph 2 ) Statistical Analysis: The replicated data with respect to different seed quality parameters were subjected to analysis by Microsoft Excel and Grapes software. RESULT AND DISCUSSION Biochemical analysis: 1. Dehydrogenase: The graph 3 shows the activity of dehydrogenase enzyme amongst 6 treatments at two distinct phases, M0 and M4. Presence of this enzyme indicates the viability and liveliness of the embryo inside the seed. Across all treatments, dehydrogenase activity was higher at M0 than at M4, indicating a general decline in microbial enzymatic activity over time. Treatment T3 exhibited the highest dehydrogenase activity at both time points, with values approaching 1.8 units at M0 and maintaining similar levels at M4. This consistent performance suggests superior metabolic activity under T3 conditions. In contrast, T5 and T6 showed the lowest dehydrogenase activity, particularly at M4, where values dropped below 1.0 unit. Polynomial trend lines fitted for both M0 and M4 data sets further confirm a peak at T3 and a gradual decline towards T5, with a minor recovery observed in T6 at M0 but not sustained at M4. Error bars indicate standard error, and despite some overlap, trends show a distinct decline from T3 onwards. 2. EC: It is an indicator of membrane integrity and solute leakage from internal tissue of seed. EC value ( Graph 4 ) was higher at M4 than M0 consistently, which shows high solute leakage with reduced membrane stability over time. A very promising increase was observed in T1 and T3, where EC values exceeded 0.9 at M4, signifying cellular deterioration. At T2 and T3, the EC value was lower at both M0 and M4, showing better maintenance of membrane integrity. The polynomial trend line for M4 reveals a U-shaped distribution with the lowest values at T3 and a rise subsequently at T5. The linear trend line for M0 showed a relatively stable pattern, with minor fluctuations. Large error bars at M4 indicate variability, suggesting higher leakage in some replicates. Overall, treatments T2 and T3 preserved membrane integrity best, while T1 and T5 showed greater degradation by the final observation point. 3. Alpha amylase Graph 5 illustrates the alpha amylase activity (expressed in arbitrary units) under different treatments (T1–T6) at the M4 stage, including both linear and polynomial trend lines to reflect data variation. Alpha amylase is essential to the germination of seeds by hydrolysing starch into sugars that are utilized during early growth stages. Among the treatments, T3 recorded the highest alpha amylase activity, exceeding 4500 units, followed by T2 with a value close to 3700 units. These treatments suggest enhanced enzymatic activation, potentially leading to improved germinative vigour. Conversely, treatments T1, T4, T5, and T6 exhibited comparatively lower enzyme activity, ranging between 3000 and 3300 units. The polynomial trend line demonstrates a clear peak at T3, highlighting its superior enzymatic profile, whereas the linear trend line indicates a slight overall decline across the treatments. Error bars represent standard error and show relatively low variability among replicates within each treatment, reinforcing the reliability of observed trends. These results underscore that treatment T3 was most effective in promoting alpha amylase activity, which could contribute to improved metabolic readiness during germination. The reduced enzymatic activity in other treatments suggests potential impairment or lesser stimulation of the germinative enzyme machinery under those conditions. Alpha amylase activity under six treatments (T1–T6) at initial (M0) and final (M4) stages with polynomial trend lines. 4. Protein Protein content was assessed across six time points (T1–T6) for two treatments: M0 (control) and M4 (treatment group). As shown in Figure 6, both groups demonstrated distinct trends in protein concentration over time. At T1, protein content was higher in the M0 group (2.9 ± 0.2) compared to the M4 group (2.1 ± 0.2). This trend reversed slightly at T2, where M4 exhibited a modest increase (2.8 ± 0.3) compared to M0 (2.6 ± 0.3). Peak protein concentrations were observed at T3 for both treatments, with M0 reaching 4.3 ± 0.2 and M4 reaching 3.8 ± 0.3. This peak was followed by a gradual decline in both groups. At T4 and T5, protein levels decreased, with M4 maintaining a slightly higher concentration at T4 (3.0 ± 0.3) than M0 (2.9 ± 0.2), and both groups showing similar values at T5 (M0: 2.6 ± 0.2; M4: 2.4 ± 0.2). By T6, the M0 group again showed higher protein levels (3.2 ± 0.2) compared to M4 (1.6 ± 0.2). Polynomial trend lines elucidated that pronounced fluctuation in M0 for one time increase towards the peak and secondary rise at T6. In contrast, the M4 group followed a smoother unimodal curve with a clear decline after T3. This exhibits temporal modulation of protein content. 5. SOD: SOD activity was evaluated across 6 time points (T1–T6) under two different groups, i.e., M0 and M4. It resulted in remarkable differential changes amongst the treatments. At T1, both groups showed comparable levels of SOD activity, with M0 at approximately 0.52 ± 0.02 and M4 slightly lower at 0.48 ± 0.02. Activity increased in both groups at T2 and peaked at T3. The M0 group exhibited the highest SOD ( Graph 7 ) activity at T3 (approximately 0.79 ± 0.03), surpassing the M4 group (0.66 ± 0.03). This trend of higher SOD activity in M0 compared to M4 persisted through T4 (M0: ~0.65 ± 0.03; M4: ~0.57 ± 0.02). A marked reduction in SOD activity was observed in both treatments at T5, with M4 showing a sharper decline (0.31 ± 0.03) compared to M0 (0.42 ± 0.03). By T6, activity increased slightly in both groups, though M0 maintained higher levels (0.50 ± 0.02) than M4 (0.45 ± 0.02). Polynomial trendlines revealed that the M0 group followed a more pronounced bimodal curve with a distinct peak at T3 and a secondary increase at T6. In contrast, the M4 group displayed a smoother, less variable trend with a single, modest peak and gradual fluctuations. These observations suggest that M0 may induce a more robust antioxidant response, whereas M4 treatment modulates SOD activity more conservatively across the measured time points. 6. POD: Peroxidase activity ( Graph 8 ) was monitored at 6 points under M0 and M4 conditions. It is depicted that the M0 group exhibited higher activity across all time points. At T1, peroxidase activity in the M0 group was approximately 0.056 ± 0.004, significantly higher than the M4 group, which recorded an activity of 0.030 ± 0.003. This pattern continued through T2 and T3, where M0 activity remained relatively stable (T2: 0.060 ± 0.005; T3: 0.062 ± 0.005), while M4 showed a slight increase (T2: 0.035 ± 0.003; T3: 0.041 ± 0.004). A decline in peroxidase activity occurred in both treatments at T4, though the drop was more pronounced in M4 (0.036 ± 0.003) compared to M0 (0.049 ± 0.004). The lowest levels were observed at T5, with M4 at 0.013 ± 0.002 and M0 at 0.020 ± 0.003. A recovery was noted at T6 for both, especially in M0 (0.048 ± 0.004), while M4 modestly rose to 0.018 ± 0.003. The polynomial trend shows a performance curve with a peak at T3 and a secondary increase at T6 in M0. On the other hand, M4 reveals a single peak. This shows a more robust antioxidant response in M0, whereas M4 moderates POD activity with a conservative peak across time points. 7. Catalase: Catalase action ( Graph 9 ) was quantified at six time points (T1–T6) under two conditions: M0 (control) and M4 (treated). The results, shown in Figure 5, reveal significant temporal variation and treatment-dependent differences in catalase activity. At T1, catalase activity in the M0 group was markedly higher (24 ± 3) than in M4 (15 ± 2). Activity in both groups increased sharply at T2, with M4 reaching 30 ± 3 and M0 peaking at 33 ± 3. This upward trend continued to a maximum at T3, where M4 reached 41 ± 3 and M0 peaked slightly higher at 43 ± 3. Following T3, catalase activity declined sharply in both treatments. At T4, M4 dropped to 16 ± 2 while M0 was moderately higher at 24 ± 3. At T5, levels remained relatively low and comparable (M4: 19 ± 2; M0: 18 ± 2), but both groups exhibited a slight increase by T6 (M4: 21 ± 2; M0: 23 ± 2). Polynomial trendlines highlight the dynamic nature of catalase activity. M4 followed a pronounced unimodal curve with a sharp rise to T3 and a steep decline, thereafter, followed by a mild secondary rise. In contrast, M0 showed a more moderate and sustained elevation through T3, followed by a gradual decline and stabilization toward T6. Overall, M0 consistently exhibited higher catalase activity than M4 at nearly all time points, suggesting a more sustained antioxidant response in the control condition in contrast to the treated group. Correlation Analysis Among Biochemical and Morphophysiological Parameters Correlation Analysis of Biochemical and Physiological Parameters under Salicylic Acid : To elucidate the interrelationships among physiological and biochemical responses under salicylic acid (SA) treatments, a Pearson's correlation matrix was constructed ( Figure 1 ). Notably, strong positive correlations (r > 0.90, p < 0.001) were observed among antioxidative enzyme activities, including M0-AM and M0-CAT (r = 0.95), M0-AM and M4-POD (r = 0.94), and M0-SOD with both M0-AM (r = 0.99) and M0-CAT (r = 0.97), suggesting a coordinated upregulation of the antioxidant defence system. Furthermore, germination-associated parameters such as M4-AM, M0-DHY, and M4-DHY exhibited significant positive correlations with these