The effects of Silica nanoparticles (SiNPs) application on maize (Zea mays L) growth, defense system and cadmium accumulation under Drought and Cadmium Stress

The effects of Silica nanoparticles (SiNPs) application on maize (Zea mays L) growth, defense system and cadmium accumulation under Drought and Cadmium Stress | 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 The effects of Silica nanoparticles (SiNPs) application on maize (Zea mays L) growth, defense system and cadmium accumulation under Drought and Cadmium Stress Dongfeng Ning, Linjing Li, Yan Chen, Anzhen Qin, Yingying Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8518329/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 6 You are reading this latest preprint version Abstract Background and aims Abiotic stresses, particularly drought and cadmium (Cd) stress, are among the primary limiting factors for global crop production, significantly threatening the growth and development of maize. Silicon nanoparticles (SiNPs) have demonstrated substantial potential in enhancing crop resilience. However, the regulatory mechanisms of SiNPs under combined drought and Cd stress conditions remain insufficiently explored. Methods The experiment included eight treatments: control [100% field capacity (FC), 0 mg/kg Cd)], drought (50% FC, 0 mg/kg Cd), Cd stress (100% FC, 5 mg/kg Cd), combined stress (50% FC, 5 mg/kg Cd ) and each of these with or without SiNPs application (0 or 50 mg/kg). Results Drought and combined drought-Cd stress remarkably reduced maize photosynthetic efficiency, root traits, and grain yield. Cd stress alone had minimal impact on growth parameters but significantly increased Cd accumulation in plant tissues. However, SiNPs application significantly improved root morphology, increased leaf relative water content (LRWC), enhanced antioxidant enzymes activities and increased the contents of soluble sugars and soluble proteins. These changes reduced reactive oxygen species (ROS) and malondialdehyde (MDA) levels, thereby promoting photosynthetic efficiency and ultimately increasing grain yield by 27.3% and 18.9% under drought stress and combined stress compared to the non-Si treated plants. Additionally, SiNPs application significantly decreased Cd concentration in plant tissues by reducing Cd bioavailability in soil under Cd stress. Conclusion SiNPs is an effective strategy to mitigate drought stress and Cd accumulation in maize. Maize Silicon nanoparticles Drought stress Cadmium stress Antioxidant system Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Abiotic stresses including drought, salinity, high temperatures, flooding and heavy metals are major limiting factors for agricultural development and yield potential worldwide (Sánchez-Bermúdez et al., 2022 ). Drought, with its growing frequency and severity, has emerged as a critical challenge to agricultural productivity and food security (Gu et al., 2019 ). Drought stress impacts crop growth and development through synergistic mechanisms: it compromises cell membrane integrity, disrupts the equilibrium between reactive oxygen species (ROS) and the antioxidant system, and impairs water-nutrient transport, ultimately resulting in a significant reduction in photosynthetic efficiency (Hussain et al., 2018 ; Mukarram et al., 2021 ). Meanwhile, human activities, such as mining and metallurgy, industrial emission, agricultural fertilization have significantly increased heavy concentrations in agricultural soil, making them a key global environmental challenge (Zhao et al., 2020 ). Among heavy metals, cadmium (Cd) is one of the highly toxic heavy metals, exerting profound adverse effects on both plants and humans even at low concentrations (Lu et al., 2023 ). Cd can easily transfer from soil to plant tissues due to its high mobility (Cai et al., 2022 ; Zhao et al., 2023 ), and bioaccumulate in higher-trophic-level organisms through the food chain (Yang et al., 2022). Long-term intake of Cd-contaminated materials causes excessive Cd buildup in the human body, damaging organs and tissues irreversibly (Marques et al., 2024 ). Therefore, developing effective strategies to mitigate Cd pollution is essential ensuring food security, particularly for staple crops (Deng et al., 2024 ). Silicon (Si) is acknowledged as a beneficial element, demonstrating remarkable efficiency in alleviating both biotic stresses (e.g., plant diseases and pest infestations) and abiotic stresses (e.g., salinity, drought, heavy metal toxicity, and freezing). The alleviating mechanism mainly involved in improving water absorption, enhancing the antioxidant system, boosting osmotic regulation, increasing photosynthetic efficiency, and reducing metal uptake (Ayub et al., 2023 ; Ma et al., 2015; Qayyum et al., 2017 ; Yin et al., 2019 ). Although Si is the second most abundant element in soil, the majority of soil Si exists in forms such as silicate crystals or precipitates, whereas plants primarily absorb Si as monosilicic acid (Ma et al., 2015; Yin et al., 2019 ). This discrepancy significantly limits the bioavailability of plant-available Si in soils. Recently, nanoparticles (NPs) have attracted attention in agricultural production due to their altered size and shape properties, becoming a very promising alternative to traditional agricultural chemicals (Mukarram et al., 2022 ). Among these nanomaterials, silicon nanoparticles (SiNPs) have demonstrated significant potential in promoting plant growth and enhancing plant tolerance to various abiotic stresses owing to their large surface area, good biocompatibility, and low risk (Ahmed et al., 2023 ; Chen F et al., 2024; Haider et al., 2025 ; Jalil et al., 2023 ; Mukarram et al., 2022 ). For instance, SiNPs application mitigated Cd toxicity by regulating oxidative stress metabolism and inhibiting Cd translocation (Ahmed et al., 2023 ; Jalil et al., 2023 ). SiNPs improved drought tolerance by modulating photosynthesis, stomatal activity, antioxidant enzyme activities, and carbon fixation (Chen F et al., 2024a; Haider et al., 2025 ). Maize ( Zea mays L .), one of the three major food crops, plays a triple role in grain production, animal feed, and industrial raw materials, holds strategic significance for national food security and economic development in China (Kaushal et al., 2023 ). Maize has high water demands and is particularly sensitive to drought during its flowering stage (Hu et al., 2023 ). Additionally, maize is considered as a cadmium (Cd) accumulator and capable of accumulating high Cd concentrations in Cd-contaminated soils (Rizwan et al., 2017 ). To date, few studies have investigated the mitigating effects and mechanisms of SiNPs under combined drought and Cd stress. Therefore, a pot experiment was conducted with the following objectives: (i) to elucidate the impacts of SiNPs application on plant growth, physiological attributes, and yield performance of maize under individual or combined drought and Cd stress; and (ii) to determine the regulatory effects of SiNPs application on Cd uptake, translocation, and Cd speciation and bioavailability in soil systems under single and combined stress conditions. This research is expected to provide an economical strategy for mitigating drought and Cd stress in maize production. Materials and methods Experimental site A soil column field experiment was conducted from June to October 2024 under a rain-shelter system at the Chinese Academy of Agricultural Sciences (CAAS) Xinxiang Comprehensive Experimental Base (35°18'N, 113°54'E) in Qiliying Town. The region exhibits typical temperate semi-humid drought-prone climatic conditions, with a mean annual temperature of 14 °C , 582 mm of precipitation, and 210 frost-free days. Each soil column system comprised two nested stainless steel buckets: a larger outer bucket (32 cm diameter × 100 cm depth) buried in the soil, and a smaller inner bucket (30 cm diameter × 100 cm depth) inserted into the larger one. To simulate field conditions, the columns were constructed with a 5 cm basal sand layer, followed by regionally typical field soil layers packed from 0-90 cm depth. This design facilitated robust root system development throughout the experiment. The selected soil physico-chemical properties are shown in Table 1. Experimental design The experiment included eight treatments: control [100% field capacity (FC), 0 mg kg -1 Cd)], drought stress (50% FC, 0 mg/kg Cd ), Cd stress (100% FC, 5 mg kg -1 Cd), combined stress (50% FC, 5 mg kg -1 Cd) and each of these with or without SiNPs application (0 or 10 mg kg -1 ). Eight treatments in a randomized complete block design with six replications. Three biological replicates per treatment were selected for parameter measurements. At the maize flowering stage, plants under drought stress treatments were subjected to moderate drought stress (50% FC) for 7 days. Soil water content was measured by weighing soil columns. Irrigation was supplemented daily or every other day based on soil moisture, maize growth stage, and weather. Drought stress was imposed by reducing irrigation amount for 2-3 days, after which the columns were reweighed and irrigated to keep soil water at 50% field capacity. To achieve a water-soluble cadmium (Cd) concentration of 10 mg kg -1 , soil samples in the Cd stress treatment were artificially amended with exogenous CdCl 2 ·2H 2 O solutions. Silicon nanoparticles (SiNPs) were applied at rates of 30%, 20%, 30%, and 20% during the maize growth stages of sowing, jointing, tasseling, and flowering, respectively. Following regional fertilization practices, nutrient inputs were calculated based on 0-30 cm cm soil dry weight and applied at rates of 0.2 g N, 0.05 g P 2 O 5 , and 0.10 g K 2 O per kg dry soil to meet maize requirements. Urea (with 46% N), superphosphate (with 18% P 2 O 5 ), and potassium sulfate (with 50% K 2 O) served as the sources of N, P, and K, respectively. P and K fertilizers were applied as basal dressing, whereas N fertilizer was split into two applications: 50% at the seedling stage and 50% at the jointing stage. Weeding and nitrogen topdressing were performed manually. Sampling and measurements Leaf samples At the end of the drought period, ear leaf samples were destructively collected from three randomly selected pots per treatment. The collected samples were promptly flash-frozen in liquid nitrogen and then stored at -80 °C until physiological analyses. The physio-biochemical indices determined mainly included leaf relative water content (LRWC), chlorophyll content, activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), as well as the contents of superoxide radical (O 2 ·− ), malondialdehyde (MDA), proline, soluble sugar, soluble protein. Detailed analytical protocols for these selected indices are presented in Table 2. Photosynthetic rate, transpiration rate, and stomatal conductance At the end of the drought period, three replicate ear leaves per treatment were selected to measure the photosynthetic rate, transpiration rate, and stomatal conductance using a portable photosynthesis system (LI-6400, LI-COR., Lincoln, NE, USA) between 9:00 and 11:00 a.m. Root system and grain yield At the end of the drought stress period, three intact maize root samples were collected. Soil adhering to the roots was removed by rinsing with a high-pressure water spray, ensuring complete soil removal while maintaining root system integrity. Measurements of total root length, root diameter, root volume, and root surface area were conducted using the WinRHIZO root analysis system. Subsequently, the dry weight of the roots was determined after oven-drying at 75 °C until reaching a constant weight. At the maize harvest stage, three uniformly grown plants per treatment were chosen. Grains, leaves, and stems were individually collected. The samples were subsequently oven-dried at 75 °C until a constant mass was achieved, and the final dry weight was recorded. Plant Cd content A representative sample of up to 0.5 g was digested in 10mL of concentrated nitric acid (HNO 3 ) for 15 min in a suitable laboratory microwave system. After the vessel had cooled, the solution was filtered and diluted to 25 mL with 0.5 M HCl. The concentration of Cd was determined using AAS (Wu et al., 2018). Soil Cd content determination Soil samples were collected from three pots at the flowering stages for sequential metal fractionation analysis using the BCR (Community Bureau of Reference) extraction procedure (Chenb R et al., 2024b). The detailed analytical protocols are presented in Table 3. The concentration of Cd was determined using AAS. Statistical analysis All data presented in the figures and tables are expressed as means ± standard deviation (SD) of three biological replicates. Statistical analysis involved one-way analysis of variance (ANOVA), followed by the least significant difference (LSD) test to determine significant differences ( P < 0.05) among treatment means. Pearson correlation analysis was conducted to assess the relationships between grain yield, physiological parameters, and Cd content in both plant tissues and soil. All statistical analyses were conducted using SPSS 18.0, and graphical representations were generated using Origin 2022. Results Maize growth parameters and yield Eight-day drought stress applied during the maize VT stage caused significant reductions in both leaf area (LA) and leaf relative water content (LRWC) ( p < 0.05, Fig. 1). Compared to the control (CK), drought stress alone decreased LA and LRWC by 6.92% and 5.57%, respectively, while