{"paper_id":"4d259c69-727e-404d-be66-6e55bd872092","body_text":"Enhancing Indian Rice Plant resilience to toxic heavy metals with Glycine betaine as a modulator. | 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 Enhancing Indian Rice Plant resilience to toxic heavy metals with Glycine betaine as a modulator. Monika Bhaskar, Ashwini kumar Dixit, Amar Abhishek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4695832/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Contamination of arable land with potentially toxic heavy metals (PTHMs) is a critical global issue resulting from industrialization. To tackle this problem, a two-year pot experiment was carried out on Indian rice plants (Oriza sativa L.) using four different treatments of PTHMs at varying concentrations (T1: 5; T2: 10; T3: 20; T4: 40 mg/kg). The intent was to explore the impact of glycine betaine (GB) application on the plants' resilience and stress response. Findings indicated that exposure to PTHMs led to a significant increase in the accumulation of these metals and oxidative stress indices during the 2.5th and 4th month growth stages. However, when GB was applied to the soil, there was a decrease in the accumulation of PTHMs and oxidative stress indices. This was attributed to the enhancement of antioxidant enzyme activity and metabolic functions in the rice plants. Interestingly, the study revealed that Indian rice plants had the highest accumulation of Fe, followed by Mn, Zn, Cr, Ni, Pb, Cd, and Cu in their roots. When exposed to PTHMs, the roots exhibited higher metal uptake compared to the shoots and seeds, with uptake levels rising with increasing concentrations of PTHMs. Notably, under the highest PTHMs stress (T4), the content of Cr and Pb in the roots, shoots, and seeds decreased significantly. This reduction was even more pronounced when treated with 400 mM GB, showcasing decreases of up to 33.3%, 36%, and 89.3% in Cr content, and 36.4%, 55%, and 80.5% in Pb content, respectively. Keywords: Amelioration; Oryza sativa; Heavy metals; Glycine betaine; Antioxidant Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction The Indian rice plant ( Oryza sativa L) is a versatile member of the Gramineae family. It is cultivated globally, with India ranking second in terms of rice production (110 million metric tonnes), following China (Ito, 2019 ). Rice plays a crucial role in ensuring food security, as it provide more than 50% of the dietary calories required by billions of people living in poverty in India and south Asia (Ghose et al., 2013 ). However, agricultural production worldwide has suffered significant damage due to environmental changes caused by human intervention. This issue must be addressed. The growth and production of rice are often affected by various abiotic stresses, including salinity, drought, and inorganic pollution, particularly the toxicity caused by heavy metals (Sarma et al., 2024). These factors pose significant challenges to rice farmers and may impact overall rice production. Chhattisgarh state, well-known as one of the primary rice producers in India, has recently encountered a hindrance to the growth of its rice crop in highly industrialized regions such as Korba, Durg-bhilai, and Raigarh. These areas of Chhattisgarh state have suffered from extensive contamination of agricultural land and water resources of various potential toxic heavy metals (PTHMs) such as Iron (Fe), Chromium (Cr), copper (Cu), cadmium (Cd), etc (Sharma et al., 2019 ). The contamination may be attributed to the modern industrial activities including the establishment of refractory steel factories, coal and bauxite mining, coal based thermal power plants, and discharge of untreated or partially treated industrial solid or liquid waste (Bhaskar et al., 2020 ). These industrial activities serve as prevalent sources of mixture of different heavy metals in both water and soil. In plants, it caused adverse impact on morpho-physiological characteristics, photosynthesis, plant defense system, root impairment, and ultimately plant mortality. In addition, heavy metals like Cr, Pb, and Cd generates a detrimental impact on the proper functioning plasma membrane, leading to swift alteration in the level of essential metals like sodium and calcium, as well as lipid composition cell membrane (Rawat et al., 2021 ). This impairment in plasma membrane integrity also influences the activity of proton pumps, which has been observed to decrease in different crop such as maize, rice, sorghum and chick pea when exposed to PTHMs stress (Astolfi et al., 2005 ; Cao et al., 2013 ; Kumar, 2021 ; Singh et al., 2022 ). Stressors experienced by plants prompt metabolic changes, resulting in varying the level of cellular metabolites. These modifications within the cell due to abiotic stress may seemingly contribute to the plant’s enhanced survival capabilities under such challenging circumstances. In order to tackle environmental challenges, numerous plant species have developed a similar approach of accumulation appropriate solute or osmolytes (Ghosh et al., 2021 ). Among these, polyols, sugars, amino acids (such as proline and histadine), and glycine betaine (GB) are commonly used to protect plants from abiotic stresses (Kumar, 2021 ). GB is safe, water soluble quaternary ammonium compound that can be found in marine invertebrates, archaea, bacteria, as well as plants and animals (Hill, 2022 ). However, some plants do not naturally accumulate enough GB to adequately safeguard themselves against environmental stress. After conducting extensive research, it has become apparent that GB plays a crucial role in mitigating the detrimental impacts of heavy metals on plants (Kumar, 2021 ; Sharma et al., 2024 ). In particular, when plants are exposed to one or two heavy metals, this compound actively enhances the functionality of antioxidant enzymes. It is crucial to highlight that the presence of refractory steel factories, coal and bauxite mining, and coal-fired thermal power plants in specific locations can lead to soil contamination. In these sites, it is more common to find elevated levels of multiple heavy metals rather than just one or two type of heavy metal. The main focus of this study was to address these concerns by investigating the effects of a combination of eight potentially harmful PTHMs and the inclusion of GB on different aspects of the physiological and biological resilience of the Indian rice plant. Additionally, the study aimed to analyze the plant's stress response in the presence of mixture of PTHMs. Surprisingly, there is currently no available research on the sensitivity of the Indian rice plant when exposed to a combination of various heavy metals. 2. Material and methods 2.1 Plant selection The present research was conducted in the open field of Thakur Chedilal Agricultural College, Bilaspur, Chhattisgarh, India. Indian rice plant ( Oryza sativa L), variety MTU1010, were purchase from same college. This verity was selected because it serves as one of the main staple foods of Chhattisgarh state. However, there are no report about the sensitivity of this cultivars for GB under mixed heavy metal toxicity. 2.2 Pot experimental design and raising the crop The objective of this study was to investigate the Indian rice plant's capacity to mitigate the negative impact of a combination of PTHMs such as Cadmium (Cd), Copper (Cu), Iron (Fe), Manganese (Mn), Nickel (Ni), Zinc (Zn), Chromium (Cr), and Lead (Pb), both with and without the presence of GB. The rice seeds were immersed in water for approximately 2 days at normal room temperature. To facilitate germination, the seeds were kept in a moist environment (using two-layer cloth gauze to retain moisture) at room temperature for additional 30 hours. Once seeds had sprouted, they were grown in seedbed under field condition to develop into seedlings. Following a one-month duration, the seedlings were transplanted into pots filled with soil that encompassed varying levels of PTHMs alone and with GB. Soil properties are mentioned in Table 1 . Each pot accommodated a total of four plants. The plants were exposed to two different level of treatment: the initial treatment involved various concentration of the PTHMs alone, namely TC-0 mg/kg (as control), T1: 5 mg/kg, T2: 10 mg/kg, T3: 20 mg/kg, and T4: 40 mg/kg. The second treatment involving combining PTHMs with GB (mM), with concentration of T1 + GB: 50 mM, T2 + GB: 100 mM, T3 + GB: 200 mM, T4 + GB: 400 mM (Table 2 ). Fertilizer containing NPK nutrients was applied as per previous study by Singh et al., 2022 . The rice crops were grown for a span of four months using a randomized block pattern, with five separate plots for replication. Table 1: General physic-chemical parameters of experimental soil Parameters Soil pH Slightly acidic 6.6±0.13 Color Greyish black Consistency Less sticky Sand (%) 45.7±1.02 Slit (%) 37.33±0.5 Clay (%) 14.72±0.82 Organic matter (%) 1.37±0.03 EC (dS m -1 ) 0.38±0.01 Nitrogen (kg/hectare) 326.14±8 Phosphorus (kg/hectare) 12.54±0.9 Potassium ((kg/hectare) 240.44±5 Sulphur (mg/kg) 15±0.4 Boron (mg/kg) 1.80±0.03 Metals (mg/kg) Cd BDL Cr 0.012±0.06 Cu 0.95±0.03 Zn 0.36±0.05 Fe 3.64±0.01 Ni 0.28±0.015 Mn 1.12±0.02 Pb 0.06±0.002 BDL: below detection limit Table 2 Treatment details Treatment name Treatment conditions TC Treatment Control (0 for THMs mg/kg and GB mM) T1 THMs (5 mg/kg) T1 + GB PTHMs (5 mg/kg) + GB (50 mM) T2 THMs (10 mg/kg) T2 + GB PTHMs (10 mg/kg) + GB (100 mM) T3 THMs (20 mg/kg) T3 + GB PTHMs (20 mg/kg) + GB (200 mM) T4 THMs (40 mg/kg) T4 + GB PTHMs (40 mg/kg) + GB (400 mM) 2.3 Measurement of plant growth parameters The plant samples were collected on three occasions throughout the experiment. The first sampling occurred prior to the transplantation of rice seedling into the pot, which took place in the first month. The second sampling was carried out after the transplantation when the plants were flowering stage (2.5th month), and third sampling was conducted just before harvest in the 4th month. To prepare the collected plants for analysis, they were carefully plucked and rinsed with running water followed by 20 mM calcium chloride to eliminate any adhering particle. 2.3.1 Morphological changes In order to showcase the physical development, parameters like root length (RL), shoot length (SL), fresh weight (FW), dry weight (DW), and harvesting index (HI) were assessed at the end of experiment. The fresh biomass of the plant was precisely measured right after harvesting using a digital electric balance. To determine the dry biomass, the freshly harvested rice plant sample was subjected to oven drying at 80 ℃ for a duration of 24 hours. The weight of the filled grains was used to obtain grain yield per pot. Separation of filled grains from unfilled and partially filled ones was accomplished through water floating, as the filled grains sank to the bottom of the beaker and were manually counted. The percentage of filled grains (% FG) was then determined (Jia-Kuan et al., 2005 ). Subsequently, the harvesting index (HI) was computed following the subsequent formula. $$\\:\\%FG=\\frac{Filled\\:Grain\\:}{Filled+unfilled+Partially\\:filled\\:grain}\\times\\:100$$ $$\\:HI=\\frac{Grain\\:yield\\:\\left(dry\\:weight\\right)}{Grain+Straw\\:yield}\\times\\:100$$ 2.3.2 Estimation of pigments To extract Chlorophyll, 1 gm leaf sample was mixed with a solution consisting of 80% aqueous acetone (v/v). The resultant plant extract was then subjected to centrifugation at 5000 rpm for 5 minutes at 4℃. To determine the extraction co-efficient, blank samples (consisting of 80% aqueous acetone) were assessed against the extract at different wavelengths (663 and 645 nm). Finally, the chlorophyll content was calculated using the standard method developed by Lichtenthaler and Wellburn in 1983. 2.4 Determination of leaf malondialdehyde (MDA) and electrolyte leakage (EL) The overall MDA content in rice plants leaves were assessed using the method introduced by Heath and Parker in 1968. EL leakage was measured using the protocol described by Valentovic et al., 2006 . In brief, three randomly selected plants, each with two mature leaves, were chosen and cut into 1 cm segments. These segments were washed three times with distilled water to eliminate any surface contaminants and then placed in a stopper vial containing 10 ml of deionized water. The samples were subsequently incubated at a temperature of 25 ℃ on a rotator shaker at 120 rpm for 24 hours. After the incubation period, the electrical conductivity of the bathing solution (EL0) was measured. The samples were then subjected to autoclaving at a temperature of 120 ℃ for 30 minutes, and after cooling the solution, a second reading of electrical conductivity (ELt) was obtained. The percentage of EL was determined using the formula: EL% = EL0/ELt × 100. 