Evaluation of the saline tolerance of gamma-ray-induced mutant lines of rice (Oryza sativa L.) under field conditions

Evaluation of the saline tolerance of gamma-ray-induced mutant lines of rice (Oryza sativa L.) under field conditions | 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 Article Evaluation of the saline tolerance of gamma-ray-induced mutant lines of rice (Oryza sativa L.) under field conditions Leila Bagheri, Sara Saadatmand, Neda Soltani, Vahid Niknam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1793728/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 Rice is highly sensitive crop to salt stress, especially at reproductive stage, and obtaining salt-tolerant genotypes is key for the rice production in salt-affected soils. In this study, ten mutant lines (obtained through gamma ray and pre-selected for their tolerance to salinity) accompanying by three Iranian traditional rice varieties (TRVs) were evaluated for biochemical and morpho-physiological parameters related to salt tolerance under saline field condition. The experiment was conducted as a randomized complete block design with three replications during two growing seasons. The salt tolerant mutant lines exhibited higher proline accumulation, K + concentration, and activities of antioxidant enzymes, and lower Na + concentration, Na + /K + ratio, malondyaldehide (MDA) content that led to higher grain yield and quality under saline field condition, as compared with TRVs. Higher yield in these tolerant mutants was associated with more number panicle per hill, number filled grain per panicle, and 1000-grain weights. Results of correlation as well as principle component analysis also indicated that grain yield had high correlated with proline content, Fv/Fm index, stomata conductivity, SOD activity, MDA content, concentration of sodium (Na + ) and Na + /K + ratio at the reproductive stage under saline field condition, indicating that indirect selection according to these physiological criteria would be more effective approach for screening salt tolerance. According to these results, mutant lines 13 − 3, 32 − 18 and 22 − 1 indicated superiority in the grain yield and agronomical traits such as early- maturity and dwarfism, and also desirable grain quality that are promising mutant lines for cultivation in salt-affected coastal areas. Oryza sativa saline field mutant lines physiological criteria grain yield Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Salinity is one of the main abiotic stresses that is becoming a significant menace for crop productivity and quality in worldwide 1 . It is estimated that salt stress influenced 5% of the total cultivated area in the world 2 , predictably increasing up to 21%, by the year 2050 3 . In Iran, the problem of soil salinity (about 34 million ha) is widely distributed in arid and semi-arid areas as well as north region as the consequence of primary (natural) process or anthropogenic activities 4 . Salinity impairs the growth and development of plants through salinity-induced water stress which takes place in a short period, brings about dehydration symptoms to appear in the plant and inhibition of cell extension 1 , 5 . Plants subjected to long term salinity (over days or even weeks) undergo cytotoxicity of salt ions [like chloride (Cl − ) and sodium (Na + )] and nutrient availability imbalance, especially in the shoots, that cause a range of metabolic problems, precocious senescence, and afterwards cell death 6 , 7 . Additionally, salinity is typically lead to increasing production of reactive oxygen species (ROS) causing oxidative stress in plants 1 . Tolerance to this conditions, beside anatomical and morphological plasticity, is raised by a complex of physiological and molecular mechanisms such as rapid decrease in stomatal conductance, restricting influx and translocation of toxic ions, vacuolar compartmentation of toxic ions, compatible solutes synthesis, and the involvement of antioxidant defense system and plant hormones 1 , 5 . Although the above strategies have been revealed in many types of plants, these adaptive features in most commercially grown crops, such as rice, inefficient to cope with the salinity and are usually sensitive to given levels of salt stress 8 . Rice ( Oryza sativa L.) is the most important carbohydrate crop providing a staple food to over three billion consumers in the world 9 , but this crop very susceptible to salt stress, especially at the seedling and reproductive growth stages, that negatively influenced its yields and yield components even when levels of salt is very low 8,10−12 . For most cultivated varieties of rice, 3.0 dS m 1 (EC) is a threshold level of salinity and rice productivity reduce 12% for each unit (dS m − 1 ) rising in salinity from this level 13 . The average salinity levels (EC) ranged from 7.2 to 8 dS m − 1 resulting in 50% yield decrease of rice 14 , 15 . Evaluation of salt tolerance in rice is complex due to the variation in salinity sensitivity during its growth cycle 8 , 16 . Generally, rice has been reported to be sensitive during early seedling and flowering/reproductive stages, but is comparatively tolerant to salinity stress during germination, active tillering, and grain filling 8 , 17 . However, different varieties of rice can differ in their tolerance to salinity during these phonological stage 8 . Therefore, two separate steps including screening salinity tolerance of seedling under controlled conditions from large segregating populations and evaluating promising lines to salinity tolerance, preferably under the field conditions, at the reproductive stage, has been suggested for screening of salinity tolerance in breeding programs 8 , 18 . Using yield and yield components has been considered as a reliable and efficient method for screening salt tolerance 8 . Furthermore, the use of physiological criteria accompanying yield may be considered as an effective approach for screening salt tolerance genotypes. A number of strategies have been employed to diminish the effect of salinity stress on rice. Among that, crop improvement is one of the most important strategy to develop salt tolerant varieties. For this, sufficient variation plays a key role to create and identify salt tolerant genotypes. Induced mutation, especially by gamma ray, is an important supplementary approach to creating variation within a crop variety 19 . This approach has been successfully employed in the rice for genetic improvements with high-yield, dwarf, early-maturity, and other agronomic traits 20 – 22 . Therefore, creation of new mutant from existing landraces rice can be useful for screening new varieties that are salinity tolerant. The purpose of the present study was the evaluation of the morphological and physiological responses of gamma-ray-induced mutant lines of rice at reproductive stage as well as the association between these consequences with yield and grain quality under saline field condition. Finally, the selected promising mutant lines can be used directly as a new cultivar or indirectly as a new source of germplasm in breeding. Results Morphological and phenological parameters There were significant differences (P<0.01) among mutant lines for plant height, days to flowering, and panicle length under saline field condition. The plant height were significantly lower in 32-26, 32-14, 32-18 and 32-15 mutant lines compared with their corresponding origin grown under saline field condition. However, the minimum value (121 cm) of plant height was observed in 32-18 that evaluated as short rice plant category (Table 3). The results of days to 50% flowering showed decreasing trend in all the mutant lines compared to their parent varieties. The lowest value (68 day) of days to 50% flowering was observed in 13-3 mutant line that no significant differences from 11-16, 11-17, and 12-6 (Table 3). The panicle length was significantly higher in 13-3 and 22-1 mutant lines than the values measured in the corresponding parental plants under salinity. Among TRVs, Anbarbo exhibited significantly higher plant height, days to 50% flowering, and panicle length compared to Tarom and Hasani varieties (Table 3). Yield and Yield components There was a significant variation (P<0.01) among mutant lines for the number of panicles per hill, the number of filled and total grains per panicle, weight of 1000 grains, and grain yield. The number of panicles per hill in 11-17, 13-3, 22-1, 32-18, and 32-26 of mutant lines were significantly higher than their corresponding origin grown under saline field condition (Table 3). Some of mutant lines (13-3, 32-16, and 32-18) exhibited higher values of filled grains per panicle compared to their parent varieties, meanwhile 11-16 mutant line indicated lower value than the origin. 13-3 and 32-18 mutant lines had significantly higher value of the weight of 1000 grains as compared to their corresponding TRVs (Table 3). All of mutant lines, except 11-16, exhibited significantly higher grain yield under saline field condition, as compared to their parents. The maximum grain yield (7079 kg ha -1 ) was obtained in 13-3 mutant line that exhibited two time over than its origin (Tarom) under saline field condition (Table 3). Physiological and biochemical parameters The chlorophyll contents were significantly higher in 11-16, 11-17, 13-3, 22-1, 32-18, and 32-15 of mutant lines than TRVs (Fig 2 A). The values of Fv/Fm index were recorded in the ranges of 0.63-0.64 and 0.75-0.82 under saline field condition for TRVs and mutant lines, respectively. The Fv/Fm was significantly higher in all the mutant lines than TRVs (Fig 2 B). The majority of mutant lines exhibited higher values of stomata conductivity compared to TRVs, meanwhile some mutant lines such as11-16 and 12-6 indicated lower stomata conductivity than their origin (Fig 2 C). The highest value of stomata conductivity was observed in 13-3, followed by 22-1 and 32-15 mutant lines (Fig 2 D). The proline contents were significantly higher in mutant lines compared to TRVs. The highest value of proline was accumulated in 13-3 line that indicated 138% enhancement compared to its origin (Fig 2 E). TRVs contained higher levels of MDA than mutant lines under saline condition. The minimum level of MDA was detected in 13-3 mutant line that indicated 44% reduction compared to its origin. Total protein content accumulated in 32-18 mutant line was significantly higher than TRVs. Among TRVs, Anbarbo exhibited higher levels of MDA and protein compared to Tarom and Hassani varieties (Fig 2 F). There was a significant variation (P<0.01) among mutant lines for the activities of CAT, POX, and SOD enzymes. All of mutant lines, except 11-16, exhibited significantly higher CAT activity than their corresponding origin grown under saline field condition. Maximum activity of CAT was observed in 32-18, followed by 22-1 mutant lines (Fig 3 A). POX activity of 11-17, 13-3, 22-1, 32-26, 32-14, 32-18, and 32-15 was significantly higher than TRVs. The highest activity of POX was observed in 32-14 line that indicated 135% enhancement compared to its origin cultivar (Fig 3 B). All of mutant lines exhibited significantly higher activities of SOD compared to TRVs. The maximum SOD activity was observed in 13-3 mutant line that exhibited nearly two times more than its origin (Tarom) under saline field condition (Fig 3 C). The Na level and Na:K ratio were much higher in TRVs than all mutant lines under saline condition. The levels of Na accumulated of 32-18, 32-16, 22-1, 22-5, 13-3, and 11-17 mutant lines were 46%, 44%, 42%, 41%, 40%, and 41%, respectively, lower than in TRVs, while in 11-16, 12-6, 32-14, and 32-15 mutant lines Na accumulation was around 18% lower than in TRVs (Fig 3 D). The levels of K were significantly higher in 11-17, 12-6, 13-3, 21-5, 22-1, 32-14, and 32-26 of mutant lines than their corresponding origin grown under saline field condition (Fig 3 E). Grain quality There were significantly differences (P<0.01) among mutant lines for all investigated aspects of grain quality. Maximum milling quality was observed in 13-3 (70.03%), followed by 32-18 (69.66%), that showed significant difference from TRVs. the lowest value of full grain was observed in Anbarbo cultivar (67.13%) that exhibited significant difference from others studied genotypes. The levels of grain elongation were significantly higher in 11-16 and 11-17 of mutant lines than their corresponding origin. However, some mutant lines such as 21-5, 32-26, 32-14, 32-18, and 32-15 indicated lower grain elongation than their origin TRVs. The percentage of amylose of 11-16, 11-17, 13-3, 32-26, and 32-14 mutant lines was significantly higher than their origin TRVs. The maximum value of gelatinization temperature (6.35) was observed in Hassani variety that exhibited significant difference from others studied genotypes. Furthermore, 32-26 mutant line exhibited higher value of gelatinization temperature compared to its origin TRV (Fig 4). Associations between traits across the mutant lines The results of correlation analysis between different traits with grain yield are presented in Fig 5. Among the agronomy traits, number of panicles per hill (NPH), weight of 1000 grains (W 1000) exhibited a high and positive correlation with grain yield under saline filed condition. Regarding to physiological and biochemical traits, grain yield had a significant and positive association with SPAD, stomatal conductivity (SC), Fv/Fm index, proline content, SOD activity and potassium (K) concentration. Furthermore, MDA content, Na concentration and Na/K ratio had a significant and negative correlations with grain yield under saline field condition. It showed that milling recovery (MR) and full grain percentage (FGP) had a high and positive correlation with grain yield. The PCA helped in identifying those traits that best separated the mutant lines studied for their tolerance to salinity. The first two principal component explained 65% of total variation. The biplot (Fig. 6) according to PC1 and PC2 indicated the distribution of the mutant lines. PC1 had positive correlation with yield, NPH, PL, TNGP, FGP, W 1000, Proline, Fv/Fm, SC, SPAD, Pr, SOD, CAT, POD, K, MR, and Amylose. Therefore, PC1 was named as the yield and tolerance to salinity component. Also PC1 was observed positive for the