enzymatic markers (r = 0.83–0.97, p < 0.01), indicating a functional linkage between antioxidative capacity and early seedling vigour. In contrast, electrical conductivity (EC), an indicator of membrane damage and electrolyte leakage, showed strong negative correlations with enzymatic activities, including M0-SOD (r = –0.89), M0-AM (r = –0.89), and M0-CAT (r = –0.85), all statistically significant ( p < 0.05 to p < 0.001). These findings reinforce the role of protection of SA-induced antioxidant enzymes in maintaining membrane integrity under stress conditions. Together, the data underscore a tightly coordinated network between antioxidative responses and physiological performance, highlighting the efficacy of salicylic acid in modulating stress resilience during tomato seed germination and early seedling development. Pearson’s Correlation Analysis of Physiological and Biochemical Responses to Salicylic Acid Integrated Correlation Analysis of Biochemical and Physiological Parameters Under Salicylic Acid Influence: A comprehensive correlation matrix with pie-chart representation ( Figure 2 ) was employed to examine the interrelationships among physiological and biochemical traits under control (M0) and salicylic acid-treated (M4) conditions. The dual representation—colour gradients and pie segment proportions—visually underscores both the direction and strength of Pearson’s correlation coefficients. Antioxidative enzymes, including Superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), demonstrated robust positive correlations with growth-associated parameters (e.g., M0-AM, M4-AM, M0-DHY, M4-DHY), with correlation coefficients exceeding 0.85 across multiple comparisons. These findings indicate a synchronized activation of enzymatic antioxidants contributing to improved metabolic activity and seedling development. Conversely, electrical conductivity (EC)—an indicator of membrane damage—was strongly negatively correlated with all biochemical and physiological parameters evaluated. M4-EC and M0-EC displayed marked inverse relationships with M0-SOD (r ≈ –0.95), M0-AM (r ≈ –0.90), and M4-DHY (r ≈ –0.88), visualized clearly through large red segments in the pie charts and dark red colour coding. These patterns reinforce the role of SA-induced oxidative defence in maintaining cellular integrity under stress. The dense clustering of strong correlations among antioxidant enzymes and metabolic indicators under both M0 and M4 conditions points to a highly integrated stress-response network. The amplification of these interactions under M4 treatments suggests that salicylic acid enhances system-wide resilience through upregulation of antioxidative and metabolic pathways. This correlation structure provides compelling evidence for the systemic role of salicylic acid in enhancing seedling vigour by modulating redox balance and physiological functionality under abiotic stress conditions. Principal Component Analysis Reveals Distinct Clustering and Variable Contributions Under Salicylic Acid Treatment: Principal component analysis (PCA) was carried out to investigate the multivariate relationships among physiological and biochemical parameters under control (M0) and salicylic acid-treated (M4) conditions. The first two principal components (PC1 and PC2) accounted for 90.58% of the total variance, with PC1 explaining a dominant 82.69%, indicating strong data structuring along this axis. The biplot ( Figure 3 ) illustrates a clear separation between variables associated with salicylic acid treatment (M4) and the control (M0), particularly along PC1. Traits such as M4-CAT, M4-AM, and M4-PC, which lie positively along PC1 and PC2, are closely grouped, indicating a synergistic enhancement of enzymatic activity and metabolic performance in response to salicylic acid. Conversely, EC under both M0 and M4 conditions is oriented negatively along PC1, reinforcing its inverse association with the beneficial physiological traits and its role as a stress indicator. The strong vector magnitudes of antioxidative enzymes (SOD, CAT, POD) under M4, in addition to close alignment of M4-DHY and M4-AM, signify a coordinated upregulation of both protective enzymatic defences and growth-associated parameters under SA application. Notably, the proximity of M4-DHY and M4-PC to M4-AM suggests that membrane stability and osmolyte accumulation contribute significantly to metabolic improvement during early seedling development. These findings highlight that salicylic acid induces a tightly integrated physiological response, predominantly captured by PC1, promoting antioxidant defence and osmotic balance, while downregulating damage-related indicators such as electrical conductivity. The PCA thus affirms the pivotal role of SA in modulating multiple interdependent pathways to enhance seedling resilience. Comprehensive Correlation Analysis Reveals Strong Positive Associations Among Growth and Germination Traits Across Salicylic Acid Treatments: A correlation matrix was constructed to explore the interrelationships among key seedling growth and germination parameters across different salicylic acid concentrations (M0–M4). The matrix ( Figure 4 ) reveals a highly coordinated pattern of positive correlations among all assessed traits, as indicated by the dense clustering of dark green cells. Specifically, parameters such as root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigour index I (SVGI), and seedling vigour index II (SVGII) exhibited consistently strong positive correlations (r > 0.85) with each other under all treatment levels. This reflects a tightly coupled physiological response, whereby enhancement in one trait (e.g., RL) is strongly predictive of improvements in others (e.g., GP and SVG). The strength of these correlations was especially pronounced under the M4 treatment, suggesting that higher concentrations of salicylic acid amplify the synchrony among early seedling growth traits. Notably, both SVG-I and SVG-II exhibited the highest degree of correlation with all other parameters, underscoring their robustness as composite indicators of seedling performance. Conversely, no significant negative correlations were observed, and minimal variability in correlation coefficients across treatments implies that salicylic acid promotes a harmonized and stable enhancement of germinative and developmental traits. This integrated trait coordination highlights the systemic regulatory effect of salicylic acid, promoting seedling vigour through concurrent modulation of multiple morpho-physiological processes. Extensive Trait Interconnectivity Evidenced by Uniformly Strong Positive Correlations Across Salicylic Acid Treatments: The correlation matrix (Figure 5) elucidates the intricate relationships among a wide array of germination and seedling growth parameters under varying concentrations of salicylic acid. The visualization, incorporating both colour intensity and pie chart representations, reveals an overwhelmingly positive and tightly clustered correlation structure, with coefficients predominantly approaching unity (r > 0.9). Key indicators such as root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigour index I (SVGI), and seedling vigour index II (SVGII) demonstrated robust interrelationships across all salicylic acid levels (M0 to M4). The dark blue shades in matrix & dark segments in pie chart indicate a consistent strong positiveness amongst all variable pairs. Remarkably, the uniform correlation amongst treatments showed that it promotes coordinated expression as well as increases the individual physiological traits. This exhibits that early seedling improvement does not occur in isolation but is a synchronized development. The intensity results in multiple roles of SA in improving germination and seedling vigour by affecting cell expansion, oxidative balance, and metabolic efficiency. The result shows the power of composite indices like SVI & SVII, which act as central integrators for this seedling performance matrix. Notably, this matrix envisages that the application of SA results in fostering physiological responses like growth, biomass accumulation, and vigour indicators, which may lead to increased crop establishment. Principal Component Analysis Reveals Salicylic Acid-Induced Differentiation in Seedling Performance and Trait Interdependence: This PCA biplot ( Figure 6 ) shows the response of SA application on variable traits visualisation as well as clustering of specific treatments. It explains the cumulative effect of both PC1 & PC2 with a total variance of 93.39%, PC1 is having 87.31% which indicates the variation of seedling traits is due to single factor predominantly. Trait vectors representing root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigor indices I and II (SVGI and SVGII), and other biometric parameters are densely clustered and aligned in a common direction, suggesting strong positive inter-correlations and shared underlying physiological mechanisms. This configuration highlights the coordinated enhancement of growth-related traits under salicylic acid treatment. Notably, treatments M3 and M4 (particularly M3_RL and M4_GP) are distinctly projected along the positive axis of PC1, indicating their superior influence on the most variance-explaining traits. This supports the conclusion that moderate to high concentrations of salicylic acid markedly boost early seedling vigour by synchronously enhancing growth and biomass allocation traits. Conversely, earlier treatments (e.g., M0, M1) and stress-related traits such as SOG (speed of germination) show