2.5 Proline and antioxidant activity To obtain the enzyme extract, we selected 0.5 grams of fresh leaf sample and crushed it in 4 milliliters of phosphate buffer (100mM, pH: 7.5). This buffer also contained 1 millimolar of EDTA and a small amount (50 milligrams) of PVP (Polyvinyl polypyrrolidone). After crushing, the samples were centrifuged at 10,000 rpm for 10 minutes at 4℃. The resulting supernatant was then extracted and stored in a micro-centrifuge tube for further quantification of various enzymes. To assess the level of proline (µmol/gm), we employed the method developed by Sarker and Oba, 2019 . It involved measuring the proline level of the samples at a wavelength of 520 nm using a spectrophotometer. The defense mechanism of plants against any damage can be measured by assessing the activity level of ascorbate peroxidase activity (APX) superoxide dismutase (SOD) and catalase (CAT). The APX, SOD and CAT were evaluated using the standard method given by Nakano and Asada ( 1981 ), Nishikimi et al. ( 1972 ), and Maehly (1955), respectively. 2.6 Metal analysis of plant samples At the end of experiment, the plant samples were divided into three parts: root, shoot, and seeds. Subsequently, they were subjected to an oven-drying process at 80°C for a duration of 48 hours. To further analyze the plant samples, a crushed form of the dried specimen was incinerated in a muffle furnace at a temperature of 500°C for a period of 5 hours. Next, a gram of the resulting ash was individually mixed with a digestion mixture consisting of nitric acid and perchloric acid in a ratio of 5:1. This process was continued until the appearance of white fumes. The beaker's walls were rinsed with a minimal quantity of distilled water, followed by filtration of the solution. Furthermore, the filtrate was transferred and brought up to a volume of 20 mL in a volumetric flask, following the standardized protocol outlined by APHA ( 2005 ). Finally, the concentration of various heavy metals present in the samples was determined using an atomic absorption spectrophotometer (AAS), (ZEE nit 700 model manufactured by Analytic Jena, Germany). 2.6.1 Quality control assurance In order to ensure the accuracy, reliability, and reproducibility of the data collected, we conducted two replicated batch isotherm tests and carried out experimental blanks in parallel. To calibrate and verify the instruments, we utilized multiple sources of National Institute of Standard and Technology (NIST) traceable standards from Merk. For each set of data points, we employed both linear and nonlinear regression analyses. Using Microsoft Excel and Sigma Plot V6.0 for Windows (SPSS Inc., Chicago, IL), we obtained a regression coefficient (R 2 ) and a probability value ( p ) that indicate the level of fit of the Freundlich and Langmuir models to the data. 2.7 Statistical analysis Normality of continuous data was confirmed by Kolmogorov-Smirnov test. Numerical data were presented in the form of mean and standard deviation. To examine the significant differences among the mean values, a post hoc analysis using the least significant difference (LSD) method was performed. The statistical analysis was conducted using the Statistical Package for the Social Sciences version 22 (SPSS-22) from IBM, based in Chicago, USA. The significance level (p-value) was set at less than 0.05. For generating the graphics, Sigma Plot V6.0 for Windows (SPSS Inc., Chicago, IL) was utilized. 3. Results 3.1 Impact of GB application under PTHMs stress on physio-biochemical parameters The impact of treating PTHMs with and without GB was assessed by measuring the length of plant roots (RL), length of shoots (SL), weight of fresh plant material (FW), weight of dry plant material (DW), and harvesting index (HI). The data was collected at the 1st, 2.5th, and 4th month. Throughout the course of one month, the selected parameters were mostly consistent in nature (data not shown). However, after exposure to PTHMs for two and a half months, there was a significant impact on the growth parameters compared to control plants (TC). As compare to control plants (TC), PTHMs contamination under treatments T1, T2, T3, and T4, the RL decreased by 22.3%, 33.6%, 41%, and 50.2% respectively, while SL decreased by 9.0%, 12.7%, 28.01%, and 29.3% respectively. Similarly, HI decreased by 10.6%, 16.4%, 25.9%, and 30.3%, FW decreased by 18.6%, 29.4%, 40.4%, and 45.4%, and DW decreased by 22.2%, 36.5%, 46.8%, and 54.3% respectively (all p < 0.05, ANOVA, LSD). This decline in growth could be attributed to the high concentration of metals, which hinder the normal growth of plants by acting as growth inhibitors (Fig. 1 ). When comparing the parameters in PTHMs treated plants to those in plants treated with T1 to T4 in combination with GB, there was an increase in RL by 26.9%, 29.6%, 30.1%, and 37.4% respectively, SL increased by 9.8%, 11.1%, 20.9%, and 21.6% respectively, HI increased by 9.12%, 13.1%, 20%, and 20.4%, FW increased by 16.6%, 19.9%, 32.3%, and 30.2%, and DW increased by 20.7%, 23.4%, 30.3%, and 33.2% respectively. These findings indicate that the growth parameters directly respond to PTHMs stress by undergoing changes in morphology, and the application of GB therapy helps alleviate these reactions. 3.2 Impact of GB treatment on proline, oxidative stress, and electrolyte leakage (EL) in plants under PTHMs stress During the initial month, the content of proline (µmol/gm) remained constant ( p > 0.05). However, after 2.5 months, when compared to the control plant, the proline content exhibited a significant increase under PTHMs stress (all p < 0.05). Notably, the T4 level (40 mg/kg) of PTHMs treatment demonstrated the highest accumulation of proline compared to other treatment levels. Furthermore, the combination of GB and PTHMs resulted in increased proline accumulation, although this increase shows marginal significance when compared to the treatment with PTHMs alone (Fig. 2 A). However, the proline activity was decrease with plant age but this pattern persisted until the end of the experiment (4th month). Exposure to heavy metals in the environment is closely linked to an elevated risk of oxidative stress. To evaluate this, we measured stress biomarkers, specifically malondialdehyde (MDA) and electrolyte leakage (EL%), in Indian rice plants grown in soil with different levels of PTHMs. We observed a significant increase in MDA and EL% levels in rice plants subjected to PTHMs stress after 2.5 months, compared to control plants (MDA: 48.6%, 54.2%, 64.6%, and 64.4%; EL: 45.6%, 58.1%, 65.8%, and 70.7% at T1, T2, T3, and T4 PTHMs levels). However, the application of GB leads to a significant decline in MDA and EL% levels compare to plant treated with PTHMs only (all p < 0.05) (Fig. 2 B, C). Consequently, the exogenous application of GB proved to be effective in alleviating stress in rice plants. 3.3 Variation in pigments under PTHMs stress with or without GB A significant difference was observed in the pigments like Chl, including Chl-a, Chl-b, total Chl, and carotenoid content, between the groups exposed to only PTHMs and the groups exposed to both PTHMs and GB. The homogeneity of pigment levels in plants was found in the initial month (all p > 0.05) (Fig. 3 ). At the 2.5-month mark, Chl-a in Indian rice plants decreased by 32.1%, 45.2%, 50.2%, and 66.5% under T1, T2, T3, and T4 levels of PTHMs stress respectively, compared to the control plants (TC). Likewise, Chl-b exhibited a significant reduction with increasing concentrations of PTHMs from T1 to T4 at the 2.5-month stage ( p < 0.05). Additionally, total Chl and carotenoid contents decreased by 33.2%, 21.6%, 51.1%, and 49.5%, and 11%, 39.9%, 71.1%, and 83.9%, respectively, under PTHMs stress levels T1, T2, T3, and T4. Therefore, higher concentrations of PTHMs resulted in a greater decrease in chlorophyll-a, chlorophyll-b, and carotenoid content. Notably, the application of GB treatment led to a significant increase in chlorophyll content in rice plants. Compared with plants treated at levels T1, T2, T3, and T4, Chl-a increased by 28.7%, 49.6%, 63.2%, and 71.3%, while Chl-b increased by 28.1%, 50.4%, 60.1%, and 59%. Total Chl increased by 37.7%, 14.3%, 51.6%, and 40.1%, and carotenoids increased by 15.4%, 43.3%, 75.5%, and 84.1%, respectively (all p < 0.05). Furthermore, after the fourth month, all treatments showed a significant decrease in chlorophyll and carotenoid levels (ANOVA, LSD p < 0.01). Overall, the findings confirmed that GB treatment restored the chlorophyll level in rice plants when exposed to high levels of mixture of PTHMs. 3.4 Distribution of Antioxidant enzyme activity under PTHMs with or without GB We evaluate the effectiveness of various antioxidant enzymes, SOD, CAT, and APX, in the leaves of rice plants subjected to stress caused by PTHMs stress. Comparing them to the leaves of unaffected plants (TC), a significant reduction in the activity of these antioxidant enzymes was observed in plants treated with T4 at every stage of growth in the rice plants (2.5th month and 4th month). Specifically, the enzymatic activities of APX, SOD, and CAT in rice plants exposed to T4 levels of PTHMs decreased by 44.9%, 62.7%, and 80.26%, respectively. Conversely, when additional GB was applied along with PTHM treatment, the enzymatic activities of APX, SOD, and CAT in Oriza sative plants increased compared to the values observed in plants solely treated with PTHMs (all p < 0.01). These findings clearly demonstrate that the external application of GB significantly amplifies the enzymatic activities in the leaves of rice plants experiencing mixed PTHMs stress. On other hand, homogeneity of antioxidant levels in rice plants was found in the initial month (all p > 0.05) (Fig. 3 -D, E, F). 3.5 Effect of exogenous GB on mixture of PTHMs accumulation and distribution and translocation factor (TF) in rice plant The heavy metal content of roots, shoot and seeds were determined at the end of experiment. Heavy metal content of all part (root, shoot and seeds) increased with increasing with heavy metal stress. Heavy metal uptake was remarkably higher in roots followed by shoot and seeds, which increased with increasing concentration of heavy metals. A maximum increase of PTHMs content was observed at T4 treatment in all parts of plants. Indian rice plant has shown maximum accumulation of Fe followed by Mn, Zn Cr, Ni, Pb, Cd and Cu. However, the exogenous application of GB resulted in a decline of a combination of 8 heavy metals in various parts of the plants. The most significant reduction in chromium (Cr) and lead (Pb) content was observed in the roots, stems, and seeds of plants treated with 400 mM GB (T4 + GB). Under T4 PTHMs stress, the Cr and Pb content in the roots, shoots, and seeds was decreased by as much as 33.3%, 36%, and 89.3% respectively, and 36.4%, 55%, and 80.5% respectively when treated with 400 mM GB (Fig. 4 ). Further, translocation factor (TF) values were notably elevated for vital elements such as Mn, Cu, Zn and Fe in comparison to harmful heavy metals Cd, Cr and Pb. Furthermore, the research demonstrated that the application of GB led to a decrease in the TF values for specific metals (Fig. 5 ). 4. Discussion The soil obtained from the experimental plots had a lower stickiness and exhibited a dark gray color. The absorption, accumulation, and distribution of metals in different parts of the plant are significantly influenced by both the plant itself and the characteristics of the soil. The pH level and organic matter content of the soil play crucial roles in regulating the availability of metals to plant species. When the pH level and organic matter increase, the movement of heavy metals decreases due to the precipitation of hydroxides and carbonates, along with the formation of insoluble organic complexes (Adamczyk-Szabela and Wolf, 2022 ). Conversely, metals exhibit higher mobility in soils with a pH lower than 7 and lower organic matter content. In the present study, the pH of the experimental soil was determined to be 6.6 ± 0.13, while the organic matter content was found to be 1.37 ± 0.03%. This finding aligns with the work of Srivastava et al. ( 2017 ) and Li et al. ( 2022 ), who also emphasized that the mobilization of heavy metals in soil is influenced by pH and organic matter. Furthermore, the concentration of heavy metals in the experimental soil was found to be within the normal range. Plants, being inherently immobile, frequently encounter various forms of environmental stress, one of which is the presence of heavy metals. PTHMs like Cr, Pb, Cd do not serve any essential metabolic function in plants, and in fact, disturb various physiological and biochemical process, ultimately reducing crop yield (Sarma et al., 2023 ). To combat the toxic effects of different PTHMs on various plants, including rice, numerous substances such as silicon, GB, hydrogen sulfide, selenium, and melatonin have been extensively studied (Dotaniya et al., 2014 ; Kumar et al., 2019 ). In this study, we aimed to investigate the effects of exogenous GB, an organic osmolyte known for enhancing physiological and biochemical processes, on Indian rice plants cultivated under stress from a mixture of PTHMs. 