mutant lines including 32-18, 13-3, 22-1, 11-17, 32-26, 32-14, 21-5. PC2 had high correlation with MDA, Na, Na:K ratio, PH, DF and GT. Thus, PC2 was presented as component of sensitivity to salinity. Anbarbo, Tarom, Hasani, 32-15, 12-6 and 11-16 were categorized as the sensitive ones (Fig 7). Furthermore, the biplot figure indicated a high and positive correlation (an acute angle) between grain yield with NPH, W 1000, Proline, Fv/Fm, SC, SOD, and FGP that were extremely consistent with the numerical Pearson correlation coefficients (Fig. 6). Grouping of the mutant rice genotypes Cluster analysis according to morpho-physiological, biochemical and grain quality data using Euclidean distance coefficient grouped the mutant lines and parent ̛s plants into two main clusters. The first cluster included Tarom, Hasani, Anbarbo, 11-16, 21-5 and 12-6. Lines of 32-26, 32-15, 32-14, 11-17, 13-3, 22-1, and 32-18 were clustered in the second group. Dendrogram using ward clustering method clearly separated the mutant lines based on their tolerance. The first cluster had the sensitive varieties such as Tarom, Hasani and Anbarbo, while the second cluster included the mutant lines with the highest tolerance (Fig 7). Discussion Like most plants, rice responses to salinity stress involved alterations in various physiological and biochemical processes. These alterations have been considered as a major adaptation mechanisms to salinity tolerance in rice plant 8 . In this study, the pattern of these changes and its association with grain yield were investigated in reproductive stage of new derived mutant lines and TRVs of rice plants under saline field conditions. Genotypes differed significantly for morpho-physiological aspects, grain yield, and grain quality indicating a considerable variation of salt tolerance in the mutant lines and their parents. The effect of salinity on plants is commenced by the osmotic effect characterized by lowered osmotic potential followed by later ionic effect leading to ion toxicity 1 , 6 . The accumulation of ions of salts in the soil environment increased Na + concentration in the cytosol by passive influx 33 through K + transporters and then symplastic transport to the shoot 34 . Toxic concentrations of this ion creates cellular nutrient ion imbalance and can ultimately impact yield and performance of plant 1 . The results of biplot analysis showed that concentration of sodium (Na + ) and Na + /K + ratio in the leaves had a high and negative association with yield and yield components (Fig. 6 ). Exclusion Na + uptake by roots is one of the most important mechanisms of salinity tolerance in plants, which result in maintaining low Na + concentrations in the shoot 1 , 35 . In this study, The Na + concentration and Na + /K + ratio was much higher in TRVs than all mutant lines under saline condition (Fig. 3 ). In both Indica and Japonica varieties of rice, the concentration of sodium ion in the leaves associated to the salinity tolerance level, thereby salt sensitive cultivars accumulate more Na + in shoots and leaves than salt tolerant ones 15,36−38 . Accordingly, several previous researches revealed that low cytosolic Na + /K + ratio is necessary to preserve an appropriate ionic homeostasis 8 , 39 , 40 which result in improving photosynthesis and plant growth under salinity stress condition 1 , 41 . Therefore, Na + /K + ratio can be employed as a standard reliable criterion for screening salt tolerant genotypes in rice 15 , 40 , 42 . In this research, there was a high and negative correlation between grain yield and Na + /K + ratio plus Na + concentration of leaves of rice under saline condition (Fig. 5 ). Based on these criteria, some of mutant lines such as 32 − 18, 32 − 16, 22 − 1, 22 − 5, 13 − 3, and 11–17 accumulated less Na and maintained low Na+/K + ratio that exhibited more tolerance to salinity stress compared to TRVs (Fig. 3 ). Recently, other physiological parameters have been proposed as alternative criteria for evaluating and screening rice genotypes for salt tolerance 15 . Chlorophyll is considered to be an initial signal of responses in plants under salt stress 43 . The chlorophyll loss in the leaves is explained by the impairment of its biosynthetic pathways and also, hydrolysis of chlorophyll by chlorophyllase in salinity conditions 1 indicating that reduction in chlorophyll content can be applied as a stress indicator 44 . The chlorophyll reduction under salinity condition was more pronounced in the salt sensitive rice cultivars compared to the salt tolerant ones 15 , 38 . In this study, the chlorophyll contents were significantly higher in some of mutant lines compared to TRVs (Fig. 2 ). Furthermore, the grain yield positively associated with chlorophyll content under saline condition (Figs. 5 and 6 ), suggesting that tolerant mutant lines maintaining more chlorophyll in leaf at reproductive stage. Maximum quantum yield (Fv/Fm) value provides an appropriate approach to the evaluation of stress-induced damages in photosynthesis process 35 , 45 . For unstressed leaves, the approximate optimal value of Fv/Fm is ranged of 0.79 to 0.84, with lowered values indicating plant stress 46 . In this research, the Fv/Fm ratio in TRVs significantly reduced than optimum range, while in some mutant lines ones' decrease in the proportion was not found under saline conditions (Fig. 2 ). Furthermore, the result of correlation and biplot analyses exhibited a high and positive correlation between Fv/Fm index and grain yield of rice under salinity stress (Figs. 5 and 6 ), suggesting that Fv/Fm can be used for rapid screening salt tolerant lines. In this study, the majority of mutant lines exhibited higher values of stomata conductivity compared to TRVs (Fig. 2 ), the reduction of stomatal conductivity in salt-sensitive varieties can be due to the lower K + and the greater Na + accumulation in stoma guard cells 47 . The biplot figure illustrated a high and positive correlation (an acute angle) between K and stomata conductivity, while it had a negative correlation with Na concentration. Osmotic adjustment in plants is achieved via over accumulation of compatible solutes such as proline 1 , 6 , 8 . Proline accumulation in plants has been revealed to play adaptive roles in storage of nitrogen and carbon 48 , osmoregulation 49 , ROS scavenging 50 , and prevent K + efflux from root 51 under salinity condition. Although the proline accumulation can differ considerably in response to stresses, there is no obvious relationship among the accumulation of proline and ability of plant to cope with stress 12 , 52 . In rice, some reports stated that proline accumulation was a reaction to stress rather than an indicator of the tolerance 12 , 53 . However, others studies suggested that proline was a plant criteria associated with tolerance to salt stress 8,54−56 . This study clearly revealed that proline accumulation correlated positively with grain yield plus yield components and negatively with Na plus Na/K ratio (Figs. 5 and 6 ). In some mutant lines, the mounts of proline were more than 1.5 folds compared to TRVs (Fig. 2 ). In agreement with this results, previous researches showed that salt tolerant rice cultivars accumulated greater amounts of proline compared to salt sensitive once 55 , 56 . Salinity stress induced a cascade of reactive oxygen species (ROS) production leading to oxidative stress in plant tissue, causing membrane demolition due to peroxidation of lipids. Malondialdehyde (MDA) is the main product of the decomposition of unsaturated fatty acids in biological membranes, and it can be used to evaluate the degree of lipid peroxidation and cell membrane injury 57 . The strong negative correlation was observed between MDA level and grain yield (Fig. 5 ). Also, the results of biplot analysis showed that MDA content had a high and positive correlation with Na concentration plus Na/K ratio in the leaves (Fig. 6 ). Previous reports showed that MDA content accumulated greater in salt sensitive rice cultivars under salinity stress compared to salt tolerant cultivars 15 , 38 . In this study, the most of mutant lines exhibited less MDA levels compared to TRVs (Fig. 2 ), suggesting more tolerance to saline condition in those mutant lines. Scavenge and detoxify ROS by antioxidant defense system protect the cells from oxidative injury and known as an important mechanism of salt tolerance in the plants 58 – 60 . The antioxidant enzymes activities of mutant lines differed significantly in response to saline field condition compared to TRVs. In this study, SOD, CAT and POX activities of mutant lines such as 13 − 3, 22 − 1, 32 − 18, and 32 − 14 significantly increased compared to TRVs (Fig. 3 ). In agreement with this results, previous reports supported that the activity of antioxidant enzymes increased in salt-tolerant rice genotypes with elevation of salt levels, as compare with salt-sensitive genotypes 61 – 64 . SOD catalyzes the disputation of superoxide to hydrogen peroxide and oxygen and is the first enzyme during the ROS detoxification process 65 . The higher activity of SOD was observed in all mutant lines compared to their origin. In line with these results, several studies have shown that salt tolerant plants exhibited more SOD activity under salinity stress 66 – 68 . Further, the effectiveness of SOD largely determines by the role of other antioxidative components such as CAT and peroxidases to eliminate of hydrogen peroxide 69 . In this study, higher activities of CAT and POX were observed in some mutant lines including 13 − 3, 22 − 1, 32 − 14, and 32 − 18 than TRVs (Fig. 3 ). This pattern of changes in activities of antioxidant enzymes may reflect that the harmful effects of ROS in mutant lines were generally kept at balanced levels by a synchronized action of antioxidant enzymes led to reducing membrane lipid peroxidation and keeping the integrity of membranes and stabilizing enzymes and proteins. The quality of rice grain may be affected by salt-induced changes in the vegetative growth stage and the physio-biochemical processes during the grain filling stage 70 . Quality in rice grain is considered from the viewpoint of milling quality, grain appearance, and cooking characteristics 71 . The milling quality is one the most important criteria of rice grain quality and define as the ability of rice grain to stand milling without undue breakage 72 . Khush et al. 73 stated that about 70% milled rice was obtained from a rough rice. The results of this study showed that some of the mutant lines such as 13 − 3 and 32 − 18 exhibited about 70% milling quality. However, the percentage of milling recovery was less than 70% in TRVs and other mutant lines under saline condition (Fig. 4 ). Furthermore, the results of correlation analysis showed that the milling recovery had a positive association with grain yield under saline condition (Figs. 5 and 6 ). The head-rice (full grain) recovery of rice grain may varied between ranges 25% of low to 65% of high 73 . In this study, all of investigated genotypes exhibited high values of full grain (Fig. 4 ). Further, some of mutant lines such as 13 − 3 and 32 − 18 exhibited the values (67.13% and 66.76%, respectively) higher than the ranges defined by Khush et al. 73 . Also, full grain percentage exhibited a high and positive correlation with grain yield under saline field conditions (Figs. 5 and 6 ), suggesting this character may influence by the amount of genotype yield. Amylose content is the most important chemical characteristics that determines the hardness quickly after cooling 74 . The rice with high amylose content (> 25%) is less sticky on cooking. Intermediate amylose rice (20–25%) is the preferred type in most rice-growing areas of the world 74 . Based on previous studies, the impacts of salinity stress on amylose or starch variation of rice grain were depend on salinity intensity or genotype. Rao et al. 75 reported that amylose content of rice grain decreased at 8 dS/m or higher salt levels. In other studies, 7–11% reduction in amylose content was observed at 40 mM NaCl 76 , 77 . In this study, EC of soil in experimental field was ranged 6.4 to 8.1 dS/m during transplanting stage to harvest time (Table 2 ). In this condition, the percentage of amylose in some of mutant lines such as 11–16, 11–17, 13 − 3, 32 − 26, and 32 − 14 was significantly higher than their origin TRVs (Fig. 4 ). The physical cooking properties of rice are intimately related to the gelatinization temperature (GT) 32 . Rice varieties with a high GT need more water and time to cook than those with a low or intermediated GT. Starchy endosperm is rated visually according to a 7-point numerical (1 pasty and 7 well separated) scale 30 . In this research, all the mutant lines had intermediate GT (between 3 and 4 scale). Increase in length of rice grain is a desirable quality trait 78 . In this study, grain elongation ratio in all the mutant lines and also their parents was highly desirable (1.9 to 2.1), so that they expand in size upon cooking (Fig. 4 ). Mutation breeding, by using gamma radiation, has been showed as being an effective approach to obtain new rice genotypes with improved features. Also, this research reveal that it is an excellent method to improve salinity tolerance in TRVs. Based on cluster analysis (Fig. 7 ), mutant lines in second group showed better performance in saline filed condition via high values of grain yield and yield components, chlorophyll content, Fv/Fm index, stomata conductivity, proline content, K concentration, but had low values of Na + concentration, Na + /K + ratio and MDA content, as compared to TRVs. Higher yield in these tolerant mutants was associated with more number panicle per hill, number filled grain per panicle, and 1000-grain weights (Fig. 5 ). Conclusion The results of this study suggested that large genotypic variation was observed among mutant lines and TRVs for most of the investigated traits. Some of mutant lines including 13 − 3, 32 − 18 and 22 − 1 maintained a relatively higher photosynthetic capacity, preserving cells constituents from oxidative damage by improved the antioxidant defense system, compatible solutes synthesis such as proline, and restricting the entry of toxic ions under saline field condition that led to higher yield and yield components than