Improving the genetic potential of okra (Abelmoschus esculentus L.) germplasm to tolerate salinity stress

Okra (Abelmoschus esculentus L.) is the most consumed vegetable worldwide with the potential for diverse ecological adaptation. However, increasing salinization and changing climatic conditions are posing serious threats to the growth, yield, and quality of okra. Therefore, to mitigate increasing soil salinization and ensure sustainable okra production under rapidly changing climatic conditions, evaluation of new okra germplasm to develop salt tolerant cultivars is direly needed. The present study was designed to evaluate the genetic resources of okra genotypes for salt tolerance at growth and reproductive phases. Based on mophological and physio-biochemical responses of plants under stress condition, genotypes were divided into salt tolerant and succeptible groups. The experiment was comprised of 100 okra genotypes and each genotype was grown under control conditions and 6.5 dS m−1 NaCl concentration in a pot having 10 kg capacity. The experiment was conducted in a completely randomized design and each treatment was replicated three times. The results showed vast genetic variability among the evaluated okra germplasm traits like days to emergence, pod length, pod diameter, plant height, stem girth, and other yield-related parameters. Correlation analysis showed a highly significant positive association among the number of leaves at first flower and plant height at first flower.Likewise, pod weight also revealed a highly significant positive relationship for pod weight plant-1, pod length, and K+: Na+. Principal Component Analysis (PCA) revealed that out of 16 principal components (PCs), five components showed more than one eigenvalue and the first six PCs contributed 67.2% of the variation. Bi-plot analysis illustrated that genotypes 95, 111, 133, 99, and 128, under salt stress conditions, exhibited both high yield per plant and salt-tolerant behavior in other yield-related traits. On the basis of all studied traits, a salt susceptible group and a salt-tolerant group were formed. The salt tolerant group comprised of 97, 68, 95, 114, 64, 99, 111, 133, 128, and 109 genotypes, whereas, the salt susceptible group contained 137, 139, 130, 94, and 125 genotypes. Salt-tolerant okra genotypes were suggested to be used in further breeding programs aimed to develop salt tolerance in okra. These insights will empower precision breeding, underscore the importance of genetic diversity, and bear the potential to address the challenges of salt-affected soils while promoting broader agricultural resilience, economic prosperity, and food security.

www.nature.com/scientificreports/ the rising salinization rates and increasing vegetable demand in Pakistan, this study aims to investigate the salt tolerance potential of okra (Abelmoschus esculentus L.) genotypesand identify genotypes suitable for further breeding programs.This would help to develop salt tolerant okra cultivars which will facilitate sustainable okra cultivation without compromizing the yield and improve farm income.