4.1 Change in plant growth parameters Roots serve as the primary entry point for PTHMs and are typically the first organ to experience the toxic effects of these substances. In the current investigation, a significant reduction in growth, both in terms of RL, SL, HI and over all biomass production (FW, DW) were observed in rice plants subjected to heavy metal stress. These findings are consistent with previous studies that have reported similar outcomes (AbdElgawad et al., 2020 ; Tang et al., 2023 ). However, numerous studies have demonstrated that the external application of GB can alleviate the impacts of PTHMs and enhance the morphological characteristics of cultivated plants (Kumar et al., 2019 ). The present study further confirms that the application of exogenous GB effectively reduces the detrimental effects of a combination of PTHMs on the RL, SL, FW, DW and HI. GB has been known to enhance plant growth even in the presence of heavy metal stress. This could be attributed to the improved development of nutrient absorption and gas exchange qualities in plants when GB is applied. Scientists have reported similar findings in rice plants experiencing abiotic drought stress (Chaum and Kirdmanee, 2010 ). Additionally, GB may have a protective effect on key enzymes involved in CO 2 fixation, such as RuBisCo and RuBisCo activase, when plants are exposed to abiotic stress conditions. Consequently, this protection leads to an overall enhancement in plant growth. The reduction in stress caused by different heavy metals following the application of GB has also been documented in wheat, mungbean, and chickpea crops (Ali et al., 2015 ; Chen and Murata. 2011; Singh et al., 2022 ). 4.2 The impact of GB treatment on proline, oxidative stress, and electrolyte leakage (EL) in plants under PTHMs stress Exposure to PTHMs in the surroundings has a direct correlation with an increased likelihood of experiencing oxidative stress. In order to assess this relationship, we measured stress biomarkers, specifically proline level, malondialdehyde (MDA) and electrolyte leakage (EL%). An evident rise in the accumulation of proline was noticed primarily in the leaves of rice plants when subjected to PTHMs stress as compare to the control group (TC). Moreover, the application of GB resulted in a moderate increase in proline accumulation in rice plants, when compared to the treatment involving only PTHMs. Proline is a basic amino acid found in proteins, and free proline plays a crucial role in plants during biotic and abiotic stress conditions. The molecular mechanism underlying increase proline level under heavy metal stress are yet to be identified, but one hypothesis suggests that protein is broken down into amino acid and converted into proline for storage. Singh et al. ( 2022 ) reported that soil heavy metal increased the proline content of chick pea plant, and high heavy metal (Cr) with GB application resulted in a marked increases in proline content. PTHMs stress significantly enhances the levels of MDA and EL (%) in rice plants compared to the control group. However, when the PTHMs combined with GB treatment was applied, the levels of MDA and EL (%) in rice plants showed a decrease compared to the PTHMs-treated plants without GB application. The elevated MDA and EL percentage suggest that there is an excess generation of intracellular free radicals, which leads to membrane damage and cytotoxicity through the production of malondialdehyde, a byproduct of lipid peroxidation. Similar findings were observed by Singh et al. ( 2015 ), where they reported an increase in MDA levels in various parts of plants under mixture of heavy metal stress. Additionally, Bhargava et al. (2008) conducted a study on the Indian mustard plant ( Brassica nigra L.), which also concluded that exposure to a mixture of heavy metals resulted in elevated levels of MDA in the plant's leaves. 4.3 Variation in pigments under PTHMs with or without GB PTHMs toxicity has a significant negative impact on the pigment system of plants. This toxicity disrupts the photosynthetic system by causing heavy metals to enter the leaf tissue, potentially damaging the chloroplast's laminar membrane (Wang et al., 2009 ). The present study demonstrates that a high concentration of PTHMs in plant tissues leads to a decrease in chlorophyll content compare to control, which ultimately hinders plant growth and affects biochemical traits. Under the PTHMs exposure, rice plants exhibited a noticeable reduction in levels of Chlorophyll a, b, and carotenoid. Moreover, when PTHMs in elevated levels, metals exhibit a detrimental effect on chlorophyll production. Take the PTHMs Cd and Cr, for instance, which hampers the creation of the photoactive protochlorophyll reductase enzyme complex and disrupts the synthesis of aminolevulinic acid, both crucial steps in chlorophyll biosynthesis. Heavy metals like Cd, Cr, Cu accomplishes this by obstructing the sulfhydryl group of the enzyme, which is essential for its function, through the formation of a complex with active thiol groups (Hossain et al., 2012 ). The application of GB promotes shoot elongation by augmenting cell expansion and division. This mechanism may explain GB's positive impact on growth performance when plants are exposed to heavy metal stress. A comparable effect has been previously observed in sweet pepper and chick pea plants (Wang et al., 2016 ; Singh et al., 2022 ). Furthermore, the enhanced accumulation of antioxidant enzymes and pigment levels may have contributed to the improved growth performance in rice plants when treated with a combination of heavy metals and GB, compared to treatment with PTHMs alone. 4.4 Distribution of Antioxidant enzyme activity Plant body is equipped with a range of scavenging machinery. Superoxide Dismutase (SOD), APX and Catalase (CAT) are considered primary antioxidants which are involved in direct scavenging of ROS. SOD catalyses the decomposition of superoxide as well as play important role in detoxification of anion to radical oxygen, hydrogen peroxide and finally convert to oxygen and water. SOD usually depends on different metals as cofactor. Further, CAT act as a primary indicator for removal of hydrogen peroxide under metal stress in peroxisomes. On other hand APX also involves in detoxifying H 2 O 2 to H 2 0 in plant cell via bate-glutathione cycle. The results of the present investigation revealed an amelioration of mixed heavy metals toxicity in rice plant exposed to GB. This amelioration might be resulted due to reduction in heavy metal uptake on GB application. It means there was no disturbance to stress machinery of the plants which turn maintains proper stomatal conductance, chloroplast ultrastructure, photosynthetic capacity and proper nutrient uptake. All these resulted in an increase the tolerance capacity of the plant. GB further increase the activity of antioxidant activity which in turns prevent plant to oxidative damage caused by free radicles generation due to stress condition that might also be the reason for enhancing amelioration process in rice plant. Kumar et al. (2021) demonstrated similar effect on GB application in sorghum plant under Cr stress, as were observed during the present investigation. However, the mechanism involved in the enhancement of amelioration behavior of the plant by GB application is still not clear. In this study, SOD (superoxide dismutase) and CAT increased by 17.5–38.4% and 25.5–50% in Indian rice plants treated PTHMs in combination with Glycine Betain. Conversely, a small rise was observed in APX (ascorbate peroxidase) in all heavy metal treatments combined with GB. Our finding reveals that PTHMs in mixed condition increase the indices of oxidative stress parameters. However exogenous application of GB significantly enhances the antioxidant system which in turns reduced the indices of oxidative stress parameters under mixed heavy metal stress. 4.5 Uptake, Accumulation and distribution of PTHMs in different part of plant with or without GB Heavy metal contamination in arable land is a pressing issue associated with industrialization globally. It has detrimental effects on plant growth and yield, leading to a significant concern for agriculture. Numerous studies have highlighted the hazardous impact of heavy metal toxicity on crop plants (Bharagava et al., 2008 ; Singh et al., 2015 ; Kumar et al., 2021; Singh et al., 2022 ). While there are reports suggesting the use of osmolytes such as GB to alleviate heavy metal toxicity, most of these studies focus on a single metal contamination scenario. Various crop plants have distinct mechanisms for accumulating and distributing metals in different parts of the plant such as the roots, shoots, fruits, or seeds. This study demonstrates that plants exposed to mixed concentrations of metals exhibit unique patterns of metal accumulation. However, uptake and distribution of metals in plants are influenced by factors such as the availability of metals, plant metabolism, and microbial interactions. The research findings indicate that the Indian rice plant has the highest accumulation of Fe, followed by Mn, Zn, Cr, Ni, Pb, Cd, and Cu in its roots. When subjected to PTHMs stress, the uptake of metals was significantly higher in the roots compared to the shoots and seeds, and this uptake increased with higher concentrations of PTHMs. The high accumulation of heavy metals in the roots may be attributed to the higher metabolic rate in this plant part, as suggested by Haddad et al. ( 2023 ). The levels of PTHMs in all plant parts increased as the PTHMs stress intensified, surpassing the permissible limits set by FAO/WHO (1984) for Cr, Pb, Ni, Cu, Cd, and Mn in terms of human consumption suitability (permissible limit, PL: mg/kg) Cr: 0.02; Pb: 0.43; Ni: 1.63; Cu: 3.0; Cd: 0.21; Mn: 2.0). However, the levels of Zn (PL: 27.4) and Fe (20.0 mg/kg) in the seeds of the rice plant were below the permissible limits. Hence, it may be advisable that this Indian rice plant treated with high concentration of heavy metals should not be taken as food by human beings and cattle because these metal rich plants may cause several clinical problems (Rattan et al., 2005 ). Nonetheless, the application of GB externally led to a decrease in the levels of 8 heavy metals across different parts of the plants. The most substantial decrease in chromium (Cr) and lead (Pb) concentrations was noted in the roots, stems, and seeds of the treated plants with 400 mM GB. PTHMs like Cr, Pb, Cu are known to impede plant metabolism and growth factors, cause changes in chloroplasts and cell membranes, reduce photosynthetic pigments, induce chlorosis, disrupt the movement of water and minerals, and hinder enzymatic activity in plants (Haddad et al., 2023 ). Under T4 PTHMs stress, the Cr and Pb content in the roots, shoots, and seeds was decreased by as much as 33.3%, 36%, and 89.3% respectively, and 36.4%, 55%, and 80.5% respectively when treated with 400 mM GB (Fig. 4 ). The decrease in the concentration of heavy metals in plant samples could be attributed to the presence of GB, which helps in maintaining the integrity of cell membranes and protects cells from damage. This protective mechanism reduces the likelihood of heavy metals entering the cells. Additionally, the application of GB may also shield the cell membranes, thereby preventing the movement of heavy metals into the cells. Similar findings have been observed for Pb and Cd levels in mung beans, rice, and wheat. Studies by Kumar et al. (2021) and Karagiannidis and Hadjisavva (1998) have shown that the use of GB as an osmolyte, along with arbuscular mycorrhizal fungi (AMF) inoculation, can enhance nutrient uptake and inhibit the absorption of various heavy metals such as Cr, Mn, Fe, Co, Ni and Pb in beans and Durum wheat. It is suggested that the competition between essential nutrients and heavy