Mycobiogenic Silver Nanoparticle Priming: A Strategy to Mitigate Salinity Stress in Sorghum

Mycobiogenic Silver Nanoparticle Priming: A Strategy to Mitigate Salinity Stress in Sorghum | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mycobiogenic Silver Nanoparticle Priming: A Strategy to Mitigate Salinity Stress in Sorghum Ana B. S. Ziotti, Cristiane A. Otonni, Vitória C. P. Kuhl, Milton Lima Neto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6768384/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 Abiotic stresses, including salinity, significantly threaten crop production worldwide. Nanotechnology, particularly seed priming with silver nanoparticles (AgNP), offers a potential strategy for enhancing plant stress tolerance. This study compared the effects of biogenic (AgNP b ), synthetic (AgNP s ) silver nanoparticles with their metal precursor (AgNO 3 ) on sorghum germination and early seedling growth and evaluated AgNP b priming to improve salinity tolerance. Sorghum seeds were treated with 0, 10, or 100 mM of AgNP b , AgNP s , or AgNO 3 . AgNP b enhanced germination rate, increased root and shoot biomass, improved photosynthetic performance (net photosynthetic rate, stomatal conductance, and electron transport rate), and maintained higher relative water content. Conversely, AgNO 3 , particularly at 100 mM, inhibited germination, reduced biomass, impaired photosynthesis, and induced significant oxidative stress (elevated H 2 O 2 and TBARS). AgNP s showed intermediate effects. Furthermore, seed priming with 100 mM AgNP b mitigated the negative impacts of subsequent 100 mM NaCl exposure, improving photosynthesis and reducing oxidative damage markers compared with non-primed, salt-stresses seedlings. While the millimolar concentrations used limit direct field application, these findings highlight the critical role of the form of silver (ionic versus nanoparticulate) in determining phytotoxicity. AgNP b shows potential for promoting early growth and, crucially, enhancing salinity tolerance via seed priming, warranting investigation at lower, environmentally relevant concentrations. Biogenic nanoparticles oxidative stress photosynthesis nanopriming silver toxicity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Background Abiotic stresses, particularly salinity, pose a major threat to global food security, and these challenges are projected to intensify under climate change scenarios (Hasegawa et al., 2021 ). The significant threat of salinity to food security necessitates innovative strategies to improve plant stress resilience for sustainable agriculture. Nanotechnology offers innovative approaches for mitigating abiotic stress impacts on crop plants through mechanisms including targeted nutrient delivery, modulation of stress signaling, and improved resource use efficiency. Nanoparticles (NP), typically ranging from 1 to 100 nm in size, possess unique physicochemical properties due to their high surface area-to-volume ratio, which allows for enhanced interaction with plant systems (Yusefi-Tanha et al., 2023 ). Among various nanomaterials, silver nanoparticles (AgNP) have attracted considerable attention in plant science due to their potential to enhance stress tolerance, attributed partly to their antimicrobial properties and their ability to modulate plant physiological processes (Siddiqi and Husen, 2022 ). AgNP application has been shown to enhance plant stress tolerance by modulating key physiological processes, including antioxidant enzyme activities, nutrient absorption, and root system development, potentially aiding plants in coping with abiotic stresses (Chen et al., 2023 ). The effects of AgNP on plants are complex and often contradictory, with beneficial and harmful impacts reported depending on factors such as NP synthesis method, concentration, size, physicochemical properties, environmental conditions, and plant species (Chen et al, 2023 ; Siddiqi and Husen, 2022 ). For instance, Ziotti et al. ( 2021 ) and Khan et al. ( 2023 ) demonstrated that AgNP exposure can promote plant growth and alleviate stress. Nonetheless, other studies have reported phytotoxic effects at higher concentrations, including reduced seed germination, impaired root growth, and hormonal imbalances (Yang et al ., 2022; Matras et al., 2022 ). The balance between beneficial and detrimental outcomes often relates to how AgNP influences various mechanisms, such as the modulation of antioxidant defenses, water uptake, and gene expression (Chen et al., 2023 ). One of the primary mechanisms proposed to underlie these diverse plant responses is the modulation of reactive oxygen species (ROS) production (Yan and Chen, 2019 ). Reactive oxygen species (ROS) play a complex, dual role in plant biology. At low concentrations, ROS act as signaling molecules, triggering various developmental processes and stress responses (Foyer and Hanke 2022 ). However, excessive ROS accumulation leads to oxidative stress, damaging cellular components and inhibiting growth. This duality – redox signaling versus oxidative damage – is crucial for understanding the effects of AgNP on plants. AgNP have been shown to influence ROS levels, which may be a key factor driving their biological effects, whether positive or negative (Ziotti et al., 2021 ; Zwar et al., 2023 ). A biphasic dose-response is often observed, where low concentrations of AgNP potentially stimulate growth through ROS signaling, while higher concentrations may induce oxidative stress and inhibit growth (Ziotti et al., 2021 ; Mirzajini et al ., 2013). Indeed, previous studies have reported detrimental effects of AgNP, including the generation of oxidative stress, inhibition of photosynthesis, and reduced plant growth, often associated with high exposure doses (Yan and Chen, 2019 ). While chemically synthesized AgNP (AgNP s ) have shown some success in crop applications (Siddiqi and Husen 2022 ), concerns remain regarding their potential environmental impacts and toxicity. Biogenic silver nanoparticles (AgNP b ), synthesized using plant extracts or microorganisms, offer a more sustainable, cost-effective, and environmentally friendly alternative (Abasi et al., 2022 ). Fungi are particularly promising for AgNP b synthesis due to their metabolic capabilities, efficient biomass production, and ease handling (Ottoni et al., 2017 ). Fungal synthesis often utilizes biomolecules as reducing and stabilizing agents, potentially yielding NP with high colloidal stability, low agglomeration tendency and enhanced efficacy in plant systems (Costa et al., 2025 ; Malik et al., 2024 ). Recent studies highlight the diverse applications and complex effects of mycogenic AgNP b : they can influence germination and growth in a dose- and species-dependent manner, sometimes inhibiting (e.g, in rice Ottoni et al., 2020 ) and sometimes promoting (e.g. in safflowher, Zhu et al., 2024 ). Furthermore, fungal AgNP b have demonstrated efficacy in alleviating biotic stress, partly by modulating plant antioxidant systems (e.g, in tomato, Narware et al., 2024 ). Understanding whether the production method (biogenic vs. synthetic) also modulates the observed divergent results is an important question in science. Seed priming, a pre-sowing treatment that involves controlled hydration, is a well-established technique for improving germination and seedling vigor. Combining seed priming with nanoparticle application (nanopriming) represents a promising strategy for delivering the benefits of AgNP directly to the developing seedlings and enhancing their effects. A growing number of studies have shown that seed priming with AgNP promoted seedling development, including increased root and shoot growth, improved biomass accumulation, and enhanced photosynthetic efficiency (Zhou et al., 2022 ). However, the precise physiological and biochemical mechanisms underlying the beneficial effects of AgNP b priming, particularly in the context of abiotic stress tolerance, remain to be fully elucidated (Chen et al., 2023 ). In addition to improving seed germination and early growth under non-stressed conditions, AgNP seed priming has been shown to increase the stress tolerance of some crops such as wheat and barley (Mohamed et al., 2017 , Cembrowska-Lech and Rybak, 2023 ). Salinity is a major abiotic stress affecting crop yield, productivity and reducing the land-usage area for agricultural practices (Wahid et al., 2020 ). It negatively impacts plants through a cascade of physiological and biochemical disruptions, including damage to cell membranes, the overproduction of reactive oxygen species (ROS) leading to oxidative stress, reduced photosynthetic efficiency, and impaired stomatal function (Munns and Tester, 2008 ). Excessive accumulation of sodium (Na⁺) and chloride (Cl⁻) ions causes ionic imbalances, further disrupting nutrient uptake and cellular integrity. To cope with salinity, plants employ various defense mechanisms such as regulating ion uptake and transport, synthesizing protective osmolytes like proline, and modulating hormone levels, particularly abscisic acid (ABA) (Munns et al., 2020 ). Given its economic importance in arid and semi-arid regions and its inherent tolerance to several abiotic stresses, sorghum [ Sorghum bicolor (L.) Moench], a C4 cereal crop, serves as a valuable model system for studying plant responses to stress, including the potential of novel approaches like nanopriming to enhance salinity tolerance. Despite the growing interest in AgNP b for agricultural applications, few studies have directly compared their effects to those of AgNP s on plant growth and stress responses, particularly when applied as a seed priming agent. Furthermore, most studies have focused on a limited range of physiological parameters, lacking a comprehensive assessment of the underlying mechanisms (Chen et al., 2023 ). Moreover, while some studies suggest AgNP b priming can enhance stress tolerance, the specific physiological and biochemical mechanisms involved, particularly in a C4 crop like sorghum, remain to be fully elucidated. Thus, this study aimed to: 1) compare the effects of a biogenic and a synthetic AgNP, and AgNO 3 , on sorghum seed germination and early seedling growth; 2) investigate the physiological and biochemical mechanisms underlying AgNP b -mediated responses; and 3) evaluate the potential of AgNP b seed priming as a strategy for improving sorghum performance under salinity stress. We hypothesized that: 1) AgNP b seed priming improves sorghum germination and seedling growth under both non-stressed and saline conditions; and 2) AgNP b -induced improvement is associated with enhanced antioxidant defenses and improved photosynthetic efficiency, particularly under salinity. 2. Methods 2.1 Synthesis and characterization of biogenic and chemically synthesized silver nanoparticles Aspergillus niger IBCLP20 was initially cultured on malt extract agar (MEA) medium composed of (g L − 1 ): malt extract (20.0), glucose monohydrate (20.0), bacteriological peptone (1.0), and agar (15.0), and incubated for 7 days. Fungal biomass was obtained by transferring five 6 mm-diameter agar disks from the culture into 50 mL of ME broth (MEA without agar) in a 250 mL Erlenmeyer flask, followed by incubation at 30°C and 150 rpm for 72 hours. After this period, the biomass was filtered and thoroughly washed with deionized water. Approximately 10 g of wet biomass was then transferred to a 250 mL Erlenmeyer flask containing 100 mL of deionized water and incubated again under the same conditions (30°C, 150 rpm) for an additional 72 hours. The biomass was removed by filtration using Whatman No. 1 filter paper, and the resulting supernatant was further filtered through a 0.22 µm membrane filter. This cell-free filtrate was transferred to a 50 mL Erlenmeyer flask, where silver nitrate (AgNO₃) was added to a final concentration of 1 mM. The mixture was incubated in the dark at 30°C and 150 rpm for 72 hours. The formation of AgNP b /IBCLP20 was initially indicated by a visible color change in the reaction mixture, shifting from yellow to brown. This transformation was further confirmed by UV-visible spectrophotometry, which revealed a characteristic surface plasmon resonance (SPR) band at 423 nm. According to Silva et al. ( 2022 ), AgNP b synthesized by Aspergillus niger IBCLP20 were predominantly spherical, as observed by transmission electron microscopy (TEM), with particle sizes ranging from 37.4 to 67.4 nm. In aqueous dispersion, these nanoparticles exhibited a hydrodynamic diameter of 80.5 nm, as determined by dynamic light scattering (DLS), a zeta potential of -38.56 mV, indicating good colloidal stability and a polydispersity index (PDI) of 0.215. Silver-supported carbon nanoparticles (Ag/C) with 20% metal loading were synthesized following the sodium borohydride reduction method, as described by Fontes et al. ( 2021 ), using AgNO₃ (Aldrich) as the metal precursor. The process of metal reduction started when the metal sources were added and diluted in a mixture of water/2-propanol (50/50,v/v) followed by addition of carbon Vulcan XC 72 support dispersed in the solution. The mixture was submitted to ultrasonic agitation for 10 minutes. Then, a solution of sodium borohydride (NaBH 4 ) diluted in 0.01 mol L − 1 NaOH was added and kept under mechanical stirring for 30 minutes at room temperature. Finally, the mixture was vacuum filtered, and the solid part, AgNP s , were washed with deionized water (ultrapure) and dried in the incubator at 70°C for 2 hours. The particle sizes, as determined by TEM, ranged from 10.0 to 20.0 nm. 2.2 Plant material and germination assay Seeds of sorghum ( Sorghum bicolor (L.) Moench) from the cultivar BRS-658 were provided by EMBRAPA Milho Sorgo, Brazil. Seeds were disinfected by immersion in 2% (v/v) sodium hypochlorite solution for 10 minutes and rinsed abundantly with sterile water. For the germination assay, seeds were placed in two sheets of Germitest germination paper. The paper was then moistened with a volume of solution six times the mass of the paper, as described by Ziotti et al ( 2021 ) and Zwar et al . (2022). Seeds were treated with different concentrations (0, 10 and 100 mM) of AgNO 3 , biogenic AgNPs (AgNP b ), or synthetic AgNPs (AgNP s ) in separate Petri dishes. The control treatment consisted of seeds moistened with distilled water (0 mM). The Petri dishes were placed in a growth chamber under controlled conditions: 27 o C, 75% relative humidity, 450 µmol m − 2 s − 1 irradiance, and 12-hour photoperiod. Germination was assessed daily, with the criterion for germination being a radicle length of at least 5 mm (Ziotti et al. 2021 ). The experiment was conducted with five replicates per treatment, with each replicate consisting of a Petri dish containing 30 seeds. The Petri dishes were arranged in the growth chamber in a completely randomized design to minimize the influence of any potential environmental gradients. 2.3 Seedling experiments 2.3.1 Effects of AgNP and AgNO 3 on seedling growth Sorghum seedlings, previously germinated as described in section 2.2 , were transferred to a hydroponic system in a greenhouse with a naturally controlled environment. The hydroponic system consisted of five-liter plastic pots filled with a ½ concentration of Hoagland and Arnon's nutrient solution (Hoagland and Arnon, 1950 ). The nutrient solution was renewed weekly, and the pH was monitored daily and adjusted to 5.8 ± 0.2 using 1M KOH when needed. Continuous aeration was provided using an air pump to ensure adequate oxygenation of the root system. Plants were supported with polystyrene cover in the pots. After 30 days of cultivation, the plants were harvested. Root and aboveground fresh biomass were weighed separately using a semi-analytical scale. Plant materials were then frozen in liquid nitrogen and stored at -80°C for further analysis. The experiment was conducted with five biological replicates per treatment, with each replicate consisting of a 5L pot containing two plants. The pots were arranged in the greenhouse using a completely randomized design to minimize the influence of any potential environmental gradients. In this experiment, seedlings were grown using the initial treatments from the germination assay. 2.3.2 Seed priming with AgNP b and salinity tolerance A second experiment was conducted using a hydroponic system with NaCl-induced salt stress to investigate the potential AgNP b seed priming to enhance salinity tolerance in sorghum. Seeds were exposed to 0 or 100 mM AgNP b for 24 h and then germinated as described above. After 10 days of germination in Germitest paper rolls, the seedlings were transplanted to a hydroponic system as described above. Four treatment groups were established: control (no AgNPb, no NaCl), AgNP b priming (100 mM AgNP b , no NaCl), salinity stress (no AgNPb, 100 mM NaCl), and combined treatment (100 mM AgNP b , 100 mM NaCl). A set of plants was watered with a modified Hoagland and Arnon's nutrient solution (Hoagland and Arnon, 1950 ). Another group of plants received the addition of 100 mM NaCl (50 mM per day, to avoid osmotic shock) (Dehnave et al . 2024). Plants were cultivated for 10 days after the start of salinity treatment and harvested for analysis. 2.4 Relative water content, membrane damage and pigment content Leaf and root samples (0.25 g) were stored in test tubes with deionized water at 7°C in the dark and subsequently weighed to determine their turgid mass (TM). The samples were then dried in an oven with forced air circulation at 70°C until constant weight to determine their dry mass (DM). Relative water content (RWC) was calculated according to the formula: RWC = [(FM – DM) / (TM – DM)] x 100, following the methodology used by Lima Neto et al. ( 2017 ). The membrane damage was assessed with 0.25 g of leaf or root segments immersed in test tubes containing deionized water. The tubes were incubated in a shaking bath at 25°C for 6 hours, and the electrical conductivity of the medium (L 1 ) was measured. Subsequently, the segments were boiled at 90°C for 60 minutes in closed test tubes and cooled to ambient temperature. After cooling, the electrical conductivity (L 2 ) was measured. The membrane damage (MD) was estimated by the ratio [MD = (L 1 / L 2 ) × 100] (Lima Neto et al. 2017 ). The determination of total chlorophylls and carotenoids was performed after extraction of leaf samples (0.25 mg) in cold 80% acetone in the dark. The absorbance of the extract was measured using a spectrophotometer (VERSAMAX, Molecular Devices, USA) at different wavelengths according to Lichtenthaler and Wellburn (1983). 2.5 Gas exchange and chlorophyll fluorescence Gas exchange parameters were assessed using an infrared gas analyzer (IRGA, LI-6400XT, Li-COR, Lincoln, NE, USA) equipped with a leaf chamber fluorometer (LI-6400-40, Li-COR, Lincoln, NE, USA). Measurements were taken on the second fully expanded leaf from each plant. The IRGA chamber conditions were regulated to maintain a photosynthetic photon flux density (PPFD) of 600 µmol m − 2 s − 1 , an ambient CO₂ concentration of 380 µmol mol − 1 , a vapor pressure deficit (VPD) of 1.0 ± 0.5 kPa, and a chamber air temperature of 27°C. Blue light intensity within the chamber was set to represent 10% of the total PPFD to enhance stomatal opening (Busch et al., 2024 ). Chlorophyll a fluorescence was recorded using the fluorometer coupled to the IRGA. To determine the initial fluorescence ( Fo ) and the maximum fluorescence ( Fm ), leaves were dark-adapted for 30 minutes. Following dark adaptation, leaves were illuminated with actinic light at an intensity of 600 µmol m − 2 s − 1 . Saturation pulses were administered with an intensity of 8,000 µmol m − 2 s − 1 for a duration of 0.7 seconds. Various fluorescence parameters were evaluated, including the potential quantum yield of PSII [ Fv/Fm = (Fm - Fo)/Fm ], the effective quantum yield of PSII [ Y(II) = (F < m' - Fs)/Fm' ], the photochemical quenching ( qP ) and non-photochemical quenching ( NPQ = (Fm - Fm')/Fm') , the quantum yield of non-regulated non-photochemical energy loss in PSII [ Y(NO) = F/Fm ], and the quantum yield of regulated non-photochemical energy loss in PSII [ Y(NPQ) = F/Fm' - F/Fm ]. Here, Fm and Fo are the maximum and minimum fluorescence yields of dark-adapted leaves, Fm' and Fs represent the corresponding maximum and steady-state fluorescence yields under light-adapted conditions (Murchie and Lawson, 2013 ). 2.6 Lipid peroxidation and hydrogen peroxide Lipid peroxidation was assessed based on the formation of thiobarbituric acid reactive substances (TBARS) using 0.2 g of fresh leaf tissue. TBARS concentration was calculated using its absorption coefficient (155 mM − 1 cm − 1 ) (Cakmak and Horst, 1991 ). The H 2 O 2 content was determined by the Amplex Red oxidation method (Zhou et al., 1997 ) using 250 mg of fresh leaf tissue. Leaf segments were ground in a 0.1M phosphate buffer (pH 7.5). The homogenate was then squeezed through one layer of Miracloth. The crude extract was centrifuged at 12,000 rcf for 30 minutes at 4 o C. According to the manufacturer's protocol, the supernatant was supplemented with 10 mM Amplex-Red and 10 U of horseradish peroxidase. The production of resorufin was measured at 560 nm in a spectrophotometer. 