Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters

Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters Neha Patwa, Vanita Pandey, Om Parkash Gupta, Anita Yadav, Mintu Ram Meena, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4454318/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Sep, 2024 Read the published version in BMC Plant Biology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Salt stress is a prominent abiotic stressor that imposes constraints on grain yield and quality across various crops, including wheat ( Triticum aestivum ). This study focused on assessing the genetic diversity of 20 wheat genotypes categorized as tolerant, moderately tolerant, and sensitive with three genotypes of unknown tolerance. To address salinity stress-related problems, different morphophysiological, osmoprotectant, biochemical, yield, and grain quality-related parameters were analyzed under saline-sodic conditions. Results The research findings revealed noteworthy variations among the genotypes in response to salinity stress. Greater accumulation of Na + and lower K + content were observed in response to salt stress in the sensitive varieties HD1941 and K9162. Proline, a stress indicator, exhibited significantly (p ≤ 0.05) greater accumulation in response to salinity stress, particularly in the tolerant cultivars KRL210 and KH65. Salt stress induced the most significant decrease (p ≤ 0.05) in spike length, thousand-grain weight, and hectolitre weight coupled with an increase in protein content in sensitive varieties such as K9162 and HD1941, resulting in diminished yield. Furthermore, salt-sensitive genotypes exhibited elevated protein content, reduced moisture, and increased sedimentation value. Conclusion Correlation analysis of parameters under salinity stress showed that SOD, proline, and K + contents can be used as the most efficient screening criteria for salinity stress during early developmental stages. Principal component analysis (PCA) revealed that DBW187, DBW303, and DBW222 varieties were tolerant to salinity stress and exhibited an effective antioxidant system against salinity. This study will facilitate salt-tolerant wheat breeding in terms of the identification of tolerant lines by screening for limited traits in a wide range of germplasms. salt stress oxidative stress wheat yield quality Figures Figure 1 Figure 2 Background Wheat ( Triticum aestivum L.) is a major staple food crop that contributes significantly to food and nutritional security worldwide. Wheat provides approximately 30% of the world’s population with 23.8% calories and 33.06% protein requirements [ 1 ]. Abiotic stresses such as salt, heat, and drought create a suboptimal environment and have a negative impact on the yield and productivity of wheat [ 2 ]. Salinity stress in arid and semi-regions of the world leads to a loss in agricultural productivity because of the accumulation of salts in the soil [ 3 ]. At any stage of crop growth, salt stress causes irreversible losses in yield potential in various crops, including wheat, barley, and rice [ 4 ]. Almost 7 million hectares of Indian soil are now contaminated by salt, and by 2050, salinization of the soil will result in the loss of 50% of cultivable land globally [ 5 ]. In salt-affected soils, excess Na + ions are present at exchange sites, and high concentrations of carbonate and bicarbonate anions are associated with high pH. High concentrations of Na + ions in soils compete for K + uptake, which leads to K + deficiency and promotes K + leakage from cells. This K + -induced deficiency inhibits the growth of plants because it plays an important role in maintaining cell turgor, membrane potential, and enzymatic activities [ 6 ]. Salinity stress is responsible for the generation of osmotic and ionic stresses, the influx of large amounts of Na + inside plant cells, and increased Na + concentrations in the cytoplasm and vacuole, which are toxic to metabolic mechanisms and lead to cell death. Wheat production is severely hampered by soil salinity, which reduces growth and productivity by lowering water uptake and creating nutritional deficiencies through ion toxicity [ 7 ]. Salinity stress leads to a significant reduction in photosynthetic performance and weakens the photosynthetic pigments present in the thylakoid membrane of the chloroplast. High salt toxicity in soil impairs the generation of photosynthetic pigments because of the inhibitory effect of salt ions on the biosynthesis of various chlorophyll components [ 8 ]. The chlorophyll content (CC), relative water content (RWC), normal difference vegetation index (NDVI), and membrane stability index (MSI) in wheat were negatively impacted by soil salinity. Wheat plants are less able to absorb nutrients from roots as the salinity increases because less water is accessible to roots. In response to salinity stress, primary plant activities, including protein synthesis, energy production and lipid metabolism, change during the plant's embryonic phases [ 9 , 10 ]. As a result of the plant's significant growth retardation, toxic metabolite synthesis and molecular damage can cause plant death [ 11 ]. Plants have developed internal resistance mechanisms to scavenge the harmful effects of reactive oxygen species (ROS), such as superoxide (O 2 ), hydrogen peroxide (H 2 O 2 ), hydroxyl radical (OH), and singlet oxygen (O 2 ), generated due to salinity stress [ 12 ]. To combat stress, plants modify their metabolism and enzymatic and non-enzymatic antioxidant mechanisms. Plants have also evolved various biochemical defences against osmotic and ionic stress, including osmotic tolerance, ion exclusion, tissue tolerance, synthesis of compatible solutes, amino acids, and organic acids, adjustments to membrane structure, induction of antioxidant defence, and hormone homeostasis [ 4 , 8 ]. Reactive oxygen species scavenging enzymes, which are part of the antioxidant defence, play a direct role in the degradation of ROS, including CAT (catalase), SOD (superoxide dismutase), GR (glutathione reductase), and APX (ascorbate peroxidase) [ 13 ]. SOD dismutases O 2 − into H 2 O 2, which is further catalyzed into H 2 O and O 2 by CAT and APX [ 14 ]. Furthermore, to overcome the osmotic stress induced by salinity, plants synthesize and accumulate metabolically compatible solutes such as proline, sugars, and betaines. Proline acts as an osmoprotectant and helps plants maintain tissue water potential lower than that of the soil to maintain turgor pressure for growth [ 7 ]. In addition to osmotic balance, these compatible solutes also act as antioxidants and help to stabilize subcellular structures, buffering the cellular redox potential against stress [ 15 ]. Wheat grain yield is a quantitative trait affected by salinity stress. Salinity stress suppresses the growth and development of spikes at the reproductive and maturity stages. Plant height, spike length, and grain weight are negatively affected by salinity stress. The ability of wheat to produce unique baked products, such as bread and chapatti, depends on grain quality. This attribute is assessed by physical and compositional properties such as grain hardness (GH), protein content (PC), and moisture content (MC) [ 16 ]. This study aimed to assess the effects of salinity stress on physiological, biochemical, yield, and other quality-related parameters in 20 wheat genotypes with different genetic backgrounds to identify parameters that can be used as biomarkers for rapid selection and improvement of salt-tolerant cultivars. The lack of precise indices of physiological and agronomic traits related to salinity stress and the low genetic variability in the currently available wheat germplasm lines are among the main reasons for the limited success in breeding salt-tolerant varieties. Previously reported salt-tolerant varieties have been used for the breeding of crops, but because of a lack of understanding of the mechanism of salt tolerance, less success has been achieved. Most saline-prone areas remain largely uncultivated. Growing salt-tolerant wheat on saline soils could be a significant attempt to use these areas and to meet the demands of the ever-increasing population and to satisfy their food needs. This would be possible by understanding the mechanism behind the variations in the tolerance of different wheat cultivars and by identifying salt-tolerant genotypes. Results Agro-morphology and physiological responses of wheat to saline-sodic conditions The agronomic and physiological responses of the wheat genotypes significantly differed under salinity stress. In this study, a significant reduction in agronomic traits during the early flag leaf stage and maturity stage of plants was observed. Significant growth and biomass reductions were observed in twenty wheat cultivars grown under salt stress. All physiological traits, such as plant height, chlorophyll content, SPAD, NDVI, RWC, and MSI, showed significant ( p ≤ 0.05) reductions except in the tolerant cultivars under salinity stress compared to their respective controls. The overall means and ranges of these traits for the 20 genotypes under both control and stress conditions are shown in Table 1. Salt stress significantly affects the plant height of wheat genotypes. The highest plant height was found in DBW187 (100.00 cm), and the least plant height was found in GW89 (66.00 cm) under salt stress. The highest percent reduction in plant height was observed for the sensitive varieties HD2009 (-32.03%) and GW89 (-29.29%), followed by the moderate varieties (Table 1), whereas the highest percent increase in plant height was observed for DBW187 (4.20%), the tolerant varieties KRL210 (1.19%), and AJANTA (1.50%) compared to the control under salinity stress (Table 1). The maximum SPAD chlorophyll value was observed in AJANTA (46.60), and the minimum was observed in the sensitive variety HD2009 (38.10) under salt stress. The SPAD chlorophyll value decreased the most in the sensitive variety K9162 (-12.55%) and HD2009 (-12.01%), and a significant percentage increase was observed in the tolerant variety KRL210 (2.69%) and AJANTA (1.75%) compared to the control under salt stress (Table 1). The water status of the plant is expressed by the RWC. The highest relative water content was detected in DBW 17 (85.04%), and the lowest relative water content (41.90%) was detected in sensitive HD1941 under salt stress. In our study, the RWC decreased significantly in some moderate and sensitive wheat cultivars under stress, but greater reductions were observed in sensitive cultivars. The greatest percent reduction was observed in the sensitive varieties HD1941 (-85.48%) and K9162 (-76.93%), whereas an increase in percent change was observed for DBW222 (7.46%), KH65 (5.42%), and DBW17 (0.21%) compared to the control under salt stress (Table 1). The NDVI was measured, and a maximum value was observed in DBW222 (0.71) and a minimum in HD1941 (0.21) under salt stress. The greatest percent reduction was measured in HD1941 (-59.75%) and K9162 (-44.86%), and the lowest was observed in KRL 210 (-0.55%) and DBW187 (-1.43%) compared to the control (Table 1). The maximum MSI was observed in DBW222 (88.64%), and the minimum was found in GW89 (44.01). A greater percentage of the reduction in MSI was observed in the sensitive varieties GW89 (-42.90%), HD3086 (-27.84%), and K9162 (-26.50%) than in the control. The tolerant varieties KRL210 (5.74%) and PBW502 (5.67%) can maintain the integrity of the plasma membrane more efficiently (Table 1). The maximum total chlorophyll accumulation was found in KRL210 (11.62 mg/gFW), and the minimum was found in GW89 (3.97 mg/gFW) under salt stress. A decrease in the total chlorophyll content percentage was detected in the sensitive varieties K9162 (-39.29%) and GW89 (-38.13%), whereas an increase was detected in the tolerant varieties AJANTA (3.07%) and KRL210 (0.18%), and a smaller reduction was detected in the moderate variety PBW65 (-19.96%) under salt stress compared with the control (Table 2). Biochemical parameters The oxidative stress markers H 2 O 2 and MDA increased significantly ( p < 0.05) under salinity stress. Salt stress led to the accumulation of H 2 O 2 in all the wheat genotypes. The sensitive genotype K9162 showed the highest accumulation of H 2 O 2 (7.56 μmol/g FW), and the lowest was found in KRL210 (4.82 μmol/g FW) under salt stress (Table 3). The greatest percent increase was observed for the sensitive varieties K9162 (94.96%) and HD2009 (62.02%), and the least percent increase was observed for the tolerant and of unknown tolerance levels and for the moderate varieties KRL210 (13.75%), DBW222 (15.97%), and KH65 (19.02%) (Table 3). MDA is used as a biomarker of the response to oxidative stress. Salt stress significantly increased the MDA content in all the wheat genotypes. The highest MDA accumulation was observed in the sensitive variety HD2009 (8.38 μM/g FW), and the lowest was observed in the tolerant variety KRL210 (3.99 μM/g FW) under salt stress. The greatest percent increase was observed among the sensitive varieties K9162 (71.54%) and GW89 (70.92%), and the greatest percent reduction was observed among the tolerant varieties KRL210 (-24.35%) and KH65 (-11.70%) compared to the control under salt stress conditions (Table 3). Antioxidant enzymes SOD activity increased significantly at p ≤ 0.05 in response to salt stress in all the wheat genotypes. The highest SOD activity was observed in KRL210 (30.70 units/g FW), and the lowest activity was observed in HD2009 (14.68 units/g FW). An increase in percent change was observed in the tolerant varieties KRL210 (24.63%) and GW190 (24.62%), whereas a decrease in percent change was observed in the sensitive varieties K9162 (-32.17%) and HD2009 (-28.62%) compared to the control under salt stress conditions (Table 3). Glutathione (GR) activity was also lower in the sensitive variety than in the tolerant variety under salt stress. The highest GR activity was observed in KRL210 (15.51 mM TNB min/g FW), and the lowest was observed in HD2009 (2.29 mM TNB min/g FW). The highest percent decrease in glutathione activity was detected in the sensitive varieties K9162 (-78.28%) and HD1941 (-68.44%), and the highest percent increase in glutathione activity was detected in KRL210 (15.13%) (Table 3). Similar results were also observed for CAT and APX under salt stress. The highest CAT activity was observed in KRL210 (26.49 μmoles/min/g FW), and the lowest activity was observed in HD2009 (9.10 μmoles/min/g FW) under salt stress. The highest percent reduction in CAT activity was observed in the sensitive varieties HD2009 (-29.78%) and K9162 (-29.44%), whereas a significant percent increase ( p < 0.05) was detected in the tolerant varieties KRL210 (66.92%) AJANTA (65.50%) and the unknown tolerance level varieties DBW222 (68.13%) and DBW187 (59.72%) compared with the control (Table 3). The maximum APX activity was observed in KRL210 (8.51 μmoles/min/g FW), and the minimum was observed in HD2009 (1.06 μmoles/min/g FW). APX activity was also found to decrease among sensitive varieties. The highest percent reduction was observed in HD2009 (75.00%) and GW89 (-54.65%), and the highest percent