metals for entry into the cells could be another reason for the reduced absorption of heavy metals with GB application. Bioaccumulation and Translocation factor The factor responsible for transporting metals within plants, known as the translocation factor (TF), plays a critical role in monitoring metal presence across different plant parts. Essentially, TF evaluates the movement of metals either from the roots to the shoots or from the shoots to the seeds in plants (Baker and Walker, 1990 ). Research has shown that TF values were consistently below 1 when metals were moved from roots to shoots and shoots to seeds across all tested metals. Notably, the TF values for root to shoot translocation increased significantly with higher levels of PTHMs, ranging from T1 to T4 concentrations. Intriguingly, essential metals such as Mn, Cu, Ni, Zn, and Fe exhibited higher TF values compared to toxic heavy metals like Cd, Cr, and Pb. This disparity may be attributed to the crucial role of these essential metals in protein and pigment synthesis within plants (Rotkittikhun et al., 2006 ). Generally, plants tend to avoid accumulating unnecessary heavy metals that do not contribute to their metabolic processes (Liu et al., 2007 ; Satpathy et al., 2014 ). TF values for metals like Cd, Ni, Pb, Cr, and Fe increased with PTHMs concentration, but were subsequently reduced following the application of a GB. On the whole, GB has been acknowledged as a beneficial natural compound that enhances plants' resilience against stress induced by heavy metals. Conclusion In conclusion, the toxicity of PTHMs at varying concentrations (T1: 5; T2: 10, T3: 20, and T4: 40 mg/kg) leads to biochemical changes in rice plants that impact the plant's morpho-physiological characteristics and increase oxidative stress levels. The harmful effects become more pronounced as the concentration of PTHMs increases. The application of glycine betaine (GB) externally enhances stress tolerance by boosting the activity of enzymes and metabolites in the antioxidant defense system, thereby reducing oxidative stress. The external application of GB at different levels (50-, 100-, 200-, and 400-mM) in soil significantly improves the alleviation in terms of translocation factor (TF) of heavy metal toxicity. This improvement may be attributed to the chelation of heavy metals induced by GB in the cellular vacuoles. Hence, the use of GB could enhance the quality and yield of rice plants in areas contaminated with various heavy metals. Declarations Author Contribution Conceptualization: MB, A.K.D and AA Formal analysis: AA Investigation: MBMethodology: AKDWriting and editing: MB, AKD and AA Acknowledgement Special thanks are extended to Dr. Nasreen Gazi Ansari, a Scientist at CSIR- Indian Institute of Toxicology Research in Lucknow, India, for generously offering the resources and assistance necessary for the completion of this work. Conflict of interest: None References AbdElgawad, H., Zinta, G., Hamed, B.A., Selim, S., Beemster, G., Hozzein, W.N., Wadaan, M.A., Asard, H. and Abuelsoud, W., 2020. Maize roots and shoots show distinct profiles of oxidative stress and antioxidant defense under heavy metal toxicity. Environmental Pollution , 258 , p.113705. DOI: 10.1016/j.envpol.2019.113705 Adamczyk-Szabela, D. and Wolf, W.M., 2022. 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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-4695832\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":326103012,\"identity\":\"9a4d644b-5eac-465e-96e0-ddbe4c1067b3\",\"order_by\":0,\"name\":\"Monika Bhaskar\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guru Ghasidas Vishwavidyalaya\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Monika\",\"middleName\":\"\",\"lastName\":\"Bhaskar\",\"suffix\":\"\"},{\"id\":326103013,\"identity\":\"1bae4d8b-d785-43c7-a912-2050064fb767\",\"order_by\":1,\"name\":\"Ashwini kumar Dixit\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guru Ghasidas Vishwavidyalaya\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ashwini\",\"middleName\":\"kumar\",\"lastName\":\"Dixit\",\"suffix\":\"\"},{\"id\":326103014,\"identity\":\"16ef86b4-934a-4463-bdb1-6205900f9b78\",\"order_by\":2,\"name\":\"Amar Abhishek\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYDCCAwxszAwGEjxsEjxgvhxY8AFhLTZy/BAtBsZgwQSCWhjSjCVnQLQkNoAofFr4bh9+9rig4HDihtu9Bz9X1PxJnx92+CHQFjs53QbsWiTPpZkbzzAAarlzLlnyzDGD3I230wyAWpKNzQ5g12JwhsFMmgek5UaOgWQDG1DL7ASQlgOJ23BqYf8G02L8s+GfQbrh7PQPBLTwgGwBeT/HTLKxzSBBXjoHvy2SZ3jKjXlAgSxzxsyysc/YcIN0TsGBBAPcfuE7w77tMc8fYFRK9xjfbPgmJy8/O33zhw8VdnK4tGBxKlilAbHKQUC+gRTVo2AUjIJRMBIAAIFpYzA4tH+aAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Guru Ghasidas Vishwavidyalaya\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Amar\",\"middleName\":\"\",\"lastName\":\"Abhishek\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-07-06 08:36:03\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4695832/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4695832/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":61499789,\"identity\":\"981152b4-fda2-419c-8806-e554407ee08b\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 12:30:06\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":314920,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEffect of GB treatment on morphological indices (A: root length; B Shoot length; C: harvesting index, D: fresh and dry weight) in Indian rice plant under PTHMs toxicity; Treatments with distinct alphabets were found to be significantly different from each other based on post hoc Tukey test at a significance level of p≤0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/987a2836f0eb15d14244757f.png\"},{\"id\":61499793,\"identity\":\"496d30bb-efc4-41e1-a509-219db6e32354\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 12:30:07\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":511946,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEffect of GB treatment on proline (A); MDA level (B) and electrolyte leakage (C) in Indian rice plant under PTHMs toxicity at 1\\u003csup\\u003est\\u003c/sup\\u003e; 2.5\\u003csup\\u003eth\\u003c/sup\\u003e and 4\\u003csup\\u003eth\\u003c/sup\\u003e months; Treatments with distinct alphabets were found to be significantly different from each other based on post hoc Tukey test at a significance level of p≤0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/a60728b706bd470b043ea409.png\"},{\"id\":61499790,\"identity\":\"036bb47c-3e4f-44d1-b6f7-b604b4ddc4ff\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 12:30:06\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":392960,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEffect of GB treatment on pigments (A-C); APX (D); SOD (E) and CAT level (F) in Indian rice plant under PTHMs toxicity at 1\\u003csup\\u003est\\u003c/sup\\u003e; 2.5\\u003csup\\u003eth\\u003c/sup\\u003e and 4\\u003csup\\u003eth\\u003c/sup\\u003e months; Treatments with distinct alphabets were found to be significantly different from each other based on post hoc Tukey test at a significance level of p≤0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/e7bb6ed0d39512d592dbca8b.png\"},{\"id\":61499808,\"identity\":\"74cfdd86-7044-4184-be0d-b177b76aa982\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 12:30:08\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":513505,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEffect of GB treatment on PTHMs accumulation in root, shoot and seeds in Indian rice plant under PTHMs toxicity; Treatments with distinct letters or numerical were found to be significantly different from each other based on post hoc Tukey test at a significance level of p≤0.05. #: permissible limit of heavy metals in seeds.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/64f8d0f4bdbea100bf395a4e.png\"},{\"id\":61499791,\"identity\":\"5f247346-1820-4ec9-8666-c3eff8300ac4\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 12:30:06\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1351853,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDistribution pattern of bioaccumulation factor of different heavy metals in Indian rice plant.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/2d8d611e2f3696327cd8eedf.png\"},{\"id\":62845167,\"identity\":\"b8ec2a2d-e275-4e96-b31a-affb0eae8fd6\",\"added_by\":\"auto\",\"created_at\":\"2024-08-20 07:19:02\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":4121965,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4695832/v1/f4d323ad-a8f4-4b96-9d5d-07f70a5642e7.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"\\u003cp\\u003eEnhancing Indian Rice Plant resilience to toxic heavy metals with Glycine betaine as a modulator.\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eThe Indian rice plant (\\u003cem\\u003eOryza sativa\\u003c/em\\u003e L) is a versatile member of the Gramineae family. It is cultivated globally, with India ranking second in terms of rice production (110\\u0026nbsp;million metric tonnes), following China (Ito, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Rice plays a crucial role in ensuring food security, as it provide more than 50% of the dietary calories required by billions of people living in poverty in India and south Asia (Ghose et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e). However, agricultural production worldwide has suffered significant damage due to environmental changes caused by human intervention. This issue must be addressed.\\u003c/p\\u003e \\u003cp\\u003eThe growth and production of rice are often affected by various abiotic stresses, including salinity, drought, and inorganic pollution, particularly the toxicity caused by heavy metals (Sarma et al., 2024). These factors pose significant challenges to rice farmers and may impact overall rice production. Chhattisgarh state, well-known as one of the primary rice producers in India, has recently encountered a hindrance to the growth of its rice crop in highly industrialized regions such as Korba, Durg-bhilai, and Raigarh. These areas of Chhattisgarh state have suffered from extensive contamination of agricultural land and water resources of various potential toxic heavy metals (PTHMs) such as Iron (Fe), Chromium (Cr), copper (Cu), cadmium (Cd), etc (Sharma et al., \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). The contamination may be attributed to the modern industrial activities including the establishment of refractory steel factories, coal and bauxite mining, coal based thermal power plants, and discharge of untreated or partially treated industrial solid or liquid waste (Bhaskar et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). These industrial activities serve as prevalent sources of mixture of different heavy metals in both water and soil. In plants, it caused adverse impact on morpho-physiological characteristics, photosynthesis, plant defense system, root impairment, and ultimately plant mortality. In addition, heavy metals like Cr, Pb, and Cd generates a detrimental impact on the proper functioning plasma membrane, leading to swift alteration in the level of essential metals like sodium and calcium, as well as lipid composition cell membrane (Rawat et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). This impairment in plasma membrane integrity also influences the activity of proton pumps, which has been observed to decrease in different crop such as maize, rice, sorghum and chick pea when exposed to PTHMs stress (Astolfi et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Cao et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Kumar, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Singh et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). Stressors experienced by plants prompt metabolic changes, resulting in varying the level of cellular metabolites. These modifications within the cell due to abiotic stress may seemingly contribute to the plant\\u0026rsquo;s enhanced survival capabilities under such challenging circumstances.\\u003c/p\\u003e \\u003cp\\u003eIn order to tackle environmental challenges, numerous plant species have developed a similar approach of accumulation appropriate solute or osmolytes (Ghosh et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). Among these, polyols, sugars, amino acids (such as proline and histadine), and glycine betaine (GB) are commonly used to protect plants from abiotic stresses (Kumar, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). GB is safe, water soluble quaternary ammonium compound that can be found in marine invertebrates, archaea, bacteria, as well as plants and animals (Hill, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). However, some plants do not naturally accumulate enough GB to adequately safeguard themselves against environmental stress.