2.7 Protein extraction and enzymatic assays Fresh sorghum leaves were collected and immediately frozen in liquid nitrogen. Approximately 0.1 g of the frozen leaves were ground into a fine powder using a mortar and pestle. An extraction buffer was prepared, consisting of 100 mM K + -phosphate buffer (pH 7.5), 1 mM EDTA, 1 mM ascorbate and 1 mM PMSF. The powdered leaf material was added to the extraction buffer at a ratio of 1:1.5 (w/v). The mixture was then centrifuged at 14,000 x g for 15 minutes at 4°C, and the supernatant was carefully collected. Soluble protein content was quantified from the above extract by the Bradford method (Bradford, 1976 ) using BSA as standards with a spectrophotometer (VERSAMAX, Molecular Devices, USA). Superoxide dismutase (SOD - E.C. 1.15.1.1) activity was determined using the nitroblue tetrazolium chloride (NBT) photoreduction method. Leaf extracts were added to a solution containing 50 mM potassium phosphate buffer (pH 7.8), 0.1 mM EDTA, 13 mM L-methionine, 2 µM riboflavin, and 75 µM NBT, incubated in darkness. The photoreduction reaction was activated under a 30 W incandescent lamp at 25°C for 6 minutes, and absorbance was read at 540 nm (Giannopolotis and Ries, 1977 ). SOD activity was defined as the enzyme amount causing 50% inhibition of NBT photoreduction, with units calculated per U mg protein − 1 min − 1 . Ascorbate peroxidase (APX - E.C. 1.11.1.11) activity was measured in a reaction mixture consisting of 0.5 mM ascorbate and 0.1 mM EDTA in a 100 mM potassium phosphate buffer (pH 7.0), supplemented with enzyme extract. The reaction commenced upon the addition of 30 mM H 2 O 2 , and the decline in absorbance at 290 nm was monitored for 300 seconds. APX activity was expressed as U mg protein − 1 min − 1 as described by Nakano and Asada ( 1981 ). Catalase (CAT - E.C. 1.11.1.6) activity was evaluated by monitoring the decomposition of H 2 O 2 at 240 nm. The assay was initiated by mixing the enzyme extract in 50 mM potassium phosphate buffer (pH 7.0) with 20 mM H 2 O 2 . The decrease in absorbance was recorded over a period of 300 seconds (Havir and McHale, 1987 ). CAT activity was calculated using the molar extinction coefficient of H 2 O 2 (36 mM cm − 1 ), and expressed as U mg protein − 1 min − 1 . 2.8 Statistical Analysis The experimental design for both experiments (seed priming exposure of AgNO 3 , AgNP b and AgNP b and AgNP b priming to saline tolerance) was completely randomized, with five biological replicates per treatment. Each replicate consisted of a 5L pot containing two plants. Normality of the data for each variable was assessed using the Shapiro-Wilk test, and homogeneity of variance was assessed using Levene's test. If these assumptions were violated, data were transformed using a log transformation, or the non-parametric Kruskal-Wallis test was used followed by Dunn's post-hoc test. For comparisons among treatments in both experiments, one-way ANOVA was used, followed by Tukey's HSD post-hoc test to compare means when significant differences were detected. All statistical analyses were performed using R software (version 4.4.2) and RStudio (version 2023.09.0 + 420). A significance level of p < 0.05 was used for all tests. Principal component analysis (PCA) was used to explore relationships among the measured physiological parameters and identify potential patterns associated with treatment groups. Prior to PCA, data were scaled (z-score standardization) to standardize variables with different scales. The number of principal components to retain was determined using the broken-stick criterion (Vítolo et al., 2012 ). PCA was performed using the R packages FactoMineR and factoextra. 3. Results 3.1 Effects of biogenic and synthetic AgNP on germination and biomass allocation Silver nitrate (AgNO 3 ) exposure had the most detrimental effect on early seedling development, inhibiting germination in a dose-dependent manner (Fig. 1 A). Germination was significantly reduced at both 10 and 100 mM AgNO 3 compared to the control. AgNP b treatments resulted in high germination rates, with 100 mM AgNP b showing the highest mean percentage on day one, significantly exceeding the control and AgNO 3 treatments. AgNP s treatments resulted in significantly higher germination rates than the control on day 1, while showing no significant difference from the control by day 2 (Fig. 1 A). Regarding biomass accumulation after 30 days of hydroponic growth (Fig. 1 B), AgNP b treatment at 100 mM resulted in a significant increase in both root and shoot biomass, indicating a positive impact on overall plant growth and development. Both concentrations of AgNO 3 exposure resulted in significantly lower total biomass compared to the control, primarily due to a significant reduction in shoot biomass, confirming its negative impact on plant growth. AgNP s , at either 10 or 100 mM, did not significantly affect total biomass accumulation compared to the control (Fig. 1 B). 3.3 Physiological parameters Following the analysis of germination rates and biomass allocation, we investigated the effects of the different treatments on various physiological and biochemical parameters (Table 1 ). AgNO 3 , particularly at 100 mM, significantly reduced the relative water content (RWC) compared to the control and AgNP b treatments. In contrast, AgNP b treatment at both concentrations increased RWC significantly higher than the control and both concentrations of AgNO 3 . Both concentrations of AgNP b resulted in similar RWC values and both concentrations of AgNP s maintained RWC levels not significantly different from the control. Membrane damage (MD), an indicator of cellular integrity, was significantly increased by AgNO 3 exposure in a dose-dependent manner, with the highest MD observed at 100 mM AgNO 3 . Both 10 mM and 100 mM AgNP b treatments resulted in significantly lower MD compared to the control. Both concentrations of AgNP s resulted in similar levels of MD compared to 10 mM AgNO 3 , but significantly lower than 100 mM AgNO 3 . Table 1 – Relative water content (RWC, %), membrane damage (MD, %), chlorophyll a (Chla, mg g − 1 FM), chlorophyll b (Chlb, mg g − 1 FW), total chlorophyll [ChlT, mg g − 1 FW) and carotenoids content [Car (mg g − 1 FW)] in sorghum leaves. Seedlings grown from seeds pre-treated with 0, 10 or 100 mM AgNO 3 , biogenic silver nanoparticles (AgNP b ) or synthetic AgNP (AgNP s ). Data are the means ± SD of five replicates. Different letters within a row indicate significant differences according toTukey's HSD test (P < 0.05). Control AgNO 3 AgNPb AgNPs 0mM 10 mM 100 mM 10 mM 100 mM 10 mM 100 mM RWC (%) 80.92 ± 2.12b 71.10 ± 1.36c 65.02 ± 2.14c 82.03 ± 1.84a 83.01 ± 2.11a 78.08 ± 2.12b 80.03 ± 1.56b MD (%) 22.21 ± 1.82c 25.21 ± 2.02b 38.42 ± 2.84a 18.32 ± 1.05d 20.21 ± 1.8d 25.14 ± 1.20b 30.25 ± 2.25b Chla (mg g − 1 FM) 2.51 ± 0.29c 1.82 ± 0.18d 1.11 ± 0.10e 3.22 ± 0.18a 3.61 ± 0.21a 2.66 ± 0.12b 2.81 ± 0.21b Chlb (mg g − 1 FM) 1.4 ± 0.08c 0.81 ± 0.06d 0.60 ± 0.04d 2.01 ± 0.21a 1.81 ± 0.14a 1.41 ± 0.16c 1.60 ± 0.14b ChlT (mg g-1 FM) 3.90 ± 0.26b 2.63 ± 0.20c 1.70 ± 0.15d 5.23 ± 0.32a 5.42 ± 0.36a 4.1 ± 0.28b 4.60 ± 0.32b Car (mg g − 1 FM) 27.60 ± 1.82b 22.00 ± 1.76c 18.32 ± 1.80d 32.24 ± 2.01a 36.21 ± 2.18a 30.25 ± 2.21a 33.65 ± 1.83a In relation to pigment content, AgNO 3 significantly reduced chlorophyll a , b , and total chlorophyll compared to control plants in a dose-dependent manner (Table 1 ). Both concentrations of AgNP b significantly enhanced all chlorophyll pigments (a, b, and total) compared to the control and all other treatments. AgNP s also increased chlorophyll content compared to the control and AgNO 3 treatments, but to a lesser extent than AgNP b , and this increase was not always statistically significant (e.g., Chl a at 10 mM AgNP s ). Similarly, carotenoid content was significantly lower in AgNO 3 -treated plants compared to all other treatments (Table 1 ). Both concentrations of AgNP b and AgNP s resulted in significantly higher carotenoid levels than the control and AgNO 3 treatments. 3.4 Photosynthetic responses to different AgNP treatments Gas exchange parameters were significantly influenced by different treatments (Fig. 2 ). AgNP b at 100 mM led to the highest stomatal conductance ( gs ), transpiration rate ( E ), and photosynthetic rate ( A ), while AgNO 3 at 100 mM consistently resulted in the lowest values for these parameters (Fig. 2 A-C). Specifically, A, gs and E were significantly higher in plants treated with 100 mM AgNP b compared to all other treatments. Conversely, 100 mM AgNO 3 significantly reduced A, gs and E compared to all other treatments. Interestingly, AgNP b at 100 mM also resulted in the lowest intercellular CO 2 concentration ( Ci ) (Fig. 2 D), while AgNO 3 at 100 mM had the highest Ci . In contrast to the significant effects of AgNP b and AgNO 3 , AgNP s had a less pronounced impact on gas exchange. While AgNP s did not significantly affect A compared to the control, 10 mM AgNP s significantly reduced Ci while 100 mM AgNP s did not. Both 10 and 100 mM AgNP s significantly decreased E (Fig. 2 B-C). The potential quantum yield of PSII ( FvFm ), a measure of the maximum efficiency of PSII photochemistry, was significantly decreased in plants treated with 100 mM AgNO 3 , indicating damage or stress to PSII (Fig. 3 A). The other treatments did not significantly affect FvFm compared to the control. However, plants treated with AgNP b (100 mM) showed the highest effective quantum yield of PSII [Y(II)], while those treated with AgNO 3 (100 mM) showed the lowest (Fig. 3 B). AgNP s at 10 mM did not significantly affect Y(II), but 100 mM AgNP s significantly decreased Y(II) compared to control (Fig. 3 B). A similar trend was observed for the apparent electron transport rate (ETR), with the highest ETR observed in plants treated with AgNP b (100 mM) and the lowest ETR values were observed in plants treated with both 10 mM and 100 mM AgNO 3 (Fig. 3 C). Specifically, ETR was significantly higher in the 100 mM AgNP b treatment compared to all other treatments, and significantly lower in both 10 and 100 mM AgNO 3 treatments compared to the control and AgNP treatments. Non-photochemical quenching (NPQ), a mechanism for dissipating excess excitation energy as heat, was highest in plants treated with 100 mM AgNO 3 (Fig. 3 D). This increase in NPQ was related to increases in both the slow-relaxing (NPQ s ) and fast-relaxing (NPQ f ) components of NPQ. Plants treated with AgNP b showed significantly lower total NPQ compared to the 100 mM AgNO 3 treatment, while plants treated with AgNP s had no significant difference in total NPQ compared to the control (Fig. 3 D). 3.5 Reactive oxygen species and antioxidant response AgNO 3 at 100 mM induced the highest levels of H 2 O 2 in leaves, significantly higher than all other treatments (Fig. 4 A). This was followed by 10 mM AgNO 3 , 100 mM AgNP b and 100 mM AgNP s , which were all significantly higher than the control. Both 10 mM AgNP b and 10 mM AgNP s also had significantly higher H 2 O 2 levels than the control. Lipid peroxidation, as measured by malondialdehyde (MDA) equivalents (TBARS content), showed a somewhat similar pattern (Fig. 4 B). The 100 mM AgNO 3 and 100 mM AgNP s treatments resulted in the highest TBARS levels, significantly higher than all other treatments. These were followed by 10 mM AgNO 3 and 100 mM AgNP b , which were not significantly different from each other but were significantly higher than the control, 10 mM AgNP s and 10 mM AgNP s . To investigate the antioxidant response, we measured the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) in sorghum leaves (Table 2 ). SOD activity was significantly increased by all treatments compared to the control. The highest SOD activity was observed in the 100 mM AgNO 3 treatment, followed by 100 mM AgNP b , and both concentrations of AgNP s also resulted in significant increases in SOD activity, though generally to a lesser extent than the 100 mM AgNO 3 and 100 mM AgNP b treatments. APX activity showed a similar pattern, with the highest activity in the 100 mM AgNO 3 treatment, followed by the 10 and 100 mM of AgNP s and 10 mM AgNO 3 treatments. The 10 mM AgNP b treatment did not significantly affect APX activity relative to control. CAT activity was significantly increased by both concentrations of AgNO 3 , 100 mM AgNP b , and 100 mM AgNP s compared to the control. In contrast, 10 mM AgNP b and 10 mM AgNP s did not significantly alter CAT activity from control levels. Overall, AgNO 3 , particularly at 100 mM, generally induced the greatest or among the greatest increases in the activities of the measured antioxidant enzymes. Table 2 – Superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) activities in sorghum leaves. Activities were expressed in U mg − 1 protein. Seedlings grown from seeds pre-treated with 10 or 100 mM AgNO 3 , biogenic (AgNP b ) or synthetic silver nanoparticles (AgNP s ). Data are the means of five replicates ± SD. Different letters within a row indicate significant differences according to Tukey's HSD test (P < 0.05). Control AgNO 3 AgNPb AgNPs 0mM 10 mM 100 mM 10 mM 100 mM 10 mM 100 mM SOD 15 ± 1.2c 22 ± 1.6b 31 ± 1.4a 25 ± 1.4b 28 ± 1.1a 23 ± 1.2b 26 ± 1.5b APX 0.19 ± 0.012c 0.25 ± 0.021b 0.38 ± 2.84a 0.18 ± 1.05c 0.23 ± 1.85b 0.25 ± 1.20b 0.3 ± 2.25b CAT 3.5 ± 0.29b 4.3 ± 0.18a 4.4 ± 0.10a 3.21 ± 0.18b 4.5 ± 0.21a 3.3 ± 0.12b 4.3 ± 0.21a 3.6 Principal component analysis Principal component analysis (PCA) was conducted to explore the relationships between the different treatments and the measured variables, encompassing growth, physiological, and biochemical parameters (Fig. 5 ). The first two principal components (PCs) explain 89.4% of the total variation (PC1: 76%, PC2: 13.4%), indicating that the PCA effectively summarizes the major physiological responses. The biplot reveals a clear separation of the 100 mM AgNO 3 treatment, strongly associated with variables indicative of oxidative stress (H 2 O 2 , TBARS) and increased antioxidant enzyme activities (SOD, APX, CAT). The 10 mM AgNO 3 treatment also shows a distinct separation, but to a lesser extent than 100 mM AgNO 3 . Conversely, AgNP b treatment shows a separation mainly attributed to its positive association with variables related to plant growth and photosynthetic performance. This suggests a potential beneficial effect of the biogenic AgNP at this concentration. The AgNP b treatments also grouped more closely with growth and photosynthetic parameters then the AgNP s treatments. The remaining treatments, including the control and both concentrations of AgNPs clustered more closely together, suggesting more similar effects on the measured variables, and a less pronounced deviation from the baseline physiological state represented by the control group. 3.7 Effects of AgNP b priming on salinity tolerance To investigate the potential of AgNP b seed priming to enhance salinity tolerance in sorghum, one group of seedlings was primed with 100 mM AgNP b while a control was not primed; both groups were subsequently exposed to 100 mM NaCl. The effects of priming on various physiological and biochemical parameters, relative to non-primed, salt-stressed plants, are shown in Fig. 6 . AgNP b priming significantly increased net photosynthetic rate ( A ) by approximately 125% compared to non-primed plants under salinity stress. Similarly, stomatal conductance ( gs ) and transpiration rate ( E ) were also significantly higher (by 111% and 43%, respectively) in primed seedlings. The ETR was also strongly increased by AgNP b priming (197%), concomitant with a significant decrease in NPQ (58%). These results suggest that AgNP b priming helps improve photosynthetic function under salt stress, possibly by facilitating CO 2 uptake and enhancing the efficiency of light energy utilization. Furthermore, AgNP b priming resulted in a significant increase in relative water content (RWC) by 18%, indicating improved water status in the primed plants. Conversely, membrane damage (MD) was significantly reduced (by 52%) in AgNP b -primed seedlings, suggesting protection against salt-induced cellular damage. Regarding oxidative stress, AgNP b priming led to a significant reduction in TBARS (by 40%) and H 2 O 2 (by 25%) levels compared to non-primed, salt-stressed plants. AgNP b priming significantly increased CAT activity by 87% compared with non-primed, salt-stressed plants. SOD activity was also significantly increased, by 20%, while APX activity showed a small but significant decrease with priming. Overall, these results suggest that AgNP b seed priming can mitigate some of the negative impacts of salinity stress on sorghum seedlings, particularly by improving photosynthetic performance, water status, and reducing oxidative damage (Fig. 6 ). 4. Discussion This study aimed to compare the effects of mycogenic (AgNP b ) and synthetic (AgNP s ) silver nanoparticles with silver nitrate (AgNO 3 ) on sorghum germination, and seedling growth, and underlying physiological mechanisms, while also evaluating the AgNP b priming effect on subsequent salinity tolerance. Our results demonstrate that high concentrations of AgNO 3 are severely toxic to sorghum seedlings, while AgNP b , even at high concentrations, exhibit less toxicity and appear to promote some aspects of growth and increase photosynthesis. Synthetic AgNP showed intermediate effects. 4.1 Contrasting effects of AgNO 3 and silver nanoparticles on sorghum A key finding was the pronounced toxicity of AgNO 3 at the millimolar concentrations tested (10 and 100 mM), as evidenced by significant reductions in germination rate (Fig. 1 A), seedling biomass (Fig. 1 B), relative water content (Table 1 ), and chlorophyll content (Table 1 ). Furthermore, AgNO 3 exposure resulted in substantial increases in membrane damage (Table 1 ), elevated levels of H 2 O 2 and TBARS (Fig. 4 ), indicating oxidative stress, and impairment of photosynthetic function (Figs. 2 and 3 ). These findings are consistent with previous studies demonstrating the toxicity of high concentrations of ionic silver (Ag + ) to plants (Ziotti et al., 2021 ; Zwar et al., 2024). Silver ions are known to interfere with various cellular processes, including enzyme function, nutrient uptake, and DNA replication (Siddiqi and Husen, 2022 ). The observed increase in antioxidant enzyme activities (SOD, APX, CAT) in response to AgNO 3 (Table 2 ) reflects a compensatory mechanism to mitigate the oxidative damage caused by excessive ROS production. Importantly, both AgNP b and AgNP s exhibited significantly less toxicity than AgNO 3 at equivalent millimolar concentrations of total silver. This difference highlights the critical role of the form of silver (ionic versus nanoparticulate) in determining its phytotoxicity. While AgNP s also induced some oxidative stress at 100 mM, as indicated by increased TBARS in the case of AgNP s and H 2 O 2 in both AgNP treatments, the magnitude of these effects was considerably smaller than that observed with AgNO 3 . This suggests that the gradual release of Ag + ions from AgNP, or potentially other nanoparticle-specific interactions, results in a lower effective concentration of toxic Ag + within plant tissues compared to direct exposure to AgNO 3 (Ziotti et al., 2021 ). 