increase was observed in the tolerant varieties GW503 (141.67%) and KRL210 (111.11%) compared to the control under salt stress conditions (Table 3). Na + /K + accumulation Salinity stress significantly ( p < 0.05) increased the amount of Na + ions, decreased the K + content, and decreased the K + /Na + ratio in the wheat cultivars. The maximum Na + content accumulation was observed in HD2009 (9.87 mg/gDW) and the minimum was observed in KRL210 (3.97 mg/gDW) under salt stress conditions (Table 2). A greater percentage increase in Na + was observed in the sensitive varieties HD1941 (1323.28%) and GW89 (1261.14%), whereas the tolerant varieties KRL210 (543.78%) and AJANTA (570.46%) exhibited a smaller percentage increase compared with the control under salt stress. Interestingly, the increase in Na + content among the cultivars was inversely proportional to the decrease in K + content. Under salt stress, a decrease in K + content was observed in all the wheat genotypes. The maximum K + content accumulation was observed in KRL210 (24.46 mg/gDW) and the minimum was observed in K9162 (11.29 mg/gDW) under salt stress conditions (Table 2). A large percentage reduction was observed in the sensitive varieties K9162 (-39.30%) and HD1941 (-32.55%) compared with the control, and the lowest percentage reduction was detected in the tolerant variety KRL210 (-1.12) and the unknown tolerance level variety DBW222 (-2.38%) compared with the control under salt stress conditions. A decrease in the K + /Na + ratio was observed under salt stress conditions. The maximum K + /Na + ratio accumulation was observed in KRL210 (6.16), and the minimum was observed in K9162 (1.25) under salt stress conditions (Table 2). Proline as an osmoprotectant Exposure to salinity stress leads to the accumulation of osmolytes for better protection of cellular functions. Proline acts as an osmolyte under stress conditions. The maximum accumulation of proline was observed in KRL210 (8.52 µmol/gFW), and the minimum accumulation was detected in the sensitive variety HD2009 (3.36 µmol/gFW) under salt stress conditions. The highest percent increase was observed in the tolerant variety KRL210 (240.24%) and the unknown tolerance level variety DBW222 (226.39%), and the least percent increase was observed in the sensitive varieties K9162 (38.38%) and HD2009 (39.56%) under salt stress conditions (Table 2). Yield contributing factors The sensitive genotypes exhibited a decrease in yield under salt stress conditions, while the tolerant and moderately tolerant cultivars maintained their photosynthetic ability; consequently, their yield was less affected by salinity. A decrease in spike length was observed in sensitive wheat cultivars under salinity stress. The maximum spike length was observed in KRL210 (13.77 cm), and the minimum spike length was observed in HD2009 (9.43 cm) under salt stress conditions. The highest percent reduction in spike length compared to the control was observed in K9162 (15.71%) and HD2009 (-14.24), while the greatest percent increase in spike length was observed in the tolerant varieties GW503 (20.63%) and KRL210 (18%) (Table 4). GW/S decreased under salinity stress in sensitive wheat cultivars, while the maximum GW was observed in DBW187 (3.10 g) and the minimum was observed in HD1941 (0.66 gm) under salt stress conditions. The maximum percent reduction was observed in GW89 (-40.60%), HD2009 (-31.25%), and K9162 (-26.80), whereas the maximum percent increase was found in the tolerant cultivars DBW187 (33.26%) and DWR162 (19.88%) under salt stress compared to the control (Table 4). The TGW decreased under salinity stress in sensitive wheat cultivars, and the maximum TGW was observed in KH65 (39.21gm) and the minimum TGW was observed in GW89 (21.38 gm) under salt stress conditions. A higher percent reduction was detected in HD1941 (-24.64%), K9162 (-22.55%) and HD2009 (-22.50), whereas a percent increase was found in the tolerant variety KRL210 (11.57%) and unknown tolerance level variety DBW222 (9.57%) under salt stress. The highest reduction in thousand-grain weight was found in the sensitive varieties (Table 4). Hectoliter weight (HW) decreased significantly (p ≤ 0.05) in sensitive varieties. The Hectolitre weight is a measure of the volume of grain per unit. It is a good measure of grain quality and is used by millers globally as an indicator of expected flour yield. The maximum HW was observed in KH65 (76.1g) and the minimum was observed in K9162 (58.05 gm) under salt stress conditions. The highest percent reduction was observed in GW89 (-17.37%) and HD1941 (-15.74%), whereas the highest percent increase was observed in the tolerant variety KRL210 (3.82%) (Table 4). Salt stress is generally associated with an increase in quality-related parameters such as PC, gluten, and sedimentation value, but not moisture content. Therefore, the maximum protein content was observed in NI5643 (16.28%), the minimum was found in PBW65 (12.92%) under the control, the maximum was found in GW89 (16.67%), and the minimum was found in PBW65 (13.35%) under salt stress conditions (Table 4). Among the sensitive varieties, K9162 (12.15%), GW89 (11.92%), and HD2009 (11.85%) had the greatest increase in protein content, whereas less of an increase was observed among the tolerant variety GW503 (1.17%) and the unknown tolerance level variety DBW187 (1.30%). The maximum moisture content was observed in KRL210 (11.34%), the minimum moisture content was found in HD2009 (10.04%) under the control, the maximum moisture content was found in DWR162 (11.10%), and the minimum moisture content was found in K9162 (9.31%) under salt stress conditions. A decrease in moisture level was observed under salinity stress, and the greatest percentage reduction was observed in the sensitive varieties K9162 (-13.19%) and GW89 (-10.97%) compared to the control, while a smaller percentage reduction was found in DBW303 (-0.90%) (Table 4). A sedimentation test was performed, and an increase in all varieties was observed under salinity stress. The maximum sedimentation value was observed in DBW187 (67.78 ml), and the minimum sedimentation value was found in PBW502 (40.25 ml) under the control, while the maximum sedimentation value was found in K9162 (65.49 ml), and the minimum sedimentation value was found in PBW502 (47.18 ml) under salt stress conditions (Table 5). The greatest percent increase was observed for the sensitive varieties K9162 (44.09%) and GW89 (33.88%), and the least percent change was observed for the DBW187 (10.22%) and tolerant KRL210 (10.62%) and KH65 (12.22%) varieties (Table 5). Gluten content The gluten content was significantly affected by salinity stress. The maximum wet gluten content was observed in HD3086 (30.5%), the minimum was found in KH65 (26.4%) under the control conditions, and the maximum was found in GW89 (36.8%), while the minimum was found in KH65 (28.2%) under salt stress conditions (Table 5). The maximum dry gluten content was observed in HD1941 (11.1%), the minimum was found in KRL210 (9.1%) under the control conditions, the maximum was found in HD1941 (13.6%), and the minimum was found in KRL210 (9.7%) under salt stress conditions. The highest percentage change in wet gluten was found in GW89 (32.85%), and the least percentage change was found in DBW222 (5.78%) and KRL210 (6.74%) compared to the control under salt stress. The highest percent change in dry gluten was found in K9162 (30.30%), and the least percentage change was found in DBW222 (3.85%) and KRL210 (6.59%) compared to the control under salt stress (Table 5). Statistical analysis Principal component analysis (PCA) PCA based on a correlation matrix was performed to study the relationships among 20 different wheat genotypes and different parameters related to growth, physiological, biochemical, yield, and quality traits under both control and salt conditions. Biplot vectors are trait factor loadings for PC1 and PC2 of 25 measured traits. Under control conditions, PC1 and PC2 explained 32.58% of the total variance (Fig. 1a), and under salt conditions, PC1 and PC2 explained 70.41% of the total variance (Fig. 1b). This PCA revealed four groups of genotypes based upon their salt tolerance level and all the parameters measured. The first group consisted of the highly tolerant genotypes KH65 and KRL210 along with three varieties of unknown tolerance, namely, DBW187, DBW222, and DBW303. This group was characterized by high activity of the enzymes CAT, APX, GR, and SOD under salt stress. The second group also contained the tolerant varieties AJANTA, PBW502, GW503 and GW190. This group had a high RWC, chlorophyll content, HW and moisture content. The third group contained the moderately tolerant genotypes NW1076, NW1014, and NI5643, and these genotypes showed elevated Na + and protein contents. The fourth group contained the sensitive genotypes HD1941, HD2009, GW89, K9162, and HD3086. This group had high Na + , H 2 O 2 , MDA and gluten contents. Under control conditions, Na + had a negative correlation with PC1 and a positive correlation with PC2. K + showed a positive correlation for both PC1 and PC2. Under salt conditions, Na + was negatively correlated with both PC1 and PC2, and K + was positively correlated with PC1 but negatively correlated with PC2 (Fig. 1a). Correlation analysis between different traits Correlation analysis between morphophysiological, osmoprotectants, biochemical, yield, and quality-related parameters was performed under control and salinity stress conditions (Fig. 2a; Fig. 2b). Under salt stress conditions, correlation analysis revealed a positive correlation between the Na + content and the MDA and H 2 O 2 contents (r = 0.84, and 0.78; p < 0.05), whereas the K + content negatively correlated with the H 2 O 2 content (r = -0.86; p < 0.05). The Na + content was positively correlated with the wet gluten and dry gluten contents (r = 0.81 and 0.80; p < 0.05, respectively) under salt stress. A positive correlation was observed between the yield parameter GW/S and SOD (r = 0.87; p < 0.05) under salinity stress, indicating a synergistic relationship. A significant positive correlation (p ≤ 0.05) was detected between the yield parameter GW/S and the proline content (r = 0.82; p < 0.05), and a negative correlation was detected between the GW/S and the Na + content (r = -0.80, p < 0.05) under salinity stress, which indicates an antagonistic relationship (Fig. 2b). K + content positively correlated with GW/S (r = 0.71; p < 0.05) under salinity stress. SOD, proline and K + exhibited a synergistic relationship with yield under salinity stress; conversely, Na + exhibited an antagonistic relationship with yield under salinity stress. Discussion The adverse effects of salinity on associated morphophysiological, biochemical, and yield-related traits are researchable areas for the development of better-performing salt-tolerant genotypes. Large agricultural areas in arid and semiarid regions worldwide are affected by salinity, which is projected to worsen due to abrupt climatic change [ 30 ]. These findings suggest that several important physio-biochemical parameters are useful and effective for evaluating the salt tolerance of wheat cultivars and are good indicators of grain yield and related growth parameters under salinity stress. The loss of intracellular water content in plants is one of the main consequences of salinity. Water content is the key factor in the determination of growth and development in plants. Salinity stress decreases root hydraulic conductivity and reduces the water reuptake requirement from the soil, which in turn causes a significant reduction in leaf water content and leads to a decreased transpiration rate and photosynthetic efficiency [ 31 , 32 ]. In the present study, compared with the moderately tolerant and tolerant cultivars, the moderately sensitive NW1014, NI5643 and sensitive cultivars K9162, HD2009, HD1941, and GW89 exhibited significant reductions in RWC, MSI, NDVI, and chlorophyll content. Compared with the salt-sensitive cultivar, the salt-tolerant wheat cultivar had greater leaf water potential and RWC, which is positively associated with the accumulation of more osmoprotectants, indicating that the tolerant cultivar underwent effective osmotic adjustment. Sensitive cultivars are less capable of adjusting osmotically under salt stress conditions. Munns [ 33 ] reported that a reduction in plant water status under salinity stress is the major cause of growth reduction. The tolerant varieties KRL210 and KH65 and of unknown tolerance varieties DBW187 and DBW222 displayed improved performance under salinity stress compared to the control. The results suggested that a greater reduction in photosynthetic pigments in sensitive varieties resulted in a decrease in growth and yield under salt stress. Overproduction of ROS, including H 2 O 2 , O 2 - and OH −, as a result of salinity stress leads to the degradation of chlorophyll pigments, which are harmful oxidative markers [ 34 ]. Salinity treatment was observed to increase the generation of H 2 O 2 and free radicals, causing significant damage to membrane lipids and loss of the membrane stability index. To prevent the oxidative damage that is triggered by ROS, plants intensify ROS-scavenging mechanisms. In the present study, salt stress elevated the level of H 2 O 2 . It has been reported that increased accumulation of ROS enhances antioxidant defense mechanisms, particularly in tolerant varieties [ 10 ]. MDA is one of the final products of the peroxidation of polyunsaturated fatty acids in the cell membrane. An increase in free radicals causes the overproduction of MDA, which is commonly known as a marker of oxidative stress and is used for evaluating plant tolerance or sensitivity to salt stress. MDA and electrolyte leakage (EL) diminish cell membrane integrity, cellular water content, and metabolic functions under salinity stress conditions. In this study, less accumulation of MDA was observed in the tolerant variety, and greater accumulation was observed in the sensitive wheat cultivars. Feki [ 35 ] reported that tolerance in wheat was associated with decreased accumulation of MDA and increased activity of antioxidant enzymes, which was substantiated by our results. Plants utilize a complex antioxidant defense system to mitigate salt stress-induced damage [ 36 ]. CAT acts as a primary cellular H 2 O 2 scavenging system by converting H 2 O 2 to water and oxygen [ 6 ]. SOD is considered the main intracellular enzymatic antioxidant because it provides the first line of defense against ROS toxicity [ 6 ]. In the present study, the antioxidant activities of the enzymes SOD, CAT, APX, and GR were observed higher in tolerant, unknown tolerance level, and moderately tolerant wheat genotypes than in sensitive cultivars. The results indicate that the ability of the genotypes to utilize their antioxidant system plays an important role in limiting the damage caused by salinity stress [ 13 , 37 ]. It was reported that CAT and APX work in coordination with SOD activity to counteract the negative effects of O 2 − and H 2 O 2 − generated by salinity stress, which was also confirmed in this study [ 38 ]. To obtain electrons from