\\u003c/p\\u003e \\u003cp\\u003eAfter conducting extensive research, it has become apparent that GB plays a crucial role in mitigating the detrimental impacts of heavy metals on plants (Kumar, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Sharma et al., \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). In particular, when plants are exposed to one or two heavy metals, this compound actively enhances the functionality of antioxidant enzymes. It is crucial to highlight that the presence of refractory steel factories, coal and bauxite mining, and coal-fired thermal power plants in specific locations can lead to soil contamination. In these sites, it is more common to find elevated levels of multiple heavy metals rather than just one or two type of heavy metal. The main focus of this study was to address these concerns by investigating the effects of a combination of eight potentially harmful PTHMs and the inclusion of GB on different aspects of the physiological and biological resilience of the Indian rice plant. Additionally, the study aimed to analyze the plant's stress response in the presence of mixture of PTHMs. Surprisingly, there is currently no available research on the sensitivity of the Indian rice plant when exposed to a combination of various heavy metals.\\u003c/p\\u003e\"},{\"header\":\"2. Material and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Plant selection\\u003c/h2\\u003e \\u003cp\\u003eThe present research was conducted in the open field of Thakur Chedilal Agricultural College, Bilaspur, Chhattisgarh, India. Indian rice plant (\\u003cem\\u003eOryza sativa\\u003c/em\\u003e L), variety MTU1010, were purchase from same college. This verity was selected because it serves as one of the main staple foods of Chhattisgarh state. However, there are no report about the sensitivity of this cultivars for GB under mixed heavy metal toxicity.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cem\\u003e2.2 Pot experimental design and raising the crop\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003eThe objective of this study was to investigate the Indian rice plant's capacity to mitigate the negative impact of a combination of PTHMs such as Cadmium (Cd), Copper (Cu), Iron (Fe), Manganese (Mn), Nickel (Ni), Zinc (Zn), Chromium (Cr), and Lead (Pb), both with and without the presence of GB. The rice seeds were immersed in water for approximately 2 days at normal room temperature. To facilitate germination, the seeds were kept in a moist environment (using two-layer cloth gauze to retain moisture) at room temperature for additional 30 hours. Once seeds had sprouted, they were grown in seedbed under field condition to develop into seedlings. Following a one-month duration, the seedlings were transplanted into pots filled with soil that encompassed varying levels of PTHMs alone and with GB. Soil properties are mentioned in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Each pot accommodated a total of four plants. The plants were exposed to two different level of treatment: the initial treatment involved various concentration of the PTHMs alone, namely TC-0 mg/kg (as control), T1: 5 mg/kg, T2: 10 mg/kg, T3: 20 mg/kg, and T4: 40 mg/kg. The second treatment involving combining PTHMs with GB (mM), with concentration of T1\\u0026thinsp;+\\u0026thinsp;GB: 50 mM, T2\\u0026thinsp;+\\u0026thinsp;GB: 100 mM, T3\\u0026thinsp;+\\u0026thinsp;GB: 200 mM, T4\\u0026thinsp;+\\u0026thinsp;GB: 400 mM (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Fertilizer containing NPK nutrients was applied as per previous study by Singh et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e. The rice crops were grown for a span of four months using a randomized block pattern, with five separate plots for replication.\\u003c/p\\u003e \\u003cp\\u003e\\u003cstrong\\u003eTable 1:\\u003c/strong\\u003e General physic-chemical parameters of experimental soil \\u0026nbsp;\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" align=\\\"\\\" width=\\\"457\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\"\\u003e\\n \\u003cp\\u003eParameters\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSoil\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003epH\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSlightly acidic 6.6\\u0026plusmn;0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eColor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGreyish black\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eConsistency\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLess sticky\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSand (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e45.7\\u0026plusmn;1.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSlit (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e37.33\\u0026plusmn;0.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eClay (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e14.72\\u0026plusmn;0.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOrganic matter (%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.37\\u0026plusmn;0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eEC (dS m\\u003csup\\u003e-1\\u003c/sup\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.38\\u0026plusmn;0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNitrogen (kg/hectare)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e326.14\\u0026plusmn;8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePhosphorus (kg/hectare)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e12.54\\u0026plusmn;0.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePotassium ((kg/hectare)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e240.44\\u0026plusmn;5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eSulphur (mg/kg)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e15\\u0026plusmn;0.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eBoron (mg/kg)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.80\\u0026plusmn;0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"100%\\\" colspan=\\\"2\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMetals (mg/kg)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCd\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eBDL\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.012\\u0026plusmn;0.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCu\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.95\\u0026plusmn;0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eZn\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.36\\u0026plusmn;0.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFe\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e3.64\\u0026plusmn;0.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNi\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.28\\u0026plusmn;0.015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMn\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.12\\u0026plusmn;0.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"47.4835886214442%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePb\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"52.5164113785558%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.06\\u0026plusmn;0.002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eBDL: below detection limit\\u003c/em\\u003e\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eTreatment details\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"2\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTreatment name\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTreatment conditions\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTC\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTreatment Control (0 for THMs mg/kg and GB mM)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTHMs (5 mg/kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT1\\u0026thinsp;+\\u0026thinsp;GB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePTHMs (5 mg/kg)\\u0026thinsp;+\\u0026thinsp;GB (50 mM)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTHMs (10 mg/kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT2\\u0026thinsp;+\\u0026thinsp;GB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePTHMs (10 mg/kg)\\u0026thinsp;+\\u0026thinsp;GB (100 mM)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTHMs (20 mg/kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT3\\u0026thinsp;+\\u0026thinsp;GB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePTHMs (20 mg/kg)\\u0026thinsp;+\\u0026thinsp;GB (200 mM)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTHMs (40 mg/kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eT4\\u0026thinsp;+\\u0026thinsp;GB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePTHMs (40 mg/kg)\\u0026thinsp;+\\u0026thinsp;GB (400 mM)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Measurement of plant growth parameters\\u003c/h2\\u003e \\u003cp\\u003eThe plant samples were collected on three occasions throughout the experiment. The first sampling occurred prior to the transplantation of rice seedling into the pot, which took place in the first month. The second sampling was carried out after the transplantation when the plants were flowering stage (2.5th month), and third sampling was conducted just before harvest in the 4th month. To prepare the collected plants for analysis, they were carefully plucked and rinsed with running water followed by 20 mM calcium chloride to eliminate any adhering particle.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.1 Morphological changes\\u003c/h2\\u003e \\u003cp\\u003eIn order to showcase the physical development, parameters like root length (RL), shoot length (SL), fresh weight (FW), dry weight (DW), and harvesting index (HI) were assessed at the end of experiment. The fresh biomass of the plant was precisely measured right after harvesting using a digital electric balance. To determine the dry biomass, the freshly harvested rice plant sample was subjected to oven drying at 80 ℃ for a duration of 24 hours. The weight of the filled grains was used to obtain grain yield per pot. Separation of filled grains from unfilled and partially filled ones was accomplished through water floating, as the filled grains sank to the bottom of the beaker and were manually counted. The percentage of filled grains (% FG) was then determined (Jia-Kuan et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e). Subsequently, the harvesting index (HI) was computed following the subsequent formula.\\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:\\\\%FG=\\\\frac{Filled\\\\:Grain\\\\:}{Filled+unfilled+Partially\\\\:filled\\\\:grain}\\\\times\\\\:100$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Equb\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equb\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:HI=\\\\frac{Grain\\\\:yield\\\\:\\\\left(dry\\\\:weight\\\\right)}{Grain+Straw\\\\:yield}\\\\times\\\\:100$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.2 Estimation of pigments\\u003c/h2\\u003e \\u003cp\\u003eTo extract Chlorophyll, 1 gm leaf sample was mixed with a solution consisting of 80% aqueous acetone (v/v). The resultant plant extract was then subjected to centrifugation at 5000 rpm for 5 minutes at 4℃. To determine the extraction co-efficient, blank samples (consisting of 80% aqueous acetone) were assessed against the extract at different wavelengths (663 and 645 nm). Finally, the chlorophyll content was calculated using the standard method developed by Lichtenthaler and Wellburn in 1983.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cem\\u003e2.4 Determination of leaf malondialdehyde (MDA) and electrolyte leakage (EL)\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003eThe overall MDA content in rice plants leaves were assessed using the method introduced by Heath and Parker in 1968. EL leakage was measured using the protocol described by Valentovic et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e. In brief, three randomly selected plants, each with two mature leaves, were chosen and cut into 1 cm segments. These segments were washed three times with distilled water to eliminate any surface contaminants and then placed in a stopper vial containing 10 ml of deionized water. The samples were subsequently incubated at a temperature of 25 ℃ on a rotator shaker at 120 rpm for 24 hours. After the incubation period, the electrical conductivity of the bathing solution (EL0) was measured. The samples were then subjected to autoclaving at a temperature of 120 ℃ for 30 minutes, and after cooling the solution, a second reading of electrical conductivity (ELt) was obtained. The percentage of EL was determined using the formula: EL% = EL0/ELt \\u0026times; 100.