TRVs. Results of correlation as well as principle component analysis indicated that grain yield had high correlated with proline content, Fv/Fm index, stomata conductivity, SOD activity, MDA content, Na + concentration, and Na + /K + ratio at the reproductive stage under saline field condition, indicating that indirect selection based on these physiological criteria would be more effective for screening salt tolerance. Materials And Methods Plant materials Plants of three Iranian traditional rice varieties (TRVs) and ten mutant lines, derived from irradiation of seeds of TRVs, were used as plant materials in this experiment after screening in situ to identify those mutants more tolerant to salinity. These mutant lines produced through gamma irradiation (200-300 Gy) in TRVs of Tarom, Anbarbo, and Hasani and screened and selected up to six generations (M 6 ) based on tolerant to salinity under saline field conditions. The mutant names and their originality are summarized in Table 1. Site description The experiment was conducted in the saline paddy field at Fereydunkenar, Mazandaran province; Iran (36.6730 ◦ N, 52.5369 ◦ E), during growing season of 2018 and 2019. The total field size was 20 * 30 m and the study was arranged in a randomized complete block design with three replications. The soil type was loam clay silty, characterized by 5.04 % organic matter (O.M), 130.55, 0.93, 27.50, and 161.30 meq L -1 of sodium (Na), potassium (K), calcium plus magnesium (Ca+Mg), and chloride (Cl), respectively. Thirty-day-old seedlings of mutant lines and TRVs raised in a nursey were transplanted into saline field in April of both years. Plot size was 5.0 x 2.0 m 2 and with 25cm x 25cm distance between rows and plants. For each replicate, seedlings of each mutant line were sown in 8 rows and 20 plants in each row. The space among two adjacent plots was 1 m. The plots received general maintenances including fertilization, irrigation, weed control, and etc. All fertilizers were applied during final land preparation excluding urea. Urea was applied at three equal installments at 7, 30 and 55 days after transplanting. The plots were kept saturated with irrigation until maturity and three hand weeding were made during growing season. The climate is wet temperate with average annual maximum temperature of 21.5 °C, average annual minimum temperature of 13.7 °C, and average annual precipitation of 870 mm. The monthly variations in local humidity, temperature and precipitation during experimental time are presented in figure 1. Physico-chemical characters of the soil Twenty soil samples (0-30 cm) were collected to determine the physical and chemical properties including the electrical conductivity (EC) and pH in vegetative, reproductive, and ripening stages of rice growth. Also, the water above soil surface was randomly harvested for determination surface water salinity and pH by using EC and pH meters (INDEX, Innovation Beyond 2000, USA, model ID1040 for EC and ID1000 for pH), respectively. Physico-chemical properties of soil of the field during growth period are showed in Table 2. Morphological and phenological parameters Plant height : Shoot height were measured from 10 randomly selected mutant plants per plot at booting stage as height from ground level to tip of panicle excluding the owns. Day to heading : days to 50% heading was calculated as the number of days from the date of sowing until when 50% of plants in each plot produced panicles and recorded through visual observation. Panicle length : Length of the panicle was measured from the node to the tip of the main panicle of randomly selected 10 competitive plants in each plot at the time of maturity. Yield and Yield components At the time of harvest, total grain yield, number of panicles per hill, filled and unfilled grains per panicle, and 100-grain weight were evaluated. Number of panicles was measured from 10 randomly selected hill per plot. Filled and unfilled grains per panicle was recorded from randomly selected 10 main panicles per plot. For 1000-grain weights, thousand grains of each plot were randomly selected after harvesting and then weighed. Grain yield was recorded by harvesting from 1 m 2 area and then converting it to get final yield in kg ha −1 at 14% moisture. Physiological and biochemical parameters At reproductive stage, mutant lines were analyzed for chlorophyll content, the efficiency of photosystem II, Stomatal conductance, proline content, lipid peroxidation intensity determined by the malondialdehyde (MDA) content, the activities of antioxidant enzymes, and elements concentration. Measurement of chlorophyll content Leaf chlorophyll content was measured on the fully expanded leaves of the four randomly selected plants per plot using chlorophyll meter (SPAD-502 Chlorophyll Meter, Minolta Camera Co. Ltd., Japan). The three SPAD readings were taken on each plant and averaged to provide a single reading per plant. The efficiency of photosystem II Maximum photochemical efficiency of photosystem II (Fv/Fm) parameter was measured with a portable Photosynthetic Efficiency Analyzer (Handy PEA, Hansatech Instruments Ltd, Norfolk, UK) in the fully expanded leaves at midday (11:00 A.M to 13:00 P.M, solar time). The Fv/Fm index were measured after dark adaptation of leaves for 30 min. Stomatal conductance assay Mature leaves, from four randomly selected plants of each plot, were used in gas-exchange measurements. The measurements were recorded using Leaf Porometer (Model SC -1 ; Decagon Devices, Inc 2365 NE Hopkins Ct. Pullman, WA 99163 USA) at 9.00 a.m. to 11.00 pm. During measurement time, temperature of leaf was ranged 28 to 31.2 C◦ and relative humidity was 80% at the leaf area. Proline content Proline was extracted from 0.5 g of fresh sample in 10 mL of 5-sulphosalicylic acid (3%, w/v) and quantified using the acid ninhydrin procedure described by Bates et al. 18 . Light absorbance of extracts was recorded at 520 nm with a spectrophotometer (Model 6705 uv/vis. JENWAY). Free proline concentration per gram of fresh weight (FW) was determined using L-proline as standard. Lipid peroxidation intensity The amount of malondialdehyde (MDA) as a product of lipid peroxidation was measured according to the method described by. The absorbance of the supernatant was assayed by Heath and Packer 23 a spectrophotometer (Model 6705 uv/vis. JENWAY) at 532 and 600 nm and was reported as μmol MDA g −1 FW using the extinction coefficient of 155 mM −1 cm −1 . Antioxidant enzymes activities Leaf tissues of 0.2-0.29 were homogenized in 10 ml of 50 mM potassium phosphate buffer (pH 6.5) containing 10% glycerol. The homogenate was centrifuged at 10.000 rpm at 4( ◦ C) for 5 min. The supernatant was used to measure total protein content based on Bradford 24 and for determination of enzyme activities of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD). All assays were done using a spectrophotometer (Model 6705 uv/vis. JENWAY). SOD (EC 1.15.1.1) activity was determined by measuring its ability to inhibit the photo-reduction of nitro blue tetrazolium (NBT) based on the method of Giannopolitis and Ries 25 . The reaction mixture contained 50 mM potassium phosphate buffer (pH 7.0), 13 mM methionine, 75 µM NBT, 0.1 mM EDTA, 15 µL Riboflavin, and 50 µL of the enzyme extract. The reaction was allowed to proceed for 15 min under light supplied by two fluorescent lamps (20W), and then the tubes were covered with aluminum foil to stop the reaction. Absorbance of the reaction mixture was read at 560 nm. POD (EC 1.11.1.7) activity was assayed by the oxidation of guaiacol in the presence of H 2 O 2 . The increase in absorbance was read at 470 nm for 2 min 26 . The reaction mixture contained 20 µL of enzyme extract, 100 µL of 35 mM H 2 O 2 , 880 µL of 10 mM guaiacol, and 50 mM potassium phosphate buffer (pH 6.5). CAT (EC 1.11.1.6) activity was calculated according to the method of Luck 27 . The composition of H 2 O 2 Was followed as a decline in the absorbance at 240 nm within 120 s. 20 µL of the enzyme extract and 980 µL of 50 mM potassium phosphate buffer (pH 7.0) contained 35 mM H 2 O 2 was used as the reaction mixture. Sodium (Na) and Potassium (K) concentrations Plant material was oven-dried (70 ◦ C, 48 h) and finally ground for analysis. The samples (1g) were reduced to ashes at 550 C◦ for 5 hours. The ashes were digested with 2N hydrochloric acid (HCl), and then to drive off HCl the supernatant was heated at 90°C. After that, the supernatant was diluted (to the volume 100 ml) with deionized water. The amount of Na + and K + were measured using a flame photometer (Model PEP7, Jenway. Dunmow, UK) and quantified based on a standard curve 28 . Grain quality assays After harvesting, 400 g paddy from each plot was used to measure grain quality. Amylose content (AC) was determined using Juliano 29 and gelatinization temperature was estimated according to method of Little et al. 30 . The method of Azeez et al. 31 was used for evaluating the degree of elongation. Milling yield was calculated as a percentage from a unit of rough rice 32 . Data analysis The experiment was designed according to a complete randomized block scheme with three replicates during 2018 and 2019. The obtained data from two years were subjected to the combined analysis of variance to assess the effect of genotype and genotype Í year interaction using SAS statistical software (version 9.1; SAS institute, Cary, NC, USA). The mean values were compared through least significant difference (LSD) test (P<0.05). Stepwise multiple linear regression was used to identify the variables (as the independent variables) accounting for the majority of grain yield (as the dependent variable) using the IBM SPSS Statistic 22 software. The Pearson’s correlations coefficients between traits were also calculated using SPSS software. Hierarchical clustering of genotypes into similar groups was performed using the Ward method based on squared Euclidean distances for quantitative and qualitative variables using SPSS 22 software. A genotypeÍtrait (GT)- biplot analysis was performed to reduce the multiple dimensions of data space using Statgraphics centurion XVl software and plotting the first two symmetrically scaled principal components (PC) for the average tester coordinate and polygon view of the biplot. Declarations Data availability All data generated or analyzed during this study are included in this published article and its supplementary information files. Acknowledgments The authors are thankful to the Nuclear Science and Technology Research Institute of Iran for providing the necessary facilities for carrying out this experiment. Authors’ contributions L.B. was the proposer and executor of the project, and also wrote the draft. S.S. reviewed and edited the draft. N.S. analyzed the data. V.N. was a collaborator in the project. All authors commented on previous versions of the manuscript and all authors read and approved the final manuscript. Competing interests The authors declare no competing interests. Correspondence and requests for materials should be addressed to S.S. We confirm that all the experimental research and field studies on plants (either cultivated or wild), including the collection of plant material, complied with relevant institutional, national, and international guidelines and legislation. All of the material is owned by the authors and/or no permissions are required. References Isayenkov, S. V & Maathuis, F. J. M. Plant salinity stress: many unanswered questions remain. Front. Plant Sci. 10 , 80 (2019). Sheng, M. et al. Influence of arbuscular mycorrhizae on photosynthesis and water status of maize plants under salt stress. Mycorrhiza 18 , 287–296 (2008). Yadav, R. S. et al. Arbuscular Mycorrhizal Fungi (AMF) for sustainable soil and plant health in salt-affected soils. in Bioremediation of salt affected soils: an Indian perspective 133–156 (Springer, 2017). Qadir, M., Qureshi, A. S. & Cheraghi, S. A. 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Aromat. rices 3 , 15–28 (2000). Tables Table 1 . List of Iranian traditional rice varieties (TRVs) and mutant line used in this study TRVs and Mutant line Origin Mutagen doses (Gy) Tarom Iran - Hasani Iran - Anbarbo Iran - 11-16 Tarom 200 11-17 Tarom 200 12-6 Tarom 250 13-3 Tarom 300 21-5 Hasani 200 22-1 Hasani 250 32-14 Anbarbo 250 32-15 Anbarbo 250 32-18 Anbarbo 250 32-26 Anbarbo 250 Table 2 . Electrical conductivity (EC) and pH of soil and water of the experimental site at different growth stage of rice Growth stage 2018 2019 Soil Water Soil Water EC (dS.m -1 ) pH EC (dS.m -1 ) pH EC(dS.m -1 ) pH EC (dS.m -1 ) pH Vegetative 6.4 7.5 2.53 7.3 6.9 7.3 2.37 7.3 Reproductive 7.2 7.5 3.28 7.1 7.8 7.6 3.4 7.5 Ripening 7.7 7.6 3.6 7 8.1 7.5 3.65 7.2 Table 3 . Plant height, days to 50% flowering, panicle length, number of panicles per hill, number of filed grain per panicle, total grain per panicle, weight of 1000 grains, and grain yield of rice mutant lines and traditional rice varieties under saline field condition. Mutant lines Plant Height (cm) Days to 50% Flowering Panicle length (cm) Number of panicles per Hill Number of filed grain per panicle Total grain per panicle Weight of 1000 grains (g) Grain yield (Kg.ha -1 ) Tarom 146.66 ab 71.1 d 24.7 d 11.3 e 96.5 b-e 108.4 bcd 22.3 bc 3490.2 gh 11-16 137.61 bcd 70.4 de 25.3 bcd 12.5 e 76.1 f 91.8 d 21.8 c 3691.3 gh 11-17 137.07 bc 70.0 de 25.6 bcd 13.7 bcd 99.7 bcd 114.3 bcd 25.4 abc 5413.2 bc 12-6 134.96 b-e 70.6 de 25.3 bcd 12.9 cde 94.4 c-f 104.1 d 24.6 abc 4855.8 c-f 13-3 139.61 bc 68.6 e 26.9 ab 15.7 b 109.1 abc 120.9 bcd 27.3 a 7079.2 a Hasani 131.49 c-f 71.9 cd 24.9 cd 12.3 de 86.6 def 95.3 d 26.2 a 4006.7 fg 21-5 133.67 c-f 73.7 c 25.6 bcd 13.9 bcd 79.2 ef 91.2 d 24.7 abc 5300.5 bc 22-1 122.84 ef 71.7 cd 26.9 ab 14.9 b 105.0 a-d 114.4 bcd 26.7 a 5421.4 bc Anbarbo 157.72 a 79.6 a 27.1 ab 12.3 de 93.8 c-f 138.9 ab 22.5 bc 2796.0 h 32-26 131.45 c-f 75.9 b 26.6 abc 14.8 bc 114.2 ab 138.3 ab 25.5 ab 5143.7 cde 32-14 126.52 def 77.2 b 26.4 a-d 14.2 bcd 110.8 abc 136.1 abc 24.6 abc 4412.8 d-g 32-18 121.88 f 75.9 b 27.8 a 18.2 a 121.1 a 160.6 a 27.2 a 6087.2 bc 32-15 136.38 bcd 77.2 b 25.3 bcd 14.0 bcd 97.1 b-e 123.5 bcd 24.8 abc 4230.1 efg In each column, different letters represent significant difference at P≤0.05 according to LSD test. 