Growth and yield characteristics
Genetic diversity in plant breeding is a major tool that could also influence the salt tolerance mechanism of okra lines.The salt concentration exhibited a negative correlation with the ontogeny of the breeding accessions, growth and yield characteristics and variation in the concentration of Na + , K + and K + /Na + ratio.The okra genotypes were also graded for their relative tolerance to NaCl salinity (6.5 dS m −1 ).Salinity stress had highly significant (P ≤ 0.01) and variable effects on growth and yield characteristics in terms of DTE, DTF, plant height at first flower (PFF), No. of leaves at first flower (NL), No. of pods per plant (NP), fresh pod weight (PW), fresh pod length (PL) and fresh pod diameter (PD) (Table 1), leaf area (LA) and plant height in cm (PH) (Table 2) of all growing okra genotypes.The difference between genotypes (G) × treatment (T) interaction (G × T) showed a highly significant response at P ≤ 0.01 which revealed that all genotypes responded differently under saline conditions (Table 1).The present research agreed with Mahajan and Tuteja 34 who concluded that saline condition delayed germination and increased DTE which subsequently had a negative effect on the plant growth and yield.Ouis et al. 35 also found that firstly okra emergence was shown in control and then in saline stress environment.The delayed emergence in okra under salinity stress was associated with salinity-induced osmotic shock which reduced water absorption by seeds, and delayed the breakage of seed coat and thus germination 36 .Water is vital for the breakage of seed coat before germination.The genotypes exhibited significant differences (P ≤ 0.01), while treatment (NaCl concentration) showed non-significant effects (P ≥ 0.05) on DTF.The genotypic response showed distinct differences under different concentrations of G × T which were also significant at P ≤ 0.05.Similar findings were reported by Javaid et al. 37 , Wasaya et al. 38 , Waheed et al. 39 and Tanveer et al. 40 under saline conditions.Differential behavior of okra genotypes to DTF was attributed to their abilities to Na + , K + and Na + : K + ratio.NaCl salinity had a significant (P ≤ 0.01) influence on the number of leaf at first flower in okra accession.Genotypes and treatment of NaCl showed significant variable relation with each other.The genotypes also differed significantly (P ≤ 0.01) for plant height.The relationship between genotypes and treatment also remained significant for plant height which suggested that okra genotypes behaved differently to NaCl salinity, accessions reacted differently by altering the concentration of NaCl.Naqve et al. 8 reported that salinity stress reduced cell division and cell elongation, leading to reduced plant height.Since, okra genotypes accumulated different amounts of salt ions hence showed a differential decline in plant height.
The genotypes and treatment differed significantly (P ≤ 0.01) for the number of pods per plant and genotypes also behaved in distinct ways under different doses of NaCl as a relationship between genotypes and treatment was significant at P ≤ 0.01.Okra crop reduced the number of pods under saline condition.In mungbean, reduction was observed in different plant parameters under varying salinity levels 41,42 .These results were also supported by Elshaikh et al. 31 who reported that increasing soil salinity caused a significant decrease in plant growth and yield characteristics.
Salinity significantly (P ≤ 0.01) reduced the average fresh pod length and fresh pod diameter of all evaluated okra genotypes.The interaction between genotypes and treatment was highly significant which acknowledged www.nature.com/scientificreports/ that all okra genotypes behaved differently by increasing the concentration of NaCl.These results were in accordance with Fattah et al. 43 who demonstrated that the pod length of okra was inversely related to salinity.The results are also in agreement with Bhadana et al. 44 that by increasing the salinity level, the fresh pod diameter of okra decreased accordingly.The genotypes differed significantly (P ≤ 0.01) for stem girth of okra germplasm, and the interaction between genotypes and treatment of NaCl concentration was shown to be significant at P ≤ 0.01 (Table 2).These results were in accordance with Abbas et al. [42] who reported that the stem diameter of the okra plant showed a negative response to higher amount of salinity in irrigation water.Leaf area is a very important character that differed significantly (P ≤ 0.01) among okra genotypes under the varying concentration of NaCl.
By changing the treatment level, the response of genotypes differed significantly at P ≤ 0.01 (Table 2).Our results are in accordance with Munns 45 who found that salinity-induced decline in cell division and cell elongation as well as an injury due to specific ion toxicity were the main reasons for reduced leaf area under saline conditions.Latrach et al. 46 also added that due to reduced leaf area under saline conditions, the rate of photosynthesis decreased, causing a severe decline in overall growth and yield.It was further reported that higher accumulation of Na + and Cl − under saline conditions could be the main reason for reduced leaf area.The identification of salt-tolerant and salt-susceptible genotypes within Okra germplasm signifies not only a scientific milestone but also a transformative advancement for sustainable agriculture.These insights empower precision breeding, underscore the importance of genetic diversity, and bear the potential to address the challenges of salt-affected soils while promoting broader agricultural resilience, economic prosperity, and food security.This scientific pursuit represents a monumental stride toward the realization of sustainable and resilient agricultural systems.