greater dispersion or lesser contribution to the principal axis, further validating the dose-responsive efficiency of salicylic acid at optimized concentrations. This PCA ( Figure 7 ) reinforces that salicylic acid modulates multiple growth traits in a unified manner, with higher doses (M3 and M4) exerting a dominant influence on the multidimensional performance landscape of tomato seedlings. Abiotic stressors like heat, dryness, and salinity are lessened by exogenous plant growth regulators (PGRs), such as SA ( Finch-Savage et al., 2004). Priming increases crop production, seedling vigour, and germination, according to earlier research. Only 0.5 mM SA demonstrated notable advantages in seedling characteristics in this investigation, such as shortened mean germination time, biomass buildup, early and increased germination, emergence percentage, and seedling length. SA's function in boosting antioxidant activity and encouraging metabolite production is probably what causes these effects. Kumari et al. (Kumari et al. 2017) noted similar enhancements in maize with GA₃ and SA priming. Heydariyan et al. (Heydariyan et al. 2014) also reported improved germination and vigour in Capparis spinosa under SA treatment. Enhanced antioxidant activity (SOD, CAT, POD, APX) and reduced lipid peroxidation (MDA content) were noted throughout our investigation, in line with the results by Farooq et al. (Farooq et al. 2008) and Chang and Sung (Chang and Sung 1998). Yan (Yan 2015) similarly demonstrated improved germination and stress resilience in cabbage through priming. Ara et al. (Ara et al. 2013) showed that antioxidant enzyme levels were higher in heat-tolerant genotypes. Temperature significantly affects tomato seedling growth. Vollenweider and Georg (Vollenweider and Günthardt-Goerg, 2005) found that heat stress impairs shoot and root development, potentially due to water deficit. In our study, SA improved root development even under slightly elevated temperatures, possibly due to SA’s role in promoting cell division and elongation (Porter and Gawith, 1999; Hayat et al., 2010). The enhancement in photosynthetic performance may stem from SA-mediated protection of cell structures and membrane stability. SA may also reduce levels of membrane-degrading enzymes (Zang et al., 2003), enhancing photosynthesis, stomatal conductance, and water use efficiency. It is suggested that SA priming improves photosynthetic traits & yields under stress situation in mung bean (Kaur, 2017). The same situation also prevails in the crop quinoa (Yang et al., 2018). Singh & Singh (Singh et al., 2017) reported that SA priming is showing the best result in tomato seed production under heat stress condition. Rehman et al. (ur Rehman et al. 2015) concluded that SA priming helps in improving early development of maize under high temp. Ahmad et al. (Ahmad et al. 2021) observed that increase of antioxidant activity & membrane stability in a heat tolerant situation, S holds best. In this research we found that priming with 0.5 mM & 0.25 mM concentration dose helps in increase in root development and supporting seedling vigour. Conclusion This study demonstrates that seed priming with salicylic acid (SA), particularly at a concentration of 0.5 mM, significantly enhances germination percentage and seedling vigour in aged tomato seeds. The treatment not only improved the uniformity and speed of germination—key factors for optimizing subsequent plant growth and development—but also positively modulated the physiological and biochemical responses of the seeds. The results indicate that SA priming is an effective, economically feasible, and environmentally friendly strategy within resource-limited settings. By boosting metabolic efficiency and enhancing antioxidant and enzymatic activities, SA priming reduces the need for additional chemical inputs and increases the seeds’ innate resistance to abiotic stresses. In the context of sustainable agriculture, SA priming emerges as a promising pre-sowing treatment to mitigate stress and improve seed production. Further research is needed to clarify mechanisms and support broader agronomic application. Declarations Data availability Data utilized during the investigations is publicly available or can be shared on request to corresponding author. Author contributions Anupam Dalapati, Soubhagya Behera and S. Mohanty wrote main manuscript text. C. Patra, S. Dash, U.K. Behera, M.K. Rout, C.R. Sahoo, S.K. Swain, P. Behera, D. Sahoo and Swarnalata Das prepared all figures and built software for experimental pur­pose. Soubhagya Behera supervised the work and edited the manuscript. R. K. Rout, B.K. Mandal, S. K. Sahoo & Nishant K GR. gathered the results and improved the man­uscript. All authors reviewed the manuscript. Funding No funding and bear by authors Additional information Competing interests The authors declare no competing interests. Correspondence and requests for materials should be addressed to R. K. Rout and Soubhagya Behera. Reprints and permissions information is available at www.nature.com/reprints. References Singh, Y., & Prajapati, S. (2018). Status of horticultural crops: identifying the need for transgenic traits. In Genetic engineering of horticultural crops (pp. 1-21). Academic Press. Yan, M. (2015). Seed priming stimulate germination and early seedling growth of Chinese cabbage under drought stress. South African Journal of Botany , 99 , 88-92. Ahmad, M., Waraich, E. A., Zulfiqar, U., Ullah, A., & Farooq, M. (2021). Thiourea application improves heat tolerance in camelina (Camelina sativa L. Crantz) by modulating gas exchange, antioxidant defense and osmoprotection. Industrial Crops and Products , 170 , 113826. Ara, N., Nakkanong, K., Lv, W., Yang, J., Hu, Z., & Zhang, M. (2013). Antioxidant enzymatic activities and gene expression associated with heat tolerance in the stems and roots of two cucurbit species (“Cucurbita maxima” and “Cucurbita moschata”) and their interspecific inbred line “Maxchata”. International journal of molecular sciences , 14 (12), 24008-24028. Aberg, B. (1981). Plant growth regulators. XLI. Monosubstituted benzoic acids. Barkosky, R.R. and F.A. Einhellig (1993). Effects of salicylic acid on plant water relationships. J. Chem. Ecol., 19: 237-247 Chang, S. M., & Sung, J. M. (1998). Deteriorative changes in primed sweet corn seeds during storage. FAOSTAT (2019). Available at: http://www.fao.org/faostat/en/#home [Accessed April 15, 2019]. Fariduddin, Q., Hayat, S., & Ahmad, A. (2003). Salicylic acid influences net photosynthetic rate, carboxylation efficiency, nitrate reductase activity, and seed yield in Brassica juncea. Photosynthetica , 41 , 281-284. Farooq, M., Aziz, T., Basra, S. M. A., Cheema, M. A., & Rehman, H. (2008). Chilling tolerance in hybrid maize induced by seed priming with salicylic acid. Journal of Agronomy and Crop Science , 194 (2), 161-168. Finch-Savage, W. E., Dent, K. C., & Clark, L. J. (2004). Soak conditions and temperature following sowing influence the response of maize (Zea mays L.) seeds to on-farm priming (pre-sowing seed soak). Field Crops Research , 90 (2-3), 361-374. George, S., Jatoi, S. A., & Siddiqui, S. U. (2013). Genotypic differences against PEG simulated drought stress in tomato. Pak. J. Bot , 45 (5), 1551-1556. Singh, S. K., Singh, A. K., & Dwivedi, P. (2017). Modulating effect of salicylic acid in tomato plants in response to waterlogging stress. International Journal of Agriculture, Environment and Biotechnology , 10 (1), 31-37. Gutiérrez-Coronado, M. A., Trejo-López, C., & Larqué-Saavedra, A. (1998). 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Hussain, K., Lone, S., Mushtaq, F., Malik, A., Narayan, S., Rashid, M., & Nazir, G. (2022). Abiotic stresses and their management in vegetable crop production. In Advances in Plant Defense Mechanisms . IntechOpen. Hussein, M. M., Balbaa, L. K., & Gaballah, M. S. (2007). Salicylic acid and salinity effects on growth of maize plants. Research Journal of Agriculture and Biological Sciences , 3 (4), 321-328. Jin, S., Chen, C. C. S., & Plant, A. L. (2000). Regulation by ABA of osmotic‐stress‐induced changes in protein synthesis in tomato roots. Plant, Cell & Environment , 23 (1), 51-60. Kaur, G., & Asthir, B. (2017). Molecular responses to drought stress in plants. Biologia plantarum , 61 , 201-209. Khan, W., Prithiviraj, B., & Smith, D. L. (2003). Photosynthetic responses of corn and soybean to foliar application of salicylates. Journal of plant physiology , 160 (5), 485-492. Khan, N., Syeed, S., Masood, A., Nazar, R., & Iqbal, N. (2010). Application of salicylic acid increases contents of nutrients and antioxidative metabolism in mungbean and alleviates adverse effects of salinity stress. International Journal of Plant Biology , 1 (1), e1-e1. Khan, N. A., Nazar, R., Iqbal, N., & Anjum, N. A. (Eds.). (2012). Phytohormones and abiotic stress tolerance in plants . Springer Science & Business Media. Khan, M. I. R., Syeed, S., Nazar, R., & Anjum, N. A. (2012). An insight into the role of salicylic acid and jasmonic acid in salt stress tolerance. Phytohormones and abiotic stress tolerance in plants , 277-300. Khan, M. I. R., Iqbal, N., Masood, A., & Khan, N. A. (2012). Variation in salt tolerance of wheat cultivars: role of glycinebetaine and ethylene. Pedosphere , 22 (6), 746-754. Khan, M. I. R., Iqbal, N., Masood, A., Per, T. S., & Khan, N. A. (2013). Salicylic acid alleviates adverse effects of heat stress on photosynthesis through changes in proline production and ethylene formation. Plant Signaling & Behavior , 8 (11), e26374. Khan, M. I. R., Asgher, M., & Khan, N. A. (2014). Alleviation of salt-induced photosynthesis and growth inhibition by salicylic acid involves glycinebetaine and ethylene in mungbean (Vigna radiata L.). Plant Physiology and Biochemistry , 80 , 67-74. Kumari, N., Rai, P. K., Bara, B. M., Singh, I., & Rai, K. (2017). Effect of halo priming and hormonal priming on seed germination and seedling vigour in maize (Zea mays L.) seeds. Journal of Pharmacognosy and Phytochemistry , 6 (4), 27-30. Lalarukh, I., Al-Dhumri, S. A., Al-Ani, L. K. T., Hussain, R., Al Mutairi, K. A., Mansoora, N., ... & Galal, T. M. (2022). A combined use of rhizobacteria and moringa leaf extract mitigates the adverse effects of drought stress in wheat (Triticum aestivum L.). Frontiers in Microbiology , 13 , 813415. Larque-Saavedra, A., & Martin-Mex, R. (2007). Effects of salicylic acid on the bioproductivity of plants. Salicylic acid: a plant hormone , 15-23. Martin-Mex, R., Villanueva-Couoh, E., Herrera-Campos, T., & Larque-Saavedra, A. (2005). Positive effect of salicylates on the flowering of African violet. Scientia horticulturae , 103 (4), 499-502. Miura, K., & Tada, Y. (2014). Regulation of water, salinity, and cold stress responses by salicylic acid. Frontiers in plant science , 5 , 4. Navita Ghai, N. G., Setia, R. C., & Neelam Setia, N. S. (2002). Effects of paclobutrazol and salicylic acid on chlorophyll content, Hill activity and yield components in Brassica napus L.(CV GSL-1). Yang, A., Akhtar, S. S., Iqbal, S., Qi, Z., Alandia, G., Saddiq, M. S., & Jacobsen, S. E. (2018). Saponin seed priming improves salt tolerance in quinoa. Journal of Agronomy and Crop Science , 204 (1), 31-39. Nazar, R., Iqbal, N., Syeed, S., & Khan, N. A. (2011). Salicylic acid alleviates decreases in photosynthesis under salt stress by enhancing nitrogen and sulfur assimilation and antioxidant metabolism differentially in two mungbean cultivars. Journal of plant physiology , 168 (8), 807-815. Porter, J. R., & Gawith, M. (1999). Temperatures and the growth and development of wheat: a review. European journal of agronomy , 10 (1), 23-36. Ramagopal, S. (1987). Salinity stress induced tissue-specific proteins in barley seedlings. Plant Physiology , 84 (2), 324-331. Raskin, I. 1992. Role of salicylic acid in plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 43: 439–463. Ronga, D., Pentangelo, A., & Parisi, M. (2020). Optimizing N fertilization to improve yield, technological and nutritional quality of tomato grown in high fertility soil conditions. Plants , 9 (5), 575. Sandoval-Yapiz, M. R. (2004). Reguladores de crecimiento XXIII: efecto del acido salicilico en la biomasa del cempazuchitl (Tagetes erecta) (Doctoral dissertation, Tesis de Licenciatura. Instituto Tecnologico Agropecuario, Conkal, Yucatan, Mexico). Shakirova, F. M. (2007). Role of hormonal system in the manifestation of growth promoting and antistress action of salicylic acid. Salicylic acid: a plant hormone , 69-89. Syed, A., Liu, X., Moniruzzaman, M., Rousta, I., Syed, W., Zhang, J., & Olafsson, H. (2021). Assessment of climate variability among seasonal trends using in situ measurements: A case study of Punjab, Pakistan. Atmosphere , 12 (8), 939. Vollenweider, P., & Günthardt-Goerg, M. S. (2005). Diagnosis of abiotic and biotic stress factors using the visible symptoms in foliage. Environmental Pollution , 137 (3), 455-465. ur Rehman, H., Iqbal, H., Basra, S. M., Afzal, I., Farooq, M., Wakeel, A., & Wang, N. (2015). Seed priming improves early seedling vigor, growth and productivity of spring maize. Journal of Integrative Agriculture , 14 (9), 1745-1754. Zhang, Y., Chen, K., Zhang, S., & Ferguson, I. (2003). The role of salicylic acid in postharvest ripening of kiwifruit. Postharvest Biology and Technology , 28 (1), 67-74. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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08:56:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":270613,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation matrix\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6906482/v1/d2f115647340cfbd66df2399.png"},{"id":86316730,"identity":"c76d9d45-c23f-4904-ac3e-28e6fae2b14b","added_by":"auto","created_at":"2025-07-09 09:04:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":131869,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePCA biplot\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6906482/v1/ca42afab6d3e5afe6a9e1dd2.png"},{"id":86316165,"identity":"4d5555b9-aebf-4049-bf0b-514253e61131","added_by":"auto","created_at":"2025-07-09 08:56:13","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":68010,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePCA reinforces\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6906482/v1/a61fd4fb04ebb0e401baf96f.png"},{"id":92576128,"identity":"b6affb28-5683-4cbd-9667-a1e85f08ce7d","added_by":"auto","created_at":"2025-10-01 08:24:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1725801,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6906482/v1/1b0f1dca-a113-40bc-80a2-2fe9348e523a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSalicylic Acid-mediated Modulation of Biochemical Parameters in Aged Tomato Seeds\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eOne of the most significant widely grown horticultural crops, the tomato (\u003cem\u003eSolanum lycopersicum L\u003c/em\u003e.) is rated second globally in terms of production and consumption (Singh and Prajapati, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to FAOSTAT (FAOSTAT \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the world currently produces over 182.3\u0026nbsp;million tons of fresh tomato, with most of that output originating from nations that are primarily situated between temperate and subtropical zones. Based on IBGE's 2020 data, Brazil ranks among the top ten producers of tomato, with an annual production of 4.08\u0026nbsp;million tons. The tomato species is a tropical plant; yet environmental stress is still the key factor limiting tomato quality and potential yield (Ronga et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to George et al. (George et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), most tomato varieties are vulnerable to drought stress, particularly in the early stages of growth, which include seed germination and seedling growth.\u003c/p\u003e\u003cp\u003eCrops are significantly affected by abiotic stresses restraining yield (Lalarukh et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Major abiotic stresses include heat, drought, and salt stress, which reduce plant growth and ultimately affect harvest (Hussain et al., 2021). Among these, heat stress causes serious losses in crops like tomato by shortening the growth period, causing wilting, poor fruit set, and early maturity from May onwards in Punjab. Central Punjab, the study area, experiences scorching, semi-arid summers with temperatures above 40\u0026deg;C, often exceeding 45\u0026deg;C (Syed et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), worsening under climate change.\u003c/p\u003e\u003cp\u003eThere is a key role of salicylic acid in several plant physiological and biochemical processes, helpful for maintaining growth and yield (Arberg, 1981). Foliar application of salicylic acid in wheat increased chlorophyll contents (Hayat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2005\u003c/span\u003e); chlorophyll content increment is a direct indication of increased photosynthesis in plants, as reported in the literature (Ghai et al., 2002; Fariduddin et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) in Brassica juncea and B. napus. In soybean and corn, foliar application improved transpiration, increased leaf area, and accelerated carbon assimilation (Khan et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Exogenous salicylic acid application improved wheat yield by increasing plant height, leaf numbers, leaf area, stem diameter, and dry mass (Hussein et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Reduced metabolism leads to lesser growth and yield (Ramagopal, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) but improves with SA (Shakirova, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). SA application also enhanced root systems (Sandoval-Yapiz, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Gutierrez-Coronada et al., 1998), flowering and fruit set (Martin-Mex et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), increasing yield in tomato and cucumber (Larque-Saavedra \u0026amp; Martin-Mex, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA phenolic molecule called salicylic acid (SA) controls how plants grow, develop, and react to both biotic and abiotic stressors (Raskin, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Miura and Tada, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Under abiotic stress circumstances, salicylic acid can also have a major impact on plant water relations (Barkosky and Einhelling, 1993). In response to both biotic and abiotic stress, plants create proteins, and many of these proteins are triggered by phytohormones such as salicylic acid (Hoyos and Zhang, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and ABA (Jin et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). SA protects plants against abiotic stresses by regulating key physiological processes in plants, including photosynthesis, nitrogen metabolism, proline metabolism, GA production, antioxidant defence system, and plant-water relations under stress (Khan et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003ea, b, c, 2013b, 2014; Nazar et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Miura and Tada, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). SA enhances tolerance to metal, salinity, osmotic, drought, and heat stress. This study aims to explore the growth effects of SA priming on different doses of aged tomato seed.