combined drought-Cd stress led to more pronounced declines (LA: 8.14%, LRWC: 8.81%). Whereas, Cd stress alone exhibited no significant effect on these parameters ( p > 0.05). The application of silica nanoparticles (SiNPs) effectively counteracted drought-induced inhibition. Under drought stress, SiNPs application significantly increased LA and LRWC by 11.0% and 4.58%, respectively, compared to non-Si-treated plants. This mitigation effect was even stronger under combined stress conditions, with improvements of 12.2% (LA) and 7.36% (LRWC). All stress treatments (drought, Cd, and their combination) significantly inhibited root morphological parameters compared to the CK treatment, including reductions in root average diameter, root surface area, and root dry weight ( p < 0.05, Fig. 2). Interestingly, drought stress alone induced a significant increase in root length ( p < 0.05), suggesting a potential adaptive response. The application of SiNPs effectively mitigated these stress effects. Under drought stress, Si treatment enhanced root average diameter, root volume, root surface area, and root dry weight by 17.1%, 20.4%, 9.23%, and 17.7%, respectively, relative to non-Si-treated plants. Similar improvements were observed under Cd stress (12.7%, 14.9%, 14.6%, and 7.4%, respectively). Most notably, under combined stress conditions, Si demonstrated the strongest protective effects, with increases of 13.4% (root diameter), 24.8% (root volume), 23.4% (root surface area), and 20.0% (root dry weight). Drought stress applied during the VT growth stage of maize exerted significant negative effects on grain yield and yield components ( p < 0.05, Table 2). Compared to the CK treatment, drought stress significantly reduced grain yield by 39.5%, 100-kernel weight by 15.2%, and kernels per spike by 37.2%. Combined drought and Cd stress resulted in reductions of 39.2%, 16.9%, and 38.5% in these parameters, respectively. Notably, Cd stress alone had no significant impact on any yield components ( p > 0.05), suggesting that the observed yield declines were primarily driven by drought stress. The application of SiNPs demonstrated significant mitigation effects ( p < 0.05). Under drought conditions, Si-treated plants exhibited increases of 27.3%, 9.08%, and 14.5% in grain yield, 100-kernel weight, and kernels per spike, respectively, compared to the non-Si-treated control. Under combined stress, the corresponding increases were 18.9%, 13.5%, and 7.47%. Gas exchange parameters and photosynthetic enzymes At the VT stage of maize, drought, cadmium (Cd), and their combined stress significantly suppressed photosynthetic parameters ( p < 0.05, Fig. 3). Compared to the control (CK), drought stress reduced the net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr) by 12.5%, 64.1%, and 40.2%, respectively. Cd stress alone caused milder but still significant declines (Pn: 4.37%; Gs: 29.4%; Tr: 16.4%). Notably, their combined stress exhibited synergistic inhibition, with reductions reaching 13.4% (Pn), 69.0% (Gs), and 51.0% (Tr). SiNPs application differentially mitigated these stresses ( p < 0.05). Under drought stress, SiNPs application enhanced Pn, Sc, and Tr by 11.3%, 63.2%, and 35.0%, respectively, compared to non-Si-treated plants. For Cd stress, the improvements were 7.75% (Pn), 29.5% (Gs), and 8.5% (Tr). Most strikingly, under combined stress, SiNPs enhanced these parameters by 16.4% (Pn), 94.6% (Gs), and 66.4% (Tr), demonstrating pronounced stress-alleviating effects. Drought, Cd, and their combination significantly inhibited the enzymatic activities of both phosphoenolpyruvate carboxylase (PEPCase) and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBPCase) at the VT stage ( p < 0.05, Fig. 3). Specifically, drought stress alone reduced PEPCase and RuBPCase activities by 21.1% and 39.4%, respectively. Cd stress exhibited comparable inhibitory effects (35.6% for PEPCase, 37.4% for RuBPCase), while the combined stress showed the most severe suppression (36.3% and 49.7% reduction for PEPCase and RuBPCase, respectively). The application of SiNPs demonstrated significant stress-mitigating effects ( p < 0.05). Under drought conditions, SiNPs treatment increased PEPCase and RuBPCase activities by 6.81% and 28.1%, respectively, compared to non-Si treated plants. The enhancement was more moderate under Cd stress (4.08% for PEPCase, 14.2% for RuBPCase), but was most pronounced under combined stress (11.8% and 46.4% for PEPCase and RuBPCase, respectively), suggesting a synergistic protective mechanism. Osmotic solute content At the VT stage, maize plants exhibited significant accumulation of osmolytes ( p 0.05). Relative to the CK, drought stress elevated soluble sugar, proline, and soluble protein levels by 5.37%, 92.6%, and 13.7%, respectively. The combined drought and Cd stress exhibited the most pronounced effects, with respective increments of 10.8%, 140.8%, and 15.8%. Application of SiNPs demonstrated differential regulatory effects compared to non-Si-treated plants. Under drought stress condition, SiNPs treatment significantly enhanced soluble sugar and protein contents by 20.1% and 11.1%, respectively, while concurrently reducing proline accumulation by 12.2%. Under combined drought and Cd stress condition, the application of SiNPs led to a 20.4% increase in soluble sugar content and a 13.4% rise in soluble protein levels, while concurrently reducing proline content by 20.1%. Antioxidant enzyme activity and oxidative substance Compared to CK, drought stress significantly reduced catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities by 16.2%, 27.0%, and 39.6%, respectively, while Cd stress alone caused reductions of 8.3%, 21.7%, and 41.9%. The combined drought and Cd stress led to more pronounced decreases of 17.0%, 27.2%, and 43.6% in these enzymatic activities (Fig. 5). SiNPs application demonstrated differential enhancement effects on these antioxidant enzymes. Under drought conditions, SiNPs supplementation significantly elevated CAT, POD, and SOD activities by 17.8%, 11.1%, and 12.6% compared to non-Si treated plants. During Cd stress, Si treatment specifically enhanced POD and SOD activities by 9.07% and 11.24%. Most notably, under combined stress conditions, Si-treated plants showed substantial increases of 14.81%, 21.83%, and 20.76% in CAT, POD, and SOD activities, respectively. Drought and combined drought and Cd stress led to significant increases in superoxide radical (O 2 ·− ) and malondialdehyde (MDA) contents in maize leaves (p < 0.05), whereas, Cd stress alone had negligible effects on these oxidative markers (Fig. 6). Compared to CK, drought stress elevated O 2 ·− and MDA levels by 9.47% and 16.8%, respectively. While combined drought and Cd stress resulted in similar increases (9.06% for O 2 ·− and 16.8% for MDA). Notably, exogenous SiNPs application markedly attenuated oxidative damage, reducing O 2 ·− and MDA levels by 25.0% and 9.9%, respectively, with even greater reductions (25.3% for O 2 ·− and 15.1% for MDA) observed under combined drought and Cd stress. Cd content in maize tissues The analysis revealed a distinct gradient of Cd accumulation across maize tissues, with root tissue exhibiting the highest Cd concentrations, followed sequentially by stem, leaf, and grain compartments. Both Cd alone and combined drought-Cd stress conditions significantly enhanced Cd accumulation in plant tissues ( p 0.05). Quantitative analysis indicated pronounced magnification effects, with Cd concentrations escalating by factors of 18.5, 13.7, 8.17, and 4.05 in root, stem, leaf, and grain respectively under Cd stress, and comparable amplification factors of 18.5, 13.5, 9.5, and 4.29 under combined drought-Cd stress conditions. Notably, SiNPs supplementation exerted substantial mitigation effects, reducing Cd concentrations by 27.1%, 19.2%, 24.9%, and 23.8% in the respective tissues under Cd stress, and by 27.2%, 17.5%, 10.2%, and 27.6% under combined drought-Cd stress scenarios compared to non-Si treated controls. Statistical evaluation confirmed significant interaction effects between Cd and Si treatments across all tissue types ( p < 0.05). Contents of different Cd fractions in soil During the flowering stage, both Cd stress and combined drought-Cd stress markedly elevated the concentrations of exchangeable Cd, reducible Cd, oxidizable Cd, and residual Cd fractions in the soil (Fig. 8). In contrast, drought stress alone exhibited no significant effect on Cd content across all fractions ( p > 0.05). Notably, SiNPs application significantly reduced exchangeable Cd, reducible Cd, and oxidizable Cd contents by 28.3%, 21.9%, and 26.7%, respectively, compared to non-Si treated plants, while simultaneously increasing residual Cd content by 36.4%. Under combined drought-Cd stress, Si treatment further demonstrated efficacy, significantly decreasing exchangeable Cd, reducible Cd, and oxidizable Cd contents by 27.6%, 24.8%, and 23.9%, respectively, and substantially enhancing residual Cd content by 41.5%. Correlation analysis Correlation analysis identified six key maize yield-related indicators: relative water content (RWC), photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), superoxide dismutase (SOD), and peroxidase (POD), all of which demonstrated significant positive correlations with yield (Fig. 9). Notably, strong positive correlations were observed among SOD, catalase (CAT), POD, Pn, Tr, Gs, and phosphoenolpyruvate carboxylase (PEPC). In contrast, proline content exhibited significant negative correlations with RWC, Pn, Tr, Gs, and yield. Regarding cadmium (Cd) distribution, significant positive correlations were detected between Cd concentrations in maize grains, roots, stems, and leaves with reducible Cd, oxidizable Cd, and residual Cd fractions in soil. Discussion Effects of SiNPs application on plant growth, photosynthesis and grain yield under drought and Cd stress Drought and cadmium (Cd) stress, as representative abiotic stressors, significantly inhibit plant growth and development by disrupting water and nutrient uptake (Malik et al., 2021 ). Specifically, drought stress impairs plant water homeostasis by reducing root efficiency in absorbing both water and essential minerals, thereby impairing fundamental physiological processes, including photosynthesis and metabolic functions (Helaly et al., 2017 ). Excessive Cd decreases nutrient uptake, causes chlorophyll degradation and membrane lipid peroxidation, and inhibits photosynthesis and plant growth (Clemens et al., 2013 ). Photosynthesis plays a pivotal role in the production of plant biomass. In the present study, both drought and Cd stress significantly decreased the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate, as well as the enzymatic activities of phosphoenolpyruvate carboxylase (PEPCase) and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBPCase) ( p < 0.05) (Fig. 3 ). Notably, drought stress caused a more severe decline in photosynthetic parameters than Cd stress alone.‌ Consequently, drought stress significantly reduced leaf area (LA), leaf relative water content (LRWC) (Fig. 1 ), as well as straw dry weight and grain yield ( p 0.05).‌ However, both drought and Cd stress all significantly impacted root morphology, including root average diameter, volume, surface area, and dry weight ( p < 0.05) (Fig. 2 ). Mechanistically, drought stress primarily restricts root longitudinal extension, leading to reductions in length, volume, and biomass (Ashfaq et al., 2023), whereas Cd stress induces more comprehensive architectural changes, including diminished root length, surface area, volume, and tip number (Wang et al., 2023 ). Exogenous silicon nanoparticles (SiNPs) mitigated the adverse effects observed in this study. Under drought stress, SiNPs significantly enhanced photosynthetic efficiency (Pn, Gs, Tr), increased the enzymatic activities of PEPCase and RuBPCase, and improved key root morphological parameters including average diameter, volume, surface area, and dry weight (Fig.s 2–3). Consequently, SiNPs supplementation effectively enhanced root water absorption capacity, thereby sustaining better water balance and photosynthetic activity, ultimately reducing grain yield losses under drought stress. Peng et al. ( 2025 ) demonstrated that SiNPs significantly improved the root-to-shoot ratio and the net photosynthetic rate of Helianthus tuberosus L . seedlings under drought stress (Peng et al., 2025 ). Correlation analyses further corroborated positive relationships between LA, LRWC, Pn, Gs, Tr, root average diameter, root surface area and grain yield (Fig. 9 ). Silicon application enhances root water uptake and maintains water balance under deficit conditions, thereby boosting photosynthetic efficiency and reducing drought-induced yield losses (Cheraghi et al., 2024 ; Xu et al., 2022 ). Effects of SiNPs application on onosmotic regulation and antioxidant defense under drought and Cd stress Under abiotic stress, plants accumulate organic osmolytes like proline, glycine betaine, glucose, and fructose to maintain cellular osmotic balance and physiological activities (Easwar Rao et al., 2016). In this study, the results showed that the contents of soluble sugars, soluble proteins, and proline in maize leaves significantly increased under drought stress, Cd stress, and their combined stress conditions (Fig. 4 ). Meanwhile, supplementation with SiNPs further increased the contents of soluble sugars and soluble proteins, but decreased proline content under drought and Cd stresses