Physiological characteristics
Relative water contents (RWC) of okra genotypes were significantly (P ≤ 0.01) influenced by NaCl concentration.Salinity stress reduced the RWC due to salinity-induced osmotic shock which inhibited the movement of water from the soil to plant.The reduction in RWC of okra genotypes under salinity stress holds significant physiological implications for the plants, impacting their overall health and performance.Limited movement of water from soil to plant reduces the cell turgidity.This, in turn, prompts stomatal closure to reduce water loss through transpiration, affecting photosynthesis by limiting carbon dioxide entry.As a result, there is a reduced production of carbohydrates and energy for plant growth.Furthermore, nutrient uptake is disrupted, and the plants become more vulnerable to diseases and pests.The decreased water use efficiency due to reduced RWC results in yield loss, with smaller and fewer fruits being produced.Prolonged salinity stress can lead to stunted growth, and the overall health and vitality of the okra plants are compromised 5,46 .So, the water potential of the plant was highly influenced by salt stress conditions 48 .Many important crops like alfalfa, pea, balm, tomato, and cotton showed reduced RWC under saline conditions which ultimately caused a huge economic loss in the form of yield loss [49][50][51] .Salinity stress had a significant (P ≤ 0.01) effect on the EL of all genotypes (Table 2).A remarkable difference was observed in genotype × treatment interaction which remained significant at P ≤ 0.01.The difference in EL of okra genotypes in response to salinity showed their genetic potential to tolerate salinity, higher EL depicted lower salt tolerance 52 .An increase in EL by increasing salinity has also been reported by Salwa et al., 53 in peanuts; Latrach et al., 46 in alfalfa; Baninasab and Baghbanha 54 , in cucumber.This complex interplay of physiological changes underscores the need for effective strategies to mitigate the effects of salinity stress in affected areas, such as improved irrigation practices, the use of salt-tolerant crop varieties, and soil management techniques.

Ionic concentration and ratio
By increasing external NaCl concentration in the growth medium, the leaf Na + concentration increased differently in different genotypes, and the difference among the genotypes was found significant (P ≤ 0.01) (Table 2).The relationship between genotypes and treatment was highly significant which showed that genotypes performed differently concerning Na + concentration under saline conditions.Abbas et al. 27 reported that under salt-stressed conditions, tolerant cultivars of okra germplasm restrained Na + in their root zone and carried a low concentration of Na + in their leaves.In okra plants, the salt tolerance mechanism might be associated with the efficient exclusion of Na + as mentioned by Flowers & Yeo 55 in rice.Salinity stress conditions significantly (P ≤ 0.01) and differently affected the K + concentration of all okra genotypes.By increasing NaCl concentration externally, K + concentration significantly decreased in okra leaves and a significant difference was observed among all genotypes.Also, there was a significant relationship between genotypes and NaCl treatment (P ≤ 0.01).The reduction in leaf K + with increasing salinity was due to the antagonistic effect of Na + on K + .Since under saline conditions increased concentration of Na + inhibited the uptake of K + as uptake and transport carriers for Na + and K + are common.However, the degree of reduction varied with genotypes which was due to the differential affinity of genotypes for Na + and K + .The variations in leaf Na + concentration and the K + :Na + ratio among different okra genotypes under salinity stress highlight the diversity of salt tolerance mechanisms.Genotypes that can effectively exclude Na + from their leaves and maintain a higher K + :Na + ratio are better equipped to thrive in saline conditions.These findings are essential for identifying and breeding salt-tolerant okra cultivars.The high affinity of genotypes for K + compared to Na + could be an important salt tolerance mechanism 7,56 .Shahid et al. 57 revealed that by increasing NaCl concentration, a clear-cut reduction was noticed in K + concentration in plant tissues, and higher K + concentration was closely related to salt tolerance.
Leaf K + : Na + ratio was affected significantly (P ≤ 0.01) by adding NaCl concentration externally (Table 2).Genotype into treatment interaction differed significantly at P ≤ 0.01 among all growing okra genotypes.Increased level of NaCl salinity in the growth medium increased the concntration of Na + while simultaneously decreasing K + , resulting in a decline in K + : Na + ratio.The differences among okra genotypes for K + : Na + ratio were due to their preferential uptake of K + over Na + under saline conditions 27 .Na + exclusion and K + uptake are vital www.nature.com/scientificreports/components of okra plants' salt tolerance mechanisms.Genotypes proficient in excluding Na + and maintaining a favorable K + :Na + ratio thrive in saline conditions.These mechanisms preserve cellular integrity, support normal physiological processes, and enhance okra growth and productivity in salt-affected regions.Leveraging these mechanisms can help develop salt-tolerant okra varieties and promote sustainable agriculture in saline environments.