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Proline and antioxidant activity\\u003c/h2\\u003e \\u003cp\\u003eTo obtain the enzyme extract, we selected 0.5 grams of fresh leaf sample and crushed it in 4 milliliters of phosphate buffer (100mM, pH: 7.5). This buffer also contained 1 millimolar of EDTA and a small amount (50 milligrams) of PVP (Polyvinyl polypyrrolidone). After crushing, the samples were centrifuged at 10,000 rpm for 10 minutes at 4℃. The resulting supernatant was then extracted and stored in a micro-centrifuge tube for further quantification of various enzymes. To assess the level of proline (\\u0026micro;mol/gm), we employed the method developed by Sarker and Oba, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e. It involved measuring the proline level of the samples at a wavelength of 520 nm using a spectrophotometer. The defense mechanism of plants against any damage can be measured by assessing the activity level of ascorbate peroxidase activity (APX) superoxide dismutase (SOD) and catalase (CAT). The APX, SOD and CAT were evaluated using the standard method given by Nakano and Asada (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e1981\\u003c/span\\u003e), Nishikimi et al. (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e1972\\u003c/span\\u003e), and Maehly (1955), respectively.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 Metal analysis of plant samples\\u003c/h2\\u003e \\u003cp\\u003eAt the end of experiment, the plant samples were divided into three parts: root, shoot, and seeds. Subsequently, they were subjected to an oven-drying process at 80\\u0026deg;C for a duration of 48 hours. To further analyze the plant samples, a crushed form of the dried specimen was incinerated in a muffle furnace at a temperature of 500\\u0026deg;C for a period of 5 hours. Next, a gram of the resulting ash was individually mixed with a digestion mixture consisting of nitric acid and perchloric acid in a ratio of 5:1. This process was continued until the appearance of white fumes. The beaker's walls were rinsed with a minimal quantity of distilled water, followed by filtration of the solution. Furthermore, the filtrate was transferred and brought up to a volume of 20 mL in a volumetric flask, following the standardized protocol outlined by APHA (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e). Finally, the concentration of various heavy metals present in the samples was determined using an atomic absorption spectrophotometer (AAS), (ZEE nit 700 model manufactured by Analytic Jena, Germany).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.6.1 Quality control assurance\\u003c/h2\\u003e \\u003cp\\u003eIn order to ensure the accuracy, reliability, and reproducibility of the data collected, we conducted two replicated batch isotherm tests and carried out experimental blanks in parallel. To calibrate and verify the instruments, we utilized multiple sources of National Institute of Standard and Technology (NIST) traceable standards from Merk. For each set of data points, we employed both linear and nonlinear regression analyses. Using Microsoft Excel and Sigma Plot V6.0 for Windows (SPSS Inc., Chicago, IL), we obtained a regression coefficient (R\\u003csup\\u003e2\\u003c/sup\\u003e) and a probability value (\\u003cem\\u003ep\\u003c/em\\u003e) that indicate the level of fit of the Freundlich and Langmuir models to the data.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.7 Statistical analysis\\u003c/h2\\u003e \\u003cp\\u003eNormality of continuous data was confirmed by Kolmogorov-Smirnov test. Numerical data were presented in the form of mean and standard deviation. To examine the significant differences among the mean values, a post hoc analysis using the least significant difference (LSD) method was performed. The statistical analysis was conducted using the Statistical Package for the Social Sciences version 22 (SPSS-22) from IBM, based in Chicago, USA. The significance level (p-value) was set at less than 0.05. For generating the graphics, Sigma Plot V6.0 for Windows (SPSS Inc., Chicago, IL) was utilized.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Impact of GB application under PTHMs stress on physio-biochemical parameters\\u003c/h2\\u003e \\u003cp\\u003eThe impact of treating PTHMs with and without GB was assessed by measuring the length of plant roots (RL), length of shoots (SL), weight of fresh plant material (FW), weight of dry plant material (DW), and harvesting index (HI). The data was collected at the 1st, 2.5th, and 4th month. Throughout the course of one month, the selected parameters were mostly consistent in nature (data not shown). However, after exposure to PTHMs for two and a half months, there was a significant impact on the growth parameters compared to control plants (TC). As compare to control plants (TC), PTHMs contamination under treatments T1, T2, T3, and T4, the RL decreased by 22.3%, 33.6%, 41%, and 50.2% respectively, while SL decreased by 9.0%, 12.7%, 28.01%, and 29.3% respectively. Similarly, HI decreased by 10.6%, 16.4%, 25.9%, and 30.3%, FW decreased by 18.6%, 29.4%, 40.4%, and 45.4%, and DW decreased by 22.2%, 36.5%, 46.8%, and 54.3% respectively (all p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, ANOVA, LSD). This decline in growth could be attributed to the high concentration of metals, which hinder the normal growth of plants by acting as growth inhibitors (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). When comparing the parameters in PTHMs treated plants to those in plants treated with T1 to T4 in combination with GB, there was an increase in RL by 26.9%, 29.6%, 30.1%, and 37.4% respectively, SL increased by 9.8%, 11.1%, 20.9%, and 21.6% respectively, HI increased by 9.12%, 13.1%, 20%, and 20.4%, FW increased by 16.6%, 19.9%, 32.3%, and 30.2%, and DW increased by 20.7%, 23.4%, 30.3%, and 33.2% respectively. These findings indicate that the growth parameters directly respond to PTHMs stress by undergoing changes in morphology, and the application of GB therapy helps alleviate these reactions.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003e3.2 Impact of GB treatment on proline, oxidative stress, and electrolyte leakage (EL) in plants under PTHMs stress\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eDuring the initial month, the content of proline (\\u0026micro;mol/gm) remained constant (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05). However, after 2.5 months, when compared to the control plant, the proline content exhibited a significant increase under PTHMs stress (all p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Notably, the T4 level (40 mg/kg) of PTHMs treatment demonstrated the highest accumulation of proline compared to other treatment levels. Furthermore, the combination of GB and PTHMs resulted in increased proline accumulation, although this increase shows marginal significance when compared to the treatment with PTHMs alone (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). However, the proline activity was decrease with plant age but this pattern persisted until the end of the experiment (4th month). Exposure to heavy metals in the environment is closely linked to an elevated risk of oxidative stress. To evaluate this, we measured stress biomarkers, specifically malondialdehyde (MDA) and electrolyte leakage (EL%), in Indian rice plants grown in soil with different levels of PTHMs. We observed a significant increase in MDA and EL% levels in rice plants subjected to PTHMs stress after 2.5 months, compared to control plants (MDA: 48.6%, 54.2%, 64.6%, and 64.4%; EL: 45.6%, 58.1%, 65.8%, and 70.7% at T1, T2, T3, and T4 PTHMs levels). However, the application of GB leads to a significant decline in MDA and EL% levels compare to plant treated with PTHMs only (all p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB, C). Consequently, the exogenous application of GB proved to be effective in alleviating stress in rice plants.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Variation in pigments under PTHMs stress with or without GB\\u003c/h2\\u003e \\u003cp\\u003eA significant difference was observed in the pigments like Chl, including Chl-a, Chl-b, total Chl, and carotenoid content, between the groups exposed to only PTHMs and the groups exposed to both PTHMs and GB. The homogeneity of pigment levels in plants was found in the initial month (all p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). At the 2.5-month mark, Chl-a in Indian rice plants decreased by 32.1%, 45.2%, 50.2%, and 66.5% under T1, T2, T3, and T4 levels of PTHMs stress respectively, compared to the control plants (TC). Likewise, Chl-b exhibited a significant reduction with increasing concentrations of PTHMs from T1 to T4 at the 2.5-month stage (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Additionally, total Chl and carotenoid contents decreased by 33.2%, 21.6%, 51.1%, and 49.5%, and 11%, 39.9%, 71.1%, and 83.9%, respectively, under PTHMs stress levels T1, T2, T3, and T4. Therefore, higher concentrations of PTHMs resulted in a greater decrease in chlorophyll-a, chlorophyll-b, and carotenoid content. Notably, the application of GB treatment led to a significant increase in chlorophyll content in rice plants. Compared with plants treated at levels T1, T2, T3, and T4, Chl-a increased by 28.7%, 49.6%, 63.2%, and 71.3%, while Chl-b increased by 28.1%, 50.4%, 60.1%, and 59%. Total Chl increased by 37.7%, 14.3%, 51.6%, and 40.1%, and carotenoids increased by 15.4%, 43.3%, 75.5%, and 84.1%, respectively (all p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Furthermore, after the fourth month, all treatments showed a significant decrease in chlorophyll and carotenoid levels (ANOVA, LSD p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01). Overall, the findings confirmed that GB treatment restored the chlorophyll level in rice plants when exposed to high levels of mixture of PTHMs.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 Distribution of Antioxidant enzyme activity under PTHMs with or without GB\\u003c/h2\\u003e \\u003cp\\u003eWe evaluate the effectiveness of various antioxidant enzymes, SOD, CAT, and APX, in the leaves of rice plants subjected to stress caused by PTHMs stress. Comparing them to the leaves of unaffected plants (TC), a significant reduction in the activity of these antioxidant enzymes was observed in plants treated with T4 at every stage of growth in the rice plants (2.5th month and 4th month). Specifically, the enzymatic activities of APX, SOD, and CAT in rice plants exposed to T4 levels of PTHMs decreased by 44.9%, 62.7%, and 80.26%, respectively. Conversely, when additional GB was applied along with PTHM treatment, the enzymatic activities of APX, SOD, and CAT in \\u003cem\\u003eOriza sative\\u003c/em\\u003e plants increased compared to the values observed in plants solely treated with PTHMs (all \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01). These findings clearly demonstrate that the external application of GB significantly amplifies the enzymatic activities in the leaves of rice plants experiencing mixed PTHMs stress. On other hand, homogeneity of antioxidant levels in rice plants was found in the initial month (all p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e-D, E, F).