the photosynthetic electron transport chain and reduce the production of ROS, increasing GR activity might increase NADP + concentrations [ 39 ]. Furthermore, our study implies that salt-tolerant genotypes might have a more active ascorbate-glutathione cycle. A greater accumulation of Na + in plants in response to salt stress interferes with the accumulation of K + and further affects stomatal regulation. Previous studies have shown that the accumulation of Na + due to salt stress reduces the K + and chlorophyll contents in plants, which further leads to a decrease in growth [ 40 ]. Tolerant cultivars displayed improved K + /Na + ratio maintenance under salt stress. The soluble sugar content, proline content, chlorophyll content, and Na +/ K + ratio significantly change under salinity stress, as they are important indicators of salt tolerance, as observed in Catharanthus roseus [ 41 ], Brassica oleracea [ 42 ] and Zea mays [ 43 ]. The accumulation of osmoprotectants in plant cells is an important mechanism for preserving the osmotic balance for the maintenance of physiochemical processes in cells. Salt stress increased proline accumulation, which subsequently improved photosynthetic efficiency, ATP production, and water use efficiency. Proline is a non-enzymatic antioxidant and plays a vital role in osmotic adjustment under salinity stress. Reducing the amount of ROS generated as a result of salt stress decreases the harmful effects of ROS and increases plant tolerance. Moreover, proline improves plant antioxidant systems. Proline accumulation assisted plants in recompensing energy and increased their survival under salinity stress [ 44 ]. The proline content is considered an optimal indicator for recognizing salinity stress, particularly at high salinity levels. The current study demonstrated that the proline concentration in the leaves of wheat plants under salinity stress increased considerably compared with that in the leaves of non stressed plants. The maximum concentration of proline was detected in the tolerant wheat cultivar KRL210 and the unknown tolerance level variety DBW187 under salt stress. Among the three varieties, DBW 187, DBW 222 and DBW 303 exhibited the same behaviour for traits associated with salinity tolerance as did the tolerant genotypes; hence, DBW 187, DBW 222 and DBW 303 can be considered tolerant, which was further corroborated through PCA of the traits. The reduction in GW in our findings is consistent with those of others who have shown decreased weight of grains in wheat plants exposed to salt stress. The GW and its alterations in response to salt stress were lower in tolerant, of unknown tolerance and moderate varieties than in sensitive wheat cultivars. Under saline conditions, all glycophytes generally exhibit yield losses due to altered water and nutritional balance, a lower source-to-sink ratio, and inefficient photosynthetic efficiency [ 45 ]. Salt stress is known to affect plant height and spike length in wheat, where increasing salinity significantly reduces spike length [ 46 ]. The observed yield loss due to high salt stress during the reproduction and grain filling periods is in agreement with previous reports on wheat. A greater reduction in grain weight under saline conditions resulted in a considerable decrease in grain yield per plant [ 47 ]. Salt-tolerant wheat cultivars with lower Na + contents produced higher grain and biological yields under saline conditions. The reduction in grain yield under salt stress might have resulted from several causes, such as loss of photosynthetic capacity because of the effects of salinity on leaf development or longevity or the reduction in fertilization via a reduction in pollen viability and/or stigma receptivity. Salt stress was associated with an increase in quality-related traits, such as protein content and sedimentation value, but not moisture content. Salinity reduces yield primarily by causing severe reductions in spike number, grain number, and 1,000-grain weight in wheat [ 48 ]. Salinity stress leads to an increase in protein content and a decrease in protein quality. Increased PC due to other abiotic stresses, such as heat stress, has also been noted by other researchers [ 49 , 50 ], revealing that heat-induced grain weight loss is more significant than the loss of protein accumulation [ 51 ]. This finding is consistent with the observation that heat-sensitive genotypes possessed a much lower yield than other genotypes under heat stress conditions and, correspondingly, had a much greater PC in their grains. An increase in PC due to high temperatures during the grain-filling period can be partly explained by altered source-to-sink carbon partitioning and thereby interactions with metabolism and partitioning of N in sources and sinks [ 49 ]. In previous studies, it was reported that wet gluten and dry gluten contents, sodium dodecyl sulfate (SDS) sedimentation volume, and grain protein content significantly increased as a result of salt and drought stress. Both saline and drought stress conditions resulted in considerable reductions in thousand-grain weight, grain protein yield, and test weight [ 52 ]. Conclusion Wheat cultivars with different genetic backgrounds showed diverse responses to salinity stress, which helped to identify key morpho-physiological, biochemical, yield, and quality-related parameters governing the anticipated salt tolerance. The MDA content, MSI, nonenzymatic osmolyte concentration, antioxidant enzyme activity, and toxic ion uptake significantly increased with increasing salinity. The salt-tolerant and moderately salt-tolerant genotypes showed evidence of possessing a more efficient mechanism against salt stress by protecting themselves from ion toxicity and osmotic injury and maintaining higher contents of K + , photosynthetic pigments, and non-enzymatic osmolytes and greater antioxidant enzyme activity under salinity stress than in salt-sensitive genotypes. The proline content, K + content, and antioxidants parameters CAT, APX, SOD, and GR were found to be positively correlated with the yield-related parameters SL, GW/S, HW, and TGW under salinity stress. The unknown tolerance level varieties DBW187, DBW303, and DBW222 showed better adaptation to salinity stress due to their effective antioxidant system and higher proline and K + contents in line with those of the tolerant varieties. These varieties can be effectively used for the further development of salinity-tolerant lines and can also be cultivated in saline-sodic areas. Correlation analyses of parameters under salinity stress showed that the SOD and proline parameters were strongly positively correlated and that the Na + content was strongly negatively correlated with the grain weight per spike. Hence, these three factors could serve as effective criteria for the rapid screening of germplasms against salinity stress for the identification of new elite lines in breeding programs. Materials and methodology A total of 20 wheat cultivars tolerant, moderate, sensitive, and unknown tolerance, varieties were used in this study (Supplementary Table 1). All healthy seeds were procured from the Germplasm Resource Unit (GRU), Indian Institute of Wheat and Barley Research (IIWBR), Karnal, India. The study was conducted at the IIWBR during the 2021–2022 and 2022–2023 seasons. The field experiment was conducted using a randomized complete block design (RCBD) with three rows in each growing season. Each microplot was 3 × 6 × 1.5 m in size and had a transparent sheet of rain cover. The two microplots used for this study were as follows: 1) a control with normal soil (pH 8.0, EC 3.9) and 2) saline-sodic (pH 9.4, EC 3.9) soil. Microplots with sodic conditions were developed by adding the required quantity of sodium bicarbonate (NaHCO 3 ) and sodium carbonate (Na 2 CO 3 ) to the soil. The different wheat cultivars were planted in the third week of November. The crop was irrigated normally, and fertilizer was applied as per recommended agronomic practices (120 kg N, 60 kg P 2 O 5 , and 40 kg K 2 O per ha) with a full dosage of P 2 O 5 of 30 kg/ha and K 2 O of 20 kg/ha at the time of sowing and N in three split doses of 60 kg/ha. Various morpho-physiological parameters, namely, chlorophyll content, NDVI, proline content, and Na + /K + content, and biochemical parameters, such as H 2 O 2 , MDA, GR, SOD, CAT, and APX, were analysed at the flag leaf stage after heading, and fresh leaf samples were used for analysis of these experiments. Yield-related parameters, namely, plant height (PH), spike length (LS), grain weight per spike (GW/S), thousand-grain weight (TGW), and hectoliter weight (HW), were estimated at the maturity stage. All the chemicals used were of the highest quality and were procured from Sigma‒Aldrich unless otherwise mentioned. Physiological parameters The chlorophyll content was measured at the flag leaf stage using a chlorophyll meter (SPAD-502, Minolta, Japan) for all the genotypes under both control and stress conditions. Three biological replicates and three technical replicates from both the control and stress conditions were selected, and SPAD values were recorded from the fully mature leaves counted from the top of the plants. The normalized difference vegetation index (NDVI) was measured at the flag leaf stage using the Crop Circle model ACS-430 from Holland Scientific (Lincoln, NE, USA) at 1.5 months from 0.5 m above the canopy. The membrane stability index (MSI) was estimated by measuring the electrical conductivity of the leaf leachates in DDW. The method of [ 17 ] was used to determine electrolyte leakage. Leaves were cut into small pieces and placed in a test tube containing 20 ml of deionized water. The electrical conductivity (EC)1 was determined after shaking the tubes for 4 h at 30°C. The test tubes were then autoclaved at 121°C for 20 minutes and cooled to 25°C before the electrical conductivity (EC2) was measured. The following formula was used to determine electrolyte leakage (EC): EC1/EC2*100. Hiscox and Israelstam's [ 18 ] method was used to determine the total chlorophyll concentration by using dimethyl sulfoxide (DMSO) as a solubilizing reagent. Briefly, leaf discs 1 cm in diameter were weighed (g) and placed in a test tube with 5 ml of DMSO. The test tubes were then placed in an oven for approximately 4 h at 60°C to facilitate the extraction of chlorophyll pigments. After reaching room temperature (2 hours), the O.D. was recorded at 2 different wavelengths, i.e., 645 and 665 nm, by using a UV‒VIS spectrophotometer (Thermo Scientific, Japan). Welburn's [ 19 ] equations were used to determine the different pigments. The concentrations of all the pigments were calculated in mg g − 1 tissue fresh weight. Chl 'a' (µg/ml) = 12.19 A665–3.45 A645 Chl 'b' (µg/ml) = 21.99 A645–3.32 A665 Total chlorophyll = Chl 'a' + Chl 'b'. Antioxidant parameters Determination of H 2 O 2 content The concentration of H 2 O 2 was estimated by extracting fresh leaf samples at the flag leaf stage in 0.1% (w/v) trichloroacetic acid (TCA) using a mortar and pestle. After centrifugation at 12,000× g for 15 min, a known volume of the supernatant was mixed with 0.5 mL of 10 mM potassium phosphate buffer (pH 7.0) and 1 M potassium iodide (1 mL). Subsequently, the optical density of the mixture was measured at 390 nm, and the results are expressed as µmol g-1 FW using the extinction coefficient of 0.28 µM-1 cm -1 H 2 O 2 [ 20 ]. Determination of MDA content Lipid peroxidation was measured by estimating the MDA content [ 21 ]. For lipid peroxidation determination, fresh leaves were extracted in 1%, w/v, TCA. After centrifugation at 10,000× g for 5 min, 1.0 mL of the supernatant was mixed with 0.5% thiobarbituric acid (TBA), and the mixture was boiled at 95°C for half an hour. After that, the tubes were kept in an ice bath, followed by centrifugation for 5 min at 5000× g for clarification, and the optical density was measured at 532 nm and 600 nm. The MDA concentration was determined by dividing the difference in absorbance (A532–A600) by its molar extinction coefficient (155 mM − 1 cm − 1 ), and the results are expressed as mmol g − 1 fresh weight. Enzymatic assays The activity of the enzyme APX was assayed according to the protocol of [ 22 ]. The 3 ml reaction mixture was composed of 2.8 ml of 50 mM potassium phosphate buffer (pH 7.0), 15 µl of 0.5 mM ascorbic acid, 30 µl of tissue extract, and 155 µl of 0.5 mM H 2 O 2 . The decrease in absorbance at 290 nm was recorded, and an extinction coefficient of 2.8 mM - 1 cm -1 for reduced ascorbate was used to calculate the enzyme activity. The specific enzyme activity was expressed as µmol mg -1 protein min -1 . SOD activity was assayed using the method of [ 23 ]. For the measurement of SOD activity, 100 µl of supernatant and 400 µl of riboflavin (1 mM) were mixed with 2.5 ml of assay mixture comprising 50 mM phosphate buffer (pH 7.8) supplemented with (2 mM) EDTA, (9 mM) L-Met, (50 µM) NBT and 0.025% Triton X100. The reaction was initiated by illuminating the samples for 10 minutes, followed by recording the absorbance at 560 nm instantaneously after the reaction stopped. The enzyme activity (gFW -1 ) was estimated from the standard curve using pure SOD. The irradiation of the samples was performed under 20 W fluorescent light lamps for 40 min. The absorbance of this irradiated solution was measured at 560 nm with a spectrophotometer (Double Beam Spectrophotometer-UV 3000+, Lab-India Analytical). The enzyme activity of CAT was estimated based on H 2 O 2 decomposition at a wavelength of 240 nm for 5 min according to the method of [ 24 ]. The reaction mixture (1.5 mL) was composed of 50 mM potassium phosphate buffer (pH 7.0), EDTA (0.1 mM), H 2 O 2 (30%), and the enzyme extract (100 µL). The reduction in the OD was followed up to 5 min, and 1 unit of CAT was defined as 1 mmol H 2 O 2 mL − m min − m . GR activity was assayed by recording the increase in absorbance in the presence of oxidized glutathione (GSSG) and 5,5-dithiobis-2-nitrobenzoic acid (DTNB) [ 25 ]. For GR determination, a 3 ml assay mixture comprising 100 µl of supernatant, 1.82 ml of potassium phosphate buffer, 50 mM EDTA (2 mM), 750 µl of DTNB (0.75 mM), 30 µl of NADPH (0.1 mM), and 300 µl of GSSG (1 mM) (oxidized glutathione) was used. The reaction was initiated by the addition of GSSG, and the increase in absorbance at 412 nm was recorded for 5 minutes. The GR activity was calculated using the extinction coefficient of TNB (14.15 m-1 cm -1 ) and expressed in terms of mM TNB min/gFW [ 25 ]. Na + /K + Estimation Twenty-one-day-old flag leaves were used for the evaluation of Na + and K + . One hundred-milligram flag leaf samples were dried for 48 h at 65°C and digested with 0.5 ml of 0.5 N HNO 3 for 2 h at 80°C [ 26 ]. The digested samples were centrifuged and diluted 100 times with distilled water. Concentrations of Na + and K + ions were measured by flame photometry using standards in the range of 0.25–20 ppm and expressed as milligrams per gram dry weight (mg/g DW). Proline estimation Proline was extracted from a 21-day-old flag leaf as previously described [ 27 ]. Fifty milligrams of fresh leaf sample was homogenized in 3% sulfosalicylic acid (5 