Principal component analysis
Principal component analysis (PCA) is an important technique used to observe variation among multiple accessions and traits.PCA model was also used, to sum up various quality parameters into one major quality index to promote the quality of okra.PCA can also be used for the assessment of the independent effect of the specific parameter over the total variance observed such as the coefficient of proper vector showed the contributed index of every original variable with the association of each principal component 58,59 .PCA results provide valuable insights into the selection and breeding of okra genotypes with desired traits.By focusing on the traits that contribute the most to variance and considering trait associations, breeders can develop more effective strategies for enhancing okra quality and overall performance.According to Chen et al. [60], the first, three principal components are highly significant and widely used as variation patterns among various accessions.PCA allows for the development of a quality index, which condenses multiple traits into a single metric.This simplifies the evaluation of okra quality and facilitates the comparison and selection of genotypes based on a comprehensive quality measure.

Principal component analysis for normal condition (control)
In this study, PCA was performed to get information about how to select okra genotypes with desired traits in normal conditions.Means data were used to perform principal components analysis for the traits which showed significant results.Under normal conditions, PCA was conducted on the total variability of morpho-physiological traits in okra genotypes, resulting in 16 principal components (as presented in Table 3).which"' Among these components, the first 6 PCs contributed the most to the total variation, each with an eigenvalue greater than one, indicating a broad genetic diversity within the studied okra germplasm.The first six PCs contributed 67% cumulated variation in okra accessions while 33% variation was contributed by the remaining 10 PCs.The principal component analysis is an important tool used to distinguish genotypic responses for varying levels of salinity 36,61 .PCA findings under normal conditions provide a foundation for understanding trait prioritization and the performance of okra genotypes in non-saline environments.Comparing these results with findings from saline conditions allows breeders to assess how genotypes respond to salt stress and identify those with consistent quality across varying environments.It also reveals trade-offs and correlations between traits and assists in selecting adaptable genotypes for breeding programs.Ultimately, this approach helps in developing okra varieties that thrive under different conditions, addressing the challenges of salinity and enhancing overall quality and productivity.

Contribution of plant traits to genetic variability under normal conditions
The contribution of studied traits for genetic variability is presented in Fig. 1.Biplot analysis for morphophysiological parameters of both PC1 and PC2 revealed that stem girth, RWC, leaf area, height at the first flower, plant height, K + , and K + /Na + were the most important traits and contributed significant genetic variation in studied okra germplasm.While the share of DTE, DTF, and the number of leaves at a first flower, Na + and EL www.nature.com/scientificreports/were minimum in genetic variation.K + and K + : Na + ratio showed positive and significant association with height at first flower, number of pods, and pod weight but negative and significant association with EL and Na + .

Bi-plot analysis
Bi-plot analysis for the contribution of okra germplasm based on studied plant traits is presented in Fig. 2. It revealed that okra genotypes Silky-360, Clemson, and Acc-15379 showed maximum variation for height at first flower and overall plant height, while Acc-15376, Acc-34398, and Ok-135 contributed minimum share to create variation due to their location near the base point.Genotypes Sanura and Peted revealed broad genetic  www.nature.com/scientificreports/diversity for K + and K + : Na + because these accessions remained at a distant location from the origin of the biplot.However, accession Ok-1300 and Acc-15366 contributed okra accessions were located at a distant position from starting point of the bi-plot whereas, genotypes 93, 131, 116, and 72 contributed the smallest share for the development of genetic variation due to their position at the origin of bi-plot.Genotypes 91, 99, 15, 19, 82, 39, 84, 23, 137 showed significant associations for node length, DTF and DTE.Similarly, accessions 62, 125, 70, and 81 revealed a positive relationship with Na + and EL.The integrity of the PCA bi-plot makes it more predictable than other statistical tools for the evaluation of all genotypes under saline conditions [27] the slightest share for genetic variation because these genotypes were placed at starting point of the bi-plot.Due to the farthest placement maximum genetic variation was calculated for stem girth and RWC regarding Acc-15365, Acc-20246, Acc-36962, Parbhani, and Acc-19223.Meanwhile, Acc-34402 and Acc-1582 had little share to produce genetic variation, however, these accessions were found near the center of origin of the bi-plot.Accession 20,376 exhibited the greatest variation for the number of pods and pod diameter while accession 34,400 revealed the lowest genetic variation regarding these parameters due to the presence near the base point.Similarly, Acc-34406, Acc-20376 and Acc-20297 displayed maximum genetic variation for pod length, pod weight plant-1, fresh pod weight because these okra accessions were located at a distant position from starting point of the bi-plot whereas, genotypes 93, 131, 116, and 72 contributed the smallest share for the development of genetic variation due to their position at the origin of bi-plot.Genotypes 91, 99, 15, 19, 82, 39, 84, 23, 137 showed significant associations for node length, DTF and DTE.Similarly, accessions 62, 125, 70, and 81 revealed a positive relationship with Na + and EL.The integrity of the PCA bi-plot makes it more predictable than other statistical tools for the evaluation of all genotypes under saline conditions [27]   Cluster analysis of okra germplasm under normal conditions (control) Cluster analysis graded okra genotypes into five clusters (cluster-1 to cluster-5) based on genetic diversity present in germplasm under studied morpho-physiological parameters (Table 4).Cluster-1 represented 18 genotypes based on high yield while cluster-2 displayed 24 genotypes that showed minimum pod yield.The remaining clusters such as cluster-3, cluster-4, and cluster-5 comprised 23, 18, and 17 okra accessions, respectively showing a moderate contribution to the genetic diversity of okra germplasm.All the above said clusters showed that okra genotypes performed similar or nearly the same response within the cluster but exhibited different behavior across the cluster.