compared with non-Si treated plants. These results are consistent with findings in maize (Altansambar et al., 2024 ) and wheat (Ning et al., 2023 ). Soluble sugars reduce cellular osmotic potential to preserve water status (Pilon et al., 2019 ), while soluble protein content, a crucial physiological indicator, positively correlates with plant stress resistance. Exogenous SiNPs application improves root water uptake under drought conditions through the active accumulation of soluble sugars and amino acids (Ali et al., 2018 ). Proline acts as a signaling molecule under stressful environments (Kavi Kishor et al., 2014). In this study, the decline induced by Si application under drought and Cd stresses indicated that proline merely serves as an indicator of stress damage in plants and does not play a role in osmotic regulation. This result was in line with studies of pei et al. ( 2010 ) and Zhu et al. (2014), which also demonstrated that decreased the osmotic potential and proline content and increased the soluble sugar content under drought stress (Pei et al., 2010 ; Zhu et al., 2014). However, other studies fond that Si application markedly increased proline content under drought or Cd stress (Alzahrani et al., 2018 ; Zhang et al., 2018 ). Therefore, how silicon regulates the accumulation of osmotic substances under abiotic stress, as well as the regulatory roles of these solutes in drought response, requires further in-depth investigation and clarification. When plants are subjected to abiotic stresses, their aerobic metabolic processes generate excessive reactive oxygen species (ROS). If ROS generation surpasses the scavenging capacity of the plant's antioxidant defense system, oxidative damage occurs (Fahad et al., 2016 ). In response, plants activate both enzymatic (e.g., CAT, POD, SOD) and non-enzymatic factors (e.g., phenolic compounds, flavonoids, anthocyanins) to counteract the harmful effects of ROS. This activation aims to prevent lipid peroxidation and the subsequent accumulation of malondialdehyde (MDA), thereby mitigating oxidative stress (Malik et al., 2021 ; Ur Rahman et al., 2021 ). In the present work, the results revealed that drought, Cd and their combined stress markedly decreased the activities of CAT, POD, and SOD, thereby increasing MDA and O 2 ·− accumulation in maize leaves. Exogenous Si application significantly enhanced activities of SOD, POD, and CAT while reducing MDA and O 2 ·− levels compared to non-Si treated plants under drought, Cd and their combined stresses (Fig.s 5, 6). Previous studies have also confirmed that exogenous Si application alleviates drought or Cd stress mainly through the activation of antioxidant enzymes, such as CAT, POD, SOD, and ascorbate peroxidase (APX), to enhance the ROS scavenging in plant cells (Eghlima et al., 2024 ; Ning et al., 2023 ; Shang et al., 2025 ; Thakral et al., 2024 ). Effects of SiNPs application on Cd accumulation in plant tissues and Cd distribution in soil under drought and Cd stress Cd accumulation exhibited significant among maize organs. Our results revealed that maize root tissues had the highest Cd contents, followed by leaf, stem, and grain. Meanwhile, Cd and combined drought-Cd stress significantly enhanced Cd accumulation in maize tissues, with the highest proportional increase observed in the roots and the lowest in the grains ( p < 0.05, Fig. 7 ). The results were in line with previous studies (Liu et al., 2020 ). Retaining higher levels of Cd in the roots is regarded as a protective strategy employed by the plant to alleviate metal-induced stress. Nevertheless, when the concentration of the element in the growth medium is elevated, a greater quantity of toxic metals can potentially enter the roots and be translocated to the aboveground plant tissues. In this work, we found that Si application significantly decreased Cd concentration in plant roots, stems, leaves and grains. Silicon's immobilization mechanisms operated mainly through two pathways. Firstly, silicon supplementation effectively reduced cadmium (Cd) bioavailability in soil. In this study, SiNPs application significantly decreased the levels of exchangeable and reducible Cd fractions (Fig. 8 ), which are highly bioavailable and readily absorbed by plants. The mechanisms underlying Si-induced Cd immobilization may involve two pathways: firstly, Si promotes the formation of Si-Cd hydroxyl compound precipitates through the interaction between SiO 3 2− and Cd in the soil, which significantly decreases the exchangeable Cd content while increasing the proportion of chemically stable residual Cd (Li et al., 2022 ); additionally, Si facilitates the transformation of Cd into more stable chemical forms by elevating soil pH (Kong et al., 2021 ). Secondly, within plants, it facilitates the formation of Si-Cd complexes that inhibit cadmium apoplastic transport (Khan et al., 2021 ; Ye et al., 2012). Specifically, Si-Cd complexes formed in stem and leaf tissues effectively block Cd translocation to grains, while monosilicic acid in leaves suppresses transmembrane Cd transport by competing for transporter binding sites (Zeng et al., 2022 ). Therefore, the application of exogenous Si represents a feasible and effective approach to reduce Cd accumulation in crops. Conclusions The results of this study demonstrated that drought and combined drought-Cd stress remarkably reduced maize growth parameters, including leaf area, leaf relative water content (LRWC), photosynthetic parameters, root attributes, activities of antioxidant enzymes, and grain yield. Cd stress alone had minimal impact on these growth parameters but significantly increased Cd accumulation in plant tissues. However, the application of SiNPs significantly improved root morphology, increased LRWC, enhanced the activities of antioxidant enzymes, and elevated the levels of soluble sugars and soluble proteins. These effects reduced reduced reactive oxygen species (ROS) and malondialdehyde (MDA) levels, thereby promoting photosynthetic efficiency and ultimately increasing grain yield compared with the non-Si treated plants under drought and combined stress. Additionally, SiNPs application significantly decreased Cd concentration in plant tissues by reducing Cd bioavailability in the soil under Cd stress. This study highlights the critical physicochemical role of silicon in strengthening maize resilience to drought and cadmium stress. Declarations Acknowledgements This work was jointly supported by the Central Public-Interest Scientific Institution Basal Research Fund, Chinese Academy of Agricultural Sciences/Farmland Irrigation Research Institute (IFI2023-05), the Agricultural Science and Technology Innovation Program (ASTIP), the Agriculture Research System of China (CARS-02). Author contributions Lin jing Li: Investigation, Data curation, Writing-original draft; Yan chen: Investigation; Anzhen Qin: Conceptualization ;Yingying Zhang: Formal analysis; Dongfeng Ning: Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Writing-review & editing. Zhandong Liu: Funding acquisition, Writing-review & editing. All authors read and approved the final manuscript. Data availability Data will be made available on request. Competing interests The authors have no relevant financial or non-financial interests to disclose. References Ahmed T, Masood HA, Noman M, AL-Huqail AA, Alghanem SM, Khan MM, Muhammad S, Manzoor N, Rizwan M, Qi X, Abeed AHA, Li B (2023) Biogenic silicon nanoparticles mitigate cadmium (Cd) toxicity in rapeseed (Brassica napus L.) by modulating the cellular oxidative stress metabolism and reducing Cd translocation. J Hazard Mater 459:132070. 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Agron Sustain Dev 34 (2):455–472. Tables Table 1 . Selected physico-chemical properties of the experimental soil (0–20 cm depth) Organic matter (g kg −1 ) Total N (g kg −1 ) Olsen-P (mg kg −1 ) Available K (mg kg −1 ) Available Si (mg kg −1 ) Bulk density (g cm −3 ) Field capacity (%) 16.8 1.12 10.9 277 328 1.35 24 Table 2. Protocol measurements for the indicators selected in this study Indicators Protocol Reference Relative Leaf water content (LRWC) Leaf was oven-dried to constant weight at 80 °C to determine the dry weight. LRWC was calculated by the equation: (Gong et al., 2005) Malondialdehyde (MDA) Thiobarbituric acid (TBA) method, supernatant was measured at 532 nm, 450 nm and 600 nm (Sudhakar et al., 2001) Superoxide radical (O 2 ·− ) Hydroxylamine oxidation method (He et al., 2020) Proline Acidic ninhydrin method (Zhang et al., 2017) Soluble sugar Anthrone-sulfuric acid method Soluble protein Coomassie brilliant blue method. SOD activity Nitro-blue tetrazolium reduction method (Gunes et al., 2007) CAT activity Measured as the reduction in absorbance at 240 nm due to the reduction of H 2 O 2 (He et al., 2020) POD activity Based on the determination of guaiacol oxidation at 470 nm by H 2 O 2 PEPCase PEPC activity was calculated by measuring the rate of NADH depletion at 340 nm (Liu et al., 2020) RuBPCase Rubisco activity was determined by monitoring the rate of NADH oxidation at 340 nm Table 3 BCR sequential extraction method of heavy metal in steel slag Fraction (0.5 g soil) Reagent conditions Exchangeable state (F1) Add 20 mL of 0.11 mol L -1 CH 3 COOH (pH 2.8), shake 16 h under 25°C, centrifuge, and filter. Reducible state (F2) Added 20 mL of 0.1 M NH 2 OH·HCl (adjusted to pH 2 with HNO 3 ), shake 16 h under 25°C, centrifuge, and filter. Oxidizable state (F3) Add 10 mL of 30% H 2 O 2 , digest 1 h at room temperature (covered with a watch glass), digest under 85 °C in a water bath for 1 h, repeat once; add 20 mL of 1 mol L -1 NH4Ac (adjusted to pH 2 with HNO 3 ), shake under 2 °C, centrifuge and filter. Residual state (F4) 3 mL HNO 3 +9 mL HCl beakers, heated on a hot plate and evaporated to near dryness Table 4. The effect of drought, cadmium stress and nano-Si application on grain yield, yield components, and straw biomass Treatment Straw dry weight (g plot -1 ) Yield (g plot -1 ) 100-kernel weight (g) kernels per spike CK 282.12 ±9.33 c 114.15 ± 5.24 b 33.74 ± 0.32 b 324.3 ± 8.54 ab D 279.82 ±6.11 c 69.07 ± 6.04 e 28.63 ± 0.89 d 203.7 ± 24.2 d Cd 281.37 ±1.62 c 106.76 ±1.13 bc 33.30 ± 0.05 b 315.4 ± 12.3 b D+Cd 278.53 ±3.24 c 69.33 ± 3.21e 28.04 ± 1.11d 199.5 ± 13.7 d CK+Si 286.08 ±6.33 c 137.78 ± 4.41a 33.94 ± 0.28 b 341.2 ± 7.26 a D+Si 307.78 ±7.61 ab 87.96 ± 4.40 d 31.23 ± 0.54 c 233.2 ± 7.53 c Cd+Si 294.34 ±3.16 bc 129.70 ± 6.45 a 35.75 ± 0.43 a 310.2 ± 6.68 b D+Cd+Si 313.53 ±4.92 a 92.42 ±1.84 cd 31.83 ± 0.09 c 214.4 ± 18.3 cd ANOVA D * ** ** ** Cd ns ns ns ns Si * ** ** ** D×Cd ns ns ns ns D×Si ns * ** ** Cd×Si ns ns ns ns D×Cd×Si ns ns ns ns Note, Data represent the mean ± standard error (SE) of three replicates. Different lowercase letters within a column indicate significant differences ( p ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium stress. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at p ≤ 0.01; * significant at p ≤ 0.05; ns, no significant difference). Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Major revisions 17 Mar, 2026 Reviewers agreed at journal 29 Jan, 2026 Reviewers invited by journal 29 Jan, 2026 Editor invited by journal 29 Jan, 2026 Editor assigned by journal 29 Jan, 2026 First submitted to journal 19 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8518329","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582326467,"identity":"c8422adb-0899-42d4-aa51-ff4e0c67650d","order_by":0,"name":"Dongfeng Ning","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYDACZiDmAWL2BiDxgSQtPAcYGBhnEG0TTAszDzGqzdl5D794U3HHroe99/Brmxo7efkG5mcP8GmxbOZLs5xz5llyD8+5NOucY8mGGw6wmRvg02JwmMfMmLftcLK9RI6ZcW4DM+MGBh42CaK08Mi/MTO2bKi3n99AWIvxY6AWOx4JIIOx4XBiwwEibGGcc+ZwAg9Pjhljz7HjyRsOs5nh13L+jPGHNxWH7XnYgYwfNdW289ubn+HVAgRgZyQ2QBmQyCUAmEHJxB7GGAWjYBSMglGAAQBRv0YJ6oNLmAAAAABJRU5ErkJggg==","orcid":"","institution":"Chinese Academy of Agricultural Sciences Farmland Irrigation Research Institute: Farmland Irrigation Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Dongfeng","middleName":"","lastName":"Ning","suffix":""},{"id":582326468,"identity":"0feaa63e-e8fd-47ea-917d-e9a7e4d77baf","order_by":1,"name":"Linjing Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Linjing","middleName":"","lastName":"Li","suffix":""},{"id":582326469,"identity":"0f6b4d36-343e-4f71-9a4d-677cae49ce46","order_by":2,"name":"Yan Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Chen","suffix":""},{"id":582326470,"identity":"33335551-1629-4fe5-8930-02c5a23220de","order_by":3,"name":"Anzhen Qin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Anzhen","middleName":"","lastName":"Qin","suffix":""},{"id":582326471,"identity":"afbe5d1f-0c69-4b9a-9d2f-683a79c547ea","order_by":4,"name":"Yingying Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Zhang","suffix":""},{"id":582326472,"identity":"03242739-5be8-4952-b48e-f3f141c17252","order_by":5,"name":"Zhandong Liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhandong","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-01-05 07:45:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8518329/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8518329/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101705432,"identity":"d2496cbf-1881-426d-9f33-8866d27324eb","added_by":"auto","created_at":"2026-02-02 19:25:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76592,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on maize leaf area (a), leaf relative water content (b) under