4.2. Biogenic AgNP promotes growth and photosynthesis In contrast to the detrimental effects of AgNO 3 , AgNP b exhibited a seemingly stimulatory effect on several growth and physiological parameters in sorghum seedlings under non-stresses conditions. This treatment resulted in the highest germination rate on day one (Fig. 1 A), significantly increased root and shoot biomass (Fig. 1 B), and enhanced photosynthetic performance, as evidenced by the highest values for net photosynthetic rate ( A ), stomatal conductance ( gs ), effective quantum yield of PSII [ Y(II) ], and the electron transport rate ( ETR ) (Figs. 2 and 3 ). The enhanced photosynthetic rate ( A ) observed in the 100 mM AgNP b treatment (Fig. 2 A) is likely linked to the significantly higher stomatal conductance ( gs ) (Fig. 2 B). Increased gs facilitates greater CO 2 uptake, providing more substrate for carbon fixation. This, coupled with the lower intercellular CO 2 concentration ( Ci ), suggests a higher carboxylation efficiency in AgNP b -treated plants. Furthermore, AgNP b -treated plants maintained higher relative water content (Table 1 ) and showed increased levels of photosynthetic pigments (Table 1 ). This improved photosynthetic efficiency, along with the maintenance of RWC and increased pigment content, could contribute to the increased biomass observed in AgNP b -treated plants (Fig. 1 B). However, it is crucial to interpret these results within the context of the high AgNP b concentrations employed. The 10- and 100-mM concentrations used in this study are considerably higher than those typically considered environmentally relevant for nanoparticles. Therefore, the observed induction is unlikely to be representative of the effects expected at lower, more realistic exposure levels and requires careful mechanistic consideration. Several, non-exclusive, mechanisms could potentially explain these observations. One possibility is a hormetic response, where a substance that is toxic at high doses exhibits stimulatory effects at lower doses. While our experimental design, with only two AgNP b concentrations, does not allow for a definitive confirmation of hormesis, the seemingly positive effects at these high concentrations are consistent with the stimulatory phase of a such biphasic response (Bello-Bello et al., 2017 ). Furthermore, as shown in our second experiment, the 100 mM AgNP b concentration was effective as a priming treatment for improving subsequent salinity tolerance (Fig. 6 ). The priming experiment demonstrated that priming with 100 mM AgNP b significantly mitigated the negative impacts of salinity stress on sorghum seedlings (Fig. 6 ). AgNP b -primed plants subjected to 100 mM NaCl exhibited significantly improved photosynthetic performance (higher A, gs, ETR and lower NPQ ), better water status (higher RWC), reduced membrane damage, and lower levels of oxidative stress markers (TBARS and H 2 O 2 ) compared to non-primed, salt-stressed plants. These findings provide compelling evidence that AgNP b priming can enhance salinity tolerance in sorghum (Fig. 6 ). Alternatively, the enhanced growth in the 100 mM AgNP b treatment could be related to indirect effects, such as the suppression of microbial growth in the hydroponic solution due to the known antimicrobial properties of silver nanoparticles (Mirzajani et al 2013 ). Reduced microbial load could potentially alleviate competition for nutrients or reduce the incidence of subclinical infections, thereby promoting seedling growth. It is also possible that the AgNP b , even at these high concentrations, are modulating ROS levels in a way that, while still elevated compared to the control, is less detrimental than the extreme oxidative stress induced by AgNO 3 . The relatively low membrane damage (Table 1 ) and the lower, but significant, increase of H 2 O 2 (Fig. 4 A) in the 100 mM AgNP b treatment compared to AgNO 3 supports this possibility. Finally, unique properties of the biogenic AgNP b , related to their fungal-mediated synthesis, may also play a role that merits to be better understood (Ottoni et al., 2017 ). 4.3. Differential oxidative stress responses and ROS modulation The observed differences in plant responses to AgNO 3 , AgNP b , and AgNP s can be understood, at least in part, by considering their effects on reactive oxygen species (ROS) production, antioxidant defense systems, and photosynthetic processes. As previously discussed, ROS play a dual role in plants, acting as signaling molecules at low concentrations but causing oxidative damage at high concentrations (Foyer and Hanke, 2022 ). Our results clearly demonstrate that high concentrations of AgNO 3 (particularly 100 mM) induce significant oxidative stress in sorghum seedlings. This is evidenced by the elevated levels of H 2 O 2 and TBARS (Fig. 4 ), indicators of oxidative damage to cellular components, and by the substantial increases in the activities of antioxidant enzymes SOD, APX, and CAT (Table 2 ). These enzymes represent a crucial line of defense against ROS, scavenging superoxide radicals (SOD), detoxifying hydrogen peroxide (APX and CAT), and preventing further oxidative damage (Foyer and Hanke, 2022 ). The increased enzyme activities likely represent a compensatory response to the elevated ROS levels induced by AgNO 3 . In contrast to AgNO 3 , the AgNP treatments, and particularly AgNP b , resulted in a less pronounced oxidative stress response. While 100 mM AgNP b and AgNP s did increase H 2 O 2 levels compared to the control, the magnitude of this increase, and the corresponding increase in TBARS, was significantly lower than that observed with AgNO 3 (Fig. 4 ). This suggests that, even at equivalent millimolar concentrations of total silver, the nanoparticulate forms of silver elicit a weaker oxidative stress response. This could be due to a slower release of Ag + ions from the nanoparticles compared to the readily available Ag + ions from AgNO 3 (Ziotti et al., 2021 ). The lower membrane damage (MD) observed in the AgNP b treatments, especially 10 mM, compared to AgNO 3 further supports this notion. The potentially beneficial effects of 100 mM AgNP b on growth and photosynthesis, both in absence and presence of salinity, raise intriguing questions about the role of ROS signaling. It's plausible that the AgNP b treatment, while increasing ROS production above control levels, maintains ROS within a range that allows for beneficial signaling effects without triggering severe oxidative damage. This is further supported by the results of the priming experiment, where AgNP b priming significantly reduced TBARS levels under salinity stress, indicating a protective effect against lipid peroxidation (Fig. 6 ). 4.4 AgNP b -mediated photosynthetic enhancement and signaling pathways The chlorophyll fluorescence data further support the enhanced photosynthetic capacity of plants treated with 100 mM AgNP b . The significantly higher effective quantum yield of PSII [Y(II)] (Fig. 3 B) and electron transport rate (ETR) (Fig. 3 C) indicate improved efficiency of light energy utilization in these plants. Conversely, the reduced Fv/Fm, Y(II), and ETR observed in the 100 mM AgNO 3 treatment suggest damage to the photosynthetic apparatus, consistent with the observed oxidative stress. Synthetic AgNP, on the other hand, did not have a significant impact on most of the measured chlorophyll fluorescence parameters, except for a decrease of Y(II) in plants treated with 100 mM AgNP s . Gupta et al. ( 2018 ) found that bio-synthesized AgNP increased the activities of catalase (CAT), ascorbate peroxidase (APX), and glutathione reductase (GR) in rice seedlings, leading to reduced lipid peroxidation and H 2 O 2 content. This suggests that a similar mechanism, involving the upregulation of antioxidant enzymes, might be contributing to the observed salinity tolerance in AgNP b -primed sorghum seedlings. While experiment 1 showed increases in CAT activity with 100 mM AgNP b (Table 2 ), experiment 2 demonstrated a significant increase in CAT activity in primed plants under salt stress, further suggesting a role for this enzyme in AgNP b -mediates stress protection (Fig. 6 ). Furthermore, the apparent stimulatory effects of AgNP b at 100 mM could be, in part, attributed to ROS-mediated signaling. As suggested by Chen (2023), AgNP-generated ROS, at appropriate levels, can act as stress signal molecules, triggering adaptive responses and inducing changes in the metabolome and transcriptome. Recently, Acharya et al. ( 2020 ) have employed 1H nuclear magnetic resonance (NMR) and liquid chromatography coupled with mass spectrometry (LC-MS) based on metabolomics to explore the metabolome profile changes in onion seeds after AgNP priming. From the changes in metabolic imprint, they elucidated the mechanisms through which AgNP priming improved the seed performance. They revealed that AgNP seed priming treatment decreased the content of hormones and growth regulators such as abscisic acid and cis-(+)-12-oxo-phytodienoic acid, while increasing germination-related stimulators such as γ-aminobutyric acid and zeatin. This study sheds light on the mechanistic analyses of nano seed priming. Further investigation into the metabolic profiles of AgNP b -treated sorghum seedlings could provide valuable insights into the specific pathways involved in the observed growth promotion. Furthermore, the enhanced salinity tolerance conferred by AgNP b priming likely involves complex signaling crosstalk within the plant, potentially interacting with key phytohormonal pathways. Methyl jasmonate (MeJa) is a crucial signaling molecule known to mediate plant responses to various stresses, including salinity (Yu et al ., 2023). MeJa signaling can activate a suite of protective mechanisms, such as boosting antioxidant enzyme activities and influencing osmotic adjustment. Intriguingly, jasmonates have also been implicated in regulating ion homeostasis under salt stress, sometimes contributing to reduced accumulation of toxic Na⁺ ions, possibly through modulation of ion transporters like SOS1 or HKT family members (Mulaudzi et al., 2023 ). It is plausible that the physiological changes induced by AgNP b priming (perhaps mild ROS signaling or other nanoparticle-specific effects) interact synergistically with endogenous MeJa pathways upon subsequent exposure to salt stress. Such synergy could amplify defense responses, leading to more effective Na⁺ exclusion or compartmentation, enhanced antioxidant capacity (like the observed CAT increase, Fig. 6 ), and ultimately contributing to the improved photosynthetic performance and reduced oxidative damage seen in primed plants under salinity (Fig. 6 ). Investigating the specific interplay between AgNPb treatment and jasmonate signaling pathways, including hormone levels and ion flux dynamics under salinity, presents a promising direction for future mechanistic studies. The differences between AgNP b and AgNP s , although less dramatic than the differences between AgNP s and AgNO 3 , are also noteworthy. The PCA analysis (Fig. 5 ) showed that AgNP b treatments were more closely associated with growth and photosynthetic parameters than AgNP s treatments. This difference could be attributed to variations in nanoparticle properties arising from the different synthesis methods. Biogenic synthesis, using fungal biomass, may result in nanoparticles with different surface coatings, sizes, or shapes compared to the chemically synthesized AgNP. These differences could influence their interactions with plant cells, their uptake and translocation, and ultimately, their effects on ROS production and downstream physiological processes. Further investigation into the precise physicochemical characteristics of the AgNP b and AgNP s used in this study would be valuable for elucidating these differences. 4.5 Limitations, Implications, and Future Research This study provides valuable insights into the differential phytotoxicity of ionic versus nanoparticulate silver in sorghum, confirming the significantly lower toxicity of both AgNP b and AgNP s compared to AgNO 3 . However, several limitations must be acknowledged. The primary limitation is the use of high, millimolar concentrations, meaning the apparent growth promotion by 100 mM AgNP b cannot be directly extrapolated to environmentally relevant scenarios. Nevertheless, investigating plant responses across different exposure levels, including potentially elevated concentrations under controlled laboratory conditions, remains crucial for fundamentally understating the physiological and molecular mechanisms underlying AgNP-plant interactions (Chen et al., 2023 ; Yan and Chen, 2019 ). Other limitations include the use of a hydroponic system ( vs . soil complexity), a single cultivar, focus on early growth, and limited variables tested in the salinity priming experiment (single salinity/priming concentration). Despite these constraints, the results underscore the potential of biogenic synthesis methods to produce less hazardous nanoparticles compared to chemical routes, and compellingly demonstrate that AgNP b priming, even initiated at this high concentration, can effectively enhance salinity tolerance in sorghum seedlings. Consequently, future research could prioritize dose-response studies using lower, environmentally relevant AgNP b concentrations to define thresholds for beneficial effects versus potential toxicity under realistic conditions. Validating these findings through long-term field trials across different cultivars and soil types is essential. Furthermore, deeper mechanistic investigations employing ' omics ' technologies (transcriptomics, proteomics, metabolomics) are crucial to fully elucidate the signaling and metabolic pathways underlying AgNP b -mediated growth effects and stress tolerance, optimizing potential agricultural applications. While AgNP b shows promise for sustainable agriculture, particularly as a priming agent, thorough risk assessments addressing potential ecological impacts and bioaccumulation in the food chain are imperative before considering widespread adoption. 5. Conclusion This study demonstrated that the form of silver significantly influences its phytotoxicity to sorghum seedlings. While high concentrations of ionic silver (AgNO 3 ) severely inhibited germination, growth, and physiological function, biogenically synthesized silver nanoparticles (AgNP b ) exhibited significantly lower toxicity. Notably, 100 mM AgNP b , even at this high concentration, promoted several aspects of seedling growth and photosynthesis under non-stressed conditions, and, importantly, enhanced salinity tolerance when used as a seed priming agent. In contrast, AgNP s showed only intermediate effects. The observed effects of AgNP b are likely linked to a complex interplay of factors, potentially involving ROS signaling, enhanced antioxidant defenses, particularly CAT, and improved photosynthetic efficiency. While the high concentrations used limit direct extrapolation to field conditions, these findings underscore the potential of biogenic synthesis as a more sustainable approach for producing AgNP with reduced toxicity and highlight the potential of AgNP b seed priming as a strategy for improving crop performance, particularly under salinity stress. This study provides valuable insights into the complex interactions between plants and different forms of silver, and future research should focus on lower, environmentally relevant concentrations, detailed mechanistic investigations, and field trials to fully evaluate the benefits and risks of using biogenic nanoparticles in sustainable agriculture Abbreviations A - net photosynthesis, AgNP - silver nanoparticles, AgNP b - biogenic silver nanoparticles, AgNP s - synthetic silver nanoparticles, AgNO 3 - silver nitrate, APX - ascorbate peroxidase, Car - carotenoids, CAT - catalase, Chla - chlorophyll a , Chlb - chlorophyll b , ChlT - total chlorophyll, Ci - intercellular CO 2 partial pressure, DLS - dynamic light scattering, E - transpiration rate, ETR - apparent electron transport rate, Fv/Fm - potential quantum yield of PSII, FW - fresh weight, gs - stomatal conductance, H 2 O 2 - hydrogen peroxide, MDA - malondialdehyde, NPQ - non-photochemical quenching, NPQ f - fast-relaxing component of NPQ, NPQ s - slow-relaxing component of NPQ, PCA - principal component analysis, PSII - photosystem II, ROS - reactive oxygen species, RWC - relative water content, SD - standard deviation, SOD - superoxide dismutase, TBARS - thiobarbituric acid reactive substances, TEM transmission electron microscopy, Y(II) - effective quantum yield of PSII. Declarations Authors’ Contributions : Ana B. S. Ziotti and Vitória C. P. Kuhl performed the experiments and analyzed the data. Cristiane A. Otonni and Milton C. Lima Neto conceived and designed the experiments, supervised and wrote and revised the manuscript. Funding: MCLN is supported by CNPq #301453/2022-5 fellowship. Ethics and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. References Abasi F, Raja NI, Mashwani ZUR, Amjad MS, Ehsan M, Mustafa N, Haroon M, Proćków J. (2022). Biogenic Silver Nanoparticles as a Stress Alleviator in Plants: A Mechanistic Overview. Molecules . 27(11):3378. doi: 10.3390/molecules27113378. Acharya P, Jayaprakasha GK, Semper J, Patil BS. (2020). 1H Nuclear Magnetic Resonance and Liquid Chromatography Coupled with Mass Spectrometry-Based Metabolomics Reveal Enhancement of Growth-Promoting Metabolites in Onion Seedlings Treated with Green-Synthesized Nanomaterials. J. Agric. Food Chem. 68(46):13206–13220. doi: 10.1021/acs.jafc.0c01281. Bello-Bello JJ, Chavez-Santoscoy RA, Lecona-Guzmán CA, Bogdanchikova N, Salinas-Ruíz J, Gómez-Merino FC, Pestryakov A. (2017). Hormetic Response by Silver Nanoparticles on In Vitro Multiplication of Sugarcane (Saccharum spp. Cv. Mex 69-290) Using a Temporary Immersion System. Dose Response . 15(4):1559325817744945. doi: 10.1177/1559325817744945. Bradford MM. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72:248–254. doi:10.1016/0003-2697(76)90527-3. Busch FA, Ainsworth EA, Amtmann A, Cavanagh AP, Driever SM, Ferguson JN, Kromdijk J, Lawson T, Leakey ADB, Matthews JSA, et al. (2024). A guide to photosynthetic gas exchange measurements: Fundamental principles, best practice and potential pitfalls. Plant Cell Environ. 47(4): 1185-1208. doi:10.1111/pce.14815. Cakmak I, Horst WJ. (1991). Effect of aluminum on lipid peroxidation, superoxide dismutase, catalase, and peroxidase activities in root tips of soybean (Glycine max). Physiol. Plant. 83(3):463–468. Cembrowska-Lech D, Rybak K. (2023). Nanopriming of Barley Seeds-A Shotgun Approach to Improve Germination under Salt Stress Conditions by Regulating of Reactive Oxygen Species. Plants (Basel) . 12(2):405. doi: 10.3390/plants12020405. Chen S, Yan X, Peralta-Videa JR, Su Z, Hong J, Zhao L. (2023). Biological effects of AgNPs on crop plants: environmental implications and agricultural applications. Environ. Sci.: Nano . 10(1):62-71. Costa, T.S., Delgado, G.G., Braga, C.B., Tasic, L. (2025). Insights into the fungal secretomes and their roles in the formation and stabilization of the biogenic silver nanoparticles. RSC Adv.15, 6938-6951, doi. 10.1039/D4RA07962K Fontes, E.H., Ramos, C.E.D., Ottoni, C.A., de Souza, R.F.B., Antolini, E., Neto, A.O. (2021). Glycerol dehydrogenation steps on Au/C surface in alkaline medium: An in-situ ATR-FTIR approach. Renewable Energy. 167, 954-959. doi.org/10.1016/j.renene Foyer CH, Hanke G. (2022). ROS production and signalling in chloroplasts: cornerstones and evolving concepts. Plant J. 111(3):642-661. Giannopolotis CN, Ries SK. (1977). Superoxide dismutases: Occurrence in higher plants. Plant Physiol. 59:309–314. Gupta SD, Agarwal A, Pradhan S. (2018). Phytostimulatory effect of silver nanoparticles (AgNPs) on rice seedling growth: An insight from antioxidative enzyme activities and gene expression patterns. Ecotoxicol. Environ. Saf. 161:624–633. Hasegawa T, Sakurai G, Fujimori S, et al. (2021). Extreme climate events increase risk of global food insecurity and adaptation needs. Nat Food . 2:587–595. doi:10.1038/s43016-021-00335-4. Havir EA, McHale NA. (1987). Biochemical and Developmental Characterization of Multiple Forms of Catalase in Tobacco Leaves. Plant Physiol. 84:450–455. doi:10.1104/pp.84.2.450. Hoagland DR, Arnon DJ. (1950). The water culture method for growing plants without soil . Agric Exp Cir 347. Khan S, Zahoor M, Sher Khan R, Ikram M, Islam NU. (2023). The impact of silver nanoparticles on the growth of plants: The agriculture applications. Heliyon . 9(6):e16928. doi: 10.1016/j.heliyon.2023.e16928. Lichtenthaler H, Wellburn A, Lichtentharler HK, Welburn AR. (1983). Determination of total carotenoids and chlorophylls a and b of leaf extracts in different solvents. Biochem. Soc. Trans. 11:591–592. doi:10.1042/bst0110591. Lima Neto MC, Silveira JAG, Cerqueira JVA, Cunha JR. (2017). Regulation of the photosynthetic electron transport and specific photoprotective mechanisms in Ricinus communis under drought and recovery. Acta Physiol. Plant. 39:183. doi:10.1007/s11738-017-2483-9. Malik, M.A., Wani, A.H., Bhat, M.Y., Siddiqui, S., Alamri, S.A.M., Alrumman, S.A. (2024). Fungal-mediated synthesis of silver nanoparticles: a novel strategy for plant disease management. Front. Microbiol. 15, 1399331. doi:10.3389/fmicb.2024.1399331 Matras E, Gorczyca A, Pociecha E, Przemieniecki SW, Oćwieja M. (2022). Phytotoxicity of silver nanoparticles with different surface properties on monocots and dicots model plants. J. Soil Sci. Plant Nutr. 22(2):1647-1664. Mirzajani F, Askari S, Hamzelou M, Farzaneh A, Ghassempour A. (2013). Effect of silver nanoparticles on Oryza sativa L. and its rhizosphere bacteria. Ecotoxicol. Environ. Saf. 88:48–54. Mohamed AKSH, Qayyum MF, Abdel-Hadi AM, Rehman RA, Ali S, Rizwan M. (2017). Interactive effect of salinity and silver nanoparticles on photosynthetic and biochemical parameters of wheat. Arch. Agron. Soil Sci. 63(12):1736–1747. doi:10.1080/03650340.2017.1300256. Mulaudzi T, Sias G, Nkuna M, Ndou N, Hendricks K, Ikebudu V, Koo AJ, Ajayi RF, Iwuoha E. (2023). Seed Priming with MeJa Prevents Salt-Induced Growth Inhibition and Oxidative Damage in Sorghum bicolor by Inducing the Expression of Jasmonic Acid Biosynthesis Genes. Int J Mol Sci. Jun 20;24(12):10368. doi: 10.3390/ijms241210368. PMID: 37373514; PMCID: PMC10299227. Munns R, Tester M. (2008). Mechanisms of salinity tolerance. Annu. Rev. Plant Biol. 59:651–81. doi:10.1146/annurev.arplant.59.032607.092911. Munns R, Passioura JB, Colmer TD, Byrt CS. (2020). Osmotic adjustment and energy limitations to plant growth in saline soil. New Phytol. 