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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-1793728","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":118431214,"identity":"464b2ed2-9365-4ad3-af6f-d94d836be295","order_by":0,"name":"Leila Bagheri","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Leila","middleName":"","lastName":"Bagheri","suffix":""},{"id":118431215,"identity":"05119dec-2ba2-48da-8b43-21bfdae37821","order_by":1,"name":"Sara Saadatmand","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYHACAwh1AERUADEzcwNhLQfgWs6AtDCSooWxDcQioEW+/fDGzx9z7PL4zh9+9uHnvNpo/naglh8V23BbcSatWOLgtuRiyRtpxjN7tx3PnXGYsYGx58xtPK7KMQBqYU7ccIPBmIF327HcBqAWZsY23Frk+98Y/zi4rT5xw/njnxn/zjmWO5+QFoYbOWZAWw4nbjiQY8zM21CTu4GQFoMbz8oszm47njjzRk4xs8yxA7kbgVoO4vOLfH/y5huV26oT+84f38z4pqYud975wwcf/KjA4zA0cBhMHiBaPRDUkaJ4FIyCUTAKRggAAArjZlX8rBkHAAAAAElFTkSuQmCC","orcid":"","institution":"Islamic Azad University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Saadatmand","suffix":""},{"id":118431216,"identity":"b039d0bb-1694-4b53-a10f-37179ec021fa","order_by":2,"name":"Neda Soltani","email":"","orcid":"","institution":"Research Institute of Applied Science, ACECR","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Neda","middleName":"","lastName":"Soltani","suffix":""},{"id":118431217,"identity":"e378b4b2-360b-44d0-9f78-3134b3508805","order_by":3,"name":"Vahid Niknam","email":"","orcid":"","institution":"Tehran University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Vahid","middleName":"","lastName":"Niknam","suffix":""}],"badges":[],"createdAt":"2022-06-25 05:44:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1793728/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1793728/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23773292,"identity":"71b60eb2-fdd5-4692-8013-4c5b033f7d01","added_by":"auto","created_at":"2022-07-12 16:37:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44200,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly maximum (T max) and minimum (T min) of air temperature (°C), average humidity (%) and precipitation at the study site for two experimental growth periods (May to August of both years).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/ad1b8efe755d3f56ef82ce49.png"},{"id":23855880,"identity":"20f5c225-9b6c-475b-b5b7-ad2fb6c60433","added_by":"auto","created_at":"2022-07-14 12:42:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76967,"visible":true,"origin":"","legend":"\u003cp\u003eChlorophyll content (SPAD, A), Fv/Fm index (B), Stomata conductivity (C), Proline content (D), MDA content (E), and Protein content (F) of mutant lines in comparison with traditional rice varieties under saline field condition. Different letters in each bar represent significant difference at P≤0.05 according to LSD test.\u0026nbsp;\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/d94bbc3167b232a4f89df3bd.png"},{"id":23772625,"identity":"7641c093-ee60-4e05-8ebe-d258817a6497","added_by":"auto","created_at":"2022-07-12 16:32:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":32868,"visible":true,"origin":"","legend":"\u003cp\u003eActivates of POX (A), CAT (B), and SOD (C), Na concentration (D), K concentration (F), and Na:K ratio of mutant lines in comparison with traditional rice varieties under saline field condition. Different letters in each bar represent significant difference at P≤0.05 according to LSD test.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/3c5c321ea9b2c985dc8823f1.png"},{"id":23772632,"identity":"a608bb53-da19-4455-9667-7525025d2830","added_by":"auto","created_at":"2022-07-12 16:32:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":29726,"visible":true,"origin":"","legend":"\u003cp\u003eFull grain (A), milling recovery (B), amylose content (C), grain elongation ratio (D), and gelatinization temperature (E) of mutant lines in comparison with traditional rice varieties under saline field condition. Different letters in each bar represent significant difference at P≤0.05 according to LSD test.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/faf68a2361065933bad09990.png"},{"id":23772630,"identity":"e97faa34-72c9-4fe9-89f7-c08be6f69ab1","added_by":"auto","created_at":"2022-07-12 16:32:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":137104,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation coefficients (r) between physiological and biochemical (left) and agronomic (right) traits with seed yield under saline field condition. \u003csup\u003ens\u003c/sup\u003e non-significant * Significant at 5 % level of probability, ** Significant at 1 % level of probability. The traits are MR (Milling recovery), GER (Grain elongation ratio), GT (Gelatinization temperature), FGP (number filled grain in panicle), NPH (number panicles per hill), PH (plant height), PL (panicle length), SC (Stomata conductivity), TNGP (total number grain per panicle), W1000 (weight of 1000 grains).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/8a7d97e409c55492d68ca1fe.png"},{"id":23775122,"identity":"6abaafd0-ea4b-4ea1-8e98-237710796432","added_by":"auto","created_at":"2022-07-12 16:47:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":24462,"visible":true,"origin":"","legend":"\u003cp\u003eThe Genotype-by-trait (GT) biplot to exhibit the traits relationships across genotypes. The traits are MR (Milling recovery), GER (Grain elongation ratio), GT (Gelatinization temperature), FGP (number filled grain in panicle), NPH (number panicles per hill), PH (plant height), PL (panicle length), Pr (protein), SC (Stomata conductivity), TNGP (total number grain per panicle), W1000 (weight of 1000 grains), DF (day of 50% flowering), Yield (grain yield) Fv/Fm index, SPAD, CAT (catalase), POX (peroxidase), SOD (superoxide dismutase), MDA (malondialdehyde content), Na and\u0026nbsp;K concentration, and Na:K ratio.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/0fe8105841a995df5baf5768.png"},{"id":23775377,"identity":"a6e332a7-1cc6-4d1a-ac41-8f68bcef4b4d","added_by":"auto","created_at":"2022-07-12 16:52:00","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":33047,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram of ten mutant lines and traditional varieties of rice evaluated under salinity stress using Ward clustering method.\u0026nbsp;\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/7eb4a2d7810bafb23da35b95.png"},{"id":28085975,"identity":"999201a3-9d39-49e3-a478-4ae063c9e0b4","added_by":"auto","created_at":"2022-10-21 11:14:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":912216,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/2176232d-5151-46fb-acc4-ac4d29c3396f.pdf"},{"id":23774215,"identity":"8d366b45-67ab-488e-959f-b7674f3d0580","added_by":"auto","created_at":"2022-07-12 16:42:00","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22071,"visible":true,"origin":"","legend":"","description":"","filename":"RawData.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1793728/v1/e49b889e88677b6668040604.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of the saline tolerance of gamma-ray-induced mutant lines of rice (Oryza sativa L.) under field conditions","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSalinity is one of the main abiotic stresses that is becoming a significant menace for crop productivity and quality in worldwide \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. It is estimated that salt stress influenced 5% of the total cultivated area in the world \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, predictably increasing up to 21%, by the year 2050 \u003csup\u003e3\u003c/sup\u003e. In Iran, the problem of soil salinity (about 34\u0026nbsp;million ha) is widely distributed in arid and semi-arid areas as well as north region as the consequence of primary (natural) process or anthropogenic activities \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSalinity impairs the growth and development of plants through salinity-induced water stress which takes place in a short period, brings about dehydration symptoms to appear in the plant and inhibition of cell extension \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Plants subjected to long term salinity (over days or even weeks) undergo cytotoxicity of salt ions [like chloride (Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e) and sodium (Na\u003csup\u003e+\u003c/sup\u003e)] and nutrient availability imbalance, especially in the shoots, that cause a range of metabolic problems, precocious senescence, and afterwards cell death \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Additionally, salinity is typically lead to increasing production of reactive oxygen species (ROS) causing oxidative stress in plants \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Tolerance to this conditions, beside anatomical and morphological plasticity, is raised by a complex of physiological and molecular mechanisms such as rapid decrease in stomatal conductance, restricting influx and translocation of toxic ions, vacuolar compartmentation of toxic ions, compatible solutes synthesis, and the involvement of antioxidant defense system and plant hormones \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Although the above strategies have been revealed in many types of plants, these adaptive features in most commercially grown crops, such as rice, inefficient to cope with the salinity and are usually sensitive to given levels of salt stress \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRice (\u003cem\u003eOryza sativa\u003c/em\u003e L.) is the most important carbohydrate crop providing a staple food to over three billion consumers in the world \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, but this crop very susceptible to salt stress, especially at the seedling and reproductive growth stages, that negatively influenced its yields and yield components even when levels of salt is very low \u003csup\u003e8,10\u0026minus;12\u003c/sup\u003e. For most cultivated varieties of rice, 3.0 dS m\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (EC) is a threshold level of salinity and rice productivity reduce 12% for each unit (dS m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) rising in salinity from this level \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The average salinity levels (EC) ranged from 7.2 to 8 dS m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e resulting in 50% yield decrease of rice \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Evaluation of salt tolerance in rice is complex due to the variation in salinity sensitivity during its growth cycle \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Generally, rice has been reported to be sensitive during early seedling and flowering/reproductive stages, but is comparatively tolerant to salinity stress during germination, active tillering, and grain filling \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, different varieties of rice can differ in their tolerance to salinity during these phonological stage \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Therefore, two separate steps including screening salinity tolerance of seedling under controlled conditions from large segregating populations and evaluating promising lines to salinity tolerance, preferably under the field conditions, at the reproductive stage, has been suggested for screening of salinity tolerance in breeding programs \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Using yield and yield components has been considered as a reliable and efficient method for screening salt tolerance \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Furthermore, the use of physiological criteria accompanying yield may be considered as an effective approach for screening salt tolerance genotypes.\u003c/p\u003e \u003cp\u003eA number of strategies have been employed to diminish the effect of salinity stress on rice. Among that, crop improvement is one of the most important strategy to develop salt tolerant varieties. For this, sufficient variation plays a key role to create and identify salt tolerant genotypes. Induced mutation, especially by gamma ray, is an important supplementary approach to creating variation within a crop variety \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This approach has been successfully employed in the rice for genetic improvements with high-yield, dwarf, early-maturity, and other agronomic traits \u003csup\u003e\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, creation of new mutant from existing landraces rice can be useful for screening new varieties that are salinity tolerant.\u003c/p\u003e \u003cp\u003eThe purpose of the present study was the evaluation of the morphological and physiological responses of gamma-ray-induced mutant lines of rice at reproductive stage as well as the association between these consequences with yield and grain quality under saline field condition. Finally, the selected promising mutant lines can be used directly as a new cultivar or indirectly as a new source of germplasm in breeding.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMorphological and phenological parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were significant differences (P\u0026lt;0.01) among mutant lines for plant height, days to flowering, and panicle length under saline field condition. The plant height were significantly lower in 32-26, 32-14, 32-18 and 32-15 mutant lines compared with their corresponding origin grown under saline field condition. However, the minimum value (121 cm) of plant height was observed in 32-18 that evaluated as short rice plant category (Table 3). The results of days to 50% flowering showed decreasing trend in all the mutant lines compared to their parent varieties. The lowest value (68 day) of days to 50% flowering was observed in 13-3 mutant line that no significant differences from 11-16, 11-17, and 12-6 (Table 3). The panicle length was significantly higher in 13-3 and 22-1 mutant lines than the values measured in the corresponding parental plants under salinity. Among TRVs, Anbarbo exhibited significantly higher plant height, days to 50% flowering, and panicle length compared to Tarom and Hasani varieties (Table 3). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYield and Yield components\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was a significant variation (P\u0026lt;0.01) among mutant lines for the number of panicles per hill, the number of filled and total grains per panicle, weight of 1000 grains, and grain yield. The number of panicles per hill in 11-17, 13-3, 22-1, 32-18, and 32-26 of mutant lines were significantly higher than their corresponding origin grown under saline field condition (Table 3). Some of mutant lines (13-3, 32-16, and 32-18) exhibited higher values of filled grains per panicle compared to their parent varieties,\u0026nbsp;meanwhile 11-16 mutant line indicated lower value than the origin. 13-3 and 32-18 mutant lines had significantly higher value of the weight of 1000 grains as compared to their corresponding TRVs (Table 3). All of mutant lines, except 11-16, exhibited significantly higher grain yield under saline field condition, as compared to their parents. The maximum grain yield (7079 kg ha\u003csup\u003e-1\u003c/sup\u003e) was obtained in 13-3 mutant line that exhibited two time over than its origin (Tarom) under saline field condition (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysiological and biochemical parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe chlorophyll contents were significantly higher in 11-16, 11-17, 13-3, 22-1, 32-18, and 32-15 of mutant lines than TRVs (Fig 2 A). The values of Fv/Fm index were recorded in the ranges of 0.63-0.64 and 0.75-0.82 under saline field condition for TRVs and mutant lines, respectively. The Fv/Fm was significantly higher in all the mutant lines than TRVs (Fig 2 B). The majority of mutant lines exhibited higher values of stomata conductivity compared to TRVs, meanwhile some mutant lines such as11-16 and 12-6 indicated lower stomata conductivity than their origin (Fig 2 C). The highest value of stomata conductivity was observed in 13-3, followed by 22-1 and 32-15 mutant lines (Fig 2 D). The proline contents were significantly higher in mutant lines compared to TRVs. The highest value of proline was accumulated in 13-3 line that indicated 138% enhancement compared to its origin (Fig 2 E). TRVs contained higher levels of MDA than mutant lines under saline condition. The minimum level of MDA was detected in 13-3 mutant line that indicated 44% reduction compared to its origin. Total protein content accumulated in 32-18 mutant line was significantly higher than TRVs. Among TRVs, Anbarbo exhibited higher levels of MDA and protein compared to Tarom and Hassani varieties (Fig 2 F).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a significant variation (P\u0026lt;0.01) among mutant lines for the activities of CAT, POX, and SOD enzymes. All of mutant lines, except 11-16, exhibited significantly higher CAT activity than their corresponding origin grown under saline field condition. Maximum activity of CAT was observed in 32-18, followed by 22-1 mutant lines (Fig 3 A). POX activity of 11-17, 13-3, 22-1, 32-26, 32-14, 32-18, and 32-15 was significantly higher than TRVs. The highest activity of POX was observed in 32-14 line that indicated 135% enhancement compared to its origin cultivar (Fig 3 B). All of mutant lines exhibited significantly higher activities of SOD compared to TRVs. The maximum SOD activity was observed in 13-3 mutant line that exhibited nearly two times more than its origin (Tarom) under saline field condition (Fig 3 C). The Na level and Na:K ratio were much higher in TRVs than all mutant lines under saline condition. The levels of Na accumulated of 32-18, 32-16, 22-1, 22-5, 13-3, and 11-17 mutant lines were 46%, 44%, 42%, 41%, 40%, and 41%, respectively, lower than in TRVs, while in 11-16, 12-6, 32-14, and 32-15 mutant lines Na accumulation was around 18% lower than in TRVs (Fig 3 D). The levels of K were significantly higher in 11-17, 12-6, 13-3, 21-5, 22-1, 32-14, and 32-26 of mutant lines than their corresponding origin grown under saline field condition (Fig 3 E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrain quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were significantly differences (P\u0026lt;0.01) among mutant lines for all investigated aspects of grain quality. Maximum milling quality was observed in 13-3 (70.03%), followed by 32-18 (69.66%), that showed significant difference from TRVs. the lowest value of full grain was observed in Anbarbo cultivar (67.13%) that exhibited significant difference from others studied genotypes. The levels of grain elongation were significantly higher in 11-16 and 11-17 of mutant lines than their corresponding origin. However, some mutant lines such as 21-5, 32-26, 32-14, 32-18, and 32-15 indicated lower grain elongation than their origin TRVs. The percentage of amylose of 11-16, 11-17, 13-3, 32-26, and 32-14 mutant lines was significantly higher than their origin TRVs. The maximum value of gelatinization temperature (6.35) was observed in Hassani variety that exhibited significant difference from others studied genotypes. Furthermore, 32-26 mutant line exhibited higher value of gelatinization temperature compared to its origin TRV (Fig 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociations between traits across the mutant lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of correlation analysis between different traits with grain yield are presented in Fig 5. Among the agronomy traits, number of panicles per hill (NPH), weight of 1000 grains (W 1000) exhibited a high and positive correlation with grain yield under saline filed condition. Regarding to physiological and biochemical traits, grain yield had a significant and positive association with SPAD, stomatal conductivity (SC), Fv/Fm index, proline content, SOD activity and potassium (K) concentration. Furthermore, MDA content, Na concentration and Na/K ratio had a significant and negative correlations with grain yield under saline field condition. It showed that milling recovery (MR) and full grain percentage (FGP) had a high and positive correlation with grain yield.\u003c/p\u003e\n\u003cp\u003eThe PCA helped in identifying those traits that best separated the mutant lines studied for their tolerance to salinity. The first two principal component explained 65% of total variation. The biplot (Fig. 6) according to PC1 and PC2 indicated the distribution of the mutant lines. PC1 had positive correlation with yield, NPH, PL, TNGP, FGP, W 1000, Proline, Fv/Fm, SC, SPAD, Pr, SOD, CAT, POD, K, MR, and Amylose. Therefore, PC1 was named as the yield and tolerance to salinity component. Also PC1 was observed positive for the mutant lines including 32-18, 13-3, 22-1, 11-17, 32-26, 32-14, 21-5. PC2 had high correlation with MDA, Na, Na:K ratio, PH, DF and GT. Thus, PC2 was presented as component of sensitivity to salinity. Anbarbo, Tarom, Hasani, 32-15, 12-6 and 11-16 were categorized as the sensitive ones (Fig 7). Furthermore,\u0026nbsp;the biplot figure indicated a high and positive correlation (an acute angle) between\u0026nbsp;grain\u0026nbsp;yield with NPH, W 1000, Proline, Fv/Fm, SC, SOD, and FGP that were extremely consistent with the numerical Pearson correlation coefficients (Fig. 6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrouping of the mutant rice genotypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCluster analysis according to morpho-physiological, biochemical and grain quality data using Euclidean distance coefficient grouped the mutant lines and parent ̛s plants into two main clusters. The first cluster included Tarom, Hasani, Anbarbo, 11-16, 21-5 and 12-6. Lines of 32-26, 32-15, 32-14, 11-17, 13-3, 22-1, and 32-18 were clustered in the second group. Dendrogram using ward clustering method clearly separated the mutant lines based on their tolerance. The first cluster had the sensitive varieties such as Tarom, Hasani and Anbarbo, while the second cluster included the mutant lines with the highest tolerance (Fig 7).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLike most plants, rice responses to salinity stress involved alterations in various physiological and biochemical processes. These alterations have been considered as a major adaptation mechanisms to salinity tolerance in rice plant \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In this study, the pattern of these changes and its association with grain yield were investigated in reproductive stage of new derived mutant lines and TRVs of rice plants under saline field conditions. Genotypes differed significantly for morpho-physiological aspects, grain yield, and grain quality indicating a considerable variation of salt tolerance in the mutant lines and their parents.\u003c/p\u003e\n\u003cp\u003eThe effect of salinity on plants is commenced by the osmotic effect characterized by lowered osmotic potential followed by later ionic effect leading to ion toxicity \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The accumulation of ions of salts in the soil environment increased Na\u0026thinsp;+\u0026thinsp;concentration in the cytosol by passive influx \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e through K\u003csup\u003e+\u003c/sup\u003e transporters and then symplastic transport to the shoot \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Toxic concentrations of this ion creates cellular nutrient ion imbalance and can ultimately impact yield and performance of plant \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The results of biplot analysis showed that concentration of sodium (Na\u003csup\u003e+\u003c/sup\u003e) and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio in the leaves had a high and negative association with yield and yield components (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). Exclusion Na\u003csup\u003e+\u003c/sup\u003e uptake by roots is one of the most important mechanisms of salinity tolerance in plants, which result in maintaining low Na\u003csup\u003e+\u003c/sup\u003e concentrations in the shoot \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In this study, The Na\u003csup\u003e+\u003c/sup\u003e concentration and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio was much higher in TRVs than all mutant lines under saline condition (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In both Indica and Japonica varieties of rice, the concentration of sodium ion in the leaves associated to the salinity tolerance level, thereby salt sensitive cultivars accumulate more Na\u003csup\u003e+\u003c/sup\u003e in shoots and leaves than salt tolerant ones \u003csup\u003e15,36\u0026minus;38\u003c/sup\u003e. Accordingly, several previous researches revealed that low cytosolic Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio is necessary to preserve an appropriate ionic homeostasis \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e which result in improving photosynthesis and plant growth under salinity stress condition \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Therefore, Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio can be employed as a standard reliable criterion for screening salt tolerant genotypes in rice \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. In this research, there was a high and negative correlation between grain yield and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio plus Na\u003csup\u003e+\u003c/sup\u003e concentration of leaves of rice under saline condition (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Based on these criteria, some of mutant lines such as 32\u0026thinsp;\u0026minus;\u0026thinsp;18, 32\u0026thinsp;\u0026minus;\u0026thinsp;16, 22\u0026thinsp;\u0026minus;\u0026thinsp;1, 22\u0026thinsp;\u0026minus;\u0026thinsp;5, 13\u0026thinsp;\u0026minus;\u0026thinsp;3, and 11\u0026ndash;17 accumulated less Na and maintained low Na+/K\u0026thinsp;+\u0026thinsp;ratio that exhibited more tolerance to salinity stress compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eRecently, other physiological parameters have been proposed as alternative criteria for evaluating and screening rice genotypes for salt tolerance \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Chlorophyll is considered to be an initial signal of responses in plants under salt stress \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The chlorophyll loss in the leaves is explained by the impairment of its biosynthetic pathways and also, hydrolysis of chlorophyll by chlorophyllase in salinity conditions \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e indicating that reduction in chlorophyll content can be applied as a stress indicator \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. The chlorophyll reduction under salinity condition was more pronounced in the salt sensitive rice cultivars compared to the salt tolerant ones \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In this study, the chlorophyll contents were significantly higher in some of mutant lines compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, the grain yield positively associated with chlorophyll content under saline condition (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e), suggesting that tolerant mutant lines maintaining more chlorophyll in leaf at reproductive stage.\u003c/p\u003e\n\u003cp\u003eMaximum quantum yield (Fv/Fm) value provides an appropriate approach to the evaluation of stress-induced damages in photosynthesis process \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. For unstressed leaves, the approximate optimal value of Fv/Fm is ranged of 0.79 to 0.84, with lowered values indicating plant stress \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. In this research, the Fv/Fm ratio in TRVs significantly reduced than optimum range, while in some mutant lines ones\u0026apos; decrease in the proportion was not found under saline conditions (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, the result of correlation and biplot analyses exhibited a high and positive correlation between Fv/Fm index and grain yield of rice under salinity stress (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e), suggesting that Fv/Fm can be used for rapid screening salt tolerant lines.