µl/mg FW), kept on ice for 5 min, and centrifuged at 14,000 rpm for 10 min at room temperature, after which the resulting supernatant was used for determining the proline content. The reaction mixture containing 200 µl of glacial acetic acid, 200 µl of ninhydrin reagent, and 100 µl of supernatant was incubated for 20 min at 90°C in a water bath. The reaction was terminated by transferring the reaction mixture tubes to ice. One milliliter of toluene was added to the reaction mixture, and the mixture was vortexed. The upper toluene phase was taken for measurement of proline using absorbance at 520 nm. The proline content was measured against proline as the calibration standard and expressed in micromole per gram fresh weight (µmol/gFW). Yield- and quality-related parameters Spike length was estimated at the time of maturity just before harvesting using a standard scale. Spike length was estimated from its base to the tip excluding the awns and measured in cm. The grain weight per spike (GW/S) was estimated after harvesting. The TGW was determined using an automatic seed counter (Digital Seed Counter, Green Agritech), and an average weight of grain samples from two years for both the control and salt stress conditions was taken from each plot. Hectoliter weight (HW) The HW was determined using a hectometer (Indigenous test weight instrument, IIWBR) and measured as kg/hl for both control and salt stress conditions [ 28 ]. Protein and moisture content The grain protein content and grain moisture content were determined by near-infrared reflectance spectroscopy (NIR, Analyser Inframatic 8620, FOSS) for both the control and under salt conditions. Sedimentation test A sedimentation test is used to measure gluten strength among different wheat genotypes. The SDS sedimentation test measures the sedimentation value of the suspension of flour in an SDS-lactic acid solution. The sedimentation value depends mainly upon the amount and swelling characteristics of glutenin. The sedimentation test was performed according to the standard protocol of the IIWBR [ 28 ]. Gluten content The gluten content of the whole meal flour was estimated using the gluten-washing method [ 29 ]. The wet gluten (WG) content was measured immediately after washing the flour with tap water, and the wet gluten obtained was dried in a hot air oven at 100°C for 24 hr, after which the dry gluten (DG) content was estimated. Statistical analysis The experiments were arranged in a randomized complete block design with three replications. The data obtained were analysed by ANOVA, and all means were separated at the p < 0.05 level using Tukey’s HSD test. Analysis was performed using STAR ver. 2.0.1 software. The data are presented as the mean ± SD from three independent biological replications for each sample. Principal component analysis (PCA) was performed on various physiological, biochemical, yield, and quality-related parameters by using PAST software (version 4.06b), and PCA plots were generated using (principal component) PC1 and PC2. Correlation analysis was performed using Minitab software. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials All data generated or analysed during this study are included in this manuscript and its supplementary information files. Competing interests The authors declare that they have no competing interests. Funding The authors are thankful to ICAR-Indian Institute of Wheat and Barley Research (IIWBR), Karnal for providing support and facilities for experiments. Authors Contributions NP, VP, AY, SR planned and designed the experiments; NP performed plant growth experiments; NP, VP carried out data interpretation; NP, VP, OPG analyzed qPCR gene expression; NP and VP drafted the manuscript; OPG, VP, AY, MRM, SR, NP and GS revised the manuscript. All authors read and approved the final version of the ma-nuscript. Acknowledgements The authors are thankful to ICAR-Indian Institute of Wheat and Barley Research (IIWBR), Karnal for providing support and facilities for experiments. The authors NP and AY are also thankful to the Department of Biotechnolo-gy, Kurukshetra University, Kurukshetra for their support. Availability of data and materials Data related to the publication are included in the manuscript. References Gupta OP, Pandey V, Saini R, Khandale T, Singh A, Malik VK, Narwal S, Ram S, & Singh GP. 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Tables Tables 1 to 5 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx SupplementaryData.docx Supplementary Table 1. List of 20 wheat cultivars used for this study along with their pedigree and year of release Cite Share Download PDF Status: Published Journal Publication published 20 Sep, 2024 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 08 Jul, 2024 Reviews received at journal 04 Jul, 2024 Reviewers agreed at journal 18 Jun, 2024 Reviews received at journal 09 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviewers agreed at journal 01 Jun, 2024 Reviewers agreed at journal 31 May, 2024 Reviewers invited by journal 31 May, 2024 Editor assigned by journal 27 May, 2024 Submission checks completed at journal 27 May, 2024 First submitted to journal 21 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4454318","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312369683,"identity":"5ca38a2c-ce07-472f-be67-fc12f170cd31","order_by":0,"name":"Neha Patwa","email":"","orcid":"","institution":"Indian Institute of Wheat and Barley Research","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Patwa","suffix":""},{"id":312369684,"identity":"9419f514-00e5-4f6d-93dd-bed3a5363261","order_by":1,"name":"Vanita Pandey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYJACCQjF2MDAUAGkmZkbiNbS2MBwBqSFkWgtQGsY22DW4QHm7GcP3vjYxpDYP7u5/cHPebXR/O1ALT8qtuHUYtmTl2w5E6hlxp2DjY29247nzjgMtK3nzG2cWgwO5JhJ87YxGDPcSGxs4N12LLcBqIWZsQ2PlvNvzKT/ArXIA7U0/p1zLHc+QS03gLYAfS1nANTSzNtQk7uBkBbLGW+MLXvOScgZArXMljl2IHcjUMtBfH4x588xvPGjzIZH7kb6g49vaupy550/fPDBjwo8DgMRjGywqGE4DCYP4FQP08LwB86vw6d4FIyCUTAKRigAAItJX3/l75FQAAAAAElFTkSuQmCC","orcid":"","institution":"Indian Institute of Wheat and Barley Research","correspondingAuthor":true,"prefix":"","firstName":"Vanita","middleName":"","lastName":"Pandey","suffix":""},{"id":312369685,"identity":"989a7be8-90cc-4cb2-be4b-b32ed4603ac0","order_by":2,"name":"Om Parkash Gupta","email":"","orcid":"","institution":"Indian Institute of Wheat and Barley Research","correspondingAuthor":false,"prefix":"","firstName":"Om","middleName":"Parkash","lastName":"Gupta","suffix":""},{"id":312369686,"identity":"239bbcee-4665-4bd8-80e4-b074aa0c13cd","order_by":3,"name":"Anita Yadav","email":"","orcid":"","institution":"Kurukshetra University","correspondingAuthor":false,"prefix":"","firstName":"Anita","middleName":"","lastName":"Yadav","suffix":""},{"id":312369687,"identity":"c49c91d7-de2c-46ea-a46a-0c69f6603e42","order_by":4,"name":"Mintu Ram Meena","email":"","orcid":"","institution":"ICAR-Sugarcane Breeding Institute, Regional Station","correspondingAuthor":false,"prefix":"","firstName":"Mintu","middleName":"Ram","lastName":"Meena","suffix":""},{"id":312369688,"identity":"c704fd35-6d70-41b6-b9db-26fa93553a08","order_by":5,"name":"Sewa Ram","email":"","orcid":"","institution":"Indian Institute of Wheat and Barley Research","correspondingAuthor":false,"prefix":"","firstName":"Sewa","middleName":"","lastName":"Ram","suffix":""},{"id":312369689,"identity":"725bea3b-8daf-4a8e-bbb7-272aff165544","order_by":6,"name":"Gyanendra Singh","email":"","orcid":"","institution":"Indian Institute of Wheat and Barley Research","correspondingAuthor":false,"prefix":"","firstName":"Gyanendra","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2024-05-21 11:07:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4454318/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4454318/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-024-05508-4","type":"published","date":"2024-09-20T15:57:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58038314,"identity":"a3af6c3d-0649-4a03-b4df-cba9a373f6d7","added_by":"auto","created_at":"2024-06-10 09:43:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":348607,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis of 20 wheat genotypes under (a) control and (b) salt stress conditions. Biplot vectors are trait loading factors for PC1 and PC2 of different measured traits. Plant height (PH); NDVI; SPAD chlorophyll content; total chlorophyll content (CC); membrane stability index (MSI); relative water content (RWC); H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content; MDA content; SOD, APX, CAT, and GR; Na\u003csup\u003e+\u003c/sup\u003e content; K\u003csup\u003e+\u003c/sup\u003e content; K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio; proline content; spike length (SL); grain weight per spike (GW/S); TGW; hectoliter weight (HW); sedimentation test (SD); wet gluten (WG); and dry gluten (DG).\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4454318/v1/db161c8bea807f7e4f271130.jpg"},{"id":58038311,"identity":"7ecbc78c-a162-4b17-8873-3f51a7efe1be","added_by":"auto","created_at":"2024-06-10 09:43:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":708826,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of wheat based on morpho-physiological, biochemical, yield, and quality-related parameters under (a) control and (b) salt stress conditions at a significance level less than ≤ 0.05. Red indicates positive values, and blue indicates negative values.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4454318/v1/ef7667e5e47f456b7b2d6e79.jpg"},{"id":65104063,"identity":"691c2622-4c1a-4c0c-b103-0a4395f2124e","added_by":"auto","created_at":"2024-09-23 16:11:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1806856,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4454318/v1/a978d4ea-3454-4d06-9307-ca8a9eeff546.pdf"},{"id":58038312,"identity":"be991db4-3448-4ed8-b2e6-e727c7ac5c38","added_by":"auto","created_at":"2024-06-10 09:43:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":52343,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4454318/v1/c240c4a2d6213a3cda336898.docx"},{"id":58038313,"identity":"76484908-4eef-4cad-b5a5-cfaceb7c8b24","added_by":"auto","created_at":"2024-06-10 09:43:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16662,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1. List of 20 wheat cultivars used for this study along with their pedigree and year of release\u003c/p\u003e","description":"","filename":"SupplementaryData.docx","url":"https://assets-eu.researchsquare.com/files/rs-4454318/v1/71e73c9fe130c9784e3792b4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUnravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eWheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.) is a major staple food crop that contributes significantly to food and nutritional security worldwide. Wheat provides approximately 30% of the world\u0026rsquo;s population with 23.8% calories and 33.06% protein requirements [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Abiotic stresses such as salt, heat, and drought create a suboptimal environment and have a negative impact on the yield and productivity of wheat [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Salinity stress in arid and semi-regions of the world leads to a loss in agricultural productivity because of the accumulation of salts in the soil [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. At any stage of crop growth, salt stress causes irreversible losses in yield potential in various crops, including wheat, barley, and rice [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Almost 7\u0026nbsp;million hectares of Indian soil are now contaminated by salt, and by 2050, salinization of the soil will result in the loss of 50% of cultivable land globally [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn salt-affected soils, excess Na\u003csup\u003e+\u003c/sup\u003e ions are present at exchange sites, and high concentrations of carbonate and bicarbonate anions are associated with high pH. High concentrations of Na\u003csup\u003e+\u003c/sup\u003e ions in soils compete for K\u003csup\u003e+\u003c/sup\u003e uptake, which leads to K\u003csup\u003e+\u003c/sup\u003e deficiency and promotes K\u0026thinsp;+\u0026thinsp;leakage from cells. This K\u003csup\u003e+\u003c/sup\u003e-induced deficiency inhibits the growth of plants because it plays an important role in maintaining cell turgor, membrane potential, and enzymatic activities [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Salinity stress is responsible for the generation of osmotic and ionic stresses, the influx of large amounts of Na\u003csup\u003e+\u003c/sup\u003e inside plant cells, and increased Na\u003csup\u003e+\u003c/sup\u003e concentrations in the cytoplasm and vacuole, which are toxic to metabolic mechanisms and lead to cell death.\u003c/p\u003e \u003cp\u003eWheat production is severely hampered by soil salinity, which reduces growth and productivity by lowering water uptake and creating nutritional deficiencies through ion toxicity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Salinity stress leads to a significant reduction in photosynthetic performance and weakens the photosynthetic pigments present in the thylakoid membrane of the chloroplast. High salt toxicity in soil impairs the generation of photosynthetic pigments because of the inhibitory effect of salt ions on the biosynthesis of various chlorophyll components [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The chlorophyll content (CC), relative water content (RWC), normal difference vegetation index (NDVI), and membrane stability index (MSI) in wheat were negatively impacted by soil salinity. Wheat plants are less able to absorb nutrients from roots as the salinity increases because less water is accessible to roots.