\u003c/p\u003e"},{"header":"MATERIAL \u0026 METHODS","content":"\u003cp\u003eOne-year-old tomato seeds (BT 10) were gathered from AICRP on Vegetable Crops to conduct the experiment. Laboratory work was done at the Department of Seed Science \u0026amp; Technology, College of Agriculture, and Dr. G.V. Chalam Seed Testing Research Laboratory, OUAT, Bhubaneswar.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime span of experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM0\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;10-month-old\u003c/p\u003e\n\u003cp\u003eM1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;11-month-old\u003c/p\u003e\n\u003cp\u003eM2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;12-month-old\u003c/p\u003e\n\u003cp\u003eM3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;13-month-old\u003c/p\u003e\n\u003cp\u003eM4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;14-month-old\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNumber of Treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Treatment\u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Salicylic acid concentration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eT1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.10 mM\u003c/p\u003e\n\u003cp\u003eT2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.25 mM\u003c/p\u003e\n\u003cp\u003eT3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.50 mM\u003c/p\u003e\n\u003cp\u003eT4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.75 mM\u003c/p\u003e\n\u003cp\u003eT5\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.00 mM\u003c/p\u003e\n\u003cp\u003eT6\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Control\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was planned under randomized complete block design WITH three replications\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical parameters:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. Dehydrogenase:\u003c/strong\u003e The seeds were positioned in a test tube after a 12-hour soaking period. Each tube was administered 20 ml of a 0.05% tetrazolium chloride solution prior to incubation for 4 hours at 32\u0026deg;C in darkness. After incubation, the sample was rinsed with distilled water, and surplus solution discarded. Then, 20 ml of methyl cellosolve was added and left for 9 hours with intermittent shaking. Colour intensity was evaluated at 470 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. EC:\u003c/strong\u003e Eight grams of seeds were introduced into a 100 ml beaker containing 40 ml of distilled water and maintained at 27 \u0026deg;C for 12 hours. Conductivity was quantified in dS/m.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Alpha-amylase:\u003c/strong\u003e The estimation of alpha-amylase activity using a citrate buffer with iodine-potassium iodide method is based on the principle that alpha-amylase breaks down starch, reducing blue-black complex intensity, thus allowing estimation of enzyme activity through colour change and compare with alpha amylase standard graph (\u003cstrong\u003eGraph 1\u003c/strong\u003e)\u003cbr\u003e\u003cstrong\u003eGraph 1:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAlpha amylase standard graph\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. SOD:\u003c/strong\u003e A seed sample weighing about 1.0 g was macerated in 2 ml of 50 M potassium phosphate buffer at pH 7.8. The homogenate was centrifuged at 10,000 rpm for 10 minutes at 4 \u0026deg;C in a refrigerated centrifuge. Each of the two test tubes (one for dark and one for light) included 0.1 ml of supernatant, 1.5 ml of potassium phosphate buffer, 0.2 ml of methionine, 0.1 ml of EDTA, 0.1 ml of NBT, 0.1 ml of riboflavin, and 0.9 ml of water. NBT was used without a sample to establish a blank, whereas another blank was prepared without NBT and the sample. Test tubes were exposed to a 400 W bulb for 15 minutes. The activity was identified by suppression of the riboflavin-NBT interaction in presence of methionine. Measurement was made at 560 nm and recorded. Enzyme activity was quantified as U/mg of protein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. POD:\u003c/strong\u003e A seed sample weighing about 1.0 g was macerated in 2 ml of 50 M sodium phosphate buffer using a pestle and mortar. The homogenate was centrifuged at 10,000 rpm for 10 minutes at 4 \u0026deg;C in a refrigerated centrifuge. 0.1 ml of supernatant, 1.5 ml of sodium phosphate buffer, 0.1 ml of guaiacol, 0.9 ml of water, and 0.5 ml of hydrogen peroxide were added to two test tubes immediately before measurement. A reference was established using guaiacol without a test sample and a blank devoid of guaiacol. Test tubes were exposed to a 400 W bulb for 15 minutes. Absorbance readings were taken at 0, 1, 2, and 3 minutes, with peak absorbance at 470 nm. POD activity was quantified as U/ml.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. Catalase:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eGrind the sample (0.1g) with 0.1M phosphate buffer, pH 7.0 in a prechilled mortar and pestle.\u003c/li\u003e\n \u003cli\u003eCentrifuge at 15,000g for 30min at 4 degree C\u003c/li\u003e\n \u003cli\u003eUtilize the supernatant as a source of enzymes.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e7. Protein:\u003c/strong\u003e The technique outlined by Lowry et al. (1951) was used to assess the protein content in seed samples. A 0.2 g seed sample was homogenized in 10 ml of TCA solution. After that, the sample was centrifuged at 5000 revolutions per minute for 10 minutes. The supernatant was removed. After adding 10 milliliters of 1N NaOH and thoroughly mixing, the mixture was centrifuged for ten more minutes at 10,000 rpm. Protein quantitation was done using the supernatant. 0.2 ml of 1N NaOH was added after pipetting standard solutions of 0, 0.2, 0.4, 0.6, 0.8, and 1.0 ml into each test tube. Two additional test tubes were pipetted with 0.1 and 0.2 milliliters of the sample extract, respectively, and filled with one milliliter of water. A blank is a tube filled with one milliliter of water. After mixing, 5 ml of Reagent C and then 0.5 ml of Reagent D were added. Measurement was taken at 660 nm and protein expressed as mg/g or % and compare with protein standard graph (\u003cstrong\u003eGraph 2\u003c/strong\u003e)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis:\u0026nbsp;\u003c/strong\u003eThe replicated data with respect to different seed quality parameters were subjected to analysis by Microsoft Excel and Grapes software.\u003c/p\u003e"},{"header":"RESULT AND DISCUSSION","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBiochemical analysis:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. \u0026nbsp; Dehydrogenase:\u003c/strong\u003e The graph 3 shows the activity of dehydrogenase enzyme amongst 6 treatments at two distinct phases, M0 and M4. Presence of this enzyme indicates the viability and liveliness of the embryo inside the seed. Across all treatments, dehydrogenase activity was higher at M0 than at M4, indicating a general decline in microbial enzymatic activity over time. Treatment T3 exhibited the highest dehydrogenase activity at both time points, with values approaching 1.8 units at M0 and maintaining similar levels at M4. This consistent performance suggests superior metabolic activity under T3 conditions. In contrast, T5 and T6 showed the lowest dehydrogenase activity, particularly at M4, where values dropped below 1.0 unit. Polynomial trend lines fitted for both M0 and M4 data sets further confirm a peak at T3 and a gradual decline towards T5, with a minor recovery observed in T6 at M0 but not sustained at M4. Error bars indicate standard error, and despite some overlap, trends show a distinct decline from T3 onwards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. \u0026nbsp;\u0026nbsp;\u003c/strong\u003eEC: It is an indicator of membrane integrity and solute leakage from internal tissue of seed. EC value (\u003cstrong\u003eGraph 4\u003c/strong\u003e) was higher at M4 than M0 consistently, which shows high solute leakage with reduced membrane stability over time. A very promising increase was observed in T1 and T3, where EC values exceeded 0.9 at M4, signifying cellular deterioration. At T2 and T3, the EC value was lower at both M0 and M4, showing better maintenance of membrane integrity. The polynomial trend line for M4 reveals a U-shaped distribution with the lowest values at T3 and a rise subsequently at T5. The linear trend line for M0 showed a relatively stable pattern, with minor fluctuations. Large error bars at M4 indicate variability, suggesting higher leakage in some replicates. Overall, treatments T2 and T3 preserved membrane integrity best, while T1 and T5 showed greater degradation by the final observation point.