under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/e40ba5e636131af9c5c3ef78.png"},{"id":101705419,"identity":"018efaa5-5d5a-477d-99cb-2e3aae70e734","added_by":"auto","created_at":"2026-02-02 19:24:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":918602,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on maize root average diameter (a), root length (b), root dry matter (c), root volume (d), and root surface area (e) under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.01; * significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/68d312ee536d03513a6dd210.png"},{"id":101754038,"identity":"48e82302-2b69-4980-bc48-2d080921a82c","added_by":"auto","created_at":"2026-02-03 10:41:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":314410,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on leaf photosynthetic rate (a), stomatal conductance (b), and transpiration rate (c), PEPCase activity (d) and RuBPCase activity under under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.01; * significant at \u003cem\u003ep\u003c/em\u003e≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/9319dbe828e4be96e6e29aa9.png"},{"id":101705428,"identity":"2af3f053-da66-4cc9-bf0d-b478d850f178","added_by":"auto","created_at":"2026-02-02 19:25:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2954639,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on the contents of soluble sugar contents (a), proline (b), soluble protein (c) in maize leaf under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e≤ 0.01; * significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/e6c158e9f61a43fd022b9a14.png"},{"id":101705433,"identity":"2c6a30bd-b090-42f8-985c-b81508620c50","added_by":"auto","created_at":"2026-02-02 19:25:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3083733,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on the activity of catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) in maize leaf under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.01; * significant at\u003cem\u003e p\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/f372626210546c892d0d6f4a.png"},{"id":101705424,"identity":"4247c6b1-ee0f-49db-b2bd-f4dd26917d92","added_by":"auto","created_at":"2026-02-02 19:25:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1762439,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on the contents of superoxide radical (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e·−, \u003c/sup\u003ea) and malondialdehyde (MDA, b) in maize leaf under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.01; * significant at\u003cem\u003e p\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/ee196a56315badc8213cccb6.png"},{"id":101705425,"identity":"69579e73-2a71-45e2-b65d-347249dd64b4","added_by":"auto","created_at":"2026-02-02 19:25:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":919350,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on Cd content in maize grain (a), stem (b), leaf (c) and root (d) under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e ≤ 0.01; * significant at\u003cem\u003e p\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/94d1428f6f78a74d58230c56.png"},{"id":101705423,"identity":"4873def7-2fe2-4a45-88c9-c6a12e80c60b","added_by":"auto","created_at":"2026-02-02 19:25:02","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":903601,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of SiNPs application on Cd content of different fractions in soil under drought, Cd and their combined stress. Different letters (a, b, c) above the bars indicate statistically significant differences (\u003cem\u003ep\u003c/em\u003e ≤ 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium. D×Si, Cd×Si, and D×Cd×Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u003c/em\u003e≤ 0.01; * significant at\u003cem\u003e p\u003c/em\u003e ≤ 0.05; ns, no significant difference).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/1bc64566de00a59a3fc6139b.png"},{"id":101705436,"identity":"3b3557be-a935-425e-8413-993892f1ab6d","added_by":"auto","created_at":"2026-02-02 19:25:05","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":379474,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation analysis among yield and selected pant growth and physiological parameters, as well as Cd content in different forms in soil. Red and blue represent positive and negative correlations, respectively. The deeper the color, the smaller the shape and the stronger the correlations. HKW, hundred-kernel weight; SDW, Straw dry weight; RA, root average diameter; RS, root surface area; LA, leaf area; RWC, relative water content; Pn, photosynthetic rate; Tr, transpiration rate; Gs, stomatal conductance; SOD, superoxidase; CAT, catalase; POD, peroxidase; MDA, malondialdehyde; O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e.-\u003c/sup\u003e, superoxide anion; SS, soluble sugar; SP, soluble protein; Rubisco, ribulose-1,5-bisphosphate carboxylase/oxygenase; PEPC, phosphoenolpyruvate carboxylase; Exch-Cd, Red-Cd, Ox-Cd and Res-Cd represents exchangeable, reducible, oxidizable, and residual Cd fractions, respectively; G-Cd, R-Cd, S-Cd and L-Cd represents Cd content in grain, root, stem, and leaf, respectively. ** indicates significance at \u003cem\u003ep\u003c/em\u003e ≤ 0.01, * Significant at\u003cem\u003e p\u003c/em\u003e ≤ 0.05.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/8577b72c71a2d594cf4a83e0.png"},{"id":101755806,"identity":"4dd79dca-2bb2-4ab5-8dee-748b35abf1bc","added_by":"auto","created_at":"2026-02-03 10:54:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13160551,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8518329/v1/b92c6e39-c0f2-432a-9f8c-8878ccbadeac.pdf"}],"financialInterests":"","formattedTitle":"The effects of Silica nanoparticles (SiNPs) application on maize (Zea mays L) growth, defense system and cadmium accumulation under Drought and Cadmium Stress","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAbiotic stresses including drought, salinity, high temperatures, flooding and heavy metals are major limiting factors for agricultural development and yield potential worldwide (S\u0026aacute;nchez-Berm\u0026uacute;dez et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Drought, with its growing frequency and severity, has emerged as a critical challenge to agricultural productivity and food security (Gu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Drought stress impacts crop growth and development through synergistic mechanisms: it compromises cell membrane integrity, disrupts the equilibrium between reactive oxygen species (ROS) and the antioxidant system, and impairs water-nutrient transport, ultimately resulting in a significant reduction in photosynthetic efficiency (Hussain et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mukarram et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Meanwhile, human activities, such as mining and metallurgy, industrial emission, agricultural fertilization have significantly increased heavy concentrations in agricultural soil, making them a key global environmental challenge (Zhao et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among heavy metals, cadmium (Cd) is one of the highly toxic heavy metals, exerting profound adverse effects on both plants and humans even at low concentrations (Lu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Cd can easily transfer from soil to plant tissues due to its high mobility (Cai et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and bioaccumulate in higher-trophic-level organisms through the food chain (Yang et al., 2022). Long-term intake of Cd-contaminated materials causes excessive Cd buildup in the human body, damaging organs and tissues irreversibly (Marques et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, developing effective strategies to mitigate Cd pollution is essential ensuring food security, particularly for staple crops (Deng et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSilicon (Si) is acknowledged as a beneficial element, demonstrating remarkable efficiency in alleviating both biotic stresses (e.g., plant diseases and pest infestations) and abiotic stresses (e.g., salinity, drought, heavy metal toxicity, and freezing). The alleviating mechanism mainly involved in improving water absorption, enhancing the antioxidant system, boosting osmotic regulation, increasing photosynthetic efficiency, and reducing metal uptake (Ayub et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ma et al., 2015; Qayyum et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yin et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Although Si is the second most abundant element in soil, the majority of soil Si exists in forms such as silicate crystals or precipitates, whereas plants primarily absorb Si as monosilicic acid (Ma et al., 2015; Yin et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This discrepancy significantly limits the bioavailability of plant-available Si in soils. Recently, nanoparticles (NPs) have attracted attention in agricultural production due to their altered size and shape properties, becoming a very promising alternative to traditional agricultural chemicals (Mukarram et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Among these nanomaterials, silicon nanoparticles (SiNPs) have demonstrated significant potential in promoting plant growth and enhancing plant tolerance to various abiotic stresses owing to their large surface area, good biocompatibility, and low risk (Ahmed et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chen F et al., 2024; Haider et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Jalil et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Mukarram et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For instance, SiNPs application mitigated Cd toxicity by regulating oxidative stress metabolism and inhibiting Cd translocation (Ahmed et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Jalil et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). SiNPs improved drought tolerance by modulating photosynthesis, stomatal activity, antioxidant enzyme activities, and carbon fixation (Chen F et al., 2024a; Haider et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMaize (\u003cem\u003eZea mays L\u003c/em\u003e.), one of the three major food crops, plays a triple role in grain production, animal feed, and industrial raw materials, holds strategic significance for national food security and economic development in China (Kaushal et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Maize has high water demands and is particularly sensitive to drought during its flowering stage (Hu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, maize is considered as a cadmium (Cd) accumulator and capable of accumulating high Cd concentrations in Cd-contaminated soils (Rizwan et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). To date, few studies have investigated the mitigating effects and mechanisms of SiNPs under combined drought and Cd stress. Therefore, a pot experiment was conducted with the following objectives: (i) to elucidate the impacts of SiNPs application on plant growth, physiological attributes, and yield performance of maize under individual or combined drought and Cd stress; and (ii) to determine the regulatory effects of SiNPs application on Cd uptake, translocation, and Cd speciation and bioavailability in soil systems under single and combined stress conditions. This research is expected to provide an economical strategy for mitigating drought and Cd stress in maize production.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eExperimental site\u003c/p\u003e\n\u003cp\u003eA soil column field experiment was conducted from June to October 2024 under a rain-shelter system at the Chinese Academy of Agricultural Sciences (CAAS) Xinxiang Comprehensive Experimental Base (35\u0026deg;18\u0026apos;N, 113\u0026deg;54\u0026apos;E) in Qiliying Town. The region exhibits typical temperate semi-humid drought-prone climatic conditions, with a mean annual temperature of 14 \u0026deg;C , 582 mm of precipitation, and 210 frost-free days. Each soil column system comprised two nested stainless steel buckets: a larger outer bucket (32 cm diameter \u0026times; 100 cm depth) buried in the soil, and a smaller inner bucket (30 cm diameter \u0026times; 100 cm depth) inserted into the larger one. To simulate field conditions, the columns were constructed with a 5 cm basal sand layer, followed by regionally typical field soil layers packed from 0-90 cm depth. This design facilitated robust root system development throughout the experiment. The selected soil physico-chemical properties are shown in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExperimental design\u003c/p\u003e\n\u003cp\u003eThe experiment included eight treatments: control [100% field capacity (FC), 0 mg kg\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eCd)], drought stress (50% FC, 0 mg/kg Cd ), Cd stress (100% FC, 5 mg kg\u003csup\u003e-1\u003c/sup\u003e Cd), combined stress (50% FC, 5 mg kg\u003csup\u003e-1\u003c/sup\u003e Cd) and each of these with or without SiNPs application (0 or 10 mg kg\u003csup\u003e-1\u003c/sup\u003e). Eight treatments in a randomized complete block design with six replications. Three biological replicates per treatment were selected for parameter measurements. At the maize flowering stage, plants under drought stress treatments were subjected to moderate drought stress (50% FC) for 7 days. Soil water content was measured by weighing soil columns. Irrigation was supplemented daily or every other day based on soil moisture, maize growth stage, and weather. Drought stress was imposed by reducing irrigation amount for 2-3 days, after which the columns were reweighed and irrigated to keep soil water at 50% field capacity. To achieve a water-soluble cadmium (Cd) concentration of 10 mg kg\u003csup\u003e-1\u003c/sup\u003e, soil samples in the Cd stress treatment were artificially amended with exogenous CdCl\u003csub\u003e2\u003c/sub\u003e\u0026middot;2H\u003csub\u003e2\u003c/sub\u003eO solutions. Silicon nanoparticles (SiNPs) were applied at rates of 30%, 20%, 30%, and 20% during the maize growth stages of sowing, jointing, tasseling, and flowering, respectively. Following regional fertilization practices, nutrient inputs were calculated based on 0-30 cm cm soil dry weight and applied at rates of 0.2 g N, 0.05 g P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e, and 0.10 g K\u003csub\u003e2\u003c/sub\u003eO per kg dry soil to meet maize requirements. Urea (with 46% N), superphosphate (with 18% P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e), and potassium sulfate (with 50% K\u003csub\u003e2\u003c/sub\u003eO) served as the sources of N, P, and K, respectively. P and K fertilizers were applied as basal dressing, whereas N fertilizer was split into two applications: 50% at the seedling stage and 50% at the jointing stage. Weeding and nitrogen topdressing were performed manually.