\u003c/p\u003e\n\u003cp\u003eIn this study, the majority of mutant lines exhibited higher values of stomata conductivity compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), the reduction of stomatal conductivity in salt-sensitive varieties can be due to the lower K\u003csup\u003e+\u003c/sup\u003e and the greater Na\u003csup\u003e+\u003c/sup\u003e accumulation in stoma guard cells \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. The biplot figure illustrated a high and positive correlation (an acute angle) between K and stomata conductivity, while it had a negative correlation with Na concentration.\u003c/p\u003e\n\u003cp\u003eOsmotic adjustment in plants is achieved via over accumulation of compatible solutes such as proline \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Proline accumulation in plants has been revealed to play adaptive roles in storage of nitrogen and carbon \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, osmoregulation \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, ROS scavenging \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, and prevent K\u003csup\u003e+\u003c/sup\u003e efflux from root \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e under salinity condition. Although the proline accumulation can differ considerably in response to stresses, there is no obvious relationship among the accumulation of proline and ability of plant to cope with stress \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. In rice, some reports stated that proline accumulation was a reaction to stress rather than an indicator of the tolerance \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. However, others studies suggested that proline was a plant criteria associated with tolerance to salt stress \u003csup\u003e8,54\u0026minus;56\u003c/sup\u003e. This study clearly revealed that proline accumulation correlated positively with grain yield plus yield components and negatively with Na plus Na/K ratio (Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). In some mutant lines, the mounts of proline were more than 1.5 folds compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In agreement with this results, previous researches showed that salt tolerant rice cultivars accumulated greater amounts of proline compared to salt sensitive once \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Salinity stress induced a cascade of reactive oxygen species (ROS) production leading to oxidative stress in plant tissue, causing membrane demolition due to peroxidation of lipids. Malondialdehyde (MDA) is the main product of the decomposition of unsaturated fatty acids in biological membranes, and it can be used to evaluate the degree of lipid peroxidation and cell membrane injury \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. The strong negative correlation was observed between MDA level and grain yield (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Also, the results of biplot analysis showed that MDA content had a high and positive correlation with Na concentration plus Na/K ratio in the leaves (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). Previous reports showed that MDA content accumulated greater in salt sensitive rice cultivars under salinity stress compared to salt tolerant cultivars \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. In this study, the most of mutant lines exhibited less MDA levels compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), suggesting more tolerance to saline condition in those mutant lines.\u003c/p\u003e\n\u003cp\u003eScavenge and detoxify ROS by antioxidant defense system protect the cells from oxidative injury and known as an important mechanism of salt tolerance in the plants \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. The antioxidant enzymes activities of mutant lines differed significantly in response to saline field condition compared to TRVs. In this study, SOD, CAT and POX activities of mutant lines such as 13\u0026thinsp;\u0026minus;\u0026thinsp;3, 22\u0026thinsp;\u0026minus;\u0026thinsp;1, 32\u0026thinsp;\u0026minus;\u0026thinsp;18, and 32\u0026thinsp;\u0026minus;\u0026thinsp;14 significantly increased compared to TRVs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In agreement with this results, previous reports supported that the activity of antioxidant enzymes increased in salt-tolerant rice genotypes with elevation of salt levels, as compare with salt-sensitive genotypes \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eSOD catalyzes the disputation of superoxide to hydrogen peroxide and oxygen and is the first enzyme during the ROS detoxification process \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. The higher activity of SOD was observed in all mutant lines compared to their origin. In line with these results, several studies have shown that salt tolerant plants exhibited more SOD activity under salinity stress \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Further, the effectiveness of SOD largely determines by the role of other antioxidative components such as CAT and peroxidases to eliminate of hydrogen peroxide \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. In this study, higher activities of CAT and POX were observed in some mutant lines including 13\u0026thinsp;\u0026minus;\u0026thinsp;3, 22\u0026thinsp;\u0026minus;\u0026thinsp;1, 32\u0026thinsp;\u0026minus;\u0026thinsp;14, and 32\u0026thinsp;\u0026minus;\u0026thinsp;18 than TRVs (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). This pattern of changes in activities of antioxidant enzymes may reflect that the harmful effects of ROS in mutant lines were generally kept at balanced levels by a synchronized action of antioxidant enzymes led to reducing membrane lipid peroxidation and keeping the integrity of membranes and stabilizing enzymes and proteins.\u003c/p\u003e\n\u003cp\u003eThe quality of rice grain may be affected by salt-induced changes in the vegetative growth stage and the physio-biochemical processes during the grain filling stage \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Quality in rice grain is considered from the viewpoint of milling quality, grain appearance, and cooking characteristics \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. The milling quality is one the most important criteria of rice grain quality and define as the ability of rice grain to stand milling without undue breakage \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. Khush et al. \u003csup\u003e73\u003c/sup\u003estated that about 70% milled rice was obtained from a rough rice. The results of this study showed that some of the mutant lines such as 13\u0026thinsp;\u0026minus;\u0026thinsp;3 and 32\u0026thinsp;\u0026minus;\u0026thinsp;18 exhibited about 70% milling quality. However, the percentage of milling recovery was less than 70% in TRVs and other mutant lines under saline condition (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Furthermore, the results of correlation analysis showed that the milling recovery had a positive association with grain yield under saline condition (Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). The head-rice (full grain) recovery of rice grain may varied between ranges 25% of low to 65% of high \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. In this study, all of investigated genotypes exhibited high values of full grain (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Further, some of mutant lines such as 13\u0026thinsp;\u0026minus;\u0026thinsp;3 and 32\u0026thinsp;\u0026minus;\u0026thinsp;18 exhibited the values (67.13% and 66.76%, respectively) higher than the ranges defined by Khush et al. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Also, full grain percentage exhibited a high and positive correlation with grain yield under saline field conditions (Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e), suggesting this character may influence by the amount of genotype yield. Amylose content is the most important chemical characteristics that determines the hardness quickly after cooling \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. The rice with high amylose content (\u0026gt;\u0026thinsp;25%) is less sticky on cooking. Intermediate amylose rice (20\u0026ndash;25%) is the preferred type in most rice-growing areas of the world \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Based on previous studies, the impacts of salinity stress on amylose or starch variation of rice grain were depend on salinity intensity or genotype. Rao et al. \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e reported that amylose content of rice grain decreased at 8 dS/m or higher salt levels. In other studies, 7\u0026ndash;11% reduction in amylose content was observed at 40 mM NaCl \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e76\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. In this study, EC of soil in experimental field was ranged 6.4 to 8.1 dS/m during transplanting stage to harvest time (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In this condition, the percentage of amylose in some of mutant lines such as 11\u0026ndash;16, 11\u0026ndash;17, 13\u0026thinsp;\u0026minus;\u0026thinsp;3, 32\u0026thinsp;\u0026minus;\u0026thinsp;26, and 32\u0026thinsp;\u0026minus;\u0026thinsp;14 was significantly higher than their origin TRVs (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The physical cooking properties of rice are intimately related to the gelatinization temperature (GT) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Rice varieties with a high GT need more water and time to cook than those with a low or intermediated GT. Starchy endosperm is rated visually according to a 7-point numerical (1 pasty and 7 well separated) scale \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In this research, all the mutant lines had intermediate GT (between 3 and 4 scale). Increase in length of rice grain is a desirable quality trait \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. In this study, grain elongation ratio in all the mutant lines and also their parents was highly desirable (1.9 to 2.1), so that they expand in size upon cooking (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eMutation breeding, by using gamma radiation, has been showed as being an effective approach to obtain new rice genotypes with improved features. Also, this research reveal that it is an excellent method to improve salinity tolerance in TRVs. Based on cluster analysis (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), mutant lines in second group showed better performance in saline filed condition via high values of grain yield and yield components, chlorophyll content, Fv/Fm index, stomata conductivity, proline content, K concentration, but had low values of Na\u003csup\u003e+\u003c/sup\u003e concentration, Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio and MDA content, as compared to TRVs. Higher yield in these tolerant mutants was associated with more number panicle per hill, number filled grain per panicle, and 1000-grain weights (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of this study suggested that large genotypic variation was observed among mutant lines and TRVs for most of the investigated traits. Some of mutant lines including 13\u0026thinsp;\u0026minus;\u0026thinsp;3, 32\u0026thinsp;\u0026minus;\u0026thinsp;18 and 22\u0026thinsp;\u0026minus;\u0026thinsp;1 maintained a relatively higher photosynthetic capacity, preserving cells constituents from oxidative damage by improved the antioxidant defense system, compatible solutes synthesis such as proline, and restricting the entry of toxic ions under saline field condition that led to higher yield and yield components than TRVs. Results of correlation as well as principle component analysis indicated that grain yield had high correlated with proline content, Fv/Fm index, stomata conductivity, SOD activity, MDA content, Na\u0026thinsp;+\u0026thinsp;concentration, and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio at the reproductive stage under saline field condition, indicating that indirect selection based on these physiological criteria would be more effective for screening salt tolerance.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003ePlant materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlants of three Iranian traditional rice varieties (TRVs) and ten mutant lines, derived from irradiation of seeds of TRVs, were used as plant materials in this experiment after screening \u003cem\u003ein situ\u003c/em\u003e to identify those mutants more tolerant to salinity. These mutant lines produced through gamma irradiation (200-300 Gy) in TRVs of Tarom, Anbarbo, and Hasani and screened and selected up to six generations (M\u003csub\u003e6\u003c/sub\u003e) based on tolerant to salinity under saline field conditions. The mutant names and their originality are summarized in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSite description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was conducted in the saline paddy field at Fereydunkenar, Mazandaran province; Iran (36.6730\u003csup\u003e◦\u003c/sup\u003eN, 52.5369\u003csup\u003e◦\u003c/sup\u003eE), during growing season of 2018 and 2019. The total field size was 20 * 30 m and the study was arranged in a randomized complete block design with three replications. The soil type was loam clay silty, characterized by 5.04 % organic matter (O.M), 130.55, 0.93, 27.50, and 161.30 meq L\u003csup\u003e-1\u003c/sup\u003e of sodium (Na), potassium (K), calcium plus magnesium (Ca+Mg), and chloride (Cl), respectively. Thirty-day-old seedlings of mutant lines and TRVs raised in a nursey were transplanted into saline field in April of both years. Plot size was 5.0 x 2.0 m\u003csup\u003e2\u003c/sup\u003e and with 25cm x 25cm distance between rows and plants. For each replicate, seedlings of each mutant line were sown in 8 rows and 20 plants in each row. The space among two adjacent plots was 1 m. The plots received general maintenances including fertilization, irrigation, weed control, and etc. All fertilizers were applied during final land preparation excluding urea. Urea was applied at three equal installments at 7, 30 and 55 days after transplanting. The plots were kept saturated with irrigation until maturity and three hand weeding were made during growing season. The climate is wet temperate with average annual maximum temperature of 21.5 \u0026deg;C, average annual minimum temperature of 13.7 \u0026deg;C, and average annual precipitation of 870 mm. The monthly variations in local humidity, temperature and precipitation during experimental time are presented in figure 1.