225:1091–1096. doi:10.1111/nph.15862. Murchie EH, Lawson T. (2013). Chlorophyll fluorescence analysis: A guide to good practice and understanding some new applications. J. Exp. Bot. 64:3983–3998. doi:10.1093/jxb/ert208. Nakano Y, Asada K. (1981). Hydrogen Peroxide is Scavenged by Ascorbate-specific Peroxidase in Spinach Chloroplasts. Plant Cell Physiol. 22:867–880. doi:10.1093/oxfordjournals.pcp.a076232. Narware, J., Singh, S.P., Chakma, J., Ranjan, P., Behera, L., Das, P., Manzar, N., Kashyap, A.S. (2024). Enhancing tomato growth and early blight disease resistance through green-synthesized silver nanoparticles: Insights into plant physiology. S. Afr. J. Bot. 166, 676-689, doi.org/10.1016/j.sajb.2024.01.059 Ottoni CA, Simões MF, Fernandes S, et al. (2017). Screening of filamentous fungi for antimicrobial silver nanoparticles synthesis. AMB Expr . 7:31. doi:10.1186/s13568-017-0332-2. Ottoni CA, Neto ML, Léo P, Ortolan BD, Barbieri E, De Souza AO. (2020). Environmental impact of biogenic silver nanoparticles in soil and aquatic organisms. Chemosphere . 239:124698. doi:10.1016/j.chemosphere.2019.124698. Siddiqi KS, Husen A. (2022). Plant response to silver nanoparticles: a critical review. Crit. Rev. Biotechnol. 42(7):973-990. Silva, A.A., Ribeiro, B.M., Trotta, C.V., Perina, F.C., Martins, R., Abessa, D.M.S., Barbieri, E., Simões, M.F., Ottoni, C.A (2022). Effects of mycogenic silver nanoparticles on organisms of different trophic levels. Chemosphere. 308, 136540,. doi.org/10.1016/j.chemosphere.136540. Vítolo HF, Souza GM, Silveira JA. (2012). Cross-scale multivariate analysis of physiological responses to high temperature in two tropical crops with C3 and C4 metabolism. Environ. Exp. Bot. 80:54–62. doi:10.1016/j.envexpbot.2012.02.002. Wahid I, Kumari S, Ahmad R, Hussain SJ, Alamri S, Siddiqui MH, Khan MIR. (2020). Silver Nanoparticle Regulates Salt Tolerance in Wheat Through Changes in ABA Concentration, Ion Homeostasis, and Defense Systems. Biomolecules . 10(11):1506. doi: 10.3390/biom10111506. Yang D, Wang L, Ma F, et al. (2023). Effects of Ag nanoparticles on plant growth, Ag bioaccumulation, and antioxidant enzyme activities in Phragmites australis as influenced by an arbuscular mycorrhizal fungus. Environ Sci Pollut Res . 30:4669–4679. doi:10.1007/s11356-022-22540-9. Yan A, Chen Z. (2019). Impacts of Silver Nanoparticles on Plants: A Focus on the Phytotoxicity and Underlying Mechanism. Int J Mol Sci. 20(5):1003. doi: 10.3390/ijms20051003. Yu, X., Zhang, W., Zhang, Y., Zhang, X., Lang, D., & Zhang, X. (2019). The roles of methyl jasmonate to stress in plants. Functional plant biology : FPB, 46 3 , 197-212 . Yusefi-Tanha E, Fallah S, Pokhrel LR, Rostamnejadi A. (2023). Addressing global food insecurity: Soil-applied zinc oxide nanoparticles promote yield attributes and seed nutrient quality in Glycine max L. Sci. Total Environ. 876:162762. doi:10.1016/j.scitotenv.2023.162762. Zhou M, Diwu Z, Panchuk-Voloshina N, Haugland RP. (1997). A Stable Nonfluorescent Derivative of Resorufin for the Fluorometric Determination of Trace Hydrogen Peroxide: Applications in Detecting the Activity of Phagocyte NADPH Oxidase and Other Oxidases. Anal. Biochem. 253:162–168. doi:10.1006/abio.1997.2391. Zhou X, Jia X, Zhang Z, Chen K, Wang L, Chen H, ... Zhao L. (2022). AgNPs seed priming accelerated germination speed and altered nutritional profile of Chinese cabbage. Sci. Total Environ. 808:151896. Zhu, Y., Hu, X., Qiao, M., Zhao, L., Dong, C. (2024) Penicillium polonicum-mediated green synthesis of silver nanoparticles: Unveiling antimicrobial and seed germination advancements. Heliyon. 7e28971. doi:10.1016/j.heliyon.2024.e28971 Ziotti ABS, Ottoni CA, Correa CN, de Almeida OJG, de Souza AO, Neto MCL. (2021). Differential physiological responses of a biogenic silver nanoparticle and its production matrix silver nitrate in Sorghum bicolor. Environ. Sci. Pollut. Res. 28:32669–32682. doi:10.1007/s11356-021-13069-4. Zwar IP, Trotta C do V, Ziotti ABS, Lima Neto M, Araújo WL, de Melo IS, Ottoni CA, de Souza AO. (2023). Biosynthesis of silver nanoparticles using actinomycetes, phytotoxicity on rice seeds, and potential application in the biocontrol of phytopathogens. J Basic Microbiol. 63:64–74. doi:10.1002/jobm.202200439. 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6768384","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471448618,"identity":"ee1da6f1-d521-492f-85d2-67e83767cc1b","order_by":0,"name":"Ana B. S. Ziotti","email":"","orcid":"","institution":"São Paulo State University (UNESP)","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"B. S.","lastName":"Ziotti","suffix":""},{"id":471448619,"identity":"fb9191c0-701e-49d7-a149-61e196d695f8","order_by":1,"name":"Cristiane A. Otonni","email":"","orcid":"","institution":"São Paulo State University (UNESP)","correspondingAuthor":false,"prefix":"","firstName":"Cristiane","middleName":"A.","lastName":"Otonni","suffix":""},{"id":471448620,"identity":"f13e6871-9bbd-4c4c-82c9-2134e11dc1a1","order_by":2,"name":"Vitória C. P. Kuhl","email":"","orcid":"","institution":"São Paulo State University (UNESP)","correspondingAuthor":false,"prefix":"","firstName":"Vitória","middleName":"C. P.","lastName":"Kuhl","suffix":""},{"id":471448621,"identity":"c742e9f9-334a-47eb-922a-c9e1f46c1f76","order_by":3,"name":"Milton Lima Neto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACZuYGECXDBhPgh9IJuLUwNoL08EC1GDBINhDSwgDVwgDTYnCAgBbddsb2Bx93MPDwiR1+wFxQ8UfO+EbuwYc/dzDkmTdg12J2mLGxceYZoMOk0wyYZ5wxMDa7kZdszHuGoVjmAG4tzbxtIC0J5r952wwSt93IMZNmbGNInIHDYUha0j8w8/4zSNw8I8f850/itOQYMPM2GCRukMgxY+AloGXmzDYJkJYCZp5jxsYSZ94YS/OekSiWwKXl/OEDHz622cjJz07fwMxTIyfH355j+PHnDps8XFqgAF2asYGABkzA2ECqjlEwCkbBKBjGAABMGFAxTkq3KAAAAABJRU5ErkJggg==","orcid":"","institution":"São Paulo State University (UNESP)","correspondingAuthor":true,"prefix":"","firstName":"Milton","middleName":"Lima","lastName":"Neto","suffix":""}],"badges":[],"createdAt":"2025-05-28 13:08:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6768384/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6768384/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84695328,"identity":"f6eff734-4d46-40fb-ae2b-f301e6f7cb6e","added_by":"auto","created_at":"2025-06-16 10:34:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106937,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e), biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), and synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e) on sorghum germination and biomass. (A) Germination rate (%) over two days. (B) Root and shoot biomass (g) after 30 days of hydroponic growth. Seeds were pre-treated with 0 (control), 10, or 100 mM of each silver form. Error bars represent ± standard deviation (SD) of the mean (n = 5). Different letters above bars indicate significant differences according to Tukey's HSD test (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/1103d2d924f85876565bc116.png"},{"id":84695329,"identity":"aa955dda-e1c6-4c1a-b9eb-1760fad5aa57","added_by":"auto","created_at":"2025-06-16 10:34:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124785,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e), biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), and synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e) on gas exchange parameters in sorghum seedlings. (A) Net photosynthetic rate (\u003cem\u003eA\u003c/em\u003e). (B) Stomatal conductance (\u003cem\u003eg\u003c/em\u003es). (C) Intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration (\u003cem\u003eC\u003c/em\u003ei). (D) Transpiration rate (\u003cem\u003eE\u003c/em\u003e). Seedlings were grown hydroponically for 30 days with 0 (control), 10, or 100 mM of each silver form. Error bars represent ± standard deviation (SD) of the mean (n = 5). Different letters above bars indicate significant differences according to Tukey's HSD test (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/a57356acf17686d01fce9144.png"},{"id":84696778,"identity":"eb4e145f-15f7-4462-b6c3-f307cf34855a","added_by":"auto","created_at":"2025-06-16 10:42:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":216275,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e), biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), and synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e) on chlorophyll \u003cem\u003ea\u003c/em\u003e fluorescence parameters in sorghum seedlings. (A) Maximum quantum yield of PSII (Fv/Fm). (B) Effective quantum yield of PSII (Y(II) or ΦPSII). (C) Apparent electron transport rate (ETR). (D) Non-photochemical quenching (NPQ), showing both fast-relaxing (NPQf, blue) and slow-relaxing (NPQs, red) components. Seedlings were grown hydroponically for 30 days with 0 (control), 10, or 100 mM of each silver form. Error bars represent ± standard deviation (SD) of the mean (n = 5). Different letters above bars indicate significant differences according to Tukey's HSD test (p \u0026lt; 0.05). For NPQ (D), different letters above the \u003cem\u003estacked\u003c/em\u003e bars indicate significant differences in \u003cem\u003etotal\u003c/em\u003e NPQ.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/5844909dc5f1b399f52631f6.png"},{"id":84695334,"identity":"3f48c41e-9839-4185-b486-0ee31683cd30","added_by":"auto","created_at":"2025-06-16 10:34:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":103377,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e), biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), and synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e) on oxidative stress markers in sorghum seedlings. (A) Hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) content. (B) Thiobarbituric acid reactive substances (TBARS) content, expressed as malondialdehyde (MDA) equivalents. Seedlings were grown hydroponically for 30 days with 0 (control), 10, or 100 mM of each silver form. Error bars represent ± standard deviation (SD) of the mean (n = 5). Different letters above bars indicate significant differences according to Tukey's HSD test (p \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/cef83905a77678efcd41ecbc.png"},{"id":84696776,"identity":"ad6a47a2-9b1e-461e-b369-1f200d90aaab","added_by":"auto","created_at":"2025-06-16 10:42:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":104858,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) biplot showing the relationships between different treatments and measured parameters in sorghum seedlings. Seedlings were grown hydroponically for 30 days with 0 (control), 10, or 100 mM of silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e), biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), or synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e). The first two principal components (PC1 and PC2) are shown, explaining 76% and 13.4% of the total variance, respectively. Colored circles represent the different treatment groups. Red arrows represent the loadings of the measured variables: A (net photosynthetic rate), APX (ascorbate peroxidase activity), Car (carotenoid content), CAT (catalase activity), Chl \u003cem\u003ea\u003c/em\u003e (chlorophyll \u003cem\u003ea\u003c/em\u003e content), Chl \u003cem\u003eb\u003c/em\u003e (chlorophyll \u003cem\u003eb\u003c/em\u003e content), Chl \u003cem\u003eT\u003c/em\u003e (total chlorophyll content), \u003cem\u003eC\u003c/em\u003ei (intercellular CO2 concentration), \u003cem\u003eE\u003c/em\u003e (transpiration rate), ETR (apparent electron transport rate), Fv/Fm (maximum quantum yield of PSII), \u003cem\u003eg\u003c/em\u003es (stomatal conductance), H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (hydrogen peroxide content), MD (membrane damage), NPQ (non-photochemical quenching), NPQf (fast-relaxing component of NPQ), NPQs (slow-relaxing component of NPQ), Root Biomass, Shoot Biomass, Total Biomass, Root Length, Shoot Length, RWC (relative water content), SOD (superoxide dismutase activity), and TBARS (thiobarbituric acid reactive substances content). The color scale (Contrib) indicates the relative contribution of each variable to the principal components.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/f89d121604b20afaa9f7a822.png"},{"id":84696784,"identity":"1e336e2b-056e-4fd8-b8b7-31db5ac362df","added_by":"auto","created_at":"2025-06-16 10:42:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":90053,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage differences in physiological and biochemical parameters between sorghum seedlings primed with 100 mM biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e) and non-primed seedlings under salinity stress (100 mM NaCl). Positive values indicate that AgNP\u003csub\u003eb\u003c/sub\u003e-primed plants had higher values than non-primed, salt-stressed plants, while negative values indicate lower values. Measured parameters include: net photosynthetic rate (\u003cem\u003eA\u003c/em\u003e), ascorbate peroxidase activity (APX), total biomass (Biomass), carotenoid content (Car), catalase activity (CAT), total chlorophyll content (Chl \u003cem\u003eT\u003c/em\u003e), transpiration rate (\u003cem\u003eE\u003c/em\u003e), apparent electron transport rate (ETR), stomatal conductance (\u003cem\u003eg\u003c/em\u003es), hydrogen peroxide content (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e), membrane damage (MD), non-photochemical quenching (NPQ), relative water content (RWC), superoxide dismutase activity (SOD), and thiobarbituric acid reactive substances content (TBARS). Error bars represent ± standard deviation (SD) of the mean (n = 5). Asterisks indicate significant differences between primed and non-primed plants (p \u0026lt; 0.05)\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/3ca55eabcc5b917d9a5e1b18.png"},{"id":91683170,"identity":"181e7d99-5958-4a17-a2cc-ea0f52a5070b","added_by":"auto","created_at":"2025-09-19 07:02:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2184350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6768384/v1/904d80bd-c816-4b4e-8413-3aa6dccb0295.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mycobiogenic Silver Nanoparticle Priming: A Strategy to Mitigate Salinity Stress in Sorghum","fulltext":[{"header":"1. Background","content":"\u003cp\u003eAbiotic stresses, particularly salinity, pose a major threat to global food security, and these challenges are projected to intensify under climate change scenarios (Hasegawa et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The significant threat of salinity to food security necessitates innovative strategies to improve plant stress resilience for sustainable agriculture. Nanotechnology offers innovative approaches for mitigating abiotic stress impacts on crop plants through mechanisms including targeted nutrient delivery, modulation of stress signaling, and improved resource use efficiency. Nanoparticles (NP), typically ranging from 1 to 100 nm in size, possess unique physicochemical properties due to their high surface area-to-volume ratio, which allows for enhanced interaction with plant systems (Yusefi-Tanha et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among various nanomaterials, silver nanoparticles (AgNP) have attracted considerable attention in plant science due to their potential to enhance stress tolerance, attributed partly to their antimicrobial properties and their ability to modulate plant physiological processes (Siddiqi and Husen, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). AgNP application has been shown to enhance plant stress tolerance by modulating key physiological processes, including antioxidant enzyme activities, nutrient absorption, and root system development, potentially aiding plants in coping with abiotic stresses (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effects of AgNP on plants are complex and often contradictory, with beneficial and harmful impacts reported depending on factors such as NP synthesis method, concentration, size, physicochemical properties, environmental conditions, and plant species (Chen et al, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Siddiqi and Husen, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For instance, Ziotti et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Khan et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) demonstrated that AgNP exposure can promote plant growth and alleviate stress. Nonetheless, other studies have reported phytotoxic effects at higher concentrations, including reduced seed germination, impaired root growth, and hormonal imbalances (Yang \u003cem\u003eet al\u003c/em\u003e., 2022; Matras et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The balance between beneficial and detrimental outcomes often relates to how AgNP influences various mechanisms, such as the modulation of antioxidant defenses, water uptake, and gene expression (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). One of the primary mechanisms proposed to underlie these diverse plant responses is the modulation of reactive oxygen species (ROS) production (Yan and Chen, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eReactive oxygen species (ROS) play a complex, dual role in plant biology. At low concentrations, ROS act as signaling molecules, triggering various developmental processes and stress responses (Foyer and Hanke \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, excessive ROS accumulation leads to oxidative stress, damaging cellular components and inhibiting growth. This duality \u0026ndash; redox signaling versus oxidative damage \u0026ndash; is crucial for understanding the effects of AgNP on plants. AgNP have been shown to influence ROS levels, which may be a key factor driving their biological effects, whether positive or negative (Ziotti et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zwar et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A biphasic dose-response is often observed, where low concentrations of AgNP potentially stimulate growth through ROS signaling, while higher concentrations may induce oxidative stress and inhibit growth (Ziotti et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mirzajini \u003cem\u003eet al\u003c/em\u003e., 2013). Indeed, previous studies have reported detrimental effects of AgNP, including the generation of oxidative stress, inhibition of photosynthesis, and reduced plant growth, often associated with high exposure doses (Yan and Chen, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile chemically synthesized AgNP (AgNP\u003csub\u003es\u003c/sub\u003e) have shown some success in crop applications (Siddiqi and Husen \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), concerns remain regarding their potential environmental impacts and toxicity. Biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e), synthesized using plant extracts or microorganisms, offer a more sustainable, cost-effective, and environmentally friendly alternative (Abasi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Fungi are particularly promising for AgNP\u003csub\u003eb\u003c/sub\u003e synthesis due to their metabolic capabilities, efficient biomass production, and ease handling (Ottoni et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Fungal synthesis often utilizes biomolecules as reducing and stabilizing agents, potentially yielding NP with high colloidal stability, low agglomeration tendency and enhanced efficacy in plant systems (Costa et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Malik et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recent studies highlight the diverse applications and complex effects of mycogenic AgNP\u003csub\u003eb\u003c/sub\u003e: they can influence germination and growth in a dose- and species-dependent manner, sometimes inhibiting (e.g, in rice Ottoni et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and sometimes promoting (e.g. in safflowher, Zhu et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, fungal AgNP\u003csub\u003eb\u003c/sub\u003e have demonstrated efficacy in alleviating biotic stress, partly by modulating plant antioxidant systems (e.g, in tomato, Narware et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Understanding whether the production method (biogenic vs. synthetic) also modulates the observed divergent results is an important question in science.