Cluster 1
Cluster-1 comprised okra genotypes 64, 73, 37, 35, 55, 109, 97, 118, 68, and 95 which showed maximum genetic diversity for okra pod yield.Although, all these accessions exhibited a narrow genetic base within the cluster while considered as high yielder breeding lines when compared with other clusters for plant traits such as height at first flower, plant height, K + , K + : Na + ratio, leaf area, RWC, and stem girth.

Cluster 2
Cluster 2 exposed narrow range of genetic variation for okra accessions

Optimal number of clusters
Total variations were shown in 10 clusters.But maximum variation occurred up to cluster number 5. Graph (Fig. 3) showed that maximum variation was recorded in cluster number 1 and minimum genetic variation was noticed in cluster number 10.It also revealed from the curve that whenever we moved from cluster 2 to 3 and onward downward curve exhibited a narrow genetic base.

Principal component analysis for stress condition
In this research principal component analysis (PCA) was conducted to get facts about how to select okra accessions for preferred traits in a salt-stressed regime.PCA was done by using mean values for those traits which showed significant genotypes and treatment interactions.Under the stressed condition, PCA distributed the total variability of okra germplasm for morpho-physiological parameters into 16 components presented in Table 6.Among these components, the first five PCs showed supreme variation having eigenvalues of more than one which revealed broad genetic variability for okra germplasm.The first five principal components added 67% cumulated variation in okra genotypes however remaining PCs contributed 33% genetic variability in okra germplasm.www.nature.com/scientificreports/

Contribution of plant traits to genetic variability under stressed condition
Bi-plot analysis for morpho-physiological parameters of both PC1 and PC2 presented in Fig. 4 showed that the number of leaves, height at first flower, RWC, leaf area, pod diameter, K + : Na + ratio, K + concentration, pod length, pod weight, stem girth, plant height, pod weight plant-1 and number of pods were the most important parameters which contributed significant genetic variations in studied okra accessions.However, DTF, DTE, Na + , and EL contributed a minimum share of genetic variations.Na + and EL showed a positive association with DTF and DTE but a negative significant association with all other yield-contributing and salinity-tolerant traits under study.The differences in salt tolerance among different okra genotypes can be attributed to various traits and physiological processes that interact to determine their responses to salinity.Understanding these mechanisms is essential for developing salt-tolerant okra cultivars.The potential mechanisms and factors that may contribute to the observed differences in salt tolerance among okra genotypes are ion transport and regulation, osmotic adjustment, antioxidant enzymes, stomatal regulation and metabolic pathway 34,52 .The variation in salt tolerance among okra genotypes is the result of complex interactions between genetic, physiological, and biochemical factors.Identification and selection of genotypes with superior traits in the context of these