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003e3.5 Effect of exogenous GB on mixture of PTHMs accumulation and distribution and translocation factor (TF) in rice plant\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe heavy metal content of roots, shoot and seeds were determined at the end of experiment. Heavy metal content of all part (root, shoot and seeds) increased with increasing with heavy metal stress. Heavy metal uptake was remarkably higher in roots followed by shoot and seeds, which increased with increasing concentration of heavy metals. A maximum increase of PTHMs content was observed at T4 treatment in all parts of plants. Indian rice plant has shown maximum accumulation of Fe followed by Mn, Zn Cr, Ni, Pb, Cd and Cu. However, the exogenous application of GB resulted in a decline of a combination of 8 heavy metals in various parts of the plants. The most significant reduction in chromium (Cr) and lead (Pb) content was observed in the roots, stems, and seeds of plants treated with 400 mM GB (T4\\u0026thinsp;+\\u0026thinsp;GB). Under T4 PTHMs stress, the Cr and Pb content in the roots, shoots, and seeds was decreased by as much as 33.3%, 36%, and 89.3% respectively, and 36.4%, 55%, and 80.5% respectively when treated with 400 mM GB (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). Further, translocation factor (TF) values were notably elevated for vital elements such as Mn, Cu, Zn and Fe in comparison to harmful heavy metals Cd, Cr and Pb. Furthermore, the research demonstrated that the application of GB led to a decrease in the TF values for specific metals (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eThe soil obtained from the experimental plots had a lower stickiness and exhibited a dark gray color. The absorption, accumulation, and distribution of metals in different parts of the plant are significantly influenced by both the plant itself and the characteristics of the soil. The pH level and organic matter content of the soil play crucial roles in regulating the availability of metals to plant species. When the pH level and organic matter increase, the movement of heavy metals decreases due to the precipitation of hydroxides and carbonates, along with the formation of insoluble organic complexes (Adamczyk-Szabela and Wolf, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). Conversely, metals exhibit higher mobility in soils with a pH lower than 7 and lower organic matter content. In the present study, the pH of the experimental soil was determined to be 6.6 ± 0.13, while the organic matter content was found to be 1.37 ± 0.03%. This finding aligns with the work of Srivastava et al. (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e) and Li et al. (\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), who also emphasized that the mobilization of heavy metals in soil is influenced by pH and organic matter. Furthermore, the concentration of heavy metals in the experimental soil was found to be within the normal range.\\u003c/p\\u003e \\u003cp\\u003ePlants, being inherently immobile, frequently encounter various forms of environmental stress, one of which is the presence of heavy metals. PTHMs like Cr, Pb, Cd do not serve any essential metabolic function in plants, and in fact, disturb various physiological and biochemical process, ultimately reducing crop yield (Sarma et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). To combat the toxic effects of different PTHMs on various plants, including rice, numerous substances such as silicon, GB, hydrogen sulfide, selenium, and melatonin have been extensively studied (Dotaniya et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e; Kumar et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). In this study, we aimed to investigate the effects of exogenous GB, an organic osmolyte known for enhancing physiological and biochemical processes, on Indian rice plants cultivated under stress from a mixture of PTHMs.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1 Change in plant growth parameters\\u003c/h2\\u003e \\u003cp\\u003eRoots serve as the primary entry point for PTHMs and are typically the first organ to experience the toxic effects of these substances. In the current investigation, a significant reduction in growth, both in terms of RL, SL, HI and over all biomass production (FW, DW) were observed in rice plants subjected to heavy metal stress. These findings are consistent with previous studies that have reported similar outcomes (AbdElgawad et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Tang et al., \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). However, numerous studies have demonstrated that the external application of GB can alleviate the impacts of PTHMs and enhance the morphological characteristics of cultivated plants (Kumar et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). The present study further confirms that the application of exogenous GB effectively reduces the detrimental effects of a combination of PTHMs on the RL, SL, FW, DW and HI. GB has been known to enhance plant growth even in the presence of heavy metal stress. This could be attributed to the improved development of nutrient absorption and gas exchange qualities in plants when GB is applied. Scientists have reported similar findings in rice plants experiencing abiotic drought stress (Chaum and Kirdmanee, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e). Additionally, GB may have a protective effect on key enzymes involved in CO\\u003csub\\u003e2\\u003c/sub\\u003e fixation, such as RuBisCo and RuBisCo activase, when plants are exposed to abiotic stress conditions. Consequently, this protection leads to an overall enhancement in plant growth. The reduction in stress caused by different heavy metals following the application of GB has also been documented in wheat, mungbean, and chickpea crops (Ali et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Chen and Murata. 2011; Singh et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003e4.2 The impact of GB treatment on proline, oxidative stress, and electrolyte leakage (EL) in plants under PTHMs stress\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eExposure to PTHMs in the surroundings has a direct correlation with an increased likelihood of experiencing oxidative stress. In order to assess this relationship, we measured stress biomarkers, specifically proline level, malondialdehyde (MDA) and electrolyte leakage (EL%). An evident rise in the accumulation of proline was noticed primarily in the leaves of rice plants when subjected to PTHMs stress as compare to the control group (TC). Moreover, the application of GB resulted in a moderate increase in proline accumulation in rice plants, when compared to the treatment involving only PTHMs. Proline is a basic amino acid found in proteins, and free proline plays a crucial role in plants during biotic and abiotic stress conditions. The molecular mechanism underlying increase proline level under heavy metal stress are yet to be identified, but one hypothesis suggests that protein is broken down into amino acid and converted into proline for storage. Singh et al. (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e) reported that soil heavy metal increased the proline content of chick pea plant, and high heavy metal (Cr) with GB application resulted in a marked increases in proline content.\\u003c/p\\u003e \\u003cp\\u003ePTHMs stress significantly enhances the levels of MDA and EL (%) in rice plants compared to the control group. However, when the PTHMs combined with GB treatment was applied, the levels of MDA and EL (%) in rice plants showed a decrease compared to the PTHMs-treated plants without GB application. The elevated MDA and EL percentage suggest that there is an excess generation of intracellular free radicals, which leads to membrane damage and cytotoxicity through the production of malondialdehyde, a byproduct of lipid peroxidation. Similar findings were observed by Singh et al. (\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), where they reported an increase in MDA levels in various parts of plants under mixture of heavy metal stress. Additionally, Bhargava et al. (2008) conducted a study on the Indian mustard plant (\\u003cem\\u003eBrassica nigra\\u003c/em\\u003e L.), which also concluded that exposure to a mixture of heavy metals resulted in elevated levels of MDA in the plant's leaves.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3 Variation in pigments under PTHMs with or without GB\\u003c/h2\\u003e \\u003cp\\u003ePTHMs toxicity has a significant negative impact on the pigment system of plants. This toxicity disrupts the photosynthetic system by causing heavy metals to enter the leaf tissue, potentially damaging the chloroplast's laminar membrane (Wang et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). The present study demonstrates that a high concentration of PTHMs in plant tissues leads to a decrease in chlorophyll content compare to control, which ultimately hinders plant growth and affects biochemical traits. Under the PTHMs exposure, rice plants exhibited a noticeable reduction in levels of Chlorophyll a, b, and carotenoid. Moreover, when PTHMs in elevated levels, metals exhibit a detrimental effect on chlorophyll production. Take the PTHMs Cd and Cr, for instance, which hampers the creation of the photoactive protochlorophyll reductase enzyme complex and disrupts the synthesis of aminolevulinic acid, both crucial steps in chlorophyll biosynthesis. Heavy metals like Cd, Cr, Cu accomplishes this by obstructing the sulfhydryl group of the enzyme, which is essential for its function, through the formation of a complex with active thiol groups (Hossain et al., \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). The application of GB promotes shoot elongation by augmenting cell expansion and division. This mechanism may explain GB's positive impact on growth performance when plants are exposed to heavy metal stress. A comparable effect has been previously observed in sweet pepper and chick pea plants (Wang et al., \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; Singh et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). Furthermore, the enhanced accumulation of antioxidant enzymes and pigment levels may have contributed to the improved growth performance in rice plants when treated with a combination of heavy metals and GB, compared to treatment with PTHMs alone.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.4 Distribution of Antioxidant enzyme activity\\u003c/h2\\u003e \\u003cp\\u003ePlant body is equipped with a range of scavenging machinery. Superoxide Dismutase (SOD), APX and Catalase (CAT) are considered primary antioxidants which are involved in direct scavenging of ROS. SOD catalyses the decomposition of superoxide as well as play important role in detoxification of anion to radical oxygen, hydrogen peroxide and finally convert to oxygen and water. SOD usually depends on different metals as cofactor. Further, CAT act as a primary indicator for removal of hydrogen peroxide under metal stress in peroxisomes. On other hand APX also involves in detoxifying H\\u003csub\\u003e2\\u003c/sub\\u003eO\\u003csub\\u003e2\\u003c/sub\\u003e to H\\u003csub\\u003e2\\u003c/sub\\u003e0 in plant cell via bate-glutathione cycle. The results of the present investigation revealed an amelioration of mixed heavy metals toxicity in rice plant exposed to GB. This amelioration might be resulted due to reduction in heavy metal uptake on GB application. It means there was no disturbance to stress machinery of the plants which turn maintains proper stomatal conductance, chloroplast ultrastructure, photosynthetic capacity and proper nutrient uptake. All these resulted in an increase the tolerance capacity of the plant. GB further increase the activity of antioxidant activity which in turns prevent plant to oxidative damage caused by free radicles generation due to stress condition that might also be the reason for enhancing amelioration process in rice plant. Kumar et al. (2021) demonstrated similar effect on GB application in sorghum plant under Cr stress, as were observed during the present investigation. However, the mechanism involved in the enhancement of amelioration behavior of the plant by GB application is still not clear.\\u003c/p\\u003e \\u003cp\\u003eIn this study, SOD (superoxide dismutase) and CAT increased by 17.5–38.4% and 25.5–50% in Indian rice plants treated PTHMs in combination with Glycine Betain. Conversely, a small rise was observed in APX (ascorbate peroxidase) in all heavy metal treatments combined with GB. Our finding reveals that PTHMs in mixed condition increase the indices of oxidative stress parameters. However exogenous application of GB significantly enhances the antioxidant system which in turns reduced the indices of oxidative stress parameters under mixed heavy metal stress.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.5 Uptake, Accumulation and distribution of PTHMs in different part of plant with or without GB\\u003c/h2\\u003e \\u003cp\\u003eHeavy metal contamination in arable land is a pressing issue associated with industrialization globally. It has detrimental effects on plant growth and yield, leading to a significant concern for agriculture. Numerous studies have highlighted the hazardous impact of heavy metal toxicity on crop plants (Bharagava et al., \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e; Singh et al., \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Kumar et al., 2021; Singh et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). While there are reports suggesting the use of osmolytes such as GB to alleviate heavy metal toxicity, most of these studies focus on a single metal contamination scenario. Various crop plants have distinct mechanisms for accumulating and distributing metals in different parts of the plant such as the roots, shoots, fruits, or seeds. This study demonstrates that plants exposed to mixed concentrations of metals exhibit unique patterns of metal accumulation. However, uptake and distribution of metals in plants are influenced by factors such as the availability of metals, plant metabolism, and microbial interactions.