\u003c/p\u003e \u003cp\u003eIn response to salinity stress, primary plant activities, including protein synthesis, energy production and lipid metabolism, change during the plant's embryonic phases [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As a result of the plant's significant growth retardation, toxic metabolite synthesis and molecular damage can cause plant death [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Plants have developed internal resistance mechanisms to scavenge the harmful effects of reactive oxygen species (ROS), such as superoxide (O\u003csub\u003e2\u003c/sub\u003e), hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e), hydroxyl radical (OH), and singlet oxygen (O\u003csub\u003e2\u003c/sub\u003e), generated due to salinity stress [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. To combat stress, plants modify their metabolism and enzymatic and non-enzymatic antioxidant mechanisms. Plants have also evolved various biochemical defences against osmotic and ionic stress, including osmotic tolerance, ion exclusion, tissue tolerance, synthesis of compatible solutes, amino acids, and organic acids, adjustments to membrane structure, induction of antioxidant defence, and hormone homeostasis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Reactive oxygen species scavenging enzymes, which are part of the antioxidant defence, play a direct role in the degradation of ROS, including CAT (catalase), SOD (superoxide dismutase), GR (glutathione reductase), and APX (ascorbate peroxidase) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. SOD dismutases O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e into H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2,\u003c/sub\u003e which is further catalyzed into H\u003csub\u003e2\u003c/sub\u003eO and O\u003csub\u003e2\u003c/sub\u003e by CAT and APX [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, to overcome the osmotic stress induced by salinity, plants synthesize and accumulate metabolically compatible solutes such as proline, sugars, and betaines. Proline acts as an osmoprotectant and helps plants maintain tissue water potential lower than that of the soil to maintain turgor pressure for growth [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In addition to osmotic balance, these compatible solutes also act as antioxidants and help to stabilize subcellular structures, buffering the cellular redox potential against stress [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWheat grain yield is a quantitative trait affected by salinity stress. Salinity stress suppresses the growth and development of spikes at the reproductive and maturity stages. Plant height, spike length, and grain weight are negatively affected by salinity stress. The ability of wheat to produce unique baked products, such as bread and chapatti, depends on grain quality. This attribute is assessed by physical and compositional properties such as grain hardness (GH), protein content (PC), and moisture content (MC) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This study aimed to assess the effects of salinity stress on physiological, biochemical, yield, and other quality-related parameters in 20 wheat genotypes with different genetic backgrounds to identify parameters that can be used as biomarkers for rapid selection and improvement of salt-tolerant cultivars. The lack of precise indices of physiological and agronomic traits related to salinity stress and the low genetic variability in the currently available wheat germplasm lines are among the main reasons for the limited success in breeding salt-tolerant varieties. Previously reported salt-tolerant varieties have been used for the breeding of crops, but because of a lack of understanding of the mechanism of salt tolerance, less success has been achieved. Most saline-prone areas remain largely uncultivated. Growing salt-tolerant wheat on saline soils could be a significant attempt to use these areas and to meet the demands of the ever-increasing population and to satisfy their food needs. This would be possible by understanding the mechanism behind the variations in the tolerance of different wheat cultivars and by identifying salt-tolerant genotypes.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eAgro-morphology and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ephysiological\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;responses of wheat to saline-sodic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econditions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe agronomic and physiological responses of the wheat genotypes significantly differed\u0026nbsp;under salinity stress. In this study, a significant reduction in agronomic traits during the early flag leaf stage and maturity stage of plants was observed. Significant growth and biomass\u0026nbsp;reductions\u0026nbsp;were observed in twenty wheat cultivars grown under salt stress. All physiological traits,\u0026nbsp;such as plant height, chlorophyll content, SPAD, NDVI, RWC, and MSI, showed\u0026nbsp;significant (\u003cem\u003ep\u003c/em\u003e \u0026le; 0.05)\u0026nbsp;reductions\u0026nbsp;except in\u0026nbsp;the\u0026nbsp;tolerant cultivars under salinity stress compared to their respective controls. The overall means and ranges of these traits for the 20 genotypes\u0026nbsp;under\u0026nbsp;both control and stress conditions are\u0026nbsp;shown\u0026nbsp;in Table 1. Salt stress significantly affects the plant height of wheat genotypes. The highest plant height was found in DBW187 (100.00 cm),\u0026nbsp;and the\u0026nbsp;least plant height\u0026nbsp;was found in GW89 (66.00 cm) under salt stress. The\u0026nbsp;highest percent\u0026nbsp;reduction\u0026nbsp;in plant height\u0026nbsp;was observed\u0026nbsp;for the\u0026nbsp;sensitive varieties HD2009 (-32.03%) and GW89 (-29.29%),\u0026nbsp;followed by\u0026nbsp;the\u0026nbsp;moderate varieties (Table 1), whereas the highest percent increase\u0026nbsp;in\u0026nbsp;plant height was observed for DBW187 (4.20%),\u0026nbsp;the\u0026nbsp;tolerant varieties KRL210 (1.19%),\u0026nbsp;and\u0026nbsp;AJANTA (1.50%) compared to\u0026nbsp;the\u0026nbsp;control under salinity stress (Table 1). The maximum SPAD chlorophyll value was observed in AJANTA (46.60),\u0026nbsp;and\u0026nbsp;the\u0026nbsp;minimum was observed in the sensitive variety HD2009 (38.10) under salt stress. The SPAD chlorophyll value\u0026nbsp;decreased the most in the\u0026nbsp;sensitive variety K9162 (-12.55%) and HD2009 (-12.01%), and a significant\u0026nbsp;percentage\u0026nbsp;increase was observed\u0026nbsp;in the\u0026nbsp;tolerant variety\u0026nbsp;KRL210\u0026nbsp;(2.69%) and AJANTA (1.75%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress (Table 1).\u003c/p\u003e\n\u003cp\u003eThe water status of the plant is expressed by the RWC. The highest relative water content was\u0026nbsp;detected\u0026nbsp;in DBW 17 (85.04%),\u0026nbsp;and\u0026nbsp;the lowest relative water content\u0026nbsp;(41.90%) was\u0026nbsp;detected\u0026nbsp;in sensitive HD1941 under salt stress. In our study, the RWC\u0026nbsp;decreased\u0026nbsp;significantly in some moderate and sensitive wheat cultivars under stress,\u0026nbsp;but\u0026nbsp;greater\u0026nbsp;reductions were observed in sensitive cultivars. The\u0026nbsp;greatest\u0026nbsp;percent reduction was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties HD1941 (-85.48%) and K9162 (-76.93%), whereas an increase in percent change was observed for DBW222 (7.46%),\u0026nbsp;KH65 (5.42%), and DBW17 (0.21%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress (Table 1). The NDVI was measured,\u0026nbsp;and a maximum value was observed in DBW222 (0.71) and a minimum in HD1941 (0.21) under salt stress. The\u0026nbsp;greatest\u0026nbsp;percent reduction was measured in HD1941 (-59.75%) and K9162 (-44.86%),\u0026nbsp;and the lowest was observed in KRL 210 (-0.55%) and DBW187 (-1.43%) compared to the control (Table 1).\u0026nbsp;The maximum\u0026nbsp;MSI was observed in DBW222 (88.64%),\u0026nbsp;and the minimum was found in GW89 (44.01). A\u0026nbsp;greater\u0026nbsp;percentage of the reduction in MSI was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties GW89 (-42.90%), HD3086 (-27.84%), and K9162 (-26.50%)\u0026nbsp;than in the\u0026nbsp;control.\u0026nbsp;The tolerant\u0026nbsp;varieties KRL210 (5.74%) and PBW502 (5.67%) can maintain the integrity of the plasma membrane more efficiently (Table 1).\u0026nbsp;The maximum\u0026nbsp;total chlorophyll accumulation was found in KRL210 (11.62 mg/gFW),\u0026nbsp;and the minimum was found in GW89 (3.97 mg/gFW) under salt stress.\u0026nbsp;A decrease in the\u0026nbsp;total chlorophyll content\u0026nbsp;percentage was detected in the\u0026nbsp;sensitive varieties K9162 (-39.29%) and GW89 (-38.13%),\u0026nbsp;whereas an increase was\u0026nbsp;detected\u0026nbsp;in\u0026nbsp;the\u0026nbsp;tolerant\u0026nbsp;varieties\u0026nbsp;AJANTA (3.07%)\u0026nbsp;and\u0026nbsp;KRL210 (0.18%), and\u0026nbsp;a smaller\u0026nbsp;reduction was\u0026nbsp;detected\u0026nbsp;in\u0026nbsp;the\u0026nbsp;moderate\u0026nbsp;variety\u0026nbsp;PBW65 (-19.96%) under salt stress compared\u0026nbsp;with the\u0026nbsp;control (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe oxidative\u0026nbsp;stress markers H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and MDA increased significantly (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05)\u0026nbsp;under salinity stress. Salt stress\u0026nbsp;led\u0026nbsp;to the accumulation of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in all\u0026nbsp;the\u0026nbsp;wheat genotypes.\u0026nbsp;The sensitive\u0026nbsp;genotype K9162 showed the highest accumulation of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (7.56\u0026nbsp;\u0026mu;mol/g FW),\u0026nbsp;and the\u0026nbsp;lowest\u0026nbsp;was found in KRL210 (4.82\u0026nbsp;\u0026mu;mol/g FW) under salt stress (Table 3). The\u0026nbsp;greatest\u0026nbsp;percent increase was observed\u0026nbsp;for the\u0026nbsp;sensitive\u0026nbsp;varieties\u0026nbsp;K9162 (94.96%) and HD2009 (62.02%),\u0026nbsp;and the least percent increase was observed\u0026nbsp;for the\u0026nbsp;tolerant\u0026nbsp;and of\u0026nbsp;unknown tolerance\u0026nbsp;levels\u0026nbsp;and\u0026nbsp;for the\u0026nbsp;moderate\u0026nbsp;varieties\u0026nbsp;KRL210 (13.75%), DBW222 (15.97%),\u0026nbsp;and\u0026nbsp;KH65 (19.02%) (Table 3). MDA is used as a biomarker\u0026nbsp;of the\u0026nbsp;response to oxidative stress. Salt stress significantly increased the MDA content in all\u0026nbsp;the\u0026nbsp;wheat genotypes. The highest MDA accumulation was observed in the sensitive variety HD2009 (8.38\u0026nbsp;\u0026mu;M/g FW),\u0026nbsp;and the\u0026nbsp;lowest\u0026nbsp;was observed in the tolerant variety KRL210 (3.99\u0026nbsp;\u0026mu;M/g FW) under salt stress. The\u0026nbsp;greatest\u0026nbsp;percent increase was observed among\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (71.54%) and GW89 (70.92%),\u0026nbsp;and the\u0026nbsp;greatest\u0026nbsp;percent reduction was observed among\u0026nbsp;the\u0026nbsp;tolerant varieties KRL210 (-24.35%) and KH65 (-11.70%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress conditions (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntioxidant enzymes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSOD\u0026nbsp;activity increased significantly at p \u0026le; 0.05 in response to salt stress in all\u0026nbsp;the\u0026nbsp;wheat genotypes. The highest SOD activity was observed in KRL210 (30.70 units/g FW),\u0026nbsp;and the\u0026nbsp;lowest activity\u0026nbsp;was observed in HD2009 (14.68 units/g FW).\u0026nbsp;An\u0026nbsp;increase in percent change was observed in\u0026nbsp;the\u0026nbsp;tolerant varieties KRL210 (24.63%) and GW190 (24.62%),\u0026nbsp;whereas a decrease in percent change was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (-32.17%) and HD2009 (-28.62%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress conditions (Table 3).\u0026nbsp;Glutathione\u0026nbsp;(GR) activity was also\u0026nbsp;lower\u0026nbsp;in\u0026nbsp;the\u0026nbsp;sensitive variety\u0026nbsp;than in the\u0026nbsp;tolerant\u0026nbsp;variety\u0026nbsp;under salt stress. The highest GR activity was observed in KRL210 (15.51 mM TNB min/g FW),\u0026nbsp;and the\u0026nbsp;lowest\u0026nbsp;was observed in HD2009 (2.29 mM TNB min/g FW). The highest percent decrease in glutathione activity was\u0026nbsp;detected\u0026nbsp;in\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (-78.28%) and HD1941 (-68.44%), and the highest percent increase in glutathione\u0026nbsp;activity\u0026nbsp;was\u0026nbsp;detected\u0026nbsp;in KRL210 (15.13%) (Table 3). Similar results were also observed for CAT and APX under salt stress. The highest CAT activity was observed in KRL210 (26.49 \u0026mu;moles/min/g FW),\u0026nbsp;and the\u0026nbsp;lowest activity\u0026nbsp;was observed in HD2009 (9.10 \u0026mu;moles/min/g FW) under salt stress. The highest percent reduction in CAT activity was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties HD2009 (-29.78%) and K9162 (-29.44%),\u0026nbsp;whereas a significant percent increase (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) was\u0026nbsp;detected\u0026nbsp;in\u0026nbsp;the\u0026nbsp;tolerant varieties KRL210 (66.92%) AJANTA (65.50%) and\u0026nbsp;the\u0026nbsp;unknown tolerance level varieties DBW222 (68.13%)\u0026nbsp;and\u0026nbsp;DBW187 (59.72%) compared\u0026nbsp;with the\u0026nbsp;control (Table 3). The maximum APX activity was observed in KRL210 (8.51 \u0026mu;moles/min/g FW),\u0026nbsp;and the minimum was observed in HD2009 (1.06 \u0026mu;moles/min/g FW). APX activity was also found to decrease among sensitive varieties. The highest percent reduction was observed in HD2009 (75.00%) and GW89 (-54.65%), and the highest percent increase was observed in\u0026nbsp;the\u0026nbsp;tolerant varieties GW503 (141.67%) and KRL210 (111.11%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress conditions (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNa\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eaccumulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSalinity stress significantly (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) increased\u0026nbsp;the amount of\u0026nbsp;Na\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eions, decreased\u0026nbsp;the\u0026nbsp;K\u003csup\u003e+\u003c/sup\u003e content, and decreased\u0026nbsp;the\u0026nbsp;K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio in\u0026nbsp;the\u0026nbsp;wheat cultivars.\u0026nbsp;The maximum Na\u003csup\u003e+\u003c/sup\u003e content accumulation was observed in HD2009 (9.87 mg/gDW) and the minimum was observed in KRL210 (3.97 mg/gDW) under salt stress conditions (Table 2). A\u0026nbsp;greater percentage\u0026nbsp;increase in Na\u003csup\u003e+\u003c/sup\u003e was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties HD1941 (1323.28%) and GW89 (1261.14%), whereas\u0026nbsp;the\u0026nbsp;tolerant\u0026nbsp;varieties\u0026nbsp;KRL210 (543.78%) and AJANTA (570.46%)\u0026nbsp;exhibited a smaller percentage\u0026nbsp;increase compared\u0026nbsp;with the\u0026nbsp;control under salt stress. Interestingly, the increase in Na\u003csup\u003e+\u003c/sup\u003e content among the cultivars was inversely proportional to the decrease in K\u003csup\u003e+\u003c/sup\u003e content. Under salt stress, a decrease in K\u003csup\u003e+\u003c/sup\u003e content was observed in all\u0026nbsp;the\u0026nbsp;wheat genotypes.\u0026nbsp;The maximum K\u003csup\u003e+\u003c/sup\u003e content accumulation was observed in KRL210 (24.46 mg/gDW) and the minimum was observed in K9162 (11.29 mg/gDW) under salt stress conditions (Table 2). A large\u0026nbsp;percentage\u0026nbsp;reduction was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (-39.30%) and HD1941 (-32.55%) compared\u0026nbsp;with the\u0026nbsp;control, and the lowest\u0026nbsp;percentage\u0026nbsp;reduction was\u0026nbsp;detected\u0026nbsp;in\u0026nbsp;the\u0026nbsp;tolerant variety KRL210 (-1.12) and\u0026nbsp;the\u0026nbsp;unknown tolerance level variety DBW222 (-2.38%) compared\u0026nbsp;with the\u0026nbsp;control under salt stress conditions.\u0026nbsp;A\u0026nbsp;decrease in the K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio was observed under salt stress conditions.