\u003c/p\u003e\n\u003cp\u003eSampling and measurements\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLeaf samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAt the end of the drought period, ear leaf samples were destructively collected from three randomly selected pots per treatment. The collected samples were promptly flash-frozen in liquid nitrogen and then stored at -80 \u0026deg;C until physiological analyses. The physio-biochemical indices determined mainly included leaf relative water content (LRWC), chlorophyll content, activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), as well as the contents of superoxide radical (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e), malondialdehyde (MDA), proline, soluble sugar, soluble protein. Detailed analytical protocols for these selected indices are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhotosynthetic rate, transpiration rate, and stomatal conductance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAt the end of the drought period, three replicate ear leaves per treatment were selected to measure the photosynthetic rate, transpiration rate, and stomatal conductance using a portable photosynthesis system (LI-6400, LI-COR., Lincoln, NE, USA) between 9:00 and 11:00 a.m.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRoot system and grain yield\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAt the end of the drought stress period, three intact maize root samples were collected. Soil adhering to the roots was removed by rinsing with a high-pressure water spray, ensuring complete soil removal while maintaining root system integrity. Measurements of total root length, root diameter, root volume, and root surface area were conducted using the WinRHIZO root analysis system. Subsequently, the dry weight of the roots was determined after oven-drying at 75 \u0026deg;C until reaching a constant weight.\u003c/p\u003e\n\u003cp\u003eAt the maize harvest stage, three uniformly grown plants per treatment were chosen. Grains, leaves, and stems were individually collected. The samples were subsequently oven-dried at 75 \u0026deg;C until a constant mass was achieved, and the final dry weight was recorded.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlant Cd content\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA representative sample of up to 0.5 g was digested in 10mL of concentrated nitric acid (HNO\u003csub\u003e3\u003c/sub\u003e) for 15 min in a suitable laboratory microwave system. After the vessel had cooled, the solution was filtered and diluted to 25 mL with 0.5 M HCl. The concentration of Cd was determined using AAS (Wu et al., 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSoil Cd content determination\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSoil samples were collected from three pots at the flowering stages for sequential metal fractionation analysis using the BCR (Community Bureau of Reference) extraction procedure (Chenb R et al., 2024b). The detailed analytical protocols are presented in Table 3.\u0026nbsp;The concentration of Cd was determined using AAS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eAll data presented in the figures and tables are expressed as means \u0026plusmn; standard deviation (SD) of three biological replicates. Statistical analysis involved one-way analysis of variance (ANOVA), followed by the least significant difference (LSD) test to determine significant differences (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) among treatment means. Pearson correlation analysis was conducted to assess the relationships between grain yield, physiological parameters, and Cd content in both plant tissues and soil. All statistical analyses were conducted using SPSS 18.0, and graphical representations were generated using Origin 2022.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eMaize growth parameters and yield\u003c/p\u003e\n\u003cp\u003eEight-day drought stress applied during the maize VT stage caused significant reductions in both leaf area (LA) and leaf relative water content (LRWC) (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 1). Compared to the control (CK), drought stress alone decreased LA and LRWC by 6.92% and 5.57%, respectively, while combined drought-Cd stress led to more pronounced declines (LA: 8.14%, LRWC: 8.81%). Whereas, Cd stress alone exhibited no significant effect on these parameters (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). The application of silica nanoparticles (SiNPs) effectively counteracted drought-induced inhibition. Under drought stress, SiNPs application significantly increased LA and LRWC by 11.0% and 4.58%, respectively, compared to non-Si-treated plants. This mitigation effect was even stronger under combined stress conditions, with improvements of 12.2% (LA) and 7.36% (LRWC).\u003c/p\u003e\n\u003cp\u003eAll stress treatments (drought, Cd, and their combination) significantly inhibited root morphological parameters compared to the CK treatment, including reductions in root average diameter, root surface area, and root dry weight (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 2). Interestingly, drought stress alone induced a significant increase in root length (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), suggesting a potential adaptive response. The application of SiNPs effectively mitigated these stress effects. Under drought stress, Si treatment enhanced root average diameter, root volume, root surface area, and root dry weight by 17.1%, 20.4%, 9.23%, and 17.7%, respectively, relative to non-Si-treated plants. Similar improvements were observed under Cd stress (12.7%, 14.9%, 14.6%, and 7.4%, respectively). Most notably, under combined stress conditions, Si demonstrated the strongest protective effects, with increases of 13.4% (root diameter), 24.8% (root volume), 23.4% (root surface area), and 20.0% (root dry weight).\u003c/p\u003e\n\u003cp\u003eDrought stress applied during the VT growth stage of maize exerted significant negative effects on grain yield and yield components (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Table 2). Compared to the CK treatment, drought stress significantly reduced grain yield by 39.5%, 100-kernel weight by 15.2%, and kernels per spike by 37.2%. Combined drought and Cd stress resulted in reductions of 39.2%, 16.9%, and 38.5% in these parameters, respectively. Notably, Cd stress alone had no significant impact on any yield components (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05), suggesting that the observed yield declines were primarily driven by drought stress. The application of SiNPs demonstrated significant mitigation effects (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). Under drought conditions, Si-treated plants exhibited increases of 27.3%, 9.08%, and 14.5% in grain yield, 100-kernel weight, and kernels per spike, respectively, compared to the non-Si-treated control. Under combined stress, the corresponding increases were 18.9%, 13.5%, and 7.47%.\u003c/p\u003e\n\u003cp\u003eGas exchange parameters and photosynthetic enzymes\u003c/p\u003e\n\u003cp\u003eAt the VT stage of maize, drought, cadmium (Cd), and their combined stress significantly suppressed photosynthetic parameters (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 3). Compared to the control (CK), drought stress reduced the net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr) by 12.5%, 64.1%, and 40.2%, respectively. Cd stress alone caused milder but still significant declines (Pn: 4.37%; Gs: 29.4%; Tr: 16.4%). Notably, their combined stress exhibited synergistic inhibition, with reductions reaching 13.4% (Pn), 69.0% (Gs), and 51.0% (Tr). SiNPs application differentially mitigated these stresses (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Under drought stress, SiNPs application enhanced Pn, Sc, and Tr by 11.3%, 63.2%, and 35.0%, respectively, compared to non-Si-treated plants. For Cd stress, the improvements were 7.75% (Pn), 29.5% (Gs), and 8.5% (Tr). Most strikingly, under combined stress, SiNPs enhanced these parameters by 16.4% (Pn), 94.6% (Gs), and 66.4% (Tr), demonstrating pronounced stress-alleviating effects.\u003c/p\u003e\n\u003cp\u003eDrought, Cd, and their combination significantly inhibited the enzymatic activities of both phosphoenolpyruvate carboxylase (PEPCase) and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBPCase) at the VT stage (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig. 3). Specifically, drought stress alone reduced PEPCase and RuBPCase activities by 21.1% and 39.4%, respectively. Cd stress exhibited comparable inhibitory effects (35.6% for PEPCase, 37.4% for RuBPCase), while the combined stress showed the most severe suppression (36.3% and 49.7% reduction for PEPCase and RuBPCase, respectively). The application of SiNPs demonstrated significant stress-mitigating effects (\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.05). Under drought conditions, SiNPs treatment increased PEPCase and RuBPCase activities by 6.81% and 28.1%, respectively, compared to non-Si treated plants. The enhancement was more moderate under Cd stress (4.08% for PEPCase, 14.2% for RuBPCase), but was most pronounced under combined stress (11.8% and 46.4% for PEPCase and RuBPCase, respectively), suggesting a synergistic protective mechanism.\u003c/p\u003e\n\u003cp\u003eOsmotic solute content\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the VT stage, maize plants exhibited significant accumulation of osmolytes (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), including soluble sugars, proline and soluble proteins in leaves under drought and combined drought and Cd stress (Fig. 4). While, Cd stress alone showed little impact on these parameters (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). Relative to the CK, drought stress elevated soluble sugar, proline, and soluble protein levels by 5.37%, 92.6%, and 13.7%, respectively. The combined drought and Cd stress exhibited the most pronounced effects, with respective increments of 10.8%, 140.8%, and 15.8%. Application of SiNPs demonstrated differential regulatory effects compared to non-Si-treated plants. Under drought stress condition, SiNPs treatment significantly enhanced soluble sugar and protein contents by 20.1% and 11.1%, respectively, while concurrently reducing proline accumulation by 12.2%. Under combined drought and Cd stress condition, the application of SiNPs led to a 20.4% increase in soluble sugar content and a 13.4% rise in soluble protein levels, while concurrently reducing proline content by 20.1%.\u003c/p\u003e\n\u003cp\u003eAntioxidant enzyme activity and oxidative substance\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Compared to CK, drought stress significantly reduced catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities by 16.2%, 27.0%, and 39.6%, respectively, while Cd stress alone caused reductions of 8.3%, 21.7%, and 41.9%. The combined drought and Cd stress led to more pronounced decreases of 17.0%, 27.2%, and 43.6% in these enzymatic activities (Fig. 5). SiNPs application demonstrated differential enhancement effects on these antioxidant enzymes. Under drought conditions, SiNPs supplementation significantly elevated CAT, POD, and SOD activities by 17.8%, 11.1%, and 12.6% compared to non-Si treated plants. During Cd stress, Si treatment specifically enhanced POD and SOD activities by 9.07% and 11.24%. Most notably, under combined stress conditions, Si-treated plants showed substantial increases of 14.81%, 21.83%, and 20.76% in CAT, POD, and SOD activities, respectively.