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysico-chemical characters of the soil\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty soil samples (0-30 cm) were collected to determine the physical and chemical properties including the electrical conductivity (EC) and pH in vegetative, reproductive, and ripening stages of rice growth. Also, the water above soil surface was randomly harvested for determination surface water salinity and pH by using EC and pH meters (INDEX, Innovation Beyond 2000, USA, model ID1040 for EC and ID1000 for pH), respectively. Physico-chemical properties of soil of the field during growth period are showed in Table 2.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMorphological and phenological parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlant height\u003c/em\u003e: Shoot height were measured from 10 randomly selected mutant plants per plot at booting stage as height from ground level to tip of panicle excluding the owns.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDay to heading\u003c/em\u003e: days to 50% heading was calculated as the number of days from the date of sowing until when 50% of plants in each plot produced panicles and recorded through visual observation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePanicle length\u003c/em\u003e: Length of the panicle was measured from the node to the tip of the main panicle of randomly selected 10 competitive plants in each plot at the time of maturity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYield and Yield components\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the time of harvest, total grain yield, number of panicles per hill, filled and unfilled grains per panicle, and 100-grain weight were evaluated. Number of panicles was measured from 10 randomly selected hill per plot. Filled and unfilled grains per panicle was recorded from randomly selected 10 main panicles per plot. For 1000-grain weights, thousand grains of each plot were randomly selected after harvesting and then weighed. Grain yield was recorded by harvesting from 1 m\u003csup\u003e2\u003c/sup\u003e area and then converting it to get final yield in kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e at 14% moisture.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysiological and biochemical parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt reproductive stage, mutant lines were analyzed for chlorophyll content, the efficiency of photosystem II, Stomatal conductance, proline content, lipid peroxidation intensity determined by the malondialdehyde (MDA) content, the activities of antioxidant enzymes, and elements concentration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of chlorophyll content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeaf chlorophyll content was measured on the fully expanded leaves of the four randomly selected plants per plot using chlorophyll meter (SPAD-502 Chlorophyll Meter, Minolta Camera Co. Ltd., Japan). The three SPAD readings were taken on each plant and averaged to provide a single reading per plant. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe efficiency of photosystem II\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaximum photochemical efficiency of photosystem II (Fv/Fm) parameter was measured with a portable Photosynthetic Efficiency Analyzer (Handy PEA, Hansatech Instruments Ltd, Norfolk, UK) in the fully expanded leaves at midday (11:00 A.M to 13:00 P.M, solar time). The Fv/Fm index were measured after dark adaptation of leaves for 30 min.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStomatal conductance assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMature leaves, from four randomly selected plants of each plot, were used in gas-exchange measurements. The measurements were recorded using Leaf Porometer (Model SC\u003csup\u003e-1\u003c/sup\u003e; Decagon Devices, Inc 2365 NE Hopkins Ct. Pullman, WA 99163 USA) at 9.00 a.m. to 11.00 pm. During measurement time, temperature of leaf was ranged 28 to 31.2 C◦ and relative humidity was 80% at the leaf area.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProline content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProline was extracted from 0.5 g of fresh sample in 10 mL of 5-sulphosalicylic acid (3%, w/v) and quantified using the acid ninhydrin procedure described by Bates et al. \u003csup\u003e18\u003c/sup\u003e. Light absorbance of extracts was recorded at 520 nm with a spectrophotometer (Model 6705 uv/vis. JENWAY). Free proline concentration per gram of fresh weight (FW) was determined using L-proline as standard.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLipid peroxidation intensity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe amount of malondialdehyde (MDA) as a product of lipid peroxidation was measured according to the method described by. The absorbance of the supernatant was assayed by Heath and Packer\u003csup\u003e23\u003c/sup\u003e a spectrophotometer (Model 6705 uv/vis. JENWAY) at 532 and 600 nm and was reported as \u0026mu;mol MDA g\u003csup\u003e\u0026minus;1\u003c/sup\u003eFW using the extinction coefficient of 155 mM\u003csup\u003e\u0026minus;1\u003c/sup\u003ecm\u003csup\u003e\u0026minus;1\u003c/sup\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntioxidant enzymes activities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLeaf tissues of 0.2-0.29 were homogenized in 10 ml of 50 mM potassium phosphate buffer (pH 6.5) containing 10% glycerol. The homogenate was centrifuged at 10.000 rpm at 4(\u003csup\u003e◦\u003c/sup\u003eC) for 5 min. The supernatant was used to\u0026nbsp;measure\u0026nbsp;total protein content based on Bradford\u0026nbsp;\u003csup\u003e24\u003c/sup\u003e and for determination of enzyme activities of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD). All assays were done using a spectrophotometer (Model 6705 uv/vis. JENWAY).\u003c/p\u003e\n\u003cp\u003eSOD (EC 1.15.1.1) activity was determined by measuring its ability to inhibit the photo-reduction of nitro blue tetrazolium (NBT)\u0026nbsp;based\u0026nbsp;on the method of Giannopolitis and Ries\u0026nbsp;\u003csup\u003e25\u003c/sup\u003e. The reaction mixture contained 50 mM potassium phosphate buffer (pH 7.0), 13 mM methionine, 75 \u0026micro;M NBT, 0.1 mM EDTA, 15 \u0026micro;L Riboflavin, and 50 \u0026micro;L of the enzyme extract. The reaction was allowed to proceed for 15 min under light supplied by two fluorescent lamps (20W), and then the tubes were covered with aluminum foil to stop the reaction. Absorbance of the reaction mixture was read at 560 nm.\u003c/p\u003e\n\u003cp\u003ePOD (EC 1.11.1.7) activity was assayed by the oxidation of guaiacol in the presence of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The increase in absorbance was read at 470 nm for 2 min \u003csup\u003e26\u003c/sup\u003e. The reaction mixture contained 20 \u0026micro;L of enzyme extract, 100 \u0026micro;L of 35 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, 880 \u0026micro;L of 10\u003csub\u003e\u0026nbsp;\u003c/sub\u003emM guaiacol, and 50 mM potassium phosphate buffer (pH 6.5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAT (EC 1.11.1.6) activity was calculated according to the method of Luck \u003csup\u003e27\u003c/sup\u003e. The composition of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e Was followed as a decline in the absorbance at 240 nm within 120 s. 20 \u0026micro;L of the enzyme extract and 980 \u0026micro;L of 50 mM potassium phosphate buffer (pH 7.0) contained 35 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003ewas used as the reaction mixture.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSodium (Na) and Potassium (K) concentrations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant material was oven-dried (70 \u003csup\u003e◦\u003c/sup\u003eC, 48 h) and finally ground for analysis. \u0026nbsp;The samples (1g) were reduced to ashes at 550 C◦ for 5 hours. The ashes were digested with 2N hydrochloric acid (HCl), and then to drive off HCl the supernatant was heated at 90\u0026deg;C. After that, the supernatant was diluted (to the volume 100 ml) with deionized water. The amount of Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e were measured using a flame photometer (Model PEP7, Jenway. Dunmow, UK) and quantified based on a standard curve \u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrain quality assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter harvesting, 400 g paddy from each plot was used to measure grain quality. Amylose content (AC) was determined using Juliano \u003csup\u003e29\u003c/sup\u003e and gelatinization temperature was estimated according to method of Little et al. \u003csup\u003e30\u003c/sup\u003e. The method of Azeez et al. \u003csup\u003e31\u003c/sup\u003e was used for evaluating the degree of elongation. Milling yield was calculated as a percentage from a unit of rough rice \u003csup\u003e32\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was designed according to a complete randomized block scheme with three replicates during 2018 and 2019. The obtained data from two years were subjected to the combined analysis of variance to assess the effect of genotype and genotype \u0026Iacute; year interaction using SAS statistical software (version 9.1; SAS institute, Cary, NC, USA). The mean values were compared through least significant difference (LSD) test (P\u0026lt;0.05). Stepwise multiple linear regression was used to identify the variables (as the independent variables) accounting for the majority of grain yield (as the dependent variable) using the IBM SPSS Statistic 22 software. The Pearson\u0026rsquo;s correlations coefficients between traits were also calculated using SPSS software. Hierarchical clustering of genotypes into similar groups was performed using the Ward method based on squared Euclidean distances for quantitative and qualitative variables using SPSS 22 software. A genotype\u0026Iacute;trait (GT)- biplot analysis was performed to reduce the multiple dimensions of data space using Statgraphics centurion XVl software and plotting the first two symmetrically scaled principal components (PC) for the average tester coordinate and polygon view of the biplot.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to the Nuclear Science and Technology Research Institute of Iran for providing the necessary facilities for carrying out this experiment. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.B. was the proposer and executor of the project, and also wrote the draft. S.S. reviewed and edited the draft. N.S. analyzed the data. V.N. was a collaborator in the project. All authors commented on previous versions of the manuscript and all authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e and requests for materials should be addressed to S.S. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe confirm that all the experimental research and field studies on plants (either cultivated or wild), including the collection of plant material, complied with relevant institutional, national, and international guidelines and legislation. All of the material is owned by the authors and/or no permissions are required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIsayenkov, S. 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Rice Sci. \u003cb\u003e24\u003c/b\u003e, 155\u0026ndash;162 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl-Shabrawi, H. \u003cem\u003eet al.\u003c/em\u003e Redox homeostasis, antioxidant defense, and methylglyoxal detoxification as markers for salt tolerance in Pokkali rice. Protoplasma \u003cb\u003e245\u003c/b\u003e, 85\u0026ndash;96 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHasanuzzaman, M. \u003cem\u003eet al.\u003c/em\u003e Exogenous proline and glycine betaine mediated upregulation of antioxidant defense and glyoxalase systems provides better protection against salt-induced oxidative stress in two rice (Oryza sativa L.) varieties. \u003cem\u003eBiomed Res. Int.\u003c/em\u003e 2014, (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStepien, P. \u0026amp; Klobus, G. Antioxidant defense in the leaves of C3 and C4 plants under salinity stress. Physiol. 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Rice Sci. \u003cb\u003e21\u003c/b\u003e, 288\u0026ndash;298 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmirikhah, R., Etemadi, N., Sabzalian, M. R., Nikbakht, A. \u0026amp; Eskandari, A. Physiological consequences of gamma ray irradiation in tall fescue with elimination potential of Epichlo\u0026euml; fungal endophyte. Ecotoxicol. Environ. Saf. \u003cb\u003e182\u003c/b\u003e, 109412 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRazzaq, A. \u003cem\u003eet al.\u003c/em\u003e Salt stress induces physiochemical alterations in rice grain composition and quality. J. Food Sci. \u003cb\u003e85\u003c/b\u003e, 14\u0026ndash;20 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuliano, B. O., Bautista, G. M., Lugay, J. C. \u0026amp; Reyes, A. C. Rice quality, studies on physicochemical properties of rice. J. Agric. Food Chem. \u003cb\u003e12\u003c/b\u003e, 131\u0026ndash;138 (1964).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb, B. D., Bollich, C. N., Carnahan, H. L., Kuenzel, K. A. \u0026amp; McKenzie, K. S. Utilization characteristics and qualities of United States rice. Rice grain Qual. Mark. IRRI, Manila, Philipp. \u003cb\u003e985\u003c/b\u003e, 25\u0026ndash;35 (1985).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhush, G. S., Paule, C. M. \u0026amp; De la Cruz, N. M. Rice grain quality evaluation and improvement at IRRI. in \u003cem\u003eProceedings of the workshop on chemical aspects of rice grain quality\u003c/em\u003e (Los Banos, Philippines, International Rice Research Institute, 1979., 1978).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuliano, B. O. \u0026amp; Pascual, C. G. Quality characteristics of milled rice grown in different countries. IRRI Res. Pap. Ser. (1980).