\u0026nbsp;The maximum K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio accumulation was observed in KRL210 (6.16),\u0026nbsp;and the minimum was observed in K9162 (1.25) under salt stress conditions (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProline as\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eosmoprotectant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExposure to salinity stress leads to the accumulation of osmolytes for better protection of cellular functions. Proline acts as an osmolyte under stress conditions. The maximum accumulation of proline was observed in KRL210 (8.52 \u0026micro;mol/gFW),\u0026nbsp;and the minimum\u0026nbsp;accumulation\u0026nbsp;was\u0026nbsp;detected\u0026nbsp;in the sensitive variety HD2009 (3.36 \u0026micro;mol/gFW) under salt stress conditions. The highest percent increase was observed in the tolerant variety KRL210 (240.24%) and the unknown tolerance level variety DBW222 (226.39%), and the least percent increase was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (38.38%) and HD2009 (39.56%) under salt stress conditions (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYield contributing factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sensitive genotypes exhibited a decrease in yield under salt stress conditions,\u0026nbsp;while\u0026nbsp;the\u0026nbsp;tolerant and moderately tolerant cultivars maintained their photosynthetic ability;\u0026nbsp;consequently, their yield was less affected\u0026nbsp;by\u0026nbsp;salinity. A\u0026nbsp;decrease\u0026nbsp;in spike length was\u0026nbsp;observed\u0026nbsp;in sensitive wheat cultivars under salinity stress. The maximum spike length was observed in KRL210 (13.77 cm),\u0026nbsp;and the minimum\u0026nbsp;spike length\u0026nbsp;was observed in HD2009 (9.43 cm) under salt stress conditions. The highest percent reduction in spike length compared to\u0026nbsp;the\u0026nbsp;control was observed in K9162 (15.71%) and HD2009 (-14.24), while the\u0026nbsp;greatest\u0026nbsp;percent increase in spike length was observed in\u0026nbsp;the\u0026nbsp;tolerant varieties GW503 (20.63%) and KRL210 (18%) (Table 4).\u003c/p\u003e\n\u003cp\u003eGW/S decreased under salinity stress in sensitive wheat cultivars,\u0026nbsp;while the maximum GW was observed in DBW187 (3.10 g) and the minimum was observed in HD1941 (0.66 gm) under salt stress conditions. The maximum percent reduction was observed in GW89 (-40.60%), HD2009 (-31.25%), and K9162 (-26.80),\u0026nbsp;whereas the maximum percent increase was found in\u0026nbsp;the\u0026nbsp;tolerant cultivars DBW187 (33.26%) and DWR162 (19.88%) under salt stress compared to\u0026nbsp;the\u0026nbsp;control\u0026nbsp;(Table 4).\u0026nbsp;The\u0026nbsp;TGW decreased under salinity stress in sensitive wheat cultivars,\u0026nbsp;and the maximum TGW was observed in KH65 (39.21gm) and the minimum\u0026nbsp;TGW\u0026nbsp;was observed in GW89 (21.38 gm) under salt stress conditions. A higher percent reduction was\u0026nbsp;detected\u0026nbsp;in HD1941 (-24.64%), K9162 (-22.55%) and HD2009 (-22.50),\u0026nbsp;whereas a percent increase was found in\u0026nbsp;the\u0026nbsp;tolerant\u0026nbsp;variety\u0026nbsp;KRL210 (11.57%) and unknown tolerance level variety DBW222 (9.57%) under salt stress. The highest reduction in thousand-grain weight was found in\u0026nbsp;the\u0026nbsp;sensitive varieties (Table 4).\u003c/p\u003e\n\u003cp\u003eHectoliter weight (HW)\u0026nbsp;decreased\u0026nbsp;significantly (p \u0026le; 0.05) in sensitive varieties. The Hectolitre weight is a measure of the volume of grain per unit. It is a good measure of grain quality and is used by millers globally as an\u0026nbsp;indicator\u0026nbsp;of expected flour yield. The maximum HW was observed in KH65 (76.1g) and the minimum was observed in K9162 (58.05 gm) under salt stress conditions.\u0026nbsp;The highest percent reduction was observed in GW89 (-17.37%) and HD1941 (-15.74%),\u0026nbsp;whereas the highest percent increase was observed in\u0026nbsp;the\u0026nbsp;tolerant variety KRL210 (3.82%) (Table 4).\u003c/p\u003e\n\u003cp\u003eSalt stress is generally associated with an increase in quality-related parameters such as PC, gluten, and sedimentation value,\u0026nbsp;but not\u0026nbsp;moisture content. Therefore, the maximum protein content was observed in NI5643 (16.28%),\u0026nbsp;the minimum was found in PBW65 (12.92%) under\u0026nbsp;the\u0026nbsp;control,\u0026nbsp;the maximum was found in GW89 (16.67%), and the minimum\u0026nbsp;was found\u0026nbsp;in PBW65 (13.35%) under salt stress conditions (Table 4).\u0026nbsp;Among the sensitive varieties,\u0026nbsp;K9162 (12.15%), GW89 (11.92%), and HD2009 (11.85%)\u0026nbsp;had the greatest increase in protein content,\u0026nbsp;whereas less\u0026nbsp;of an\u0026nbsp;increase was observed among\u0026nbsp;the\u0026nbsp;tolerant variety GW503 (1.17%) and\u0026nbsp;the\u0026nbsp;unknown tolerance level variety DBW187 (1.30%). The maximum moisture content was observed in KRL210 (11.34%),\u0026nbsp;the minimum\u0026nbsp;moisture content\u0026nbsp;was found in HD2009 (10.04%) under\u0026nbsp;the\u0026nbsp;control,\u0026nbsp;the maximum\u0026nbsp;moisture content\u0026nbsp;was found in DWR162 (11.10%),\u0026nbsp;and\u0026nbsp;the\u0026nbsp;minimum\u0026nbsp;moisture content was found\u0026nbsp;in K9162 (9.31%) under salt stress conditions.\u0026nbsp;A\u0026nbsp;decrease in moisture level was observed under salinity stress,\u0026nbsp;and the\u0026nbsp;greatest percentage\u0026nbsp;reduction was observed in\u0026nbsp;the\u0026nbsp;sensitive varieties K9162 (-13.19%) and GW89 (-10.97%) compared to\u0026nbsp;the\u0026nbsp;control,\u0026nbsp;while a smaller percentage\u0026nbsp;reduction was found in DBW303 (-0.90%) (Table 4).\u003c/p\u003e\n\u003cp\u003eA\u0026nbsp;sedimentation test was performed,\u0026nbsp;and an increase\u0026nbsp;in all varieties\u0026nbsp;was observed under salinity stress. The maximum sedimentation value was observed in DBW187 (67.78 ml),\u0026nbsp;and the minimum\u0026nbsp;sedimentation value\u0026nbsp;was found in PBW502 (40.25 ml) under\u0026nbsp;the\u0026nbsp;control,\u0026nbsp;while the maximum\u0026nbsp;sedimentation value\u0026nbsp;was found in K9162 (65.49 ml),\u0026nbsp;and\u0026nbsp;the\u0026nbsp;minimum\u0026nbsp;sedimentation value was found\u0026nbsp;in PBW502 (47.18 ml) under salt stress conditions (Table 5). The\u0026nbsp;greatest\u0026nbsp;percent increase was observed\u0026nbsp;for the\u0026nbsp;sensitive varieties K9162 (44.09%) and GW89 (33.88%), and the least percent change was observed\u0026nbsp;for the\u0026nbsp;DBW187 (10.22%) and tolerant KRL210 (10.62%) and KH65 (12.22%) varieties (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGluten content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gluten\u0026nbsp;content was significantly affected by salinity stress. The maximum wet gluten\u0026nbsp;content\u0026nbsp;was observed in HD3086 (30.5%),\u0026nbsp;the minimum was found in KH65 (26.4%) under\u0026nbsp;the\u0026nbsp;control\u0026nbsp;conditions,\u0026nbsp;and the maximum was found in GW89 (36.8%), while the\u0026nbsp;minimum\u0026nbsp;was found\u0026nbsp;in KH65 (28.2%) under salt stress conditions (Table 5). The maximum dry gluten\u0026nbsp;content\u0026nbsp;was observed in HD1941 (11.1%),\u0026nbsp;the minimum was found in KRL210 (9.1%) under\u0026nbsp;the\u0026nbsp;control\u0026nbsp;conditions,\u0026nbsp;the maximum was found in HD1941 (13.6%),\u0026nbsp;and\u0026nbsp;the\u0026nbsp;minimum\u0026nbsp;was found\u0026nbsp;in KRL210 (9.7%) under salt stress conditions. The highest percentage change in wet gluten was found in GW89 (32.85%),\u0026nbsp;and the least\u0026nbsp;percentage\u0026nbsp;change was found in DBW222 (5.78%) and KRL210 (6.74%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress. The highest percent change in dry gluten was found in K9162 (30.30%),\u0026nbsp;and the least\u0026nbsp;percentage\u0026nbsp;change was found in DBW222 (3.85%) and KRL210 (6.59%) compared to\u0026nbsp;the\u0026nbsp;control under salt stress (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrincipal component analysis (PCA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePCA based on\u0026nbsp;a\u0026nbsp;correlation matrix was performed to study the\u0026nbsp;relationships\u0026nbsp;among 20 different wheat genotypes and different parameters related to growth, physiological, biochemical, yield, and quality traits under both control and salt conditions. Biplot vectors are trait\u0026nbsp;factor loadings\u0026nbsp;for PC1 and PC2 of 25 measured traits. Under control conditions, PC1 and PC2 explained 32.58% of the total variance (Fig.\u0026nbsp;1a), and under salt conditions, PC1 and PC2 explained 70.41% of the total variance (Fig.\u0026nbsp;1b). This PCA revealed four groups of genotypes based upon their salt tolerance level and all the parameters measured. The first group\u0026nbsp;consisted of the\u0026nbsp;highly tolerant genotypes KH65 and KRL210 along with three varieties of unknown tolerance, namely, DBW187, DBW222, and DBW303. This group was characterized by high\u0026nbsp;activity of the enzymes\u0026nbsp;CAT, APX, GR, and SOD under salt stress. The second group also contained\u0026nbsp;the\u0026nbsp;tolerant varieties AJANTA, PBW502, GW503 and GW190. This group\u0026nbsp;had a\u0026nbsp;high RWC, chlorophyll content, HW and moisture content. The third group contained the moderately tolerant genotypes NW1076, NW1014, and NI5643,\u0026nbsp;and these genotypes showed elevated Na\u003csup\u003e+\u003c/sup\u003e and protein\u0026nbsp;contents. The fourth group contained the sensitive genotypes HD1941, HD2009, GW89, K9162, and HD3086. This group had high Na\u003csup\u003e+\u003c/sup\u003e, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, MDA and gluten\u0026nbsp;contents. Under control conditions, Na\u003csup\u003e+\u003c/sup\u003e had\u0026nbsp;a negative correlation with PC1 and a positive\u0026nbsp;correlation\u0026nbsp;with PC2. K\u003csup\u003e+\u003c/sup\u003e showed a positive correlation for both PC1 and PC2. Under salt conditions, Na\u003csup\u003e+\u003c/sup\u003e was negatively correlated with\u0026nbsp;both PC1 and PC2,\u0026nbsp;and K\u003csup\u003e+\u003c/sup\u003e was positively correlated with PC1 but negatively correlated with PC2 (Fig.\u0026nbsp;1a).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analysis between different traits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation analysis between\u0026nbsp;morphophysiological, osmoprotectants, biochemical, yield, and quality-related parameters was performed under control and salinity stress conditions (Fig.\u0026nbsp;2a; Fig.\u0026nbsp;2b). Under salt stress\u0026nbsp;conditions,\u0026nbsp;correlation analysis\u0026nbsp;revealed a\u0026nbsp;positive correlation between\u0026nbsp;the\u0026nbsp;Na\u003csup\u003e+\u003c/sup\u003e content\u0026nbsp;and the\u0026nbsp;MDA and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e contents\u0026nbsp;(r = 0.84, and 0.78; p \u0026lt; 0.05),\u0026nbsp;whereas\u0026nbsp;the\u0026nbsp;K\u003csup\u003e+\u003c/sup\u003e content negatively\u0026nbsp;correlated\u0026nbsp;with\u0026nbsp;the\u0026nbsp;H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content\u0026nbsp;(r = -0.86; p \u0026lt; 0.05).\u0026nbsp;The\u0026nbsp;Na\u003csup\u003e+\u003c/sup\u003e content\u0026nbsp;was positively correlated with the\u0026nbsp;wet gluten and dry gluten\u0026nbsp;contents\u0026nbsp;(r = 0.81 and 0.80; p \u0026lt; 0.05, respectively) under salt stress. A positive correlation was observed between\u0026nbsp;the\u0026nbsp;yield parameter GW/S and SOD (r = 0.87; p \u0026lt; 0.05) under salinity stress, indicating a synergistic relationship. A significant positive correlation\u0026nbsp;(p \u0026le; 0.05)\u0026nbsp;was\u0026nbsp;detected\u0026nbsp;between\u0026nbsp;the\u0026nbsp;yield parameter GW/S and\u0026nbsp;the\u0026nbsp;proline content (r = 0.82; p \u0026lt; 0.05),\u0026nbsp;and a negative correlation\u0026nbsp;was detected\u0026nbsp;between\u0026nbsp;the\u0026nbsp;GW/S and\u0026nbsp;the\u0026nbsp;Na\u003csup\u003e+\u003c/sup\u003e content (r = -0.80, p \u0026lt; 0.05) under salinity stress,\u0026nbsp;which indicates an antagonistic relationship (Fig.\u0026nbsp;2b). K\u003csup\u003e+\u003c/sup\u003e content positively\u0026nbsp;correlated\u0026nbsp;with GW/S (r = 0.71; p \u0026lt;\u0026nbsp;0.05) under salinity stress. SOD, proline and K\u003csup\u003e+\u003c/sup\u003e exhibited\u0026nbsp;a synergistic relationship with yield under salinity stress;\u0026nbsp;conversely,\u0026nbsp;Na\u003csup\u003e+\u003c/sup\u003e exhibited an antagonistic relationship with yield under salinity stress.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe adverse effects of salinity on associated morphophysiological, biochemical, and yield-related traits are researchable areas for the development of better-performing salt-tolerant genotypes. Large agricultural areas in arid and semiarid regions worldwide are affected by salinity, which is projected to worsen due to abrupt climatic change [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These findings suggest that several important physio-biochemical parameters are useful and effective for evaluating the salt tolerance of wheat cultivars and are good indicators of grain yield and related growth parameters under salinity stress. The loss of intracellular water content in plants is one of the main consequences of salinity. Water content is the key factor in the determination of growth and development in plants. Salinity stress decreases root hydraulic conductivity and reduces the water reuptake requirement from the soil, which in turn causes a significant reduction in leaf water content and leads to a decreased transpiration rate and photosynthetic efficiency [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the present study, compared with the moderately tolerant and tolerant cultivars, the moderately sensitive NW1014, NI5643 and sensitive cultivars K9162, HD2009, HD1941, and GW89 exhibited significant reductions in RWC, MSI, NDVI, and chlorophyll content. Compared with the salt-sensitive cultivar, the salt-tolerant wheat cultivar had greater leaf water potential and RWC, which is positively associated with the accumulation of more osmoprotectants, indicating that the tolerant cultivar underwent effective osmotic adjustment. Sensitive cultivars are less capable of adjusting osmotically under salt stress conditions. Munns [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] reported that a reduction in plant water status under salinity stress is the major cause of growth reduction. The tolerant varieties KRL210 and KH65 and of unknown tolerance varieties DBW187 and DBW222 displayed improved performance under salinity stress compared to the control. The results suggested that a greater reduction in photosynthetic pigments in sensitive varieties resulted in a decrease in growth and yield under salt stress.