Bi-plot analysis
Among all other parameters, RWC, height at first flower, and the number of leaf at first flower revealed the highest genetic variation for screening of okra germplasm under salt stress conditions for genotypes 111, 128, and 64 (Fig. 5).Screening of the okra breeding line was also based on the leaf area of plants because under saline conditions, leaf area was decreased as a result of the decline in photosynthetic activity for accession 133 and 95, these genotypes also negatively associated with Na + concentration and EL for genotypes 94, 137 and 30.Pod yield is the ultimate purpose which was governed by pod diameter, accession No. 133 had a maximum genetic variation for pod diameter.Similarly, maximum pod length, K + , K + : Na + was calculated for genotypes 68, 95, and 99 collectively.Genotypes 125, 139, and 27 took maximum DTE and DTF so they showed a negative relationship for these traits.Cell membrane injury is also an important parameter for the evaluation of salt tolerance.It is a widely known fact that salinity enhances osmotic stress that deteriorates the cellular activities of crop plants (Munns 2001).Concentrations of K + negatively correlated with EL 62 as it inhibited the uptake of Na + , and reduced EL.PC bi-plot also illustrated the antiparallel vector position of EL and K + : Na + .EL was used as a valuable tool to evaluate salt tolerance in breeding programs 63 because it was positively correlated with the accumulation of Na + in plant cells.

Cluster analysis
Cluster analysis is an exploratory analysis that tries to identify clusters within the data.Cluster analysis is also known as segmentation analysis.Under stress conditions cluster dendrogram divided genotypes into five major groups (cluster 1-cluster 5).Cluster 1 contains 24 genotypes, cluster 2 consists of 26 breeding lines cluster 3 to cluster 5 comprised of 6, 34 and 10 okra accessions, respectively represented in Table 7.

Cluster 2
Genotypes present in cluster 2 exhibited minimum genetic variation for okra genotypes 27, 94, 125, 139, 130, and 137.All these genotypes showed significant genetic variability with other genotypes in okra germplasm for salt tolerance-related traits having poor performance and acting as salt susceptible genotypes.Broad genetic variability was present between cluster A and cluster B.

Optimal number of clusters
Genotypes showing the same response are graded into the same cluster.Optimal number of clusters is inversely related to the genetic variation found in okra germplasm.Clusters 1 and 2 exploited the maximum genetic diversity, and cluster 3, 4 and 5 showed narrow genetic variations (Fig. 8).

Correlation Under normal condition
Correlation analysis is a very important statistical approach used to find out the association between two or more two variables.When the shift of one variable occurs along by the movement of another variable, that type of variable is said to be correlated with each other.Table 9 reveals the correlation among 17 quantitative parameters in the studied okra genotypes.If a single character increases and is used for selection purposes, the positively correlated trait will also be selected and vice versa.DTE had a positive relationship with DTF, EL, and Na + concentration at the genotypic level under normal conditions.A significant positive association was observed for number of leaf at first flower, height at the first flower, stem girth, and leaf area.The number of leaf at first flower was linked positively with height at first flower, stem girth, leaf area, EL, RWC, plant height, and K + : Na + ratio.Height at first flower displayed a significant positive association with pod weight, pod weight per plant, pod length, pod diameter, stem girth, leaf area, RWC, and plant height, K + and K + : Na + .NP showed positive associations with all growing parameters except stem girth and leaf area.Pod weight showed a negative correlation with the concentration of Na + while other parameters exhibited a positive association.Pod weight per plant revealed a positive linkage with all parameters except Na + and plant height which displayed a negative relationship.Pod length, diameter, and stem girth indicated a positive association with all developing parameters except Na + .
Under stress condition DTE revealed a negative association with all morpho-physiological traits except DTF, EL, and Na + concentration because excessive Na + in the growth medium delayed the germination and emergence of plants 8 .The number of leaf, height at first flower, No. of pods, pod weight, pod weight per plant, pod length, pod diameter, and stem girth indicated a positive correlation with all emerging parameters except EL and Na + concentration (Table 10).Under salt-stressed conditions, a positive relationship was noticed between plant height and pod yield which indicated that selection for vigorous plants would earn greater yield potential.The positive association between pod yield and plant height might be some good criteria for the development of high-yielding okra germplasm.In past, many researchers reported a similar category of a positive association between pod yield and plant www.nature.com/scientificreports/height 64,65 .A highly significant correlation was also observed for plant height with pod yield plant-1 by Shakoor et al. 66 .Hence, selection for such traits compiles desirable genes which ultimately improved the yield potential in many crop plants.