\u003c/p\u003e \u003cp\u003eSeed priming, a pre-sowing treatment that involves controlled hydration, is a well-established technique for improving germination and seedling vigor. Combining seed priming with nanoparticle application (nanopriming) represents a promising strategy for delivering the benefits of AgNP directly to the developing seedlings and enhancing their effects. A growing number of studies have shown that seed priming with AgNP promoted seedling development, including increased root and shoot growth, improved biomass accumulation, and enhanced photosynthetic efficiency (Zhou et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the precise physiological and biochemical mechanisms underlying the beneficial effects of AgNP\u003csub\u003eb\u003c/sub\u003e priming, particularly in the context of abiotic stress tolerance, remain to be fully elucidated (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to improving seed germination and early growth under non-stressed conditions, AgNP seed priming has been shown to increase the stress tolerance of some crops such as wheat and barley (Mohamed et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Cembrowska-Lech and Rybak, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSalinity is a major abiotic stress affecting crop yield, productivity and reducing the land-usage area for agricultural practices (Wahid et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It negatively impacts plants through a cascade of physiological and biochemical disruptions, including damage to cell membranes, the overproduction of reactive oxygen species (ROS) leading to oxidative stress, reduced photosynthetic efficiency, and impaired stomatal function (Munns and Tester, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Excessive accumulation of sodium (Na⁺) and chloride (Cl⁻) ions causes ionic imbalances, further disrupting nutrient uptake and cellular integrity. To cope with salinity, plants employ various defense mechanisms such as regulating ion uptake and transport, synthesizing protective osmolytes like proline, and modulating hormone levels, particularly abscisic acid (ABA) (Munns et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given its economic importance in arid and semi-arid regions and its inherent tolerance to several abiotic stresses, sorghum [\u003cem\u003eSorghum bicolor\u003c/em\u003e (L.) Moench], a C4 cereal crop, serves as a valuable model system for studying plant responses to stress, including the potential of novel approaches like nanopriming to enhance salinity tolerance.\u003c/p\u003e \u003cp\u003eDespite the growing interest in AgNP\u003csub\u003eb\u003c/sub\u003e for agricultural applications, few studies have directly compared their effects to those of AgNP\u003csub\u003es\u003c/sub\u003e on plant growth and stress responses, particularly when applied as a seed priming agent. Furthermore, most studies have focused on a limited range of physiological parameters, lacking a comprehensive assessment of the underlying mechanisms (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, while some studies suggest AgNP\u003csub\u003eb\u003c/sub\u003e priming can enhance stress tolerance, the specific physiological and biochemical mechanisms involved, particularly in a C4 crop like sorghum, remain to be fully elucidated. Thus, this study aimed to: 1) compare the effects of a biogenic and a synthetic AgNP, and AgNO\u003csub\u003e3\u003c/sub\u003e, on sorghum seed germination and early seedling growth; 2) investigate the physiological and biochemical mechanisms underlying AgNP\u003csub\u003eb\u003c/sub\u003e-mediated responses; and 3) evaluate the potential of AgNP\u003csub\u003eb\u003c/sub\u003e seed priming as a strategy for improving sorghum performance under salinity stress. We hypothesized that: 1) AgNP\u003csub\u003eb\u003c/sub\u003e seed priming improves sorghum germination and seedling growth under both non-stressed and saline conditions; and 2) AgNP\u003csub\u003eb\u003c/sub\u003e-induced improvement is associated with enhanced antioxidant defenses and improved photosynthetic efficiency, particularly under salinity.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Synthesis and characterization of biogenic and chemically synthesized silver nanoparticles\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAspergillus niger\u003c/em\u003e IBCLP20 was initially cultured on malt extract agar (MEA) medium composed of (g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e): malt extract (20.0), glucose monohydrate (20.0), bacteriological peptone (1.0), and agar (15.0), and incubated for 7 days. Fungal biomass was obtained by transferring five 6 mm-diameter agar disks from the culture into 50 mL of ME broth (MEA without agar) in a 250 mL Erlenmeyer flask, followed by incubation at 30\u0026deg;C and 150 rpm for 72 hours. After this period, the biomass was filtered and thoroughly washed with deionized water. Approximately 10 g of wet biomass was then transferred to a 250 mL Erlenmeyer flask containing 100 mL of deionized water and incubated again under the same conditions (30\u0026deg;C, 150 rpm) for an additional 72 hours. The biomass was removed by filtration using Whatman No. 1 filter paper, and the resulting supernatant was further filtered through a 0.22 \u0026micro;m membrane filter. This cell-free filtrate was transferred to a 50 mL Erlenmeyer flask, where silver nitrate (AgNO₃) was added to a final concentration of 1 mM. The mixture was incubated in the dark at 30\u0026deg;C and 150 rpm for 72 hours.\u003c/p\u003e \u003cp\u003eThe formation of AgNP\u003csub\u003eb\u003c/sub\u003e/IBCLP20 was initially indicated by a visible color change in the reaction mixture, shifting from yellow to brown. This transformation was further confirmed by UV-visible spectrophotometry, which revealed a characteristic surface plasmon resonance (SPR) band at 423 nm. According to Silva et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), AgNP\u003csub\u003eb\u003c/sub\u003e synthesized by \u003cem\u003eAspergillus niger\u003c/em\u003e IBCLP20 were predominantly spherical, as observed by transmission electron microscopy (TEM), with particle sizes ranging from 37.4 to 67.4 nm. In aqueous dispersion, these nanoparticles exhibited a hydrodynamic diameter of 80.5 nm, as determined by dynamic light scattering (DLS), a zeta potential of -38.56 mV, indicating good colloidal stability and a polydispersity index (PDI) of 0.215.\u003c/p\u003e \u003cp\u003eSilver-supported carbon nanoparticles (Ag/C) with 20% metal loading were synthesized following the sodium borohydride reduction method, as described by Fontes et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), using AgNO₃ (Aldrich) as the metal precursor. The process of metal reduction started when the metal sources were added and diluted in a mixture of water/2-propanol (50/50,v/v) followed by addition of carbon Vulcan XC 72 support dispersed in the solution. The mixture was submitted to ultrasonic agitation for 10 minutes. Then, a solution of sodium borohydride (NaBH\u003csub\u003e4\u003c/sub\u003e) diluted in 0.01 mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e NaOH was added and kept under mechanical stirring for 30 minutes at room temperature. Finally, the mixture was vacuum filtered, and the solid part, AgNP\u003csub\u003es\u003c/sub\u003e, were washed with deionized water (ultrapure) and dried in the incubator at 70\u0026deg;C for 2 hours. The particle sizes, as determined by TEM, ranged from 10.0 to 20.0 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Plant material and germination assay\u003c/h2\u003e \u003cp\u003eSeeds of sorghum (\u003cem\u003eSorghum bicolor\u003c/em\u003e (L.) Moench) from the cultivar BRS-658 were provided by EMBRAPA Milho Sorgo, Brazil. Seeds were disinfected by immersion in 2% (v/v) sodium hypochlorite solution for 10 minutes and rinsed abundantly with sterile water. For the germination assay, seeds were placed in two sheets of Germitest germination paper. The paper was then moistened with a volume of solution six times the mass of the paper, as described by Ziotti et al (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Zwar \u003cem\u003eet al\u003c/em\u003e. (2022). Seeds were treated with different concentrations (0, 10 and 100 mM) of AgNO\u003csub\u003e3\u003c/sub\u003e, biogenic AgNPs (AgNP\u003csub\u003eb\u003c/sub\u003e), or synthetic AgNPs (AgNP\u003csub\u003es\u003c/sub\u003e) in separate Petri dishes. The control treatment consisted of seeds moistened with distilled water (0 mM). The Petri dishes were placed in a growth chamber under controlled conditions: 27\u003csup\u003eo\u003c/sup\u003eC, 75% relative humidity, 450 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e irradiance, and 12-hour photoperiod. Germination was assessed daily, with the criterion for germination being a radicle length of at least 5 mm (Ziotti et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The experiment was conducted with five replicates per treatment, with each replicate consisting of a Petri dish containing 30 seeds. The Petri dishes were arranged in the growth chamber in a completely randomized design to minimize the influence of any potential environmental gradients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Seedling experiments\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Effects of AgNP and AgNO\u003csub\u003e3\u003c/sub\u003e on seedling growth\u003c/h2\u003e \u003cp\u003eSorghum seedlings, previously germinated as described in section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e2.2\u003c/span\u003e, were transferred to a hydroponic system in a greenhouse with a naturally controlled environment. The hydroponic system consisted of five-liter plastic pots filled with a \u0026frac12; concentration of Hoagland and Arnon's nutrient solution (Hoagland and Arnon, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1950\u003c/span\u003e). The nutrient solution was renewed weekly, and the pH was monitored daily and adjusted to 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 using 1M KOH when needed. Continuous aeration was provided using an air pump to ensure adequate oxygenation of the root system. Plants were supported with polystyrene cover in the pots.\u003c/p\u003e \u003cp\u003eAfter 30 days of cultivation, the plants were harvested. Root and aboveground fresh biomass were weighed separately using a semi-analytical scale. Plant materials were then frozen in liquid nitrogen and stored at -80\u0026deg;C for further analysis. The experiment was conducted with five biological replicates per treatment, with each replicate consisting of a 5L pot containing two plants. The pots were arranged in the greenhouse using a completely randomized design to minimize the influence of any potential environmental gradients. In this experiment, seedlings were grown using the initial treatments from the germination assay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Seed priming with AgNP\u003csub\u003eb\u003c/sub\u003e and salinity tolerance\u003c/h2\u003e \u003cp\u003eA second experiment was conducted using a hydroponic system with NaCl-induced salt stress to investigate the potential AgNP\u003csub\u003eb\u003c/sub\u003e seed priming to enhance salinity tolerance in sorghum. Seeds were exposed to 0 or 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e for 24 h and then germinated as described above. After 10 days of germination in Germitest paper rolls, the seedlings were transplanted to a hydroponic system as described above. Four treatment groups were established: control (no AgNPb, no NaCl), AgNP\u003csub\u003eb\u003c/sub\u003e priming (100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, no NaCl), salinity stress (no AgNPb, 100 mM NaCl), and combined treatment (100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, 100 mM NaCl). A set of plants was watered with a modified Hoagland and Arnon's nutrient solution (Hoagland and Arnon, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1950\u003c/span\u003e). Another group of plants received the addition of 100 mM NaCl (50 mM per day, to avoid osmotic shock) (Dehnave \u003cem\u003eet al\u003c/em\u003e. 2024). Plants were cultivated for 10 days after the start of salinity treatment and harvested for analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Relative water content, membrane damage and pigment content\u003c/h2\u003e \u003cp\u003eLeaf and root samples (0.25 g) were stored in test tubes with deionized water at 7\u0026deg;C in the dark and subsequently weighed to determine their turgid mass (TM). The samples were then dried in an oven with forced air circulation at 70\u0026deg;C until constant weight to determine their dry mass (DM). Relative water content (RWC) was calculated according to the formula: RWC = [(FM \u0026ndash; DM) / (TM \u0026ndash; DM)] x 100, following the methodology used by Lima Neto et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe membrane damage was assessed with 0.25 g of leaf or root segments immersed in test tubes containing deionized water. The tubes were incubated in a shaking bath at 25\u0026deg;C for 6 hours, and the electrical conductivity of the medium (L\u003csub\u003e1\u003c/sub\u003e) was measured. Subsequently, the segments were boiled at 90\u0026deg;C for 60 minutes in closed test tubes and cooled to ambient temperature. After cooling, the electrical conductivity (L\u003csub\u003e2\u003c/sub\u003e) was measured. The membrane damage (MD) was estimated by the ratio [MD = (L\u003csub\u003e1\u003c/sub\u003e / L\u003csub\u003e2\u003c/sub\u003e) \u0026times; 100] (Lima Neto et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe determination of total chlorophylls and carotenoids was performed after extraction of leaf samples (0.25 mg) in cold 80% acetone in the dark. The absorbance of the extract was measured using a spectrophotometer (VERSAMAX, Molecular Devices, USA) at different wavelengths according to Lichtenthaler and Wellburn (1983).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Gas exchange and chlorophyll fluorescence\u003c/h2\u003e \u003cp\u003eGas exchange parameters were assessed using an infrared gas analyzer (IRGA, LI-6400XT, Li-COR, Lincoln, NE, USA) equipped with a leaf chamber fluorometer (LI-6400-40, Li-COR, Lincoln, NE, USA). Measurements were taken on the second fully expanded leaf from each plant. The IRGA chamber conditions were regulated to maintain a photosynthetic photon flux density (PPFD) of 600 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, an ambient CO₂ concentration of 380 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, a vapor pressure deficit (VPD) of 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 kPa, and a chamber air temperature of 27\u0026deg;C. Blue light intensity within the chamber was set to represent 10% of the total PPFD to enhance stomatal opening (Busch et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChlorophyll \u003cem\u003ea\u003c/em\u003e fluorescence was recorded using the fluorometer coupled to the IRGA. To determine the initial fluorescence (\u003cem\u003eFo\u003c/em\u003e) and the maximum fluorescence (\u003cem\u003eFm\u003c/em\u003e), leaves were dark-adapted for 30 minutes. Following dark adaptation, leaves were illuminated with actinic light at an intensity of 600 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Saturation pulses were administered with an intensity of 8,000 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for a duration of 0.7 seconds. Various fluorescence parameters were evaluated, including the potential quantum yield of PSII [\u003cem\u003eFv/Fm = (Fm - Fo)/Fm\u003c/em\u003e], the effective quantum yield of PSII [\u003cem\u003eY(II) = (F\u0026thinsp;\u0026lt;\u0026thinsp;m' - Fs)/Fm'\u003c/em\u003e], the photochemical quenching (\u003cem\u003eqP\u003c/em\u003e) and non-photochemical quenching (\u003cem\u003eNPQ = (Fm - Fm')/Fm')\u003c/em\u003e, the quantum yield of non-regulated non-photochemical energy loss in PSII [\u003cem\u003eY(NO)\u0026thinsp;=\u0026thinsp;F/Fm\u003c/em\u003e], and the quantum yield of regulated non-photochemical energy loss in PSII [\u003cem\u003eY(NPQ)\u0026thinsp;=\u0026thinsp;F/Fm' - F/Fm\u003c/em\u003e]. Here, \u003cem\u003eFm\u003c/em\u003e and \u003cem\u003eFo\u003c/em\u003e are the maximum and minimum fluorescence yields of dark-adapted leaves, \u003cem\u003eFm'\u003c/em\u003e and \u003cem\u003eFs\u003c/em\u003e represent the corresponding maximum and steady-state fluorescence yields under light-adapted conditions (Murchie and Lawson, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Lipid peroxidation and hydrogen peroxide\u003c/h2\u003e \u003cp\u003eLipid peroxidation was assessed based on the formation of thiobarbituric acid reactive substances (TBARS) using 0.2 g of fresh leaf tissue. TBARS concentration was calculated using its absorption coefficient (155 mM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Cakmak and Horst, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content was determined by the Amplex Red oxidation method (Zhou et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) using 250 mg of fresh leaf tissue. Leaf segments were ground in a 0.1M phosphate buffer (pH 7.5). The homogenate was then squeezed through one layer of Miracloth. The crude extract was centrifuged at 12,000 rcf for 30 minutes at 4\u003csup\u003eo\u003c/sup\u003eC. According to the manufacturer's protocol, the supernatant was supplemented with 10 mM Amplex-Red and 10 U of horseradish peroxidase. The production of resorufin was measured at 560 nm in a spectrophotometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Protein extraction and enzymatic assays\u003c/h2\u003e \u003cp\u003eFresh sorghum leaves were collected and immediately frozen in liquid nitrogen. Approximately 0.1 g of the frozen leaves were ground into a fine powder using a mortar and pestle. An extraction buffer was prepared, consisting of 100 mM K\u003csup\u003e+\u003c/sup\u003e-phosphate buffer (pH 7.5), 1 mM EDTA, 1 mM ascorbate and 1 mM PMSF. The powdered leaf material was added to the extraction buffer at a ratio of 1:1.5 (w/v). The mixture was then centrifuged at 14,000 x g for 15 minutes at 4\u0026deg;C, and the supernatant was carefully collected. Soluble protein content was quantified from the above extract by the Bradford method (Bradford, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) using BSA as standards with a spectrophotometer (VERSAMAX, Molecular Devices, USA).\u003c/p\u003e \u003cp\u003eSuperoxide dismutase (SOD - E.C. 1.15.1.1) activity was determined using the nitroblue tetrazolium chloride (NBT) photoreduction method. Leaf extracts were added to a solution containing 50 mM potassium phosphate buffer (pH 7.8), 0.1 mM EDTA, 13 mM L-methionine, 2 \u0026micro;M riboflavin, and 75 \u0026micro;M NBT, incubated in darkness. The photoreduction reaction was activated under a 30 W incandescent lamp at 25\u0026deg;C for 6 minutes, and absorbance was read at 540 nm (Giannopolotis and Ries, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). SOD activity was defined as the enzyme amount causing 50% inhibition of NBT photoreduction, with units calculated per U mg protein\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAscorbate peroxidase (APX - E.C. 1.11.1.11) activity was measured in a reaction mixture consisting of 0.5 mM ascorbate and 0.1 mM EDTA in a 100 mM potassium phosphate buffer (pH 7.0), supplemented with enzyme extract. The reaction commenced upon the addition of 30 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, and the decline in absorbance at 290 nm was monitored for 300 seconds. APX activity was expressed as U mg protein\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as described by Nakano and Asada (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCatalase (CAT - E.C. 1.11.1.6) activity was evaluated by monitoring the decomposition of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at 240 nm. The assay was initiated by mixing the enzyme extract in 50 mM potassium phosphate buffer (pH 7.0) with 20 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The decrease in absorbance was recorded over a period of 300 seconds (Havir and McHale, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). CAT activity was calculated using the molar extinction coefficient of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (36 mM cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and expressed as U mg protein\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe experimental design for both experiments (seed priming exposure of AgNO\u003csub\u003e3\u003c/sub\u003e, AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003eb\u003c/sub\u003e priming to saline tolerance) was completely randomized, with five biological replicates per treatment. Each replicate consisted of a 5L pot containing two plants. Normality of the data for each variable was assessed using the Shapiro-Wilk test, and homogeneity of variance was assessed using Levene's test. If these assumptions were violated, data were transformed using a log transformation, or the non-parametric Kruskal-Wallis test was used followed by Dunn's post-hoc test. For comparisons among treatments in both experiments, one-way ANOVA was used, followed by Tukey's HSD post-hoc test to compare means when significant differences were detected. All statistical analyses were performed using R software (version 4.4.2) and RStudio (version 2023.09.0\u0026thinsp;+\u0026thinsp;420). A significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used for all tests.