\u003c/p\u003e \u003cp\u003eOverproduction of ROS, including H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, O\u003csub\u003e2\u003c/sub\u003e- and OH\u003csup\u003e\u0026minus;,\u003c/sup\u003e as a result of salinity stress leads to the degradation of chlorophyll pigments, which are harmful oxidative markers [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Salinity treatment was observed to increase the generation of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and free radicals, causing significant damage to membrane lipids and loss of the membrane stability index. To prevent the oxidative damage that is triggered by ROS, plants intensify ROS-scavenging mechanisms. In the present study, salt stress elevated the level of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. It has been reported that increased accumulation of ROS enhances antioxidant defense mechanisms, particularly in tolerant varieties [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. MDA is one of the final products of the peroxidation of polyunsaturated fatty acids in the cell membrane. An increase in free radicals causes the overproduction of MDA, which is commonly known as a marker of oxidative stress and is used for evaluating plant tolerance or sensitivity to salt stress. MDA and electrolyte leakage (EL) diminish cell membrane integrity, cellular water content, and metabolic functions under salinity stress conditions. In this study, less accumulation of MDA was observed in the tolerant variety, and greater accumulation was observed in the sensitive wheat cultivars. Feki [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported that tolerance in wheat was associated with decreased accumulation of MDA and increased activity of antioxidant enzymes, which was substantiated by our results.\u003c/p\u003e \u003cp\u003ePlants utilize a complex antioxidant defense system to mitigate salt stress-induced damage [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. CAT acts as a primary cellular H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e scavenging system by converting H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e to water and oxygen [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. SOD is considered the main intracellular enzymatic antioxidant because it provides the first line of defense against ROS toxicity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the present study, the antioxidant activities of the enzymes SOD, CAT, APX, and GR were observed higher in tolerant, unknown tolerance level, and moderately tolerant wheat genotypes than in sensitive cultivars. The results indicate that the ability of the genotypes to utilize their antioxidant system plays an important role in limiting the damage caused by salinity stress [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. It was reported that CAT and APX work in coordination with SOD activity to counteract the negative effects of O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e generated by salinity stress, which was also confirmed in this study [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. To obtain electrons from the photosynthetic electron transport chain and reduce the production of ROS, increasing GR activity might increase NADP\u003csup\u003e+\u003c/sup\u003e concentrations [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Furthermore, our study implies that salt-tolerant genotypes might have a more active ascorbate-glutathione cycle.\u003c/p\u003e \u003cp\u003eA greater accumulation of Na\u003csup\u003e+\u003c/sup\u003e in plants in response to salt stress interferes with the accumulation of K\u003csup\u003e+\u003c/sup\u003e and further affects stomatal regulation. Previous studies have shown that the accumulation of Na\u003csup\u003e+\u003c/sup\u003e due to salt stress reduces the K\u003csup\u003e+\u003c/sup\u003e and chlorophyll contents in plants, which further leads to a decrease in growth [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Tolerant cultivars displayed improved K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio maintenance under salt stress. The soluble sugar content, proline content, chlorophyll content, and Na\u003csup\u003e+/\u003c/sup\u003eK\u003csup\u003e+\u003c/sup\u003e ratio significantly change under salinity stress, as they are important indicators of salt tolerance, as observed in \u003cem\u003eCatharanthus roseus\u003c/em\u003e [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], \u003cem\u003eBrassica oleracea\u003c/em\u003e [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and \u003cem\u003eZea mays\u003c/em\u003e [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The accumulation of osmoprotectants in plant cells is an important mechanism for preserving the osmotic balance for the maintenance of physiochemical processes in cells. Salt stress increased proline accumulation, which subsequently improved photosynthetic efficiency, ATP production, and water use efficiency. Proline is a non-enzymatic antioxidant and plays a vital role in osmotic adjustment under salinity stress. Reducing the amount of ROS generated as a result of salt stress decreases the harmful effects of ROS and increases plant tolerance. Moreover, proline improves plant antioxidant systems. Proline accumulation assisted plants in recompensing energy and increased their survival under salinity stress [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The proline content is considered an optimal indicator for recognizing salinity stress, particularly at high salinity levels. The current study demonstrated that the proline concentration in the leaves of wheat plants under salinity stress increased considerably compared with that in the leaves of non stressed plants. The maximum concentration of proline was detected in the tolerant wheat cultivar KRL210 and the unknown tolerance level variety DBW187 under salt stress. Among the three varieties, DBW 187, DBW 222 and DBW 303 exhibited the same behaviour for traits associated with salinity tolerance as did the tolerant genotypes; hence, DBW 187, DBW 222 and DBW 303 can be considered tolerant, which was further corroborated through PCA of the traits.\u003c/p\u003e \u003cp\u003eThe reduction in GW in our findings is consistent with those of others who have shown decreased weight of grains in wheat plants exposed to salt stress. The GW and its alterations in response to salt stress were lower in tolerant, of unknown tolerance and moderate varieties than in sensitive wheat cultivars. Under saline conditions, all glycophytes generally exhibit yield losses due to altered water and nutritional balance, a lower source-to-sink ratio, and inefficient photosynthetic efficiency [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Salt stress is known to affect plant height and spike length in wheat, where increasing salinity significantly reduces spike length [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The observed yield loss due to high salt stress during the reproduction and grain filling periods is in agreement with previous reports on wheat. A greater reduction in grain weight under saline conditions resulted in a considerable decrease in grain yield per plant [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Salt-tolerant wheat cultivars with lower Na\u003csup\u003e+\u003c/sup\u003e contents produced higher grain and biological yields under saline conditions. The reduction in grain yield under salt stress might have resulted from several causes, such as loss of photosynthetic capacity because of the effects of salinity on leaf development or longevity or the reduction in fertilization via a reduction in pollen viability and/or stigma receptivity.\u003c/p\u003e \u003cp\u003eSalt stress was associated with an increase in quality-related traits, such as protein content and sedimentation value, but not moisture content. Salinity reduces yield primarily by causing severe reductions in spike number, grain number, and 1,000-grain weight in wheat [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Salinity stress leads to an increase in protein content and a decrease in protein quality. Increased PC due to other abiotic stresses, such as heat stress, has also been noted by other researchers [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], revealing that heat-induced grain weight loss is more significant than the loss of protein accumulation [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. This finding is consistent with the observation that heat-sensitive genotypes possessed a much lower yield than other genotypes under heat stress conditions and, correspondingly, had a much greater PC in their grains. An increase in PC due to high temperatures during the grain-filling period can be partly explained by altered source-to-sink carbon partitioning and thereby interactions with metabolism and partitioning of N in sources and sinks [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In previous studies, it was reported that wet gluten and dry gluten contents, sodium dodecyl sulfate (SDS) sedimentation volume, and grain protein content significantly increased as a result of salt and drought stress. Both saline and drought stress conditions resulted in considerable reductions in thousand-grain weight, grain protein yield, and test weight [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWheat cultivars with different genetic backgrounds showed diverse responses to salinity stress, which helped to identify key morpho-physiological, biochemical, yield, and quality-related parameters governing the anticipated salt tolerance. The MDA content, MSI, nonenzymatic osmolyte concentration, antioxidant enzyme activity, and toxic ion uptake significantly increased with increasing salinity. The salt-tolerant and moderately salt-tolerant genotypes showed evidence of possessing a more efficient mechanism against salt stress by protecting themselves from ion toxicity and osmotic injury and maintaining higher contents of K\u003csup\u003e+\u003c/sup\u003e, photosynthetic pigments, and non-enzymatic osmolytes and greater antioxidant enzyme activity under salinity stress than in salt-sensitive genotypes. The proline content, K\u003csup\u003e+\u003c/sup\u003e content, and antioxidants parameters CAT, APX, SOD, and GR were found to be positively correlated with the yield-related parameters SL, GW/S, HW, and TGW under salinity stress. The unknown tolerance level varieties DBW187, DBW303, and DBW222 showed better adaptation to salinity stress due to their effective antioxidant system and higher proline and K\u003csup\u003e+\u003c/sup\u003e contents in line with those of the tolerant varieties. These varieties can be effectively used for the further development of salinity-tolerant lines and can also be cultivated in saline-sodic areas. Correlation analyses of parameters under salinity stress showed that the SOD and proline parameters were strongly positively correlated and that the Na\u003csup\u003e+\u003c/sup\u003e content was strongly negatively correlated with the grain weight per spike. Hence, these three factors could serve as effective criteria for the rapid screening of germplasms against salinity stress for the identification of new elite lines in breeding programs.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Materials and methodology","content":"\u003cp\u003eA total of 20 wheat cultivars tolerant, moderate, sensitive, and unknown tolerance, varieties were used in this study (Supplementary Table\u0026nbsp;1). All healthy seeds were procured from the Germplasm Resource Unit (GRU), Indian Institute of Wheat and Barley Research (IIWBR), Karnal, India. The study was conducted at the IIWBR during the 2021–2022 and 2022–2023 seasons. The field experiment was conducted using a randomized complete block design (RCBD) with three rows in each growing season. Each microplot was 3 × 6 × 1.5 m in size and had a transparent sheet of rain cover. The two microplots used for this study were as follows: 1) a control with normal soil (pH 8.0, EC 3.9) and 2) saline-sodic (pH 9.4, EC 3.9) soil. Microplots with sodic conditions were developed by adding the required quantity of sodium bicarbonate (NaHCO\u003csub\u003e3\u003c/sub\u003e) and sodium carbonate (Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e) to the soil. The different wheat cultivars were planted in the third week of November. The crop was irrigated normally, and fertilizer was applied as per recommended agronomic practices (120 kg N, 60 kg P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e, and 40 kg K\u003csub\u003e2\u003c/sub\u003eO per ha) with a full dosage of P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e of 30 kg/ha and K\u003csub\u003e2\u003c/sub\u003eO of 20 kg/ha at the time of sowing and N in three split doses of 60 kg/ha. Various morpho-physiological parameters, namely, chlorophyll content, NDVI, proline content, and Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e content, and biochemical parameters, such as H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, MDA, GR, SOD, CAT, and APX, were analysed at the flag leaf stage after heading, and fresh leaf samples were used for analysis of these experiments. Yield-related parameters, namely, plant height (PH), spike length (LS), grain weight per spike (GW/S), thousand-grain weight (TGW), and hectoliter weight (HW), were estimated at the maturity stage. All the chemicals used were of the highest quality and were procured from Sigma‒Aldrich unless otherwise mentioned.\u003c/p\u003e\u003ch2\u003ePhysiological parameters\u003c/h2\u003e\u003cp\u003eThe chlorophyll content was measured at the flag leaf stage using a chlorophyll meter (SPAD-502, Minolta, Japan) for all the genotypes under both control and stress conditions. Three biological replicates and three technical replicates from both the control and stress conditions were selected, and SPAD values were recorded from the fully mature leaves counted from the top of the plants. The normalized difference vegetation index (NDVI) was measured at the flag leaf stage using the Crop Circle model ACS-430 from Holland Scientific (Lincoln, NE, USA) at 1.5 months from 0.5 m above the canopy. The membrane stability index (MSI) was estimated by measuring the electrical conductivity of the leaf leachates in DDW. The method of [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] was used to determine electrolyte leakage. Leaves were cut into small pieces and placed in a test tube containing 20 ml of deionized water. The electrical conductivity (EC)1 was determined after shaking the tubes for 4 h at 30°C. The test tubes were then autoclaved at 121°C for 20 minutes and cooled to 25°C before the electrical conductivity (EC2) was measured. The following formula was used to determine electrolyte leakage (EC): EC1/EC2*100.\u003c/p\u003e\u003cp\u003eHiscox and Israelstam's [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] method was used to determine the total chlorophyll concentration by using dimethyl sulfoxide (DMSO) as a solubilizing reagent. Briefly, leaf discs 1 cm in diameter were weighed (g) and placed in a test tube with 5 ml of DMSO. The test tubes were then placed in an oven for approximately 4 h at 60°C to facilitate the extraction of chlorophyll pigments. After reaching room temperature (2 hours), the O.D. was recorded at 2 different wavelengths, i.e., 645 and 665 nm, by using a UV‒VIS spectrophotometer (Thermo Scientific, Japan). Welburn's [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] equations were used to determine the different pigments. The concentrations of all the pigments were calculated in mg g\u003csup\u003e− 1\u003c/sup\u003e tissue fresh weight. Chl 'a' (µg/ml) = 12.19 A665–3.45 A645 Chl 'b' (µg/ml) = 21.99 A645–3.32 A665 Total chlorophyll = Chl 'a' + Chl 'b'.