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. \u0026nbsp; Alpha amylase\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGraph 5 illustrates the alpha amylase activity (expressed in arbitrary units) under different treatments (T1\u0026ndash;T6) at the M4 stage, including both linear and polynomial trend lines to reflect data variation. Alpha amylase is essential to the germination of seeds by hydrolysing starch into sugars that are utilized during early growth stages. Among the treatments, T3 recorded the highest alpha amylase activity, exceeding 4500 units, followed by T2 with a value close to 3700 units. These treatments suggest enhanced enzymatic activation, potentially leading to improved germinative vigour. Conversely, treatments T1, T4, T5, and T6 exhibited comparatively lower enzyme activity, ranging between 3000 and 3300 units. The polynomial trend line demonstrates a clear peak at T3, highlighting its superior enzymatic profile, whereas the linear trend line indicates a slight overall decline across the treatments. Error bars represent standard error and show relatively low variability among replicates within each treatment, reinforcing the reliability of observed trends. These results underscore that treatment T3 was most effective in promoting alpha amylase activity, which could contribute to improved metabolic readiness during germination. The reduced enzymatic activity in other treatments suggests potential impairment or lesser stimulation of the germinative enzyme machinery under those conditions. Alpha amylase activity under six treatments (T1\u0026ndash;T6) at initial (M0) and final (M4) stages with polynomial trend lines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. \u0026nbsp; Protein\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProtein content was assessed across six time points (T1\u0026ndash;T6) for two treatments: M0 (control) and M4 (treatment group). As shown in Figure 6, both groups demonstrated distinct trends in protein concentration over time. At T1, protein content was higher in the M0 group (2.9 \u0026plusmn; 0.2) compared to the M4 group (2.1 \u0026plusmn; 0.2). This trend reversed slightly at T2, where M4 exhibited a modest increase (2.8 \u0026plusmn; 0.3) compared to M0 (2.6 \u0026plusmn; 0.3). Peak protein concentrations were observed at T3 for both treatments, with M0 reaching 4.3 \u0026plusmn; 0.2 and M4 reaching 3.8 \u0026plusmn; 0.3. This peak was followed by a gradual decline in both groups. At T4 and T5, protein levels decreased, with M4 maintaining a slightly higher concentration at T4 (3.0 \u0026plusmn; 0.3) than M0 (2.9 \u0026plusmn; 0.2), and both groups showing similar values at T5 (M0: 2.6 \u0026plusmn; 0.2; M4: 2.4 \u0026plusmn; 0.2). By T6, the M0 group again showed higher protein levels (3.2 \u0026plusmn; 0.2) compared to M4 (1.6 \u0026plusmn; 0.2). Polynomial trend lines elucidated that pronounced fluctuation in M0 for one time increase towards the peak and secondary rise at T6. In contrast, the M4 group followed a smoother unimodal curve with a clear decline after T3. This exhibits temporal modulation of protein content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. \u0026nbsp; SOD:\u003c/strong\u003e SOD activity was evaluated across 6 time points (T1\u0026ndash;T6) under two different groups, i.e., M0 and M4. It resulted in remarkable differential changes amongst the treatments. At T1, both groups showed comparable levels of SOD activity, with M0 at approximately 0.52 \u0026plusmn; 0.02 and M4 slightly lower at 0.48 \u0026plusmn; 0.02. Activity increased in both groups at T2 and peaked at T3. The M0 group exhibited the highest SOD (\u003cstrong\u003eGraph 7\u003c/strong\u003e) activity at T3 (approximately 0.79 \u0026plusmn; 0.03), surpassing the M4 group (0.66 \u0026plusmn; 0.03). This trend of higher SOD activity in M0 compared to M4 persisted through T4 (M0: ~0.65 \u0026plusmn; 0.03; M4: ~0.57 \u0026plusmn; 0.02). A marked reduction in SOD activity was observed in both treatments at T5, with M4 showing a sharper decline (0.31 \u0026plusmn; 0.03) compared to M0 (0.42 \u0026plusmn; 0.03). By T6, activity increased slightly in both groups, though M0 maintained higher levels (0.50 \u0026plusmn; 0.02) than M4 (0.45 \u0026plusmn; 0.02). Polynomial trendlines revealed that the M0 group followed a more pronounced bimodal curve with a distinct peak at T3 and a secondary increase at T6. In contrast, the M4 group displayed a smoother, less variable trend with a single, modest peak and gradual fluctuations. These observations suggest that M0 may induce a more robust antioxidant response, whereas M4 treatment modulates SOD activity more conservatively across the measured time points.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. \u0026nbsp; POD:\u003c/strong\u003e Peroxidase activity (\u003cstrong\u003eGraph 8\u003c/strong\u003e) was monitored at 6 points under M0 and M4 conditions. It is depicted that the M0 group exhibited higher activity across all time points. At T1, peroxidase activity in the M0 group was approximately 0.056 \u0026plusmn; 0.004, significantly higher than the M4 group, which recorded an activity of 0.030 \u0026plusmn; 0.003. This pattern continued through T2 and T3, where M0 activity remained relatively stable (T2: 0.060 \u0026plusmn; 0.005; T3: 0.062 \u0026plusmn; 0.005), while M4 showed a slight increase (T2: 0.035 \u0026plusmn; 0.003; T3: 0.041 \u0026plusmn; 0.004). A decline in peroxidase activity occurred in both treatments at T4, though the drop was more pronounced in M4 (0.036 \u0026plusmn; 0.003) compared to M0 (0.049 \u0026plusmn; 0.004). The lowest levels were observed at T5, with M4 at 0.013 \u0026plusmn; 0.002 and M0 at 0.020 \u0026plusmn; 0.003. A recovery was noted at T6 for both, especially in M0 (0.048 \u0026plusmn; 0.004), while M4 modestly rose to 0.018 \u0026plusmn; 0.003. The polynomial trend shows a performance curve with a peak at T3 and a secondary increase at T6 in M0. On the other hand, M4 reveals a single peak. This shows a more robust antioxidant response in M0, whereas M4 moderates POD activity with a conservative peak across time points.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Catalase:\u003c/strong\u003e Catalase action (\u003cstrong\u003eGraph 9\u003c/strong\u003e) was quantified at six time points (T1\u0026ndash;T6) under two conditions: M0 (control) and M4 (treated). The results, shown in Figure 5, reveal significant temporal variation and treatment-dependent differences in catalase activity. At T1, catalase activity in the M0 group was markedly higher (24 \u0026plusmn; 3) than in M4 (15 \u0026plusmn; 2). Activity in both groups increased sharply at T2, with M4 reaching 30 \u0026plusmn; 3 and M0 peaking at 33 \u0026plusmn; 3. This upward trend continued to a maximum at T3, where M4 reached 41 \u0026plusmn; 3 and M0 peaked slightly higher at 43 \u0026plusmn; 3. Following T3, catalase activity declined sharply in both treatments. At T4, M4 dropped to 16 \u0026plusmn; 2 while M0 was moderately higher at 24 \u0026plusmn; 3. At T5, levels remained relatively low and comparable (M4: 19 \u0026plusmn; 2; M0: 18 \u0026plusmn; 2), but both groups exhibited a slight increase by T6 (M4: 21 \u0026plusmn; 2; M0: 23 \u0026plusmn; 2). Polynomial trendlines highlight the dynamic nature of catalase activity. M4 followed a pronounced unimodal curve with a sharp rise to T3 and a steep decline, thereafter, followed by a mild secondary rise. In contrast, M0 showed a more moderate and sustained elevation through T3, followed by a gradual decline and stabilization toward T6. Overall, M0 consistently exhibited higher catalase activity than M4 at nearly all time points, suggesting a more sustained antioxidant response in the control condition in contrast to the treated group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation Analysis Among Biochemical and Morphophysiological Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCorrelation Analysis of Biochemical and Physiological Parameters under Salicylic Acid\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the interrelationships among physiological and biochemical responses under salicylic acid (SA) treatments, a Pearson\u0026apos;s correlation matrix was constructed (\u003cstrong\u003eFigure 1\u003c/strong\u003e). Notably, strong positive correlations (r \u0026gt; 0.90, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) were observed among antioxidative enzyme activities, including M0-AM and M0-CAT (r = 0.95), M0-AM and M4-POD (r = 0.94), and M0-SOD with both M0-AM (r = 0.99) and M0-CAT (r = 0.97), suggesting a coordinated upregulation of the antioxidant defence system. Furthermore, germination-associated parameters such as M4-AM, M0-DHY, and M4-DHY exhibited significant positive correlations with these enzymatic markers (r = 0.83\u0026ndash;0.97, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), indicating a functional linkage between antioxidative capacity and early seedling vigour. In contrast, electrical conductivity (EC), an indicator of membrane damage and electrolyte leakage, showed strong negative correlations with enzymatic activities, including M0-SOD (r = \u0026ndash;0.89), M0-AM (r = \u0026ndash;0.89), and M0-CAT (r = \u0026ndash;0.85), all statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 to \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). These findings reinforce the role of protection of SA-induced antioxidant enzymes in maintaining membrane integrity under stress conditions. Together, the data underscore a tightly coordinated network between antioxidative responses and physiological performance, highlighting the efficacy of salicylic acid in modulating stress resilience during tomato seed germination and early seedling development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePearson\u0026rsquo;s Correlation Analysis of Physiological and Biochemical Responses to Salicylic