\u003c/p\u003e \u003cp\u003ePrincipal component analysis (PCA) was used to explore relationships among the measured physiological parameters and identify potential patterns associated with treatment groups. Prior to PCA, data were scaled (z-score standardization) to standardize variables with different scales. The number of principal components to retain was determined using the broken-stick criterion (V\u0026iacute;tolo et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). PCA was performed using the R packages FactoMineR and factoextra.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Effects of biogenic and synthetic AgNP on germination and biomass allocation\u003c/h2\u003e \u003cp\u003eSilver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e) exposure had the most detrimental effect on early seedling development, inhibiting germination in a dose-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Germination was significantly reduced at both 10 and 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e compared to the control. AgNP\u003csub\u003eb\u003c/sub\u003e treatments resulted in high germination rates, with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e showing the highest mean percentage on day one, significantly exceeding the control and AgNO\u003csub\u003e3\u003c/sub\u003e treatments. AgNP\u003csub\u003es\u003c/sub\u003e treatments resulted in significantly higher germination rates than the control on day 1, while showing no significant difference from the control by day 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding biomass accumulation after 30 days of hydroponic growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), AgNP\u003csub\u003eb\u003c/sub\u003e treatment at 100 mM resulted in a significant increase in both root and shoot biomass, indicating a positive impact on overall plant growth and development. Both concentrations of AgNO\u003csub\u003e3\u003c/sub\u003e exposure resulted in significantly lower total biomass compared to the control, primarily due to a significant reduction in shoot biomass, confirming its negative impact on plant growth. AgNP\u003csub\u003es\u003c/sub\u003e, at either 10 or 100 mM, did not significantly affect total biomass accumulation compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Physiological parameters\u003c/h2\u003e \u003cp\u003eFollowing the analysis of germination rates and biomass allocation, we investigated the effects of the different treatments on various physiological and biochemical parameters (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). AgNO\u003csub\u003e3\u003c/sub\u003e, particularly at 100 mM, significantly reduced the relative water content (RWC) compared to the control and AgNP\u003csub\u003eb\u003c/sub\u003e treatments. In contrast, AgNP\u003csub\u003eb\u003c/sub\u003e treatment at both concentrations increased RWC significantly higher than the control and both concentrations of AgNO\u003csub\u003e3\u003c/sub\u003e. Both concentrations of AgNP\u003csub\u003eb\u003c/sub\u003e resulted in similar RWC values and both concentrations of AgNP\u003csub\u003es\u003c/sub\u003e maintained RWC levels not significantly different from the control. Membrane damage (MD), an indicator of cellular integrity, was significantly increased by AgNO\u003csub\u003e3\u003c/sub\u003e exposure in a dose-dependent manner, with the highest MD observed at 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e. Both 10 mM and 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatments resulted in significantly lower MD compared to the control. Both concentrations of AgNP\u003csub\u003es\u003c/sub\u003e resulted in similar levels of MD compared to 10 mM AgNO\u003csub\u003e3\u003c/sub\u003e, but significantly lower than 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Relative water content (RWC, %), membrane damage (MD, %), chlorophyll \u003cem\u003ea\u003c/em\u003e (Chla, mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FM), chlorophyll \u003cem\u003eb\u003c/em\u003e (Chlb, mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FW), total chlorophyll [ChlT, mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FW) and carotenoids content [Car (mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FW)] in sorghum leaves. Seedlings grown from seeds pre-treated with 0, 10 or 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e, biogenic silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e) or synthetic AgNP (AgNP\u003csub\u003es\u003c/sub\u003e). Data are the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD of five replicates. Different letters within a row indicate significant differences according toTukey's HSD test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAgNO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAgNPb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eAgNPs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRWC (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.92\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e78.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMD (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.84a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e25.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChla\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eFM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChlb\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003eFM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChlT\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg g-1 FM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCar\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mg g\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eFM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e30.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn relation to pigment content, AgNO\u003csub\u003e3\u003c/sub\u003e significantly reduced chlorophyll \u003cem\u003ea\u003c/em\u003e, \u003cem\u003eb\u003c/em\u003e, and total chlorophyll compared to control plants in a dose-dependent manner (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Both concentrations of AgNP\u003csub\u003eb\u003c/sub\u003e significantly enhanced all chlorophyll pigments (a, b, and total) compared to the control and all other treatments. AgNP\u003csub\u003es\u003c/sub\u003e also increased chlorophyll content compared to the control and AgNO\u003csub\u003e3\u003c/sub\u003e treatments, but to a lesser extent than AgNP\u003csub\u003eb\u003c/sub\u003e, and this increase was not always statistically significant (e.g., Chl \u003cem\u003ea\u003c/em\u003e at 10 mM AgNP\u003csub\u003es\u003c/sub\u003e). Similarly, carotenoid content was significantly lower in AgNO\u003csub\u003e3\u003c/sub\u003e-treated plants compared to all other treatments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Both concentrations of AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e resulted in significantly higher carotenoid levels than the control and AgNO\u003csub\u003e3\u003c/sub\u003e treatments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Photosynthetic responses to different AgNP treatments\u003c/h2\u003e \u003cp\u003eGas exchange parameters were significantly influenced by different treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). AgNP\u003csub\u003eb\u003c/sub\u003e at 100 mM led to the highest stomatal conductance (\u003cem\u003egs\u003c/em\u003e), transpiration rate (\u003cem\u003eE\u003c/em\u003e), and photosynthetic rate (\u003cem\u003eA\u003c/em\u003e), while AgNO\u003csub\u003e3\u003c/sub\u003e at 100 mM consistently resulted in the lowest values for these parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). Specifically, \u003cem\u003eA, gs\u003c/em\u003e and \u003cem\u003eE\u003c/em\u003e were significantly higher in plants treated with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e compared to all other treatments. Conversely, 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e significantly reduced \u003cem\u003eA, gs\u003c/em\u003e and \u003cem\u003eE\u003c/em\u003e compared to all other treatments. Interestingly, AgNP\u003csub\u003eb\u003c/sub\u003e at 100 mM also resulted in the lowest intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration (\u003cem\u003eCi\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), while AgNO\u003csub\u003e3\u003c/sub\u003e at 100 mM had the highest \u003cem\u003eCi\u003c/em\u003e. In contrast to the significant effects of AgNP\u003csub\u003eb\u003c/sub\u003e and AgNO\u003csub\u003e3\u003c/sub\u003e, AgNP\u003csub\u003es\u003c/sub\u003e had a less pronounced impact on gas exchange. While AgNP\u003csub\u003es\u003c/sub\u003e did not significantly affect \u003cem\u003eA\u003c/em\u003e compared to the control, 10 mM AgNP\u003csub\u003es\u003c/sub\u003e significantly reduced \u003cem\u003eCi\u003c/em\u003e while 100 mM AgNP\u003csub\u003es\u003c/sub\u003e did not. Both 10 and 100 mM AgNP\u003csub\u003es\u003c/sub\u003e significantly decreased \u003cem\u003eE\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe potential quantum yield of PSII (\u003cem\u003eFvFm\u003c/em\u003e), a measure of the maximum efficiency of PSII photochemistry, was significantly decreased in plants treated with 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e, indicating damage or stress to PSII (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The other treatments did not significantly affect \u003cem\u003eFvFm\u003c/em\u003e compared to the control. However, plants treated with AgNP\u003csub\u003eb\u003c/sub\u003e (100 mM) showed the highest effective quantum yield of PSII [Y(II)], while those treated with AgNO\u003csub\u003e3\u003c/sub\u003e (100 mM) showed the lowest (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). AgNP\u003csub\u003es\u003c/sub\u003e at 10 mM did not significantly affect Y(II), but 100 mM AgNP\u003csub\u003es\u003c/sub\u003e significantly decreased Y(II) compared to control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). A similar trend was observed for the apparent electron transport rate (ETR), with the highest ETR observed in plants treated with AgNP\u003csub\u003eb\u003c/sub\u003e (100 mM) and the lowest ETR values were observed in plants treated with both 10 mM and 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Specifically, ETR was significantly higher in the 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatment compared to all other treatments, and significantly lower in both 10 and 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatments compared to the control and AgNP treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNon-photochemical quenching (NPQ), a mechanism for dissipating excess excitation energy as heat, was highest in plants treated with 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). This increase in NPQ was related to increases in both the slow-relaxing (NPQ\u003csub\u003es\u003c/sub\u003e) and fast-relaxing (NPQ\u003csub\u003ef\u003c/sub\u003e) components of NPQ. Plants treated with AgNP\u003csub\u003eb\u003c/sub\u003e showed significantly lower total NPQ compared to the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment, while plants treated with AgNP\u003csub\u003es\u003c/sub\u003e had no significant difference in total NPQ compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Reactive oxygen species and antioxidant response\u003c/h2\u003e \u003cp\u003eAgNO\u003csub\u003e3\u003c/sub\u003e at 100 mM induced the highest levels of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in leaves, significantly higher than all other treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). This was followed by 10 mM AgNO\u003csub\u003e3\u003c/sub\u003e, 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e and 100 mM AgNP\u003csub\u003es\u003c/sub\u003e, which were all significantly higher than the control. Both 10 mM AgNP\u003csub\u003eb\u003c/sub\u003e and 10 mM AgNP\u003csub\u003es\u003c/sub\u003e also had significantly higher H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels than the control. Lipid peroxidation, as measured by malondialdehyde (MDA) equivalents (TBARS content), showed a somewhat similar pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e and 100 mM AgNP\u003csub\u003es\u003c/sub\u003e treatments resulted in the highest TBARS levels, significantly higher than all other treatments. These were followed by 10 mM AgNO\u003csub\u003e3\u003c/sub\u003e and 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, which were not significantly different from each other but were significantly higher than the control, 10 mM AgNP\u003csub\u003es\u003c/sub\u003e and 10 mM AgNP\u003csub\u003es\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo investigate the antioxidant response, we measured the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) in sorghum leaves (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). SOD activity was significantly increased by all treatments compared to the control. The highest SOD activity was observed in the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment, followed by 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, and both concentrations of AgNP\u003csub\u003es\u003c/sub\u003e also resulted in significant increases in SOD activity, though generally to a lesser extent than the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e and 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatments. APX activity showed a similar pattern, with the highest activity in the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment, followed by the 10 and 100 mM of AgNP\u003csub\u003es\u003c/sub\u003e and 10 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatments. The 10 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatment did not significantly affect APX activity relative to control. CAT activity was significantly increased by both concentrations of AgNO\u003csub\u003e3\u003c/sub\u003e, 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, and 100 mM AgNP\u003csub\u003es\u003c/sub\u003e compared to the control. In contrast, 10 mM AgNP\u003csub\u003eb\u003c/sub\u003e and 10 mM AgNP\u003csub\u003es\u003c/sub\u003e did not significantly alter CAT activity from control levels. Overall, AgNO\u003csub\u003e3\u003c/sub\u003e, particularly at 100 mM, generally induced the greatest or among the greatest increases in the activities of the measured antioxidant enzymes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) activities in sorghum leaves. Activities were expressed in U mg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e protein. Seedlings grown from seeds pre-treated with 10 or 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e, biogenic (AgNP\u003csub\u003eb\u003c/sub\u003e) or synthetic silver nanoparticles (AgNP\u003csub\u003es\u003c/sub\u003e). Data are the means of five replicates\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Different letters within a row indicate significant differences according to Tukey's HSD test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAgNO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAgNPb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eAgNPs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e10 mM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100 mM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSOD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAPX\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.012c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.021b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.84a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCAT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Principal component analysis\u003c/h2\u003e \u003cp\u003ePrincipal component analysis (PCA) was conducted to explore the relationships between the different treatments and the measured variables, encompassing growth, physiological, and biochemical parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The first two principal components (PCs) explain 89.4% of the total variation (PC1: 76%, PC2: 13.4%), indicating that the PCA effectively summarizes the major physiological responses. The biplot reveals a clear separation of the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment, strongly associated with variables indicative of oxidative stress (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, TBARS) and increased antioxidant enzyme activities (SOD, APX, CAT). The 10 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment also shows a distinct separation, but to a lesser extent than 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e. Conversely, AgNP\u003csub\u003eb\u003c/sub\u003e treatment shows a separation mainly attributed to its positive association with variables related to plant growth and photosynthetic performance. This suggests a potential beneficial effect of the biogenic AgNP at this concentration. The AgNP\u003csub\u003eb\u003c/sub\u003e treatments also grouped more closely with growth and photosynthetic parameters then the AgNP\u003csub\u003es\u003c/sub\u003e treatments. The remaining treatments, including the control and both concentrations of AgNPs clustered more closely together, suggesting more similar effects on the measured variables, and a less pronounced deviation from the baseline physiological state represented by the control group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Effects of AgNP\u003csub\u003eb\u003c/sub\u003e priming on salinity tolerance\u003c/h2\u003e \u003cp\u003eTo investigate the potential of AgNP\u003csub\u003eb\u003c/sub\u003e seed priming to enhance salinity tolerance in sorghum, one group of seedlings was primed with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e while a control was not primed; both groups were subsequently exposed to 100 mM NaCl. The effects of priming on various physiological and biochemical parameters, relative to non-primed, salt-stressed plants, are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. AgNP\u003csub\u003eb\u003c/sub\u003e priming significantly increased net photosynthetic rate (\u003cem\u003eA\u003c/em\u003e) by approximately 125% compared to non-primed plants under salinity stress. Similarly, stomatal conductance (\u003cem\u003egs\u003c/em\u003e) and transpiration rate (\u003cem\u003eE\u003c/em\u003e) were also significantly higher (by 111% and 43%, respectively) in primed seedlings. The \u003cem\u003eETR\u003c/em\u003e was also strongly increased by AgNP\u003csub\u003eb\u003c/sub\u003e priming (197%), concomitant with a significant decrease in NPQ (58%). These results suggest that AgNP\u003csub\u003eb\u003c/sub\u003e priming helps improve photosynthetic function under salt stress, possibly by facilitating CO\u003csub\u003e2\u003c/sub\u003e uptake and enhancing the efficiency of light energy utilization.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, AgNP\u003csub\u003eb\u003c/sub\u003e priming resulted in a significant increase in relative water content (RWC) by 18%, indicating improved water status in the primed plants. Conversely, membrane damage (MD) was significantly reduced (by 52%) in AgNP\u003csub\u003eb\u003c/sub\u003e-primed seedlings, suggesting protection against salt-induced cellular damage. Regarding oxidative stress, AgNP\u003csub\u003eb\u003c/sub\u003e priming led to a significant reduction in TBARS (by 40%) and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (by 25%) levels compared to non-primed, salt-stressed plants. AgNP\u003csub\u003eb\u003c/sub\u003e priming significantly increased CAT activity by 87% compared with non-primed, salt-stressed plants. SOD activity was also significantly increased, by 20%, while APX activity showed a small but significant decrease with priming.