\u003c/p\u003e\u003ch2\u003eAntioxidant parameters\u003c/h2\u003e\u003ch2\u003eDetermination of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content\u003c/h2\u003e\u003cp\u003eThe concentration of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e was estimated by extracting fresh leaf samples at the flag leaf stage in 0.1% (w/v) trichloroacetic acid (TCA) using a mortar and pestle. After centrifugation at 12,000× g for 15 min, a known volume of the supernatant was mixed with 0.5 mL of 10 mM potassium phosphate buffer (pH 7.0) and 1 M potassium iodide (1 mL). Subsequently, the optical density of the mixture was measured at 390 nm, and the results are expressed as µmol g-1 FW using the extinction coefficient of 0.28 µM-1 cm\u003csup\u003e-1\u003c/sup\u003e H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eDetermination of MDA content\u003c/h2\u003e\u003cp\u003eLipid peroxidation was measured by estimating the MDA content [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For lipid peroxidation determination, fresh leaves were extracted in 1%, w/v, TCA. After centrifugation at 10,000× g for 5 min, 1.0 mL of the supernatant was mixed with 0.5% thiobarbituric acid (TBA), and the mixture was boiled at 95°C for half an hour. After that, the tubes were kept in an ice bath, followed by centrifugation for 5 min at 5000× g for clarification, and the optical density was measured at 532 nm and 600 nm. The MDA concentration was determined by dividing the difference in absorbance (A532–A600) by its molar extinction coefficient (155 mM\u003csup\u003e− 1\u003c/sup\u003e cm\u003csup\u003e− 1\u003c/sup\u003e), and the results are expressed as mmol g\u003csup\u003e− 1\u003c/sup\u003e fresh weight.\u003c/p\u003e\u003ch2\u003eEnzymatic assays\u003c/h2\u003e\u003cp\u003eThe activity of the enzyme APX was assayed according to the protocol of [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The 3 ml reaction mixture was composed of 2.8 ml of 50 mM potassium phosphate buffer (pH 7.0), 15 µl of 0.5 mM ascorbic acid, 30 µl of tissue extract, and 155 µl of 0.5 mM H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The decrease in absorbance at 290 nm was recorded, and an extinction coefficient of 2.8 mM\u003csup\u003e-\u003c/sup\u003e1 cm\u003csup\u003e-1\u003c/sup\u003e for reduced ascorbate was used to calculate the enzyme activity. The specific enzyme activity was expressed as µmol mg\u003csup\u003e-1\u003c/sup\u003e protein min\u003csup\u003e-1\u003c/sup\u003e. SOD activity was assayed using the method of [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For the measurement of SOD activity, 100 µl of supernatant and 400 µl of riboflavin (1 mM) were mixed with 2.5 ml of assay mixture comprising 50 mM phosphate buffer (pH 7.8) supplemented with (2 mM) EDTA, (9 mM) L-Met, (50 µM) NBT and 0.025% Triton X100. The reaction was initiated by illuminating the samples for 10 minutes, followed by recording the absorbance at 560 nm instantaneously after the reaction stopped. The enzyme activity (gFW\u003csup\u003e-1\u003c/sup\u003e) was estimated from the standard curve using pure SOD. The irradiation of the samples was performed under 20 W fluorescent light lamps for 40 min. The absorbance of this irradiated solution was measured at 560 nm with a spectrophotometer (Double Beam Spectrophotometer-UV 3000+, Lab-India Analytical). The enzyme activity of CAT was estimated based on H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e decomposition at a wavelength of 240 nm for 5 min according to the method of [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The reaction mixture (1.5 mL) was composed of 50 mM potassium phosphate buffer (pH 7.0), EDTA (0.1 mM), H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (30%), and the enzyme extract (100 µL). The reduction in the OD was followed up to 5 min, and 1 unit of CAT was defined as 1 mmol H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e mL\u003csup\u003e− m\u003c/sup\u003e min\u003csup\u003e− m\u003c/sup\u003e. GR activity was assayed by recording the increase in absorbance in the presence of oxidized glutathione (GSSG) and 5,5-dithiobis-2-nitrobenzoic acid (DTNB) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. For GR determination, a 3 ml assay mixture comprising 100 µl of supernatant, 1.82 ml of potassium phosphate buffer, 50 mM EDTA (2 mM), 750 µl of DTNB (0.75 mM), 30 µl of NADPH (0.1 mM), and 300 µl of GSSG (1 mM) (oxidized glutathione) was used. The reaction was initiated by the addition of GSSG, and the increase in absorbance at 412 nm was recorded for 5 minutes. The GR activity was calculated using the extinction coefficient of TNB (14.15 m-1 cm\u003csup\u003e-1\u003c/sup\u003e) and expressed in terms of mM TNB min/gFW [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eNa\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e Estimation\u003c/h2\u003e\u003cp\u003eTwenty-one-day-old flag leaves were used for the evaluation of Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e. One hundred-milligram flag leaf samples were dried for 48 h at 65°C and digested with 0.5 ml of 0.5 N HNO\u003csub\u003e3\u003c/sub\u003e for 2 h at 80°C [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The digested samples were centrifuged and diluted 100 times with distilled water. Concentrations of Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e ions were measured by flame photometry using standards in the range of 0.25–20 ppm and expressed as milligrams per gram dry weight (mg/g DW).\u003c/p\u003e\u003ch2\u003eProline estimation\u003c/h2\u003e\u003cp\u003eProline was extracted from a 21-day-old flag leaf as previously described [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Fifty milligrams of fresh leaf sample was homogenized in 3% sulfosalicylic acid (5 µl/mg FW), kept on ice for 5 min, and centrifuged at 14,000 rpm for 10 min at room temperature, after which the resulting supernatant was used for determining the proline content. The reaction mixture containing 200 µl of glacial acetic acid, 200 µl of ninhydrin reagent, and 100 µl of supernatant was incubated for 20 min at 90°C in a water bath. The reaction was terminated by transferring the reaction mixture tubes to ice. One milliliter of toluene was added to the reaction mixture, and the mixture was vortexed. The upper toluene phase was taken for measurement of proline using absorbance at 520 nm. The proline content was measured against proline as the calibration standard and expressed in micromole per gram fresh weight (µmol/gFW).\u003c/p\u003e\u003ch2\u003eYield- and quality-related parameters\u003c/h2\u003e\u003cp\u003eSpike length was estimated at the time of maturity just before harvesting using a standard scale. Spike length was estimated from its base to the tip excluding the awns and measured in cm. The grain weight per spike (GW/S) was estimated after harvesting. The TGW was determined using an automatic seed counter (Digital Seed Counter, Green Agritech), and an average weight of grain samples from two years for both the control and salt stress conditions was taken from each plot.\u003c/p\u003e\u003ch2\u003eHectoliter weight (HW)\u003c/h2\u003e\u003cp\u003eThe HW was determined using a hectometer (Indigenous test weight instrument, IIWBR) and measured as kg/hl for both control and salt stress conditions [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eProtein and moisture content\u003c/h2\u003e\u003cp\u003eThe grain protein content and grain moisture content were determined by near-infrared reflectance spectroscopy (NIR, Analyser Inframatic 8620, FOSS) for both the control and under salt conditions.\u003c/p\u003e\u003ch2\u003eSedimentation test\u003c/h2\u003e\u003cp\u003eA sedimentation test is used to measure gluten strength among different wheat genotypes. The SDS sedimentation test measures the sedimentation value of the suspension of flour in an SDS-lactic acid solution. The sedimentation value depends mainly upon the amount and swelling characteristics of glutenin. The sedimentation test was performed according to the standard protocol of the IIWBR [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eGluten content\u003c/h2\u003e\u003cp\u003eThe gluten content of the whole meal flour was estimated using the gluten-washing method [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The wet gluten (WG) content was measured immediately after washing the flour with tap water, and the wet gluten obtained was dried in a hot air oven at 100°C for 24 hr, after which the dry gluten (DG) content was estimated.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe experiments were arranged in a randomized complete block design with three replications. The data obtained were analysed by ANOVA, and all means were separated at the p \u0026lt; 0.05 level using Tukey’s HSD test. Analysis was performed using STAR ver. 2.0.1 software. The data are presented as the mean ± SD from three independent biological replications for each sample. Principal component analysis (PCA) was performed on various physiological, biochemical, yield, and quality-related parameters by using PAST software (version 4.06b), and PCA plots were generated using (principal component) PC1 and PC2. Correlation analysis was performed using Minitab software.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this manuscript and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to ICAR-Indian Institute of Wheat and Barley Research (IIWBR), Karnal for providing support and facilities for experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNP, VP, AY, SR planned and designed the experiments; NP performed plant growth experiments; NP, VP carried out data interpretation; NP, VP, OPG analyzed qPCR gene expression; NP and VP drafted the manuscript; OPG, VP, AY, MRM, SR, NP and GS revised the manuscript. All authors read and approved the final version of the ma-nuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful to ICAR-Indian Institute of Wheat and Barley Research (IIWBR), Karnal for providing support and facilities for experiments. The authors NP and AY are also thankful to the Department of Biotechnolo-gy, Kurukshetra University, Kurukshetra for their support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData related to the publication are included in the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGupta OP, Pandey V, Saini R, Khandale T, Singh A, Malik VK, Narwal S, Ram S, \u0026amp; Singh GP. 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Effects of salinity and drought stress on grain quality of durum wheat. \u003cem\u003eCommunications in soil science and plant analysis\u003c/em\u003e. 2014;\u003cem\u003e45\u003c/em\u003e(3):297-308.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"salt stress, oxidative stress, wheat, yield, quality","lastPublishedDoi":"10.21203/rs.3.rs-4454318/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4454318/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e Salt stress is a prominent abiotic stressor that imposes constraints on grain yield and quality across various crops, including wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e). This study focused on assessing the genetic diversity of 20 wheat genotypes categorized as tolerant, moderately tolerant, and sensitive with three genotypes of unknown tolerance. To address salinity stress-related problems, different morphophysiological, osmoprotectant, biochemical, yield, and grain quality-related parameters were analyzed under saline-sodic conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e The research findings revealed noteworthy variations among the genotypes in response to salinity stress. Greater accumulation of Na\u003csup\u003e+\u003c/sup\u003e and lower K\u003csup\u003e+\u003c/sup\u003e content were observed in response to salt stress in the sensitive varieties HD1941 and K9162. Proline, a stress indicator, exhibited significantly (p ≤ 0.05) greater accumulation in response to salinity stress, particularly in the tolerant cultivars KRL210 and KH65. Salt stress induced the most significant decrease (p ≤ 0.05) in spike length, thousand-grain weight, and hectolitre weight coupled with an increase in protein content in sensitive varieties such as K9162 and HD1941, resulting in diminished yield. Furthermore, salt-sensitive genotypes exhibited elevated protein content, reduced moisture, and increased sedimentation value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e Correlation analysis of parameters under salinity stress showed that SOD, proline, and K\u003csup\u003e+\u003c/sup\u003e contents can be used as the most efficient screening criteria for salinity stress during early developmental stages. Principal component analysis (PCA) revealed that DBW187, DBW303, and DBW222 varieties were tolerant to salinity stress and exhibited an effective antioxidant system against salinity. This study will facilitate salt-tolerant wheat breeding in terms of the identification of tolerant lines by screening for limited traits in a wide range of germplasms.\u003c/p\u003e","manuscriptTitle":"Unravelling wheat genotypic responses: insights into salinity stress tolerance in relation to oxidative stress, antioxidant mechanisms, osmolyte accumulation and grain quality parameters","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-10 09:43:28","doi":"10.21203/rs.3.rs-4454318/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T11:26:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-04T07:34:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"118952501238104410835752018029484304655","date":"2024-06-18T09:06:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-10T01:04:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339304190316938580570278845309076469299","date":"2024-06-02T13:53:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293817583622076674543758393779857532967","date":"2024-06-01T22:21:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14574862663275269582736674444376694679","date":"2024-06-01T01:33:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-31T16:06:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-27T20:45:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-27T20:44:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2024-05-21T11:06:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c5b06cb1-e6f5-46fd-99e6-8aaa4848a6dc","owner":[],"postedDate":"June 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T16:04:27+00:00","versionOfRecord":{"articleIdentity":"rs-4454318","link":"https://doi.org/10.1186/s12870-024-05508-4","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2024-09-20 15:57:54","publishedOnDateReadable":"September 20th, 2024"},"versionCreatedAt":"2024-06-10 09:43:28","video":"","vorDoi":"10.1186/s12870-024-05508-4","vorDoiUrl":"https://doi.org/10.1186/s12870-024-05508-4","workflowStages":[]},"version":"v1","identity":"rs-4454318","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4454318","identity":"rs-4454318","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}