\\u003c/p\\u003e \\u003cp\\u003eThe research findings indicate that the Indian rice plant has the highest accumulation of Fe, followed by Mn, Zn, Cr, Ni, Pb, Cd, and Cu in its roots. When subjected to PTHMs stress, the uptake of metals was significantly higher in the roots compared to the shoots and seeds, and this uptake increased with higher concentrations of PTHMs. The high accumulation of heavy metals in the roots may be attributed to the higher metabolic rate in this plant part, as suggested by Haddad et al. (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The levels of PTHMs in all plant parts increased as the PTHMs stress intensified, surpassing the permissible limits set by FAO/WHO (1984) for Cr, Pb, Ni, Cu, Cd, and Mn in terms of human consumption suitability (permissible limit, PL: mg/kg) Cr: 0.02; Pb: 0.43; Ni: 1.63; Cu: 3.0; Cd: 0.21; Mn: 2.0). However, the levels of Zn (PL: 27.4) and Fe (20.0 mg/kg) in the seeds of the rice plant were below the permissible limits. Hence, it may be advisable that this Indian rice plant treated with high concentration of heavy metals should not be taken as food by human beings and cattle because these metal rich plants may cause several clinical problems (Rattan et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eNonetheless, the application of GB externally led to a decrease in the levels of 8 heavy metals across different parts of the plants. The most substantial decrease in chromium (Cr) and lead (Pb) concentrations was noted in the roots, stems, and seeds of the treated plants with 400 mM GB. PTHMs like Cr, Pb, Cu are known to impede plant metabolism and growth factors, cause changes in chloroplasts and cell membranes, reduce photosynthetic pigments, induce chlorosis, disrupt the movement of water and minerals, and hinder enzymatic activity in plants (Haddad et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Under T4 PTHMs stress, the Cr and Pb content in the roots, shoots, and seeds was decreased by as much as 33.3%, 36%, and 89.3% respectively, and 36.4%, 55%, and 80.5% respectively when treated with 400 mM GB (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). The decrease in the concentration of heavy metals in plant samples could be attributed to the presence of GB, which helps in maintaining the integrity of cell membranes and protects cells from damage. This protective mechanism reduces the likelihood of heavy metals entering the cells. Additionally, the application of GB may also shield the cell membranes, thereby preventing the movement of heavy metals into the cells. Similar findings have been observed for Pb and Cd levels in mung beans, rice, and wheat. Studies by Kumar et al. (2021) and Karagiannidis and Hadjisavva (1998) have shown that the use of GB as an osmolyte, along with arbuscular mycorrhizal fungi (AMF) inoculation, can enhance nutrient uptake and inhibit the absorption of various heavy metals such as Cr, Mn, Fe, Co, Ni and Pb in beans and Durum wheat. It is suggested that the competition between essential nutrients and heavy metals for entry into the cells could be another reason for the reduced absorption of heavy metals with GB application.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eBioaccumulation and Translocation factor\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe factor responsible for transporting metals within plants, known as the translocation factor (TF), plays a critical role in monitoring metal presence across different plant parts. Essentially, TF evaluates the movement of metals either from the roots to the shoots or from the shoots to the seeds in plants (Baker and Walker, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e). Research has shown that TF values were consistently below 1 when metals were moved from roots to shoots and shoots to seeds across all tested metals. Notably, the TF values for root to shoot translocation increased significantly with higher levels of PTHMs, ranging from T1 to T4 concentrations. Intriguingly, essential metals such as Mn, Cu, Ni, Zn, and Fe exhibited higher TF values compared to toxic heavy metals like Cd, Cr, and Pb. This disparity may be attributed to the crucial role of these essential metals in protein and pigment synthesis within plants (Rotkittikhun et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e). Generally, plants tend to avoid accumulating unnecessary heavy metals that do not contribute to their metabolic processes (Liu et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e; Satpathy et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). TF values for metals like Cd, Ni, Pb, Cr, and Fe increased with PTHMs concentration, but were subsequently reduced following the application of a GB. On the whole, GB has been acknowledged as a beneficial natural compound that enhances plants' resilience against stress induced by heavy metals.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eIn conclusion, the toxicity of PTHMs at varying concentrations (T1: 5; T2: 10, T3: 20, and T4: 40 mg/kg) leads to biochemical changes in rice plants that impact the plant's morpho-physiological characteristics and increase oxidative stress levels. The harmful effects become more pronounced as the concentration of PTHMs increases. The application of glycine betaine (GB) externally enhances stress tolerance by boosting the activity of enzymes and metabolites in the antioxidant defense system, thereby reducing oxidative stress. The external application of GB at different levels (50-, 100-, 200-, and 400-mM) in soil significantly improves the alleviation in terms of translocation factor (TF) of heavy metal toxicity. This improvement may be attributed to the chelation of heavy metals induced by GB in the cellular vacuoles. Hence, the use of GB could enhance the quality and yield of rice plants in areas contaminated with various heavy metals.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eConceptualization: MB, A.K.D and AA Formal analysis: AA Investigation: MBMethodology: AKDWriting and editing: MB, AKD and AA\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eSpecial thanks are extended to Dr. Nasreen Gazi Ansari, a Scientist at CSIR- Indian Institute of Toxicology Research in Lucknow, India, for generously offering the resources and assistance necessary for the completion of this work.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of interest:\\u0026nbsp;\\u003c/strong\\u003eNone \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAbdElgawad, H., Zinta, G., Hamed, B.A., Selim, S., Beemster, G., Hozzein, W.N., Wadaan, M.A., Asard, H. and Abuelsoud, W., 2020. Maize roots and shoots show distinct profiles of oxidative stress and antioxidant defense under heavy metal toxicity. \\u003cem\\u003eEnvironmental Pollution\\u003c/em\\u003e, \\u003cem\\u003e258\\u003c/em\\u003e, p.113705. DOI: 10.1016/j.envpol.2019.113705\\u003c/li\\u003e\\n\\u003cli\\u003eAdamczyk-Szabela, D. and Wolf, W.M., 2022. The impact of soil pH on heavy metals uptake and photosynthesis efficiency in Melissa officinalis, Taraxacum officinalis, Ocimum basilicum. \\u003cem\\u003eMolecules\\u003c/em\\u003e, \\u003cem\\u003e27\\u003c/em\\u003e(15), p.4671. https://doi.org/10.3390/molecules27154671\\u003c/li\\u003e\\n\\u003cli\\u003eAli, S., Chaudhary, A., Rizwan, M., Anwar, H.T., Adrees, M., Farid, M., Irshad, M.K., Hayat, T. and Anjum, S.A., 2015. Alleviation of chromium toxicity by glycinebetaine is related to elevated antioxidant enzymes and suppressed chromium uptake and oxidative stress in wheat (Triticum aestivum L.). \\u003cem\\u003eEnvironmental Science and Pollution Research\\u003c/em\\u003e, \\u003cem\\u003e22\\u003c/em\\u003e, pp.10669-10678. DOI: 10.1007/s11356-015-4193-4\\u003c/li\\u003e\\n\\u003cli\\u003eAPHA, 2005. Standard Methods for the Examination of Water and Wastewater, 21th ed. American Public Health Association, Washington, DC.\\u003c/li\\u003e\\n\\u003cli\\u003eAstolfi, S., Zuchi, S., \\u0026amp; Passera, C. (2005). Effect of cadmium on H+ ATPase activity of plasma membrane vesicles isolated from roots of different S-supplied maize (Zea mays L.) plants. \\u003cem\\u003ePlant Science\\u003c/em\\u003e, \\u003cem\\u003e169\\u003c/em\\u003e(2), 361-368. https://doi.org/10.1016/j.plantsci.2005.03.025\\u003c/li\\u003e\\n\\u003cli\\u003eBaker, A.J. and Walker, P.L., 1990. 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Effect of glycinebetaine on proline, water use, and photosynthetic efficiencies, and growth of rice seedlings under salt stress. \\u003cem\\u003eTurkish Journal of Agriculture and Forestry\\u003c/em\\u003e, \\u003cem\\u003e34\\u003c/em\\u003e(6), pp.517-527. doi:10.3906/tar-0906-34\\u003c/li\\u003e\\n\\u003cli\\u003eChen, T.H. and Murata, N., 2011. Glycinebetaine protects plants against abiotic stress: mechanisms and biotechnological applications. \\u003cem\\u003ePlant, cell \\u0026amp; environment\\u003c/em\\u003e, \\u003cem\\u003e34\\u003c/em\\u003e(1), pp.1-20. DOI: 10.1111/j.1365-3040.2010.02232.x\\u003c/li\\u003e\\n\\u003cli\\u003eDotaniya, M.L., Das, H. and Meena, V.D., 2014. Assessment of chromium efficacy on germination, root elongation, and coleoptile growth of wheat (Triticum aestivum L.) at different growth periods. \\u003cem\\u003eEnvironmental Monitoring and Assessment\\u003c/em\\u003e, \\u003cem\\u003e186\\u003c/em\\u003e, pp.2957-2963. 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Amelioration of postharvest chilling injury in sweet pepper by glycine betaine. \\u003cem\\u003ePostharvest Biology and Technology\\u003c/em\\u003e, \\u003cem\\u003e112\\u003c/em\\u003e, pp.114-120. 10.1016/j.postharvbio.2015.07.008 \\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4695832/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4695832/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Contamination of arable land with potentially toxic heavy metals (PTHMs) is a critical global issue resulting from industrialization. To tackle this problem, a two-year pot experiment was carried out on Indian rice plants (Oriza sativa L.) using four different treatments of PTHMs at varying concentrations (T1: 5; T2: 10; T3: 20; T4: 40 mg/kg). The intent was to explore the impact of glycine betaine (GB) application on the plants' resilience and stress response. Findings indicated that exposure to PTHMs led to a significant increase in the accumulation of these metals and oxidative stress indices during the 2.5th and 4th month growth stages. However, when GB was applied to the soil, there was a decrease in the accumulation of PTHMs and oxidative stress indices. This was attributed to the enhancement of antioxidant enzyme activity and metabolic functions in the rice plants. Interestingly, the study revealed that Indian rice plants had the highest accumulation of Fe, followed by Mn, Zn, Cr, Ni, Pb, Cd, and Cu in their roots. When exposed to PTHMs, the roots exhibited higher metal uptake compared to the shoots and seeds, with uptake levels rising with increasing concentrations of PTHMs. Notably, under the highest PTHMs stress (T4), the content of Cr and Pb in the roots, shoots, and seeds decreased significantly. This reduction was even more pronounced when treated with 400 mM GB, showcasing decreases of up to 33.3%, 36%, and 89.3% in Cr content, and 36.4%, 55%, and 80.5% in Pb content, respectively.\\nKeywords: Amelioration; Oryza sativa; Heavy metals; Glycine betaine; Antioxidant\",\"manuscriptTitle\":\"Enhancing Indian Rice Plant resilience to toxic heavy metals with Glycine betaine as a modulator.\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-07-31 12:30:02\",\"doi\":\"10.21203/rs.3.rs-4695832/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"9ead07f1-2f32-469d-a6f5-230758892210\",\"owner\":[],\"postedDate\":\"July 31st, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-08-20T07:10:52+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-07-31 12:30:02\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4695832\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4695832\",\"identity\":\"rs-4695832\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}