\u003c/p\u003e \u003cp\u003eOverall, these results suggest that AgNP\u003csub\u003eb\u003c/sub\u003e seed priming can mitigate some of the negative impacts of salinity stress on sorghum seedlings, particularly by improving photosynthetic performance, water status, and reducing oxidative damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study aimed to compare the effects of mycogenic (AgNP\u003csub\u003eb\u003c/sub\u003e) and synthetic (AgNP\u003csub\u003es\u003c/sub\u003e) silver nanoparticles with silver nitrate (AgNO\u003csub\u003e3\u003c/sub\u003e) on sorghum germination, and seedling growth, and underlying physiological mechanisms, while also evaluating the AgNP\u003csub\u003eb\u003c/sub\u003e priming effect on subsequent salinity tolerance. Our results demonstrate that high concentrations of AgNO\u003csub\u003e3\u003c/sub\u003e are severely toxic to sorghum seedlings, while AgNP\u003csub\u003eb\u003c/sub\u003e, even at high concentrations, exhibit less toxicity and appear to promote some aspects of growth and increase photosynthesis. Synthetic AgNP showed intermediate effects.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Contrasting effects of AgNO\u003csub\u003e3\u003c/sub\u003e and silver nanoparticles on sorghum\u003c/h2\u003e \u003cp\u003eA key finding was the pronounced toxicity of AgNO\u003csub\u003e3\u003c/sub\u003e at the millimolar concentrations tested (10 and 100 mM), as evidenced by significant reductions in germination rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), seedling biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), relative water content (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and chlorophyll content (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, AgNO\u003csub\u003e3\u003c/sub\u003e exposure resulted in substantial increases in membrane damage (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), elevated levels of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and TBARS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating oxidative stress, and impairment of photosynthetic function (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings are consistent with previous studies demonstrating the toxicity of high concentrations of ionic silver (Ag\u003csup\u003e+\u003c/sup\u003e) to plants (Ziotti et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zwar et al., 2024). Silver ions are known to interfere with various cellular processes, including enzyme function, nutrient uptake, and DNA replication (Siddiqi and Husen, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The observed increase in antioxidant enzyme activities (SOD, APX, CAT) in response to AgNO\u003csub\u003e3\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) reflects a compensatory mechanism to mitigate the oxidative damage caused by excessive ROS production.\u003c/p\u003e \u003cp\u003eImportantly, both AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e exhibited significantly less toxicity than AgNO\u003csub\u003e3\u003c/sub\u003e at equivalent millimolar concentrations of total silver. This difference highlights the critical role of the form of silver (ionic versus nanoparticulate) in determining its phytotoxicity. While AgNP\u003csub\u003es\u003c/sub\u003e also induced some oxidative stress at 100 mM, as indicated by increased TBARS in the case of AgNP\u003csub\u003es\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in both AgNP treatments, the magnitude of these effects was considerably smaller than that observed with AgNO\u003csub\u003e3\u003c/sub\u003e. This suggests that the gradual release of Ag\u003csup\u003e+\u003c/sup\u003e ions from AgNP, or potentially other nanoparticle-specific interactions, results in a lower effective concentration of toxic Ag\u003csup\u003e+\u003c/sup\u003e within plant tissues compared to direct exposure to AgNO\u003csub\u003e3\u003c/sub\u003e (Ziotti et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Biogenic AgNP promotes growth and photosynthesis\u003c/h2\u003e \u003cp\u003eIn contrast to the detrimental effects of AgNO\u003csub\u003e3\u003c/sub\u003e, AgNP\u003csub\u003eb\u003c/sub\u003e exhibited a seemingly stimulatory effect on several growth and physiological parameters in sorghum seedlings under non-stresses conditions. This treatment resulted in the highest germination rate on day one (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), significantly increased root and shoot biomass (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), and enhanced photosynthetic performance, as evidenced by the highest values for net photosynthetic rate (\u003cem\u003eA\u003c/em\u003e), stomatal conductance (\u003cem\u003egs\u003c/em\u003e), effective quantum yield of PSII [\u003cem\u003eY(II)\u003c/em\u003e], and the electron transport rate (\u003cem\u003eETR\u003c/em\u003e) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The enhanced photosynthetic rate (\u003cem\u003eA\u003c/em\u003e) observed in the 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) is likely linked to the significantly higher stomatal conductance (\u003cem\u003egs\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Increased \u003cem\u003egs\u003c/em\u003e facilitates greater CO\u003csub\u003e2\u003c/sub\u003e uptake, providing more substrate for carbon fixation. This, coupled with the lower intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration (\u003cem\u003eCi\u003c/em\u003e), suggests a higher carboxylation efficiency in AgNP\u003csub\u003eb\u003c/sub\u003e-treated plants. Furthermore, AgNP\u003csub\u003eb\u003c/sub\u003e-treated plants maintained higher relative water content (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and showed increased levels of photosynthetic pigments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This improved photosynthetic efficiency, along with the maintenance of RWC and increased pigment content, could contribute to the increased biomass observed in AgNP\u003csub\u003eb\u003c/sub\u003e-treated plants (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eHowever, it is crucial to interpret these results within the context of the high AgNP\u003csub\u003eb\u003c/sub\u003e concentrations employed. The 10- and 100-mM concentrations used in this study are considerably higher than those typically considered environmentally relevant for nanoparticles. Therefore, the observed induction is unlikely to be representative of the effects expected at lower, more realistic exposure levels and requires careful mechanistic consideration. Several, non-exclusive, mechanisms could potentially explain these observations. One possibility is a hormetic response, where a substance that is toxic at high doses exhibits stimulatory effects at lower doses. While our experimental design, with only two AgNP\u003csub\u003eb\u003c/sub\u003e concentrations, does not allow for a definitive confirmation of hormesis, the seemingly positive effects at these high concentrations are consistent with the stimulatory phase of a such biphasic response (Bello-Bello et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, as shown in our second experiment, the 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e concentration was effective as a priming treatment for improving subsequent salinity tolerance (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe priming experiment demonstrated that priming with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e significantly mitigated the negative impacts of salinity stress on sorghum seedlings (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). AgNP\u003csub\u003eb\u003c/sub\u003e-primed plants subjected to 100 mM NaCl exhibited significantly improved photosynthetic performance (higher \u003cem\u003eA, gs, ETR\u003c/em\u003e and lower \u003cem\u003eNPQ\u003c/em\u003e), better water status (higher RWC), reduced membrane damage, and lower levels of oxidative stress markers (TBARS and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) compared to non-primed, salt-stressed plants. These findings provide compelling evidence that AgNP\u003csub\u003eb\u003c/sub\u003e priming can enhance salinity tolerance in sorghum (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlternatively, the enhanced growth in the 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatment could be related to indirect effects, such as the suppression of microbial growth in the hydroponic solution due to the known antimicrobial properties of silver nanoparticles (Mirzajani et al \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Reduced microbial load could potentially alleviate competition for nutrients or reduce the incidence of subclinical infections, thereby promoting seedling growth. It is also possible that the AgNP\u003csub\u003eb\u003c/sub\u003e, even at these high concentrations, are modulating ROS levels in a way that, while still elevated compared to the control, is less detrimental than the extreme oxidative stress induced by AgNO\u003csub\u003e3\u003c/sub\u003e. The relatively low membrane damage (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and the lower, but significant, increase of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) in the 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e treatment compared to AgNO\u003csub\u003e3\u003c/sub\u003e supports this possibility. Finally, unique properties of the biogenic AgNP\u003csub\u003eb\u003c/sub\u003e, related to their fungal-mediated synthesis, may also play a role that merits to be better understood (Ottoni et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Differential oxidative stress responses and ROS modulation\u003c/h2\u003e \u003cp\u003eThe observed differences in plant responses to AgNO\u003csub\u003e3\u003c/sub\u003e, AgNP\u003csub\u003eb\u003c/sub\u003e, and AgNP\u003csub\u003es\u003c/sub\u003e can be understood, at least in part, by considering their effects on reactive oxygen species (ROS) production, antioxidant defense systems, and photosynthetic processes. As previously discussed, ROS play a dual role in plants, acting as signaling molecules at low concentrations but causing oxidative damage at high concentrations (Foyer and Hanke, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our results clearly demonstrate that high concentrations of AgNO\u003csub\u003e3\u003c/sub\u003e (particularly 100 mM) induce significant oxidative stress in sorghum seedlings. This is evidenced by the elevated levels of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and TBARS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicators of oxidative damage to cellular components, and by the substantial increases in the activities of antioxidant enzymes SOD, APX, and CAT (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These enzymes represent a crucial line of defense against ROS, scavenging superoxide radicals (SOD), detoxifying hydrogen peroxide (APX and CAT), and preventing further oxidative damage (Foyer and Hanke, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The increased enzyme activities likely represent a compensatory response to the elevated ROS levels induced by AgNO\u003csub\u003e3\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eIn contrast to AgNO\u003csub\u003e3\u003c/sub\u003e, the AgNP treatments, and particularly AgNP\u003csub\u003eb\u003c/sub\u003e, resulted in a less pronounced oxidative stress response. While 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e did increase H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels compared to the control, the magnitude of this increase, and the corresponding increase in TBARS, was significantly lower than that observed with AgNO\u003csub\u003e3\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This suggests that, even at equivalent millimolar concentrations of total silver, the nanoparticulate forms of silver elicit a weaker oxidative stress response. This could be due to a slower release of Ag\u003csup\u003e+\u003c/sup\u003e ions from the nanoparticles compared to the readily available Ag\u003csup\u003e+\u003c/sup\u003e ions from AgNO\u003csub\u003e3\u003c/sub\u003e (Ziotti et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The lower membrane damage (MD) observed in the AgNP\u003csub\u003eb\u003c/sub\u003e treatments, especially 10 mM, compared to AgNO\u003csub\u003e3\u003c/sub\u003e further supports this notion. The potentially beneficial effects of 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e on growth and photosynthesis, both in absence and presence of salinity, raise intriguing questions about the role of ROS signaling. It's plausible that the AgNP\u003csub\u003eb\u003c/sub\u003e treatment, while increasing ROS production above control levels, maintains ROS within a range that allows for beneficial signaling effects without triggering severe oxidative damage. This is further supported by the results of the priming experiment, where AgNP\u003csub\u003eb\u003c/sub\u003e priming significantly reduced TBARS levels under salinity stress, indicating a protective effect against lipid peroxidation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.4 AgNP\u003csub\u003eb\u003c/sub\u003e-mediated photosynthetic enhancement and signaling pathways\u003c/h2\u003e \u003cp\u003eThe chlorophyll fluorescence data further support the enhanced photosynthetic capacity of plants treated with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e. The significantly higher effective quantum yield of PSII [Y(II)] (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and electron transport rate (ETR) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC) indicate improved efficiency of light energy utilization in these plants. Conversely, the reduced Fv/Fm, Y(II), and ETR observed in the 100 mM AgNO\u003csub\u003e3\u003c/sub\u003e treatment suggest damage to the photosynthetic apparatus, consistent with the observed oxidative stress. Synthetic AgNP, on the other hand, did not have a significant impact on most of the measured chlorophyll fluorescence parameters, except for a decrease of Y(II) in plants treated with 100 mM AgNP\u003csub\u003es\u003c/sub\u003e. Gupta et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found that bio-synthesized AgNP increased the activities of catalase (CAT), ascorbate peroxidase (APX), and glutathione reductase (GR) in rice seedlings, leading to reduced lipid peroxidation and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content. This suggests that a similar mechanism, involving the upregulation of antioxidant enzymes, might be contributing to the observed salinity tolerance in AgNP\u003csub\u003eb\u003c/sub\u003e-primed sorghum seedlings. While experiment 1 showed increases in CAT activity with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), experiment 2 demonstrated a significant increase in CAT activity in primed plants under salt stress, further suggesting a role for this enzyme in AgNP\u003csub\u003eb\u003c/sub\u003e-mediates stress protection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, the apparent stimulatory effects of AgNP\u003csub\u003eb\u003c/sub\u003e at 100 mM could be, in part, attributed to ROS-mediated signaling. As suggested by Chen (2023), AgNP-generated ROS, at appropriate levels, can act as stress signal molecules, triggering adaptive responses and inducing changes in the metabolome and transcriptome. Recently, Acharya et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have employed 1H nuclear magnetic resonance (NMR) and liquid chromatography coupled with mass spectrometry (LC-MS) based on metabolomics to explore the metabolome profile changes in onion seeds after AgNP priming. From the changes in metabolic imprint, they elucidated the mechanisms through which AgNP priming improved the seed performance. They revealed that AgNP seed priming treatment decreased the content of hormones and growth regulators such as abscisic acid and cis-(+)-12-oxo-phytodienoic acid, while increasing germination-related stimulators such as γ-aminobutyric acid and zeatin. This study sheds light on the mechanistic analyses of nano seed priming. Further investigation into the metabolic profiles of AgNP\u003csub\u003eb\u003c/sub\u003e-treated sorghum seedlings could provide valuable insights into the specific pathways involved in the observed growth promotion.\u003c/p\u003e \u003cp\u003eFurthermore, the enhanced salinity tolerance conferred by AgNP\u003csub\u003eb\u003c/sub\u003e priming likely involves complex signaling crosstalk within the plant, potentially interacting with key phytohormonal pathways. Methyl jasmonate (MeJa) is a crucial signaling molecule known to mediate plant responses to various stresses, including salinity (Yu \u003cem\u003eet al\u003c/em\u003e., 2023). MeJa signaling can activate a suite of protective mechanisms, such as boosting antioxidant enzyme activities and influencing osmotic adjustment. Intriguingly, jasmonates have also been implicated in regulating ion homeostasis under salt stress, sometimes contributing to reduced accumulation of toxic Na⁺ ions, possibly through modulation of ion transporters like SOS1 or HKT family members (Mulaudzi et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It is plausible that the physiological changes induced by AgNP\u003csub\u003eb\u003c/sub\u003e priming (perhaps mild ROS signaling or other nanoparticle-specific effects) interact synergistically with endogenous MeJa pathways upon subsequent exposure to salt stress. Such synergy could amplify defense responses, leading to more effective Na⁺ exclusion or compartmentation, enhanced antioxidant capacity (like the observed CAT increase, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), and ultimately contributing to the improved photosynthetic performance and reduced oxidative damage seen in primed plants under salinity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Investigating the specific interplay between AgNPb treatment and jasmonate signaling pathways, including hormone levels and ion flux dynamics under salinity, presents a promising direction for future mechanistic studies.\u003c/p\u003e \u003cp\u003eThe differences between AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e, although less dramatic than the differences between AgNP\u003csub\u003es\u003c/sub\u003e and AgNO\u003csub\u003e3\u003c/sub\u003e, are also noteworthy. The PCA analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) showed that AgNP\u003csub\u003eb\u003c/sub\u003e treatments were more closely associated with growth and photosynthetic parameters than AgNP\u003csub\u003es\u003c/sub\u003e treatments. This difference could be attributed to variations in nanoparticle properties arising from the different synthesis methods. Biogenic synthesis, using fungal biomass, may result in nanoparticles with different surface coatings, sizes, or shapes compared to the chemically synthesized AgNP. These differences could influence their interactions with plant cells, their uptake and translocation, and ultimately, their effects on ROS production and downstream physiological processes. Further investigation into the precise physicochemical characteristics of the AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e used in this study would be valuable for elucidating these differences.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Limitations, Implications, and Future Research\u003c/h2\u003e \u003cp\u003eThis study provides valuable insights into the differential phytotoxicity of ionic versus nanoparticulate silver in sorghum, confirming the significantly lower toxicity of both AgNP\u003csub\u003eb\u003c/sub\u003e and AgNP\u003csub\u003es\u003c/sub\u003e compared to AgNO\u003csub\u003e3\u003c/sub\u003e. However, several limitations must be acknowledged. The primary limitation is the use of high, millimolar concentrations, meaning the apparent growth promotion by 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e cannot be directly extrapolated to environmentally relevant scenarios. Nevertheless, investigating plant responses across different exposure levels, including potentially elevated concentrations under controlled laboratory conditions, remains crucial for fundamentally understating the physiological and molecular mechanisms underlying AgNP-plant interactions (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yan and Chen, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Other limitations include the use of a hydroponic system (\u003cem\u003evs\u003c/em\u003e. soil complexity), a single cultivar, focus on early growth, and limited variables tested in the salinity priming experiment (single salinity/priming concentration). Despite these constraints, the results underscore the potential of biogenic synthesis methods to produce less hazardous nanoparticles compared to chemical routes, and compellingly demonstrate that AgNP\u003csub\u003eb\u003c/sub\u003e priming, even initiated at this high concentration, can effectively enhance salinity tolerance in sorghum seedlings.