Acid\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003cem\u003eIntegrated Correlation Analysis of Biochemical and Physiological Parameters Under Salicylic\u003c/em\u003e \u003cem\u003eAcid Influence:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comprehensive correlation matrix with pie-chart representation (\u003cstrong\u003eFigure\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e) was employed to examine the interrelationships among physiological and biochemical traits under control (M0) and salicylic acid-treated (M4) conditions. The dual representation\u0026mdash;colour gradients and pie segment proportions\u0026mdash;visually underscores both the direction and strength of Pearson\u0026rsquo;s correlation coefficients. Antioxidative enzymes, including Superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), demonstrated robust positive correlations with growth-associated parameters (e.g., M0-AM, M4-AM, M0-DHY, M4-DHY), with correlation coefficients exceeding 0.85 across multiple comparisons. These findings indicate a synchronized activation of enzymatic antioxidants contributing to improved metabolic activity and seedling development. Conversely, electrical conductivity (EC)\u0026mdash;an indicator of membrane damage\u0026mdash;was strongly negatively correlated with all biochemical and physiological parameters evaluated. M4-EC and M0-EC displayed marked inverse relationships with M0-SOD (r \u0026asymp; \u0026ndash;0.95), M0-AM (r \u0026asymp; \u0026ndash;0.90), and M4-DHY (r \u0026asymp; \u0026ndash;0.88), visualized clearly through large red segments in the pie charts and dark red colour coding. These patterns reinforce the role of SA-induced oxidative defence in maintaining cellular integrity under stress. The dense clustering of strong correlations among antioxidant enzymes and metabolic indicators under both M0 and M4 conditions points to a highly integrated stress-response network. The amplification of these interactions under M4 treatments suggests that salicylic acid enhances system-wide resilience through upregulation of antioxidative and metabolic pathways. This correlation structure provides compelling evidence for the systemic role of salicylic acid in enhancing seedling vigour by modulating redox balance and physiological functionality under abiotic stress conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrincipal Component Analysis Reveals Distinct Clustering and Variable Contributions Under Salicylic Acid Treatment:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) was carried out to investigate the multivariate relationships among physiological and biochemical parameters under control (M0) and salicylic acid-treated (M4) conditions. The first two principal components (PC1 and PC2) accounted for 90.58% of the total variance, with PC1 explaining a dominant 82.69%, indicating strong data structuring along this axis. The biplot (\u003cstrong\u003eFigure 3\u003c/strong\u003e) illustrates a clear separation between variables associated with salicylic acid treatment (M4) and the control (M0), particularly along PC1. Traits such as M4-CAT, M4-AM, and M4-PC, which lie positively along PC1 and PC2, are closely grouped, indicating a synergistic enhancement of enzymatic activity and metabolic performance in response to salicylic acid. Conversely, EC under both M0 and M4 conditions is oriented negatively along PC1, reinforcing its inverse association with the beneficial physiological traits and its role as a stress indicator. The strong vector magnitudes of antioxidative enzymes (SOD, CAT, POD) under M4, in addition to close alignment of M4-DHY and M4-AM, signify a coordinated upregulation of both protective enzymatic defences and growth-associated parameters under SA application. Notably, the proximity of M4-DHY and M4-PC to M4-AM suggests that membrane stability and osmolyte accumulation contribute significantly to metabolic improvement during early seedling development. These findings highlight that salicylic acid induces a tightly integrated physiological response, predominantly captured by PC1, promoting antioxidant defence and osmotic balance, while downregulating damage-related indicators such as electrical conductivity. The PCA thus affirms the pivotal role of SA in modulating multiple interdependent pathways to enhance seedling resilience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eComprehensive Correlation Analysis Reveals Strong Positive Associations Among Growth and Germination Traits Across Salicylic Acid Treatments:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA correlation matrix was constructed to explore the interrelationships among key seedling growth and germination parameters across different salicylic acid concentrations (M0\u0026ndash;M4). The matrix (\u003cstrong\u003eFigure 4\u003c/strong\u003e) reveals a highly coordinated pattern of positive correlations among all assessed traits, as indicated by the dense clustering of dark green cells. Specifically, parameters such as root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigour index I (SVGI), and seedling vigour index II (SVGII) exhibited consistently strong positive correlations (r \u0026gt; 0.85) with each other under all treatment levels. This reflects a tightly coupled physiological response, whereby enhancement in one trait (e.g., RL) is strongly predictive of improvements in others (e.g., GP and SVG). The strength of these correlations was especially pronounced under the M4 treatment, suggesting that higher concentrations of salicylic acid amplify the synchrony among early seedling growth traits. Notably, both SVG-I and SVG-II exhibited the highest degree of correlation with all other parameters, underscoring their robustness as composite indicators of seedling performance. Conversely, no significant negative correlations were observed, and minimal variability in correlation coefficients across treatments implies that salicylic acid promotes a harmonized and stable enhancement of germinative and developmental traits. This integrated trait coordination highlights the systemic regulatory effect of salicylic acid, promoting seedling vigour through concurrent modulation of multiple morpho-physiological processes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExtensive Trait Interconnectivity Evidenced by Uniformly Strong Positive Correlations Across Salicylic Acid Treatments:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation matrix (Figure 5) elucidates the intricate relationships among a wide array of germination and seedling growth parameters under varying concentrations of salicylic acid. The visualization, incorporating both colour intensity and pie chart representations, reveals an overwhelmingly positive and tightly clustered correlation structure, with coefficients predominantly approaching unity (r \u0026gt; 0.9). Key indicators such as root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigour index I (SVGI), and seedling vigour index II (SVGII) demonstrated robust interrelationships across all salicylic acid levels (M0 to M4). The dark blue shades in matrix \u0026amp; dark segments in pie chart indicate a consistent strong positiveness amongst all variable pairs. Remarkably, the uniform correlation amongst treatments showed that it promotes coordinated expression as well as increases the individual physiological traits. This exhibits that early seedling improvement does not occur in isolation but is a synchronized development. The intensity results in multiple roles of SA in improving germination and seedling vigour by affecting cell expansion, oxidative balance, and metabolic efficiency. The result shows the power of composite indices like SVI \u0026amp; SVII, which act as central integrators for this seedling performance matrix. Notably, this matrix envisages that the application of SA results in fostering physiological responses like growth, biomass accumulation, and vigour indicators, which may lead to increased crop establishment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrincipal Component Analysis Reveals Salicylic Acid-Induced Differentiation in Seedling Performance and Trait Interdependence:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis PCA biplot (\u003cstrong\u003eFigure 6\u003c/strong\u003e) shows the response of SA application on variable traits visualisation as well as clustering of specific treatments. It explains the cumulative effect of both PC1 \u0026amp; PC2 with a total variance of 93.39%, PC1 is having 87.31% which indicates the variation of seedling traits is due to single factor predominantly. Trait vectors representing root length (RL), shoot length (SL), dry weight (DW), germination percentage (GP), seedling vigor indices I and II (SVGI and SVGII), and other biometric parameters are densely clustered and aligned in a common direction, suggesting strong positive inter-correlations and shared underlying physiological mechanisms. This configuration highlights the coordinated enhancement of growth-related traits under salicylic acid treatment. Notably, treatments M3 and M4 (particularly M3_RL and M4_GP) are distinctly projected along the positive axis of PC1, indicating their superior influence on the most variance-explaining traits. This supports the conclusion that moderate to high concentrations of salicylic acid markedly boost early seedling vigour by synchronously enhancing growth and biomass allocation traits. Conversely, earlier treatments (e.g., M0, M1) and stress-related traits such as SOG (speed of germination) show greater dispersion or lesser contribution to the principal axis, further validating the dose-responsive efficiency of salicylic acid at optimized concentrations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis PCA (\u003cstrong\u003eFigure 7\u003c/strong\u003e) reinforces that salicylic acid modulates multiple growth traits in a unified manner, with higher doses (M3 and M4) exerting a dominant influence on the multidimensional performance landscape of tomato seedlings.