\u003c/p\u003e\n\u003cp\u003eDrought and combined drought and Cd stress led to significant increases in superoxide radical (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e) and malondialdehyde (MDA) contents in maize leaves (p \u0026lt; 0.05), whereas, Cd stress alone had negligible effects on these oxidative markers (Fig. 6). Compared to CK, drought stress elevated O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e and MDA levels by 9.47% and 16.8%, respectively. While combined drought and Cd stress resulted in similar increases (9.06% for O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e and 16.8% for MDA). Notably, exogenous SiNPs application markedly attenuated oxidative damage, reducing O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u0026nbsp;\u003c/sup\u003eand MDA levels by 25.0% and 9.9%, respectively, with even greater reductions (25.3% for O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e and 15.1% for MDA) observed under combined drought and Cd stress.\u003c/p\u003e\n\u003cp\u003eCd content in maize tissues\u003c/p\u003e\n\u003cp\u003eThe analysis revealed a distinct gradient of Cd accumulation across maize tissues, with root tissue exhibiting the highest Cd concentrations, followed sequentially by stem, leaf, and grain compartments. Both Cd alone and combined drought-Cd stress conditions significantly enhanced Cd accumulation in plant tissues (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, Fig. 7), whereas drought stress alone showed no significant influence on Cd concentrations (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). Quantitative analysis indicated pronounced magnification effects, with Cd concentrations escalating by factors of 18.5, 13.7, 8.17, and 4.05 in root, stem, leaf, and grain respectively under Cd stress, and comparable amplification factors of 18.5, 13.5, 9.5, and 4.29 under combined drought-Cd stress conditions. Notably, SiNPs supplementation exerted substantial mitigation effects, reducing Cd concentrations by 27.1%, 19.2%, 24.9%, and 23.8% in the respective tissues under Cd stress, and by 27.2%, 17.5%, 10.2%, and 27.6% under combined drought-Cd stress scenarios compared to non-Si treated controls. Statistical evaluation confirmed significant interaction effects between Cd and Si treatments across all tissue types (\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.05).\u003c/p\u003e\n\u003cp\u003eContents of different Cd fractions in soil\u003c/p\u003e\n\u003cp\u003eDuring the flowering stage, both Cd stress and combined drought-Cd stress markedly elevated the concentrations of exchangeable Cd, reducible Cd, oxidizable Cd, and residual Cd fractions in the soil (Fig. 8). In contrast, drought stress alone exhibited no significant effect on Cd content across all fractions (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). Notably, SiNPs application significantly reduced exchangeable Cd, reducible Cd, and oxidizable Cd contents by 28.3%, 21.9%, and 26.7%, respectively, compared to non-Si treated plants, while simultaneously increasing residual Cd content by 36.4%. Under combined drought-Cd stress, Si treatment further demonstrated efficacy, significantly decreasing exchangeable Cd, reducible Cd, and oxidizable Cd contents by 27.6%, 24.8%, and 23.9%, respectively, and substantially enhancing residual Cd content by 41.5%.\u003c/p\u003e\n\u003cp\u003eCorrelation analysis\u003c/p\u003e\n\u003cp\u003eCorrelation analysis identified six key maize yield-related indicators: relative water content (RWC), photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), superoxide dismutase (SOD), and peroxidase (POD), all of which demonstrated significant positive correlations with yield (Fig. 9). Notably, strong positive correlations were observed among SOD, catalase (CAT), POD, Pn, Tr, Gs, and phosphoenolpyruvate carboxylase (PEPC). In contrast, proline content exhibited significant negative correlations with RWC, Pn, Tr, Gs, and yield. Regarding cadmium (Cd) distribution, significant positive correlations were detected between Cd concentrations in maize grains, roots, stems, and leaves with reducible Cd, oxidizable Cd, and residual Cd fractions in soil.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eEffects of SiNPs application on plant growth, photosynthesis and grain yield under drought and Cd stress\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDrought and cadmium (Cd) stress, as representative abiotic stressors, significantly inhibit plant growth and development by disrupting water and nutrient uptake (Malik et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Specifically, drought stress impairs plant water homeostasis by reducing root efficiency in absorbing both water and essential minerals, thereby impairing fundamental physiological processes, including photosynthesis and metabolic functions (Helaly et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Excessive Cd decreases nutrient uptake, causes chlorophyll degradation and membrane lipid peroxidation, and inhibits photosynthesis and plant growth (Clemens et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePhotosynthesis plays a pivotal role in the production of plant biomass. In the present study, both drought and Cd stress significantly decreased the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate, as well as the enzymatic activities of phosphoenolpyruvate carboxylase (PEPCase) and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBPCase) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Notably, drought stress caused a more severe decline in photosynthetic parameters than Cd stress alone.\u0026zwnj; Consequently, drought stress significantly reduced leaf area (LA), leaf relative water content (LRWC) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), as well as straw dry weight and grain yield (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Cd stress alone did not significantly affect these shoot growth parameters (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u0026zwnj; However, both drought and Cd stress all significantly impacted root morphology, including root average diameter, volume, surface area, and dry weight (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Mechanistically, drought stress primarily restricts root longitudinal extension, leading to reductions in length, volume, and biomass (Ashfaq et al., 2023), whereas Cd stress induces more comprehensive architectural changes, including diminished root length, surface area, volume, and tip number (Wang et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExogenous silicon nanoparticles (SiNPs) mitigated the adverse effects observed in this study. Under drought stress, SiNPs significantly enhanced photosynthetic efficiency (Pn, Gs, Tr), increased the enzymatic activities of PEPCase and RuBPCase, and improved key root morphological parameters including average diameter, volume, surface area, and dry weight (Fig.s 2\u0026ndash;3). Consequently, SiNPs supplementation effectively enhanced root water absorption capacity, thereby sustaining better water balance and photosynthetic activity, ultimately reducing grain yield losses under drought stress. Peng et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) demonstrated that SiNPs significantly improved the root-to-shoot ratio and the net photosynthetic rate of \u003cem\u003eHelianthus tuberosus L\u003c/em\u003e. seedlings under drought stress (Peng et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Correlation analyses further corroborated positive relationships between LA, LRWC, Pn, Gs, Tr, root average diameter, root surface area and grain yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Silicon application enhances root water uptake and maintains water balance under deficit conditions, thereby boosting photosynthetic efficiency and reducing drought-induced yield losses (Cheraghi et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eEffects of SiNPs application on onosmotic regulation and antioxidant defense under drought and Cd stress\u003c/h2\u003e \u003cp\u003eUnder abiotic stress, plants accumulate organic osmolytes like proline, glycine betaine, glucose, and fructose to maintain cellular osmotic balance and physiological activities (Easwar Rao et al., 2016). In this study, the results showed that the contents of soluble sugars, soluble proteins, and proline in maize leaves significantly increased under drought stress, Cd stress, and their combined stress conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Meanwhile, supplementation with SiNPs further increased the contents of soluble sugars and soluble proteins, but decreased proline content under drought and Cd stresses compared with non-Si treated plants. These results are consistent with findings in maize (Altansambar et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and wheat (Ning et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Soluble sugars reduce cellular osmotic potential to preserve water status (Pilon et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while soluble protein content, a crucial physiological indicator, positively correlates with plant stress resistance. Exogenous SiNPs application improves root water uptake under drought conditions through the active accumulation of soluble sugars and amino acids (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Proline acts as a signaling molecule under stressful environments (Kavi Kishor et al., 2014). In this study, the decline induced by Si application under drought and Cd stresses indicated that proline merely serves as an indicator of stress damage in plants and does not play a role in osmotic regulation. This result was in line with studies of pei et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Zhu et al. (2014), which also demonstrated that decreased the osmotic potential and proline content and increased the soluble sugar content under drought stress (Pei et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Zhu et al., 2014). However, other studies fond that Si application markedly increased proline content under drought or Cd stress (Alzahrani et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, how silicon regulates the accumulation of osmotic substances under abiotic stress, as well as the regulatory roles of these solutes in drought response, requires further in-depth investigation and clarification.\u003c/p\u003e \u003cp\u003eWhen plants are subjected to abiotic stresses, their aerobic metabolic processes generate excessive reactive oxygen species (ROS). If ROS generation surpasses the scavenging capacity of the plant's antioxidant defense system, oxidative damage occurs (Fahad et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In response, plants activate both enzymatic (e.g., CAT, POD, SOD) and non-enzymatic factors (e.g., phenolic compounds, flavonoids, anthocyanins) to counteract the harmful effects of ROS. This activation aims to prevent lipid peroxidation and the subsequent accumulation of malondialdehyde (MDA), thereby mitigating oxidative stress (Malik et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ur Rahman et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the present work, the results revealed that drought, Cd and their combined stress markedly decreased the activities of CAT, POD, and SOD, thereby increasing MDA and O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e accumulation in maize leaves. Exogenous Si application significantly enhanced activities of SOD, POD, and CAT while reducing MDA and O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e levels compared to non-Si treated plants under drought, Cd and their combined stresses (Fig.s 5, 6). Previous studies have also confirmed that exogenous Si application alleviates drought or Cd stress mainly through the activation of antioxidant enzymes, such as CAT, POD, SOD, and ascorbate peroxidase (APX), to enhance the ROS scavenging in plant cells (Eghlima et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ning et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Thakral et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEffects of SiNPs application on Cd accumulation in plant tissues and Cd distribution in soil under drought and Cd stress\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCd accumulation exhibited significant among maize organs. Our results revealed that maize root tissues had the highest Cd contents, followed by leaf, stem, and grain. Meanwhile, Cd and combined drought-Cd stress significantly enhanced Cd accumulation in maize tissues, with the highest proportional increase observed in the roots and the lowest in the grains (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The results were in line with previous studies (Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Retaining higher levels of Cd in the roots is regarded as a protective strategy employed by the plant to alleviate metal-induced stress. Nevertheless, when the concentration of the element in the growth medium is elevated, a greater quantity of toxic metals can potentially enter the roots and be translocated to the aboveground plant tissues. In this work, we found that Si application significantly decreased Cd concentration in plant roots, stems, leaves and grains.