Screening of germplasm
Germplasm screening was conducted in the research area of the Department of Plant Breeding and Genetics, College of Agriculture, University of Sargodha, Sargodha, Pakistan (32 0.07°, Latitude N, 74.41°, E Longitude and Altitude 189 m).The pot experiment was conducted during spring 2019 in open environment and irrigated twice a week to fulfill the evapotranspiarational requirements of plants.The surface sterilized seeds with 0.2% hypochlorite of 100 okra genotypes were sown in duplicate in earthen pots filled with 10 kg silt soil lined with polythene sheet to avoid irrigation water and nutrient losses.The seeds of 100 okra genotypes were thoroughly rinsed with tap water after hypochlorite treatment to remove residues, and sown under two conditions:, control and 6.5 dS m −1 NaCl concentration conditions The salinity was induced using sodium chloride (NaCl), following the procedure developed by U.S. Salinity Laboratory Staff in 1954.According to the mthod, required amount of NaCl was mixed during pot filling stage to achieve the salinity level of 6.5 dS m −1 .Five okra seeds were sown in each pot of both conditions (control and salinity stress) and three uniform plants were kept in each pot after thinning.The plants were grown to maturity "sing'a completely randomized design (CRD) with three replications.
Half-strength Hoagland nutrient solution was added to pots once in a week to fulfill the nutrients requirement of plants.

Measurement of morphological characteristics
Data for various morphological parameters, including days to emergence (DTE), days to flowering (DTF), plant height at first flowering, number of pods per plant, pod length, pod diameter were recorded."

Measurement of Physiological characteristics
To determaine the RWC, healthy plant leaves, preferably the 3 rd topmost leaves, were selected during the 6th week after sowing when they reached the desired growth stage.First, the leaf 's fresh weight (FW) were immediately measured using a precision balance upon collection.This served as a baseline for further calculations.Subsequently, the leaves were subjected to determine their turgid weight (TW).The leaves were submerged in distilled water for a period of 4 h to ensure full hydration.After this period, the leaves were removed, and their surface was carefully blotted with tissue paper to eliminate excess water.The turged weight of leaf was then recorded.In next step oven dried weight (ODW) of leaves were determined.To prevent contamination and moisture loss, the leaves were sealed in an airtight plastic bag and labeled for identification.The leaves were placed in an oven set at 70 °C for 48 h to ensure complete drying.After this period, the leaves were removed from the oven and allowed to cool within the sealed bag.The weight was measured using the precision balance, and this recorded weight represents the ODW of the leaf.RWC was determined according to Yamasaki and Dillenburg 67 .www.nature.com/scientificreports/

Electrolyte leakage%
For electrolyte leakage (EL), the 4th leaf from the shoot tip was collected from each pot during 6th week after sowing.The collected leaves were cut into 1.0 cm diameter pieces and put in test tubes having 10 mL deionized water in two sets ensuring that leaves submerged completely.One set of test tubes was kept in water bath at 40 °C for 30 min and the EC of water having leaf sample was measured (C1).The electrode of EC meter was washed, wigh deionized water and blotted with tissue paper before moving to next tube.The second set of test tubes was autoclaved for 15 min, it was allowed to cool down at room temperature and EC was measured (C2) of each test tube containing separate genotypes leaf.Electrolyte leakage% was calculated according to Sairam 57 .

Ion determination
Wet digestion was performed for the determination of sodium (Na + ) and potassium (K + ) concentrations.Briefly, 1 g of dried plant leaf material in powdered form was transferred into a 100 ml digestion conical flask.After adding a 10 mL di-acid mixture of nitric acid and perchloric acid in the ratio of 2:1, the conical flasks were placed on a hot plate at 250 °C for 30 min.The digested samples were diluted to 50 mL using distilled water.Na + and K + were determined in mmol L −1 using Flame Photometer (Jenway PFP7).