\u003c/p\u003e\n\u003cp\u003eAbiotic stressors like heat, dryness, and salinity are lessened by exogenous plant growth regulators (PGRs), such as SA (\u0026nbsp;Finch-Savage et al., 2004). Priming increases crop production, seedling vigour, and germination, according to earlier research. Only 0.5 mM SA demonstrated notable advantages in seedling characteristics in this investigation, such as shortened mean germination time, biomass buildup, early and increased germination, emergence percentage, and seedling length. SA\u0026apos;s function in boosting antioxidant activity and encouraging metabolite production is probably what causes these effects. Kumari et al. (Kumari et al. 2017) noted similar enhancements in maize with GA₃ and SA priming. Heydariyan et al. (Heydariyan et al. 2014) also reported improved germination and vigour in \u003cem\u003eCapparis spinosa\u003c/em\u003e under SA treatment. Enhanced antioxidant activity (SOD, CAT, POD, APX) and reduced lipid peroxidation (MDA content) were noted throughout our investigation, in line with the results by Farooq et al. (Farooq et al. 2008) and Chang and Sung (Chang and Sung 1998). Yan (Yan 2015) similarly demonstrated improved germination and stress resilience in cabbage through priming. Ara et al. (Ara et al. 2013) showed that antioxidant enzyme levels were higher in heat-tolerant genotypes. Temperature significantly affects tomato seedling growth. Vollenweider and Georg (Vollenweider and G\u0026uuml;nthardt-Goerg, 2005) found that heat stress impairs shoot and root development, potentially due to water deficit. In our study, SA improved root development even under slightly elevated temperatures, possibly due to SA\u0026rsquo;s role in promoting cell division and elongation (Porter and Gawith, 1999; Hayat et al., 2010). The enhancement in photosynthetic performance may stem from SA-mediated protection of cell structures and membrane stability. SA may also reduce levels of membrane-degrading enzymes (Zang et al., 2003), enhancing photosynthesis, stomatal conductance, and water use efficiency. It is suggested that SA priming improves photosynthetic traits \u0026amp; yields under stress situation in mung bean (Kaur, 2017). The same situation also prevails in the crop quinoa (Yang et al., 2018). Singh \u0026amp; Singh (Singh et al., 2017) reported that SA priming is showing the best result in tomato seed production under heat stress condition. Rehman et al. (ur Rehman et al. 2015) concluded that SA priming helps in improving early development of maize under high temp. Ahmad et al. (Ahmad et al. 2021) observed that increase of antioxidant activity \u0026amp; membrane stability in a heat tolerant situation, S holds best. In this research we found that priming with 0.5 mM \u0026amp; 0.25 mM concentration dose helps in increase in root development and supporting seedling vigour.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that seed priming with salicylic acid (SA), particularly at a concentration of 0.5 mM, significantly enhances germination percentage and seedling vigour in aged tomato seeds. The treatment not only improved the uniformity and speed of germination—key factors for optimizing subsequent plant growth and development—but also positively modulated the physiological and biochemical responses of the seeds. The results indicate that SA priming is an effective, economically feasible, and environmentally friendly strategy within resource-limited settings. By boosting metabolic efficiency and enhancing antioxidant and enzymatic activities, SA priming reduces the need for additional chemical inputs and increases the seeds’ innate resistance to abiotic stresses. In the context of sustainable agriculture, SA priming emerges as a promising pre-sowing treatment to mitigate stress and improve seed production. Further research is needed to clarify mechanisms and support broader agronomic application.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData utilized during the investigations is publicly available or can be shared on request to corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnupam Dalapati, Soubhagya Behera\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand S. Mohanty wrote main manuscript text. C. Patra, S. Dash, U.K. Behera, M.K. Rout, C.R. Sahoo, S.K. Swain, P. Behera, D. Sahoo and Swarnalata Das prepared all figures and built software for experimental pur\u0026shy;pose. Soubhagya Behera supervised the work and edited the manuscript. R. K. Rout, B.K. Mandal, S. K. Sahoo \u0026amp; Nishant K GR. gathered the results and improved the man\u0026shy;uscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding and bear by authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u0026nbsp;\u003c/strong\u003eand requests for materials should be addressed to R. K. Rout and Soubhagya Behera.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReprints and permissions information\u0026nbsp;\u003c/strong\u003eis available at www.nature.com/reprints.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSingh, Y., \u0026amp; Prajapati, S. (2018). Status of horticultural crops: identifying the need for transgenic traits. In \u003cem\u003eGenetic engineering of horticultural crops\u003c/em\u003e (pp. 1-21). Academic Press.\u003c/li\u003e\n \u003cli\u003eYan, M. (2015). Seed priming stimulate germination and early seedling growth of Chinese cabbage under drought stress. \u003cem\u003eSouth African Journal of Botany\u003c/em\u003e, \u003cem\u003e99\u003c/em\u003e, 88-92.\u003c/li\u003e\n \u003cli\u003eAhmad, M., Waraich, E. A., Zulfiqar, U., Ullah, A., \u0026amp; Farooq, M. (2021). Thiourea application improves heat tolerance in camelina (Camelina sativa L. 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Assessment of climate variability among seasonal trends using in situ measurements: A case study of Punjab, Pakistan. \u003cem\u003eAtmosphere\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(8), 939.\u003c/li\u003e\n \u003cli\u003eVollenweider, P., \u0026amp; G\u0026uuml;nthardt-Goerg, M. S. (2005). Diagnosis of abiotic and biotic stress factors using the visible symptoms in foliage. \u003cem\u003eEnvironmental Pollution\u003c/em\u003e, \u003cem\u003e137\u003c/em\u003e(3), 455-465.\u003c/li\u003e\n \u003cli\u003eur Rehman, H., Iqbal, H., Basra, S. M., Afzal, I., Farooq, M., Wakeel, A., \u0026amp; Wang, N. (2015). Seed priming improves early seedling vigor, growth and productivity of spring maize. \u003cem\u003eJournal of Integrative Agriculture\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(9), 1745-1754.\u003c/li\u003e\n \u003cli\u003eZhang, Y., Chen, K., Zhang, S., \u0026amp; Ferguson, I. (2003). The role of salicylic acid in postharvest ripening of kiwifruit. \u003cem\u003ePostharvest Biology and Technology\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(1), 67-74.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Salicylic acid, Biochemical analyses, Seed Vigour Index, Modulation","lastPublishedDoi":"10.21203/rs.3.rs-6906482/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6906482/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated the influence of salicylic acid (SA) priming on the physiological and biochemical attributes of aged tomato seeds (Solanum lycopersicum L., variety BT-10, Utkal Kumari). Seeds were subjected to priming with varying concentrations of SA (0 mM, 0.1 mM, 0.25 mM, 0.5 mM, 0.75 mM, and 1.0 mM) for 24 hours, followed by drying under controlled conditions.\u003cbr\u003e\nThe experiment was conducted using a completely randomized design (CRD) with five trials and three replications per treatment. Key physiological parameters evaluated included germination percentage, seed vigour index (SVI), seedling length, speed of germination, and moisture content. Biochemical analyses focused on changes in electrical conductivity, dehydrogenase activity, superoxide dismutase (SOD), peroxidase (POD), catalase, alpha-amylase activity, and protein content.\u003cbr\u003e\nResults demonstrated that a moderate concentration of SA (0.5 mM) significantly improved both physiological and biochemical seed quality. Higher concentrations showed inhibitory effects. These findings highlight the potential of SA priming to support robust early growth in aged tomato seeds.\u003c/p\u003e","manuscriptTitle":"Salicylic Acid-mediated Modulation of Biochemical Parameters in Aged Tomato Seeds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-09 08:56:08","doi":"10.21203/rs.3.rs-6906482/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a433450-fb10-4ce3-b342-2f2e0bda53f0","owner":[],"postedDate":"July 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51263987,"name":"Biological sciences/Biochemistry"},{"id":51263988,"name":"Biological sciences/Chemical biology"},{"id":51263989,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-10-01T08:24:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-09 08:56:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6906482","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6906482","identity":"rs-6906482","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}