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao, P. S., Mishra, B. \u0026amp; Gupta, S. R. Effects of soil salinity and alkalinity on grain quality of tolerant, semi-tolerant and sensitive rice genotypes. Rice Sci. \u003cb\u003e20\u003c/b\u003e, 284\u0026ndash;291 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePEIRIS, B. D., Siegel, S. M. \u0026amp; Senadhira, D. Chemical characteristics of grains of rice (Oryza sativa L.) cultivated in saline media of varying ionic composition. J. Exp. Bot. \u003cb\u003e39\u003c/b\u003e, 623\u0026ndash;631 (1988).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiscar-Lee, J. J. H., Juliano, B. O., Qureshi, R. H. \u0026amp; Akbar, M. Effect of saline soil on grain quality of rices differing in salinity tolerance. Plant Foods Hum. Nutr. \u003cb\u003e40\u003c/b\u003e, 31\u0026ndash;36 (1990).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz, N. Dela \u0026amp; Khush, G. S. Rice grain quality evaluation procedures. Aromat. rices \u003cb\u003e3\u003c/b\u003e, 15\u0026ndash;28 (2000).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. List of Iranian traditional rice varieties\u0026nbsp;(TRVs)\u0026nbsp;and mutant line used in this study\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTRVs\u0026nbsp;and Mutant line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eOrigin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eMutagen doses (Gy)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eHasani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eAnbarbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e11-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e200\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e11-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e200\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e12-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e13-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e300\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e21-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eHasani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e200\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e22-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eHasani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e32-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eAnbarbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e32-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eAnbarbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e32-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eAnbarbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e32-26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003eAnbarbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n \u003cp\u003e250\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Electrical conductivity (EC) and pH of soil and water of the experimental site at different growth stage of rice\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003eGrowth stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 30.0304%;\" valign=\"top\" width=\"41.79970972423803%\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 29.4225%;\" valign=\"top\" width=\"40.9288824383164%\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9422%;\" width=\"15.239477503628446%\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.7143%;\" valign=\"top\" width=\"7.982583454281568%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003eWater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.5258%;\" valign=\"top\" width=\"4.934687953555878%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0912%;\" valign=\"top\" width=\"14.078374455732947%\"\u003e\n \u003cp\u003eSoil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.6763425253991295%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003eWater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.531204644412192%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9422%;\" valign=\"top\" width=\"15.239477503628446%\"\u003e\n \u003cp\u003eEC (dS.m\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.7143%;\" valign=\"top\" width=\"7.982583454281568%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003eEC (dS.m\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.5258%;\" valign=\"top\" width=\"4.934687953555878%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0912%;\" valign=\"top\" width=\"14.078374455732947%\"\u003e\n \u003cp\u003eEC(dS.m\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.6763425253991295%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003eEC (dS.m\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.531204644412192%\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003eVegetative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9422%;\" valign=\"top\" width=\"15.239477503628446%\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.7143%;\" valign=\"top\" width=\"7.982583454281568%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.5258%;\" valign=\"top\" width=\"4.934687953555878%\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0912%;\" valign=\"top\" width=\"14.078374455732947%\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.6763425253991295%\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.531204644412192%\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003eReproductive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9422%;\" valign=\"top\" width=\"15.239477503628446%\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.7143%;\" valign=\"top\" width=\"7.982583454281568%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.5258%;\" valign=\"top\" width=\"4.934687953555878%\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0912%;\" valign=\"top\" width=\"14.078374455732947%\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.6763425253991295%\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.531204644412192%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10.8207%;\" valign=\"top\" width=\"15.09433962264151%\"\u003e\n \u003cp\u003eRipening\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9422%;\" valign=\"top\" width=\"15.239477503628446%\"\u003e\n \u003cp\u003e7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.7143%;\" valign=\"top\" width=\"7.982583454281568%\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.5258%;\" valign=\"top\" width=\"4.934687953555878%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.0912%;\" valign=\"top\" width=\"14.078374455732947%\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.6763425253991295%\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.848%;\" valign=\"top\" width=\"13.642960812772133%\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.7416%;\" valign=\"top\" width=\"6.531204644412192%\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Plant height, days to 50% flowering, panicle length, number of panicles per hill, number of filed grain per panicle, total grain per panicle, weight of 1000 grains, and grain yield of rice mutant lines and traditional rice varieties under saline field condition.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.149750415973378%\"\u003e\n \u003cp\u003eMutant lines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003ePlant Height (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.480865224625624%\"\u003e\n \u003cp\u003eDays to 50% Flowering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.484193011647255%\"\u003e\n \u003cp\u003ePanicle length (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.148086522462563%\"\u003e\n \u003cp\u003eNumber of panicles per Hill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.813643926788686%\"\u003e\n \u003cp\u003eNumber of filed grain per panicle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003eTotal grain per panicle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003eWeight of 1000 grains (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003eGrain yield (Kg.ha\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.149750415973378%\"\u003e\n \u003cp\u003eTarom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e146.66 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.480865224625624%\"\u003e\n \u003cp\u003e71.1 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.484193011647255%\"\u003e\n \u003cp\u003e24.7 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.148086522462563%\"\u003e\n \u003cp\u003e11.3 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.813643926788686%\"\u003e\n \u003cp\u003e96.5 \u003csup\u003eb-e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e108.4 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e22.3 \u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e3490.2 \u003csup\u003egh\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.149750415973378%\"\u003e\n \u003cp\u003e11-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e137.61 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.480865224625624%\"\u003e\n \u003cp\u003e70.4 \u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.484193011647255%\"\u003e\n \u003cp\u003e25.3 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.148086522462563%\"\u003e\n \u003cp\u003e12.5 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.813643926788686%\"\u003e\n \u003cp\u003e76.1 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e91.8 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e21.8 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e3691.3 \u003csup\u003egh\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.149750415973378%\"\u003e\n \u003cp\u003e11-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e137.07 \u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.480865224625624%\"\u003e\n \u003cp\u003e70.0 \u003csup\u003ede\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.484193011647255%\"\u003e\n \u003cp\u003e25.6 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.148086522462563%\"\u003e\n \u003cp\u003e13.7 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.813643926788686%\"\u003e\n \u003cp\u003e99.7 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e114.3 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e25.4 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width=\"10.149750415973378%\"\u003e\n \u003cp\u003e32-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e121.88 \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.480865224625624%\"\u003e\n \u003cp\u003e75.9 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.484193011647255%\"\u003e\n \u003cp\u003e27.8 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.148086522462563%\"\u003e\n \u003cp\u003e18.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.813643926788686%\"\u003e\n \u003cp\u003e121.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e160.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e27.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n 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width=\"10.64891846921797%\"\u003e\n \u003cp\u003e123.5 \u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.64891846921797%\"\u003e\n \u003cp\u003e24.8 \u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.312811980033278%\"\u003e\n \u003cp\u003e4230.1 \u003csup\u003eefg\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn each column, different letters represent significant difference at P\u0026le;0.05 according to LSD test.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Oryza sativa, saline field, mutant lines, physiological criteria, grain yield","lastPublishedDoi":"10.21203/rs.3.rs-1793728/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1793728/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRice is highly sensitive crop to salt stress, especially at reproductive stage, and obtaining salt-tolerant genotypes is key for the rice production in salt-affected soils. In this study, ten mutant lines (obtained through gamma ray and pre-selected for their tolerance to salinity) accompanying by three Iranian traditional rice varieties (TRVs) were evaluated for biochemical and morpho-physiological parameters related to salt tolerance under saline field condition. The experiment was conducted as a randomized complete block design with three replications during two growing seasons. The salt tolerant mutant lines exhibited higher proline accumulation, K\u003csup\u003e+\u003c/sup\u003e concentration, and activities of antioxidant enzymes, and lower Na\u003csup\u003e+\u003c/sup\u003e concentration, Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio, malondyaldehide (MDA) content that led to higher grain yield and quality under saline field condition, as compared with TRVs. Higher yield in these tolerant mutants was associated with more number panicle per hill, number filled grain per panicle, and 1000-grain weights. Results of correlation as well as principle component analysis also indicated that grain yield had high correlated with proline content, Fv/Fm index, stomata conductivity, SOD activity, MDA content, concentration of sodium (Na\u003csup\u003e+\u003c/sup\u003e) and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio at the reproductive stage under saline field condition, indicating that indirect selection according to these physiological criteria would be more effective approach for screening salt tolerance. According to these results, mutant lines 13\u0026thinsp;\u0026minus;\u0026thinsp;3, 32\u0026thinsp;\u0026minus;\u0026thinsp;18 and 22\u0026thinsp;\u0026minus;\u0026thinsp;1 indicated superiority in the grain yield and agronomical traits such as early- maturity and dwarfism, and also desirable grain quality that are promising mutant lines for cultivation in salt-affected coastal areas.\u003c/p\u003e","manuscriptTitle":"Evaluation of the saline tolerance of gamma-ray-induced mutant lines of rice (Oryza sativa L.) under field conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-12 16:31:58","doi":"10.21203/rs.3.rs-1793728/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b6a556a2-80e8-4d31-aeba-8ce8da625b74","owner":[],"postedDate":"July 12th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-10-21T11:14:18+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-12 16:31:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1793728","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1793728","identity":"rs-1793728","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}