\u003c/p\u003e \u003cp\u003eConsequently, future research could prioritize dose-response studies using lower, environmentally relevant AgNP\u003csub\u003eb\u003c/sub\u003e concentrations to define thresholds for beneficial effects versus potential toxicity under realistic conditions. Validating these findings through long-term field trials across different cultivars and soil types is essential. Furthermore, deeper mechanistic investigations employing '\u003cem\u003eomics\u003c/em\u003e' technologies (transcriptomics, proteomics, metabolomics) are crucial to fully elucidate the signaling and metabolic pathways underlying AgNP\u003csub\u003eb\u003c/sub\u003e-mediated growth effects and stress tolerance, optimizing potential agricultural applications. While AgNP\u003csub\u003eb\u003c/sub\u003e shows promise for sustainable agriculture, particularly as a priming agent, thorough risk assessments addressing potential ecological impacts and bioaccumulation in the food chain are imperative before considering widespread adoption.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrated that the form of silver significantly influences its phytotoxicity to sorghum seedlings. While high concentrations of ionic silver (AgNO\u003csub\u003e3\u003c/sub\u003e) severely inhibited germination, growth, and physiological function, biogenically synthesized silver nanoparticles (AgNP\u003csub\u003eb\u003c/sub\u003e) exhibited significantly lower toxicity. Notably, 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e, even at this high concentration, promoted several aspects of seedling growth and photosynthesis under non-stressed conditions, and, importantly, enhanced salinity tolerance when used as a seed priming agent. In contrast, AgNP\u003csub\u003es\u003c/sub\u003e showed only intermediate effects. The observed effects of AgNP\u003csub\u003eb\u003c/sub\u003e are likely linked to a complex interplay of factors, potentially involving ROS signaling, enhanced antioxidant defenses, particularly CAT, and improved photosynthetic efficiency. While the high concentrations used limit direct extrapolation to field conditions, these findings underscore the potential of biogenic synthesis as a more sustainable approach for producing AgNP with reduced toxicity and highlight the potential of AgNP\u003csub\u003eb\u003c/sub\u003e seed priming as a strategy for improving crop performance, particularly under salinity stress. This study provides valuable insights into the complex interactions between plants and different forms of silver, and future research should focus on lower, environmentally relevant concentrations, detailed mechanistic investigations, and field trials to fully evaluate the benefits and risks of using biogenic nanoparticles in sustainable agriculture\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cem\u003eA -\u003c/em\u003e net photosynthesis, \u003cem\u003eAgNP\u003c/em\u003e - silver nanoparticles, AgNP\u003csub\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e-\u003c/b\u003e biogenic silver nanoparticles, \u003cem\u003eAgNP\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e - synthetic silver nanoparticles, \u003cem\u003eAgNO\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e - silver nitrate, \u003cem\u003eAPX\u003c/em\u003e - ascorbate peroxidase, \u003cem\u003eCar\u003c/em\u003e - carotenoids, \u003cem\u003eCAT\u003c/em\u003e - catalase, \u003cem\u003eChla\u003c/em\u003e - chlorophyll \u003cem\u003ea\u003c/em\u003e, \u003cem\u003eChlb\u003c/em\u003e - chlorophyll \u003cem\u003eb\u003c/em\u003e, \u003cem\u003eChlT\u003c/em\u003e - total chlorophyll, \u003cem\u003eCi\u003c/em\u003e - intercellular CO\u003csub\u003e2\u003c/sub\u003e partial pressure, \u003cem\u003eDLS\u003c/em\u003e - dynamic light scattering, \u003cem\u003eE\u003c/em\u003e - transpiration rate, \u003cem\u003eETR\u003c/em\u003e - apparent electron transport rate, \u003cem\u003eFv/Fm\u003c/em\u003e - potential quantum yield of PSII, \u003cem\u003eFW\u003c/em\u003e - fresh weight, \u003cem\u003egs\u003c/em\u003e - stomatal conductance, \u003cem\u003eH\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e - hydrogen peroxide, \u003cem\u003eMDA\u003c/em\u003e - malondialdehyde, \u003cem\u003eNPQ\u003c/em\u003e - non-photochemical quenching, \u003cem\u003eNPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e - fast-relaxing component of NPQ, \u003cem\u003eNPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e - slow-relaxing component of NPQ, \u003cem\u003ePCA\u003c/em\u003e - principal component analysis, \u003cem\u003ePSII\u003c/em\u003e - photosystem II, \u003cem\u003eROS\u003c/em\u003e - reactive oxygen species, \u003cem\u003eRWC\u003c/em\u003e - relative water content, \u003cem\u003eSD\u003c/em\u003e - standard deviation, \u003cem\u003eSOD\u003c/em\u003e - superoxide dismutase, \u003cem\u003eTBARS\u003c/em\u003e - thiobarbituric acid reactive substances, \u003cem\u003eTEM\u003c/em\u003e transmission electron microscopy, \u003cem\u003eY(II)\u003c/em\u003e - effective quantum yield of PSII.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions :\u0026nbsp;\u003c/strong\u003eAna B. S. Ziotti\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand Vit\u0026oacute;ria C. P. Kuhl\u003csup\u003e\u0026nbsp;\u003c/sup\u003eperformed the experiments and analyzed the data. Cristiane A. Otonni\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand Milton C. Lima Neto conceived and designed the experiments, supervised and wrote and revised the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e MCLN is supported by CNPq #301453/2022-5 fellowship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and consent to participate:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbasi F, Raja NI, Mashwani ZUR, Amjad MS, Ehsan M, Mustafa N, Haroon M, Proćk\u0026oacute;w J. (2022). Biogenic Silver Nanoparticles as a Stress Alleviator in Plants: A Mechanistic Overview. \u003cem\u003eMolecules\u003c/em\u003e. 27(11):3378. doi: 10.3390/molecules27113378.\u003c/li\u003e\n\u003cli\u003eAcharya P, Jayaprakasha GK, Semper J, Patil BS. (2020). 1H Nuclear Magnetic Resonance and Liquid Chromatography Coupled with Mass Spectrometry-Based Metabolomics Reveal Enhancement of Growth-Promoting Metabolites in Onion Seedlings Treated with Green-Synthesized Nanomaterials. \u003cem\u003eJ. Agric. Food Chem.\u003c/em\u003e 68(46):13206\u0026ndash;13220. doi: 10.1021/acs.jafc.0c01281. \u003c/li\u003e\n\u003cli\u003eBello-Bello JJ, Chavez-Santoscoy RA, Lecona-Guzm\u0026aacute;n CA, Bogdanchikova N, Salinas-Ru\u0026iacute;z J, G\u0026oacute;mez-Merino FC, Pestryakov A. (2017). Hormetic Response by Silver Nanoparticles on In Vitro Multiplication of Sugarcane (Saccharum spp. Cv. Mex 69-290) Using a Temporary Immersion System. \u003cem\u003eDose Response\u003c/em\u003e. 15(4):1559325817744945. doi: 10.1177/1559325817744945.\u003c/li\u003e\n\u003cli\u003eBradford MM. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. \u003cem\u003eAnal. Biochem.\u003c/em\u003e 72:248\u0026ndash;254. doi:10.1016/0003-2697(76)90527-3. \u003c/li\u003e\n\u003cli\u003eBusch FA, Ainsworth EA, Amtmann A, Cavanagh AP, Driever SM, Ferguson JN, Kromdijk J, Lawson T, Leakey ADB, Matthews JSA, et al. (2024). A guide to photosynthetic gas exchange measurements: Fundamental principles, best practice and potential pitfalls. \u003cem\u003ePlant Cell Environ.\u003c/em\u003e 47(4): 1185-1208. doi:10.1111/pce.14815.\u003c/li\u003e\n\u003cli\u003eCakmak I, Horst WJ. (1991). Effect of aluminum on lipid peroxidation, superoxide dismutase, catalase, and peroxidase activities in root tips of soybean (Glycine max). \u003cem\u003ePhysiol. Plant.\u003c/em\u003e 83(3):463\u0026ndash;468.\u003c/li\u003e\n\u003cli\u003eCembrowska-Lech D, Rybak K. (2023). Nanopriming of Barley Seeds-A Shotgun Approach to Improve Germination under Salt Stress Conditions by Regulating of Reactive Oxygen Species. \u003cem\u003ePlants (Basel)\u003c/em\u003e. 12(2):405. doi: 10.3390/plants12020405.\u003c/li\u003e\n\u003cli\u003eChen S, Yan X, Peralta-Videa JR, Su Z, Hong J, Zhao L. (2023). Biological effects of AgNPs on crop plants: environmental implications and agricultural applications. \u003cem\u003eEnviron. Sci.: Nano\u003c/em\u003e. 10(1):62-71.\u003c/li\u003e\n\u003cli\u003eCosta, T.S., Delgado, G.G., Braga, C.B., Tasic, L. (2025). Insights into the fungal secretomes and their roles in the formation and stabilization of the biogenic silver nanoparticles. RSC Adv.15, 6938-6951, doi. 10.1039/D4RA07962K\u003c/li\u003e\n\u003cli\u003eFontes, E.H., Ramos, C.E.D., Ottoni, C.A., de Souza, R.F.B., Antolini, E., Neto, A.O. (2021). Glycerol dehydrogenation steps on Au/C surface in alkaline medium: An in-situ ATR-FTIR approach. Renewable Energy. 167, 954-959. doi.org/10.1016/j.renene\u003c/li\u003e\n\u003cli\u003eFoyer CH, Hanke G. (2022). ROS production and signalling in chloroplasts: cornerstones and evolving concepts. \u003cem\u003ePlant J.\u003c/em\u003e 111(3):642-661.\u003c/li\u003e\n\u003cli\u003eGiannopolotis CN, Ries SK. (1977). Superoxide dismutases: Occurrence in higher plants. \u003cem\u003ePlant Physiol.\u003c/em\u003e 59:309\u0026ndash;314.\u003c/li\u003e\n\u003cli\u003eGupta SD, Agarwal A, Pradhan S. (2018). Phytostimulatory effect of silver nanoparticles (AgNPs) on rice seedling growth: An insight from antioxidative enzyme activities and gene expression patterns. \u003cem\u003eEcotoxicol. Environ. Saf.\u003c/em\u003e 161:624\u0026ndash;633. \u003c/li\u003e\n\u003cli\u003eHasegawa T, Sakurai G, Fujimori S, et al. (2021). Extreme climate events increase risk of global food insecurity and adaptation needs. \u003cem\u003eNat Food\u003c/em\u003e. 2:587\u0026ndash;595. doi:10.1038/s43016-021-00335-4. \u003c/li\u003e\n\u003cli\u003eHavir EA, McHale NA. (1987). Biochemical and Developmental Characterization of Multiple Forms of Catalase in Tobacco Leaves. \u003cem\u003ePlant Physiol.\u003c/em\u003e 84:450\u0026ndash;455. doi:10.1104/pp.84.2.450.\u003c/li\u003e\n\u003cli\u003eHoagland DR, Arnon DJ. (1950). \u003cem\u003eThe water culture method for growing plants without soil\u003c/em\u003e. Agric Exp Cir 347.\u003c/li\u003e\n\u003cli\u003eKhan S, Zahoor M, Sher Khan R, Ikram M, Islam NU. (2023). The impact of silver nanoparticles on the growth of plants: The agriculture applications. \u003cem\u003eHeliyon\u003c/em\u003e. 9(6):e16928. doi: 10.1016/j.heliyon.2023.e16928.\u003c/li\u003e\n\u003cli\u003eLichtenthaler H, Wellburn A, Lichtentharler HK, Welburn AR. (1983). Determination of total carotenoids and chlorophylls a and b of leaf extracts in different solvents. \u003cem\u003eBiochem. Soc. Trans.\u003c/em\u003e 11:591\u0026ndash;592. doi:10.1042/bst0110591.\u003c/li\u003e\n\u003cli\u003eLima Neto MC, Silveira JAG, Cerqueira JVA, Cunha JR. (2017). Regulation of the photosynthetic electron transport and specific photoprotective mechanisms in Ricinus communis under drought and recovery. \u003cem\u003eActa Physiol. Plant.\u003c/em\u003e 39:183. doi:10.1007/s11738-017-2483-9.\u003c/li\u003e\n\u003cli\u003eMalik, M.A., Wani, A.H., Bhat, M.Y., Siddiqui, S., Alamri, S.A.M., Alrumman, S.A. (2024). Fungal-mediated synthesis of silver nanoparticles: a novel strategy for plant disease management. Front. Microbiol. 15, 1399331. doi:10.3389/fmicb.2024.1399331\u003c/li\u003e\n\u003cli\u003eMatras E, Gorczyca A, Pociecha E, Przemieniecki SW, Oćwieja M. (2022). Phytotoxicity of silver nanoparticles with different surface properties on monocots and dicots model plants. \u003cem\u003eJ. Soil Sci. Plant Nutr.\u003c/em\u003e 22(2):1647-1664.\u003c/li\u003e\n\u003cli\u003eMirzajani F, Askari S, Hamzelou M, Farzaneh A, Ghassempour A. (2013). Effect of silver nanoparticles on Oryza sativa L. and its rhizosphere bacteria. \u003cem\u003eEcotoxicol. Environ. Saf.\u003c/em\u003e 88:48\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eMohamed AKSH, Qayyum MF, Abdel-Hadi AM, Rehman RA, Ali S, Rizwan M. (2017). Interactive effect of salinity and silver nanoparticles on photosynthetic and biochemical parameters of wheat. \u003cem\u003eArch. Agron. Soil Sci.\u003c/em\u003e 63(12):1736\u0026ndash;1747. doi:10.1080/03650340.2017.1300256.\u003c/li\u003e\n\u003cli\u003eMulaudzi T, Sias G, Nkuna M, Ndou N, Hendricks K, Ikebudu V, Koo AJ, Ajayi RF, Iwuoha E. (2023). Seed Priming with MeJa Prevents Salt-Induced Growth Inhibition and Oxidative Damage in Sorghum bicolor by Inducing the Expression of Jasmonic Acid Biosynthesis Genes. Int J Mol Sci. Jun 20;24(12):10368. doi: 10.3390/ijms241210368. PMID: 37373514; PMCID: PMC10299227.\u003c/li\u003e\n\u003cli\u003eMunns R, Tester M. (2008). Mechanisms of salinity tolerance. \u003cem\u003eAnnu. Rev. Plant Biol.\u003c/em\u003e 59:651\u0026ndash;81. doi:10.1146/annurev.arplant.59.032607.092911.\u003c/li\u003e\n\u003cli\u003eMunns R, Passioura JB, Colmer TD, Byrt CS. (2020). Osmotic adjustment and energy limitations to plant growth in saline soil. \u003cem\u003eNew Phytol.\u003c/em\u003e 225:1091\u0026ndash;1096. doi:10.1111/nph.15862.\u003c/li\u003e\n\u003cli\u003eMurchie EH, Lawson T. (2013). Chlorophyll fluorescence analysis: A guide to good practice and understanding some new applications. \u003cem\u003eJ. Exp. Bot.\u003c/em\u003e 64:3983\u0026ndash;3998. doi:10.1093/jxb/ert208.\u003c/li\u003e\n\u003cli\u003eNakano Y, Asada K. (1981). Hydrogen Peroxide is Scavenged by Ascorbate-specific Peroxidase in Spinach Chloroplasts. \u003cem\u003ePlant Cell Physiol.\u003c/em\u003e 22:867\u0026ndash;880. doi:10.1093/oxfordjournals.pcp.a076232.\u003c/li\u003e\n\u003cli\u003eNarware, J., Singh, S.P., Chakma, J., Ranjan, P., Behera, L., Das, P., Manzar, N., Kashyap, A.S. (2024). Enhancing tomato growth and early blight disease resistance through green-synthesized silver nanoparticles: Insights into plant physiology. S. Afr. J. Bot. 166, 676-689, doi.org/10.1016/j.sajb.2024.01.059\u003c/li\u003e\n\u003cli\u003eOttoni CA, Sim\u0026otilde;es MF, Fernandes S, et al. (2017). Screening of filamentous fungi for antimicrobial silver nanoparticles synthesis. \u003cem\u003eAMB Expr\u003c/em\u003e. 7:31. doi:10.1186/s13568-017-0332-2.\u003c/li\u003e\n\u003cli\u003eOttoni CA, Neto ML, L\u0026eacute;o P, Ortolan BD, Barbieri E, De Souza AO. (2020). Environmental impact of biogenic silver nanoparticles in soil and aquatic organisms. \u003cem\u003eChemosphere\u003c/em\u003e. 239:124698. doi:10.1016/j.chemosphere.2019.124698.\u003c/li\u003e\n\u003cli\u003eSiddiqi KS, Husen A. (2022). Plant response to silver nanoparticles: a critical review. \u003cem\u003eCrit. Rev. Biotechnol.\u003c/em\u003e 42(7):973-990.\u003c/li\u003e\n\u003cli\u003eSilva, A.A., Ribeiro, B.M., Trotta, C.V., Perina, F.C., Martins, R., Abessa, D.M.S., Barbieri, E., Sim\u0026otilde;es, M.F., Ottoni, C.A (2022). Effects of mycogenic silver nanoparticles on organisms of different trophic levels. Chemosphere. 308, 136540,. doi.org/10.1016/j.chemosphere.136540.\u003c/li\u003e\n\u003cli\u003eV\u0026iacute;tolo HF, Souza GM, Silveira JA. (2012). Cross-scale multivariate analysis of physiological responses to high temperature in two tropical crops with C3 and C4 metabolism. \u003cem\u003eEnviron. Exp. Bot.\u003c/em\u003e 80:54\u0026ndash;62. doi:10.1016/j.envexpbot.2012.02.002.\u003c/li\u003e\n\u003cli\u003eWahid I, Kumari S, Ahmad R, Hussain SJ, Alamri S, Siddiqui MH, Khan MIR. (2020). Silver Nanoparticle Regulates Salt Tolerance in Wheat Through Changes in ABA Concentration, Ion Homeostasis, and Defense Systems. \u003cem\u003eBiomolecules\u003c/em\u003e. 10(11):1506. doi: 10.3390/biom10111506.\u003c/li\u003e\n\u003cli\u003eYang D, Wang L, Ma F, et al. (2023). Effects of Ag nanoparticles on plant growth, Ag bioaccumulation, and antioxidant enzyme activities in Phragmites australis as influenced by an arbuscular mycorrhizal fungus. \u003cem\u003eEnviron Sci Pollut Res\u003c/em\u003e. 30:4669\u0026ndash;4679. doi:10.1007/s11356-022-22540-9.\u003c/li\u003e\n\u003cli\u003eYan A, Chen Z. (2019). Impacts of Silver Nanoparticles on Plants: A Focus on the Phytotoxicity and Underlying Mechanism. \u003cem\u003eInt J Mol Sci.\u003c/em\u003e 20(5):1003. doi: 10.3390/ijms20051003.\u003c/li\u003e\n\u003cli\u003eYu, X., Zhang, W., Zhang, Y., Zhang, X., Lang, D., \u0026amp; Zhang, X. (2019). The roles of methyl jasmonate to stress in plants. \u003cem\u003eFunctional plant biology : FPB, 46 3\u003c/em\u003e, 197-212 .\u003c/li\u003e\n\u003cli\u003eYusefi-Tanha E, Fallah S, Pokhrel LR, Rostamnejadi A. (2023). Addressing global food insecurity: Soil-applied zinc oxide nanoparticles promote yield attributes and seed nutrient quality in Glycine max L. \u003cem\u003eSci. \u003c/em\u003e\u003cem\u003eTotal Environ.\u003c/em\u003e 876:162762. doi:10.1016/j.scitotenv.2023.162762.\u003c/li\u003e\n\u003cli\u003eZhou M, Diwu Z, Panchuk-Voloshina N, Haugland RP. (1997). A Stable Nonfluorescent Derivative of Resorufin for the Fluorometric Determination of Trace Hydrogen Peroxide: Applications in Detecting the Activity of Phagocyte NADPH Oxidase and Other Oxidases. \u003cem\u003eAnal. Biochem.\u003c/em\u003e 253:162\u0026ndash;168. doi:10.1006/abio.1997.2391.\u003c/li\u003e\n\u003cli\u003eZhou X, Jia X, Zhang Z, Chen K, Wang L, Chen H, ... Zhao L. (2022). AgNPs seed priming accelerated germination speed and altered nutritional profile of Chinese cabbage. \u003cem\u003eSci. Total Environ.\u003c/em\u003e 808:151896.\u003c/li\u003e\n\u003cli\u003eZhu, Y., Hu, X., Qiao, M., Zhao, L., Dong, C. (2024) Penicillium polonicum-mediated green synthesis of silver nanoparticles: Unveiling antimicrobial and seed germination advancements. Heliyon. 7e28971. doi:10.1016/j.heliyon.2024.e28971\u003c/li\u003e\n\u003cli\u003eZiotti ABS, Ottoni CA, Correa CN, de Almeida OJG, de Souza AO, Neto MCL. (2021). Differential physiological responses of a biogenic silver nanoparticle and its production matrix silver nitrate in Sorghum bicolor. \u003cem\u003eEnviron. Sci. Pollut. Res.\u003c/em\u003e 28:32669\u0026ndash;32682. doi:10.1007/s11356-021-13069-4.\u003c/li\u003e\n\u003cli\u003eZwar IP, Trotta C do V, Ziotti ABS, Lima Neto M, Ara\u0026uacute;jo WL, de Melo IS, Ottoni CA, de Souza AO. (2023). Biosynthesis of silver nanoparticles using actinomycetes, phytotoxicity on rice seeds, and potential application in the biocontrol of phytopathogens. \u003cem\u003eJ Basic Microbiol.\u003c/em\u003e 63:64\u0026ndash;74. doi:10.1002/jobm.202200439.\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":"Biogenic nanoparticles, oxidative stress, photosynthesis, nanopriming, silver toxicity","lastPublishedDoi":"10.21203/rs.3.rs-6768384/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6768384/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAbiotic stresses, including salinity, significantly threaten crop production worldwide. Nanotechnology, particularly seed priming with silver nanoparticles (AgNP), offers a potential strategy for enhancing plant stress tolerance. This study compared the effects of biogenic (AgNP\u003csub\u003eb\u003c/sub\u003e), synthetic (AgNP\u003csub\u003es\u003c/sub\u003e) silver nanoparticles with their metal precursor (AgNO\u003csub\u003e3\u003c/sub\u003e) on sorghum germination and early seedling growth and evaluated AgNP\u003csub\u003eb\u003c/sub\u003e priming to improve salinity tolerance. Sorghum seeds were treated with 0, 10, or 100 mM of AgNP\u003csub\u003eb\u003c/sub\u003e, AgNP\u003csub\u003es\u003c/sub\u003e, or AgNO\u003csub\u003e3\u003c/sub\u003e. AgNP\u003csub\u003eb\u003c/sub\u003e enhanced germination rate, increased root and shoot biomass, improved photosynthetic performance (net photosynthetic rate, stomatal conductance, and electron transport rate), and maintained higher relative water content. Conversely, AgNO\u003csub\u003e3\u003c/sub\u003e, particularly at 100 mM, inhibited germination, reduced biomass, impaired photosynthesis, and induced significant oxidative stress (elevated H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and TBARS). AgNP\u003csub\u003es\u003c/sub\u003e showed intermediate effects. Furthermore, seed priming with 100 mM AgNP\u003csub\u003eb\u003c/sub\u003e mitigated the negative impacts of subsequent 100 mM NaCl exposure, improving photosynthesis and reducing oxidative damage markers compared with non-primed, salt-stresses seedlings. While the millimolar concentrations used limit direct field application, these findings highlight the critical role of the form of silver (ionic versus nanoparticulate) in determining phytotoxicity. AgNP\u003csub\u003eb\u003c/sub\u003e shows potential for promoting early growth and, crucially, enhancing salinity tolerance via seed priming, warranting investigation at lower, environmentally relevant concentrations.\u003c/p\u003e","manuscriptTitle":"Mycobiogenic Silver Nanoparticle Priming: A Strategy to Mitigate Salinity Stress in Sorghum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 10:34:49","doi":"10.21203/rs.3.rs-6768384/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":"a5f98d70-0c34-4023-a69f-25d4c3e520d7","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-19T06:53:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-16 10:34:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6768384","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6768384","identity":"rs-6768384","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}