Statistical analysis
Data collected for morpho-physiological parameters were subjected to analysis of variance (ANOVA).The traits that showed significant differences were further used to compare the means of various plant genotypes.The significance of means was compared by the Least Significance Differences test (LSD) using the software Statistics 8.1.
The LSD test is used to compare the means of multiple groups, which identifies significant differences between the means of the groups.Mean data of the traits that showed significant genotype × environment interaction were subjected to principal component analysis (PCA) using R Studio, Inc. following the method described by Husson et al. 68 ."

Conclusions
The assessment of the genetic potential of Okra germplasm for salinity tolerance revealed distinct outcomes within the study.Notably, a wide range of genetic diversity was observed among the okra genotypes in their responses to salt stress conditions.This genetic diversity was evident in the performance of these genotypes concerning traits related to salt tolerance.In essence, the genetic diversity indicated that different genotypes exhibited varying degrees of resilience or susceptibility when confronted the salinity-induced stress.Among the observed genotypes, a subset, specifically genotypes 64, 68, 95, 97, 99, 109, 111, 114, 128, and 133, demonstrated remarkable and improved responses to salt-tolerant traits under the challenging conditions of salt stress.These genotypes exhibited the ability to thrive or maintain their vital functions in the presence of elevated salinity, indicating their suitability for salt-affected environments.As such, they were selected as the group of salt-tolerant genotypes due to their superior performance.Conversely, another set of genotypes, namely genotypes 27, 94, 125, 139, 130, and 137, displayed genetic diversity compared to the other genotypes within the okra germplasm.These genotypes were characterized by their poor performance in salt tolerance-related traits.They struggled to cope with the stress imposed by salinity and exhibited lower adaptability to such adverse conditions.Consequently, they were identified as salt-susceptible genotypes, signifying their vulnerability to salinity-induced challenges.
Overall, this study underscores the significant genetic variability within the okra germplasm in response to salt stress, and it highlights the existence of distinct genotypes with varying degree of salt tolerance.This information is valuable for future breeding and selection efforts aimed at developing salt-tolerant okra cultivars, ultimately contributing to the sustainability and productivity of okra cultivation in salt-affected regions. https://doi.org/10.1038/s41598-023-48370-4

Figure 1 .
Figure 1.Contribution of plant traits towards genetic variation in studied okra germplasm.

Figure 2 .
Figure 2. Bi-plot analysis representing 17 plant traits in okra germplasm for normal condition.

Figure 5 .
Figure5.Bi-plot analysis representing plant traits in okra germplasm for stressed condition.

Figure 6 .
Figure 6.Cluster analysis showing five clusters arrangement under stress.

Figure 7 .
Figure 7. Dendrogram showing grouping of okra accessions under stress condition.

Table 1 .
Mean square values for different growth and yield characteristics of okra (Abelmoschus esculentus L.) grown under salinity stress.DTE: Days to emergence; DTF: Days to flowering; NL: No. of leaves at first flower; HFF: Plant height at first flower; NP: No. of pods per plant; PL: Fresh pod length; PD: Fresh pod diameter; PW: Fresh pod weight.**=Significant at 0.01 and 0.05 level.

Table 3 .
Eigen value and percent total variance for principle components for under normal condition.

Table 5 .
Mean values of morphological and physiological traits of okra germplasm under five clusters.

Table 6 .
Principal component of 100 okra genotypes under salinity stress.mechanisms can aid in the development of salt-tolerant okra cul-tivars, contributing to food security in regions affected by salinity 4 .

Table 7 .
Grouping of okra genotypes by means of cluster analysis.

Table 8 .
Mean values of morphological traits of okra germplasm under five clusters.

Table 9 .
Okra germplasm of 100 genotypes was randomly collected from various research institutes and stations in Pakistan including the Plant Genetic Resources Program (PGRP) National Agricultural Research Center (NARC), Optimal number of cluster for genetic diversity in okra germplasm under stress.Correlations among 17 traits of okra germplasm under normal conditions.Values in bold are different from 0 with a significance level alpha = 0.05.(DTE: Days to emergence; DTF: Days to flowering; NL: Vegetable Research Station, Ayub Agriculture Research Institute (AARI), Faisalabad and the University of Agriculture, Faisalabad.This study adheres to the institutional, national, and international guidelines and legislation.