\u003c/p\u003e \u003cp\u003eSilicon's immobilization mechanisms operated mainly through two pathways. Firstly, silicon supplementation effectively reduced cadmium (Cd) bioavailability in soil. In this study, SiNPs application significantly decreased the levels of exchangeable and reducible Cd fractions (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), which are highly bioavailable and readily absorbed by plants. The mechanisms underlying Si-induced Cd immobilization may involve two pathways: firstly, Si promotes the formation of Si-Cd hydroxyl compound precipitates through the interaction between SiO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and Cd in the soil, which significantly decreases the exchangeable Cd content while increasing the proportion of chemically stable residual Cd (Li et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); additionally, Si facilitates the transformation of Cd into more stable chemical forms by elevating soil pH (Kong et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Secondly, within plants, it facilitates the formation of Si-Cd complexes that inhibit cadmium apoplastic transport (Khan et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ye et al., 2012). Specifically, Si-Cd complexes formed in stem and leaf tissues effectively block Cd translocation to grains, while monosilicic acid in leaves suppresses transmembrane Cd transport by competing for transporter binding sites (Zeng et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, the application of exogenous Si represents a feasible and effective approach to reduce Cd accumulation in crops.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of this study demonstrated that drought and combined drought-Cd stress remarkably reduced maize growth parameters, including leaf area, leaf relative water content (LRWC), photosynthetic parameters, root attributes, activities of antioxidant enzymes, and grain yield. Cd stress alone had minimal impact on these growth parameters but significantly increased Cd accumulation in plant tissues. However, the application of SiNPs significantly improved root morphology, increased LRWC, enhanced the activities of antioxidant enzymes, and elevated the levels of soluble sugars and soluble proteins. These effects reduced reduced reactive oxygen species (ROS) and malondialdehyde (MDA) levels, thereby promoting photosynthetic efficiency and ultimately increasing grain yield compared with the non-Si treated plants under drought and combined stress. Additionally, SiNPs application significantly decreased Cd concentration in plant tissues by reducing Cd bioavailability in the soil under Cd stress. This study highlights the critical physicochemical role of silicon in strengthening maize resilience to drought and cadmium stress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThis work was jointly supported by the Central Public-Interest Scientific Institution Basal Research Fund, Chinese Academy of Agricultural Sciences/Farmland Irrigation Research Institute (IFI2023-05), the Agricultural Science and Technology Innovation Program (ASTIP), the Agriculture Research System of China (CARS-02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLin jing Li: Investigation, Data curation, Writing-original draft; Yan chen: Investigation; Anzhen Qin: Conceptualization ;Yingying Zhang: Formal analysis; Dongfeng Ning: Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Writing-review \u0026amp; editing. Zhandong Liu: Funding acquisition, Writing-review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e Data will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmed T, Masood HA, Noman M, AL-Huqail AA, Alghanem SM, Khan MM, Muhammad S, Manzoor N, Rizwan M, Qi X, Abeed AHA, Li B (2023) Biogenic silicon nanoparticles mitigate cadmium (Cd) toxicity in rapeseed (Brassica napus L.) by modulating the cellular oxidative stress metabolism and reducing Cd translocation. 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Sci Hortic 262:108745.\u003c/li\u003e\n\u003cli\u003eHelaly MN, El-Hoseiny H, El-Sheery NI, Rastogi A, Kalaji HM (2017) Regulation and physiological role of silicon in alleviating drought stress of mango. Plant Physiol Biochem 118:31\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eHu J, Zhao XY, Gu LM, Liu P, Zhao B, Zhang JW, Ren BZ (2023) The effects of high temperature, drought, and their combined stresses on the photosynthesis and senescence of summer maize. Agric Water Manag 289:108525. \u003c/li\u003e\n\u003cli\u003eHussain M, Farooq S, Hasan W, Ul-Allah S, Tanveer M, Farooq M, Nawaz A (2018) Drought stress in sunflower: physiological effects and its management through breeding and agronomic alternatives. Agric Water Manag 201:152\u0026ndash;166.\u003c/li\u003e\n\u003cli\u003eJalil S, Nazir MM, AL-Huqail AA, Ali B, Al-Qthanin RN, Asad MAU, Eweda MA, Zulfiqar F, Onursal N, Masood HA, Yong JWH, Jin XL (2023) Silicon nanoparticles alleviate cadmium toxicity in rice (Oryza sativa L.) by modulating the nutritional profile and triggering stress-responsive genetic mechanisms. Ecotoxicol Environ Saf 268:115699.\u003c/li\u003e\n\u003cli\u003eKaushal M, Sharma R, Vaidya D, Gupta A, Saini HK, Anand A, Thakur C, Verma A, Thakur M, Priyanka, Dileep KC (2023) Maize: an underexploited golden cereal crop. Cereal Res Commun 51:3\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eKavi Kishor PB, Sreenivasulu N (2014) Is proline accumulation per se correlated with stress tolerance or is proline homeostasis a more critical issue? Plant Cell Environ 37 (2):300\u0026ndash;311.\u003c/li\u003e\n\u003cli\u003eKhan I, Awan SA, Rizwan M, Ali S, Hassan MJ, Brestic M, Zhang XQ, Huang LK (2021) Effects of silicon on heavy metal uptake at the soil-plant interphase: a review. Ecotoxicol Environ Saf 222:112510. \u003c/li\u003e\n\u003cli\u003eKong L, Guo Z, Peng C, Xiao X, He Y (2021) Factors influencing the effectiveness of liming on cadmium reduction in rice: a meta-analysis and decision tree analysis. Sci Total Environ 79:146477.\u003c/li\u003e\n\u003cli\u003eLi DM, Liu HY, Gao M, Zhou J, Zhou J (2022) Effects of soil amendments, foliar sprayings of silicon and selenium and their combinations on the reduction of cadmium accumulation in rice. Pedosphere 32 (4):649\u0026ndash;659.\u003c/li\u003e\n\u003cli\u003eLiu JC, Zhao YJ, Song HY, Chen JY, Long Y (2020) Antagonism or synergism? Combined effects of enhanced UV-B radiation and acid rain on photosynthesis in seedlings of two C4 plants. Acta Ecol Sin 40:72\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eLiu XX, Yin L, Deng XP, Gong D, Du S, Wang SW, Zhang ZY (2020) Combined application of silicon and nitric oxide jointly alleviated cadmium accumulation and toxicity in maize. J Hazard Mater 395:122679.\u003c/li\u003e\n\u003cli\u003eLu HM, Qin ST, Zhao JY, Pan P, Wang FL, Tang SD, Chen LH, Kashif A, He B (2023) Silicon inhibits the upward transport of Cd in the first internode of different rice varieties in a Cd stressed farm land. J Hazard Mater 458:131860.\u003c/li\u003e\n\u003cli\u003eMa JF, Yamaji N (2015) A cooperative system of silicon transport in plants. Trends Plant Sci 20 (7):435\u0026ndash;442.\u003c/li\u003e\n\u003cli\u003eMalik MA, Wani AH, Mir SH, Rehman I, Tahir I, Ahmad P, Rashid I (2021) Elucidating the role of silicon in drought stress tolerance in plants. Plant Physiol Biochem 165:187\u0026ndash;195.\u003c/li\u003e\n\u003cli\u003eMarques DN, Piotto FA, Azevedo RA (2024) Phosphoproteomics: advances in research on cadmium-exposed plants. Int J Mol Sci 25 (22):12431. \u003c/li\u003e\n\u003cli\u003eMukarram M, Choudhary S, Kurjak D, Petek A, Khan MMA (2021) Drought: sensing, signalling, effects and tolerance in higher plants. Physiol Plant 172:1291\u0026ndash;1300. \u003c/li\u003e\n\u003cli\u003eMukarram M, Petrik P, Mushtaq Z, Khan MMA, Gulfishan M, Lux A (2022) Silicon nanoparticles in higher plants: uptake, action, stress tolerance, and crosstalk with phytohormones, antioxidants, and other signalling molecules. Environ Pollut 310:119855.\u003c/li\u003e\n\u003cli\u003eNing DF, Zhang YY, Li XJ, Qin AZ, Huang C, Fu YY, Gao Y, Duan AW (2023) The Effects of foliar supplementation of silicon on physiological and biochemical responses of winter wheat to drought stress during different growth stages. Plants 12:2386. \u003c/li\u003e\n\u003cli\u003ePei ZF, Ming DF, Liu D, Wan GL, Geng XX, Gong HJ, Zhou WJ (2010) Silicon improves the tolerance to water-deficit stress induced by polyethylene glycol in wheat (Triticum aestivum L.) Seedlings. J Plant Growth Regul 29 (1):106\u0026ndash;115.\u003c/li\u003e\n\u003cli\u003ePeng YQ, Yang R, Yang PH, Yang TQ, Liu Y, Liu YQ, Chong S, Zhu YG, Ma HH (2025) Enhancing antioxidant capacity and regulating aquaporin genes expression for better water absorption by nano-silicon. Sci Hortic 349:114234. \u003c/li\u003e\n\u003cli\u003ePilon C, Loka D, Snider JL, Oosterhuis DM (2019) Drought‐induced osmotic adjustment and changes in carbohydrate distribution in leaves and flowers of cotton (Gossypium hirsutum L.). J Agron Crop Sci 205 (2):168\u0026ndash;178.\u003c/li\u003e\n\u003cli\u003eQayyum MF, Rehman MZur, Ali S, Rizwan M, Naeem A, Maqsood MA, Khalid H, Rinklebe J, Ok YS (2017) Residual effects of monoammonium phosphate, gypsum and elemental sulfur on cadmium phytoavailability and translocation from soil to wheat in an effluent irrigated field. Chemosphere 174:515\u0026ndash;523. \u003c/li\u003e\n\u003cli\u003eRahman SU, Qi XB, Zhao ZJ, Du ZJ, Imtiaz M, Mehmood F, Lu HF, Hussain B, Ashraf MN (2021) Alleviatory effects of silicon on the morphology, physiology, and antioxidative mechanisms of wheat (Triticum aestivum L.) roots under cadmium stress in acidic nutrient solutions. Sci Rep 11 (1):1958.\u003c/li\u003e\n\u003cli\u003eRao DE, Chaitanya KV (2016) Photosynthesis and antioxidative defense mechanisms in deciphering drought stress tolerance of crop plants. Biol Plant 60 (2): 201\u0026ndash;218.\u003c/li\u003e\n\u003cli\u003eRizwan M, Ali S, Qayyum MF, Ok YS, Zia-ur-Rehman M, Abbas Z, Hannan F (2017) Use of maize (Zea mays L.) for phytomanagement of Cd-contaminated soils: a critical review. Environ Geochem Health 39 (2):259\u0026ndash;277. \u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Berm\u0026uacute;dez M, del Pozo JC, Pernas M (2022) Effects of combined abiotic stresses related to climate change on root growth in crops. Front Plant Sci 13:918537. \u003c/li\u003e\n\u003cli\u003eShang HL, Huang X, Zhang XY, Zheng ZQ, Yang Q, Gao HY (2025) Transcriptomic analysis reveals the mechanism of silicon-regulated reversion of hyperhydricity in Dendrobium officinale: transcriptomic analysis reveals the mechanism. In Vitro Cell Dev Biol Plant 61 (2):443\u0026ndash;456.\u003c/li\u003e\n\u003cli\u003eSudhakar C, Lakshmi A, Giridarakumar S (2001) Changes in the antioxidant enzyme efficacy in two high yielding genotypes of mulberry (\u003cem\u003e Morus alba L\u003c/em\u003e.) under NaCl salinity. Plant Sci 161 (3):613\u0026ndash;619.\u003c/li\u003e\n\u003cli\u003eThakral V, Sudhakaran S, Jadhav H, Mahakalkar B, Sehra A, Dhar H, Kumar S, Sonah H, Sharma TR, Deshmukh R (2024) Unveiling silicon-mediated cadmium tolerance mechanisms in mungbean (Vigna radiata (L.) Wilczek): integrative insights from gene expression, antioxidant responses, and metabolomics. J Hazard Mater 474:134671. \u003c/li\u003e\n\u003cli\u003eWang L, Zou R, Cai JH, Liu GH, Ya J, Chai GQ, Song F, Fan CW (2023) Effect of Cd toxicity on root morphology, ultrastructure, Cd uptake and accumulation of wheat under intercropping with Solanum nigrum L. Heliyon 9:e16270.\u003c/li\u003e\n\u003cli\u003eWu ZC, Xu SJ, Shi HZ, Zhao PH, Liu XX, Li FR, Deng THB, Du RY, Wang X, Wang FH (2018) Comparison of foliar silicon and selenium on cadmium absorption, compartmentation, translocation and the antioxidant system in chinese flowering cabbage. Ecotoxicol Environ Saf 166:157\u0026ndash;164.\u003c/li\u003e\n\u003cli\u003eXu JQ, Guo LF, Liu LW (2022) Exogenous silicon alleviates drought stress in maize by improving growth, photosynthetic and antioxidant metabolism. Environ Exp Bot 01:104974.\u003c/li\u003e\n\u003cli\u003eYang R, Liang X, Strawn DG (2023) Variability in cadmium uptake in common wheat under cadmium stress: impact of genetic variation and silicon supplementation. Agriculture 12:848.\u003c/li\u003e\n\u003cli\u003eYe J, Yan CG, Liu JC, Lu HL, Liu T, Song ZF (2021) Effects of silicon on the distribution of cadmium compartmentation in root tips of Kandelia obovata (S., L.) Yong. Environ Pollut 162:369\u0026ndash;373.\u003c/li\u003e\n\u003cli\u003eYin JY, Jia JH., Lian ZY, Hu YH, Guo J, Huo HQ, Zhu YG, Gong HJ (2019) Silicon enhances the salt tolerance of cucumber through increasing polyamine accumulation and decreasing oxidative damage. Ecotoxicol Environ Saf 169:8\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eZeng P, Wei BY, Zhou H, Gu JF, Liao BH (2022) Co-application of water management and foliar spraying silicon to reduce cadmium and arsenic uptake in rice: a two-year field experiment. Sci Total Environ 818:151801.\u003c/li\u003e\n\u003cli\u003eZhang WJ, Xie ZC, Wang LH, Li M, Lang DY, Zhang XH (2017) Silicon alleviates salt and drought stress of Glycyrrhiza uralensis seedling by altering antioxidant metabolism and osmotic adjustment. J Plant Res 130 (3):611\u0026ndash;624.\u003c/li\u003e\n\u003cli\u003eZhang WJ, Yu XX, Li M, Lang DY, Zhang XH, Xie ZC (2018) Silicon promotes growth and root yield of Glycyrrhiza uralensis under salt and drought stresses through enhancing osmotic adjustment and regulating antioxidant metabolism. Crop Prot 107:1-11.\u003c/li\u003e\n\u003cli\u003eZhao JY, Yu BS, Wang XL, Chen LH, Akhtar K, Tang SD, Lu HM, He JH, Wen RH, He B (2023) Differences in the response mechanism of cadmium uptake, transfer, and accumulation of different rice varieties after foliar silicon spraying under cadmium-stressed soil. Front Plant Sci 13:1064359.\u003c/li\u003e\n\u003cli\u003eZhao L, Meng B, Feng XB (2020) Mercury methylation in rice paddy and accumulation in rice plant: a review. Ecotoxicol Environ Saf 195:110462. \u003c/li\u003e\n\u003cli\u003eZhu YX, Gong HJ (2014) Beneficial effects of silicon on salt and drought tolerance in plants. Agron Sustain Dev 34 (2):455\u0026ndash;472. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Selected physico-chemical properties of the experimental soil (0\u0026ndash;20 cm depth)\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eOrganic matter\u003c/p\u003e\n \u003cp\u003e(g kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTotal N\u003c/p\u003e\n \u003cp\u003e(g kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eOlsen-P\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eAvailable K\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eAvailable Si\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eBulk density\u003c/p\u003e\n \u003cp\u003e(g cm\u003csup\u003e\u0026minus;3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eField capacity\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eProtocol measurements for the indicators selected in this study\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"502\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eIndicators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eProtocol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eRelative Leaf water content (LRWC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eLeaf was oven-dried to constant weight at 80 \u0026deg;C to determine the dry weight. LRWC was calculated by the equation:\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e(Gong et al., 2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eMalondialdehyde (MDA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eThiobarbituric acid (TBA) method, supernatant was measured at 532 nm, 450 nm and 600 nm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e(Sudhakar et al., 2001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSuperoxide radical (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026middot;\u0026minus;\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eHydroxylamine oxidation method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e(He et al., 2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eProline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eAcidic ninhydrin method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 88px;\"\u003e\n \u003cp\u003e(Zhang et al., 2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSoluble sugar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eAnthrone-sulfuric acid method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSoluble protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eCoomassie brilliant blue method.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSOD activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eNitro-blue tetrazolium reduction method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e(Gunes et al., 2007)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eCAT activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eMeasured as the reduction in absorbance at 240 nm due to the reduction of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e(He et al., 2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003ePOD activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBased on the determination of guaiacol oxidation at 470 nm by H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003ePEPCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003ePEPC activity was calculated by measuring the rate of NADH depletion at 340 nm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e(Liu et al., 2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eRuBPCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eRubisco activity was determined by monitoring the rate of NADH oxidation at 340 nm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eBCR sequential extraction method of heavy metal in steel slag\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eFraction (0.5 g soil)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 385px;\"\u003e\n \u003cp\u003eReagent conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eExchangeable state (F1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 385px;\"\u003e\n \u003cp\u003eAdd 20 mL of 0.11 mol L\u003csup\u003e-1\u003c/sup\u003e CH\u003csub\u003e3\u003c/sub\u003eCOOH (pH 2.8), shake 16 h under 25\u0026deg;C,\u0026nbsp;centrifuge, and filter.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eReducible state (F2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 385px;\"\u003e\n \u003cp\u003eAdded 20 mL of 0.1 M NH\u003csub\u003e2\u003c/sub\u003eOH\u0026middot;HCl (adjusted to pH 2 with HNO\u003csub\u003e3\u003c/sub\u003e), shake 16 h under 25\u0026deg;C, centrifuge, and filter.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eOxidizable state (F3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 385px;\"\u003e\n \u003cp\u003eAdd 10 mL of 30% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e,\u003csub\u003e\u0026nbsp;\u003c/sub\u003edigest 1 h at room temperature (covered with a watch glass), digest under 85 \u0026deg;C in a water bath for 1 h, repeat once; add 20 mL of 1 mol L\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eNH4Ac (adjusted to pH 2 with HNO\u003csub\u003e3\u003c/sub\u003e), shake under 2 \u0026deg;C, centrifuge and filter.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eResidual state (F4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 385px;\"\u003e\n \u003cp\u003e3 mL HNO\u003csub\u003e3\u003c/sub\u003e+9 mL HCl beakers, heated on a hot plate and evaporated to near dryness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e The effect of drought, cadmium stress and nano-Si application on grain yield, yield components, and straw biomass\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"482\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStraw dry weight\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g plot\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYield\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g plot\u003csup\u003e-1\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100-kernel weight\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;(g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ekernels per spike\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e282.12 \u0026plusmn;9.33 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e114.15 \u0026plusmn; 5.24 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e33.74 \u0026plusmn; 0.32 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e324.3 \u0026plusmn; 8.54 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e279.82 \u0026plusmn;6.11 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e69.07 \u0026plusmn; 6.04 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e28.63 \u0026plusmn; 0.89 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e203.7 \u0026plusmn; 24.2 d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e281.37 \u0026plusmn;1.62 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e106.76 \u0026plusmn;1.13 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e33.30 \u0026plusmn; 0.05 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e315.4 \u0026plusmn; 12.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD+Cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e278.53 \u0026plusmn;3.24 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e69.33 \u0026plusmn; 3.21e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e28.04 \u0026plusmn; 1.11d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e199.5 \u0026plusmn; 13.7 d\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCK+Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e286.08 \u0026plusmn;6.33 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e137.78 \u0026plusmn; 4.41a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e33.94 \u0026plusmn; 0.28 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e341.2 \u0026plusmn; 7.26 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD+Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e307.78 \u0026plusmn;7.61 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e87.96 \u0026plusmn; 4.40 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e31.23 \u0026plusmn; 0.54 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e233.2 \u0026plusmn; 7.53 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCd+Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e294.34 \u0026plusmn;3.16 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e129.70 \u0026plusmn; 6.45 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e35.75 \u0026plusmn; 0.43 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e310.2 \u0026plusmn; 6.68 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD+Cd+Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e313.53 \u0026plusmn;4.92 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e92.42 \u0026plusmn;1.84 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e31.83 \u0026plusmn; 0.09 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e214.4\u0026nbsp;\u0026plusmn; 18.3 cd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 482px;\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eSi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD\u0026times;Cd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD\u0026times;Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eCd\u0026times;Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eD\u0026times;Cd\u0026times;Si\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote, Data represent the mean \u0026plusmn; standard error (SE) of three replicates. Different lowercase letters within a column indicate significant differences (\u003cem\u003ep\u003c/em\u003e \u0026le; 0.05). +Si, Si addition; -Si, no Si addition; CK, control; D, drought; Cd, cadmium; D+Cd, combined drought and cadmium stress. D\u0026times;Si, Cd\u0026times;Si, and D\u0026times;Cd\u0026times;Si represent interaction effects analyzed by ANOVA (** Significant at \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026le; 0.01; * significant at\u003cem\u003e\u0026nbsp;p \u0026le;\u0026nbsp;\u003c/em\u003e0.05; ns, no significant difference).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Maize, Silicon nanoparticles, Drought stress, Cadmium stress, Antioxidant system","lastPublishedDoi":"10.21203/rs.3.rs-8518329/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8518329/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground and aims\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e \u003c/em\u003eAbiotic stresses, particularly drought and cadmium (Cd) stress, are among the primary limiting factors for global crop production, significantly threatening the growth and development of maize. Silicon nanoparticles (SiNPs) have demonstrated substantial potential in enhancing crop resilience. However, the regulatory mechanisms of SiNPs under combined drought and Cd stress conditions remain insufficiently explored.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods \u003c/strong\u003e\u003c/em\u003eThe experiment included eight treatments: control [100% field capacity (FC), 0 mg/kg Cd)], drought (50% FC, 0 mg/kg Cd), Cd stress (100% FC, 5 mg/kg Cd), combined stress (50% FC, 5 mg/kg Cd ) and each of these with or without SiNPs application (0 or 50 mg/kg).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults \u003c/strong\u003e\u003c/em\u003eDrought and combined drought-Cd stress remarkably reduced maize photosynthetic efficiency, root traits, and grain yield. Cd stress alone had minimal impact on growth parameters but significantly increased Cd accumulation in plant tissues. However, SiNPs application significantly improved root morphology, increased leaf relative water content (LRWC), enhanced antioxidant enzymes activities and increased the contents of soluble sugars and soluble proteins. These changes reduced reactive oxygen species (ROS) and malondialdehyde (MDA) levels, thereby promoting photosynthetic efficiency and ultimately increasing grain yield by 27.3% and 18.9% under drought stress and combined stress compared to the non-Si treated plants. Additionally, SiNPs application significantly decreased Cd concentration in plant tissues by reducing Cd bioavailability in soil under Cd stress.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion \u003c/strong\u003e\u003c/em\u003eSiNPs is an effective strategy to mitigate drought stress and Cd accumulation in maize.\u003c/p\u003e","manuscriptTitle":"The effects of Silica nanoparticles (SiNPs) application on maize (Zea mays L) growth, defense system and cadmium accumulation under Drought and Cadmium Stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-02 19:24:32","doi":"10.21203/rs.3.rs-8518329/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2026-03-17T08:02:31+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-01-29T18:56:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-29T09:31:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2026-01-29T07:59:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-29T07:37:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2026-01-20T02:44:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0419dfd5-c38a-447b-9ea9-afc970361a59","owner":[],"postedDate":"February 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-03-17T12:03:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-02 19:24:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8518329","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8518329","identity":"rs-8518329","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}