The sustainable development of Egyptian agriculture faces many challenges, including the reduction of freshwater allocations and the increase in the use of saline water in agriculture. Addressing the adverse consequences of the salt problem on agricultural production requires a diversified strategy. The current study coupled mutant breeding with conservation agriculture by injecting plant wastes into the soil to alleviate salt issues and sustainable food production. We have used spike length as a selection criterion because it is easily detectable in the open field [27]. In M3 generation, we evaluated 13 mixtures of wheat mutations along with the mother varieties under 6 organic amendment treatments for PH and grain yield components. Analysis of variance in Table 1 showed that there were significant differences between genotypes, organic amendment treatments and genotypes x organic amendment treatments interaction under salinity conditions for studied traits. Since the G × E interaction was present and played a central role, there is an opportunity for selection and improvement to determine the extent to which mutations adapt under CA [45, 46]. The significant differences among genotypes may be due to the variations in their genetic makeup that compelled the lines to exhibit varied behavior under salinity conditions [27, 47]. Maybe due to mutagenesis leads to up or down regulation of gene expression, shifted in mRNA stability or modification in protein structure. In the same context, Ulukapi and Nasircilar [48] pointed out that adaptation can be found in one gene, which resulted from mutation or a detected new allele into the lines by gene flow. The organic amendment treatments also reduced the electrical conductivity (EC) as shown in Table 3, which led to sodium leaching [49, 50]. Likewise, El-Nahas [51] indicated that plant wastes increase the proportion of carbon and organic cations in the soil, and increase its water holding capacity, leading to a decrease in salinity concentration. This was reflected in an improvement in the average performance of the mutant lines for grain production components compared to their parents, organic materials that contributed to increasing the availability of nutrients, and the mutants benefited from it better than their parents (Table 2). Organic amendments promote the biological and enzymatic activities of the soil and enhance the abundance of organisms, thus increasing soil fertility [52]. Trethowan [47] pointed out that conservation agriculture contributed to shift the host-pest and host-pathogen in a desirable direction, and decreased weed competition, and this contributed to enhancing grain yield. In this study, we recommended the use of formulation No. 6 in the next generation as a suitable organic amendment under saline conditions because it is low cost compared to other mixtures. This generation produced 150 mutant lines to produce the fourth generation, and in the fifth generation, there were 66 mutant lines. Mutant lines reached a high degree of homozygous, the best 6 mutant lines that achieved the highest grain yield were selected (Table 6). This is due to the contribution of the mutagen in modifying grain yield components in the desired direction, as the average SW of the mutant lines was 5.3 g, while the parents were 3.9 g. As for SY, mutant lines achieved 4.3 g, and the parents had 3.3 g, which was reflected in the SG, whose mutant lines reached 81.8 grains, while the parents achieved 66 grains. As for the trait that has the most influence on the final yield, which is SN, the mutant lines reached 226.8 spikes/m2, while the parents achieved 121.0 spikes, which were reflected in the final yield of the distinct lines. As for GY, mutant lines were achieved. Regarding the water productivity trait, the mutant lines achieved the higher average WP, 1.88, while the parents achieved 0.95. The total variance was expressed in terms of the phenotypic (PCV) and the genotypic (GCV) coefficients variability (Figs. 2 and 3). The differences between GCV and PCV values were very low for all studied traits, indicating that the environmental factors had a lower influence on the expression of these traits than the genetic factors [53]. Therefore, the phenotype reflects the genotype, and therefore direct selection based on the phenotypic performance of these traits in future mutant generations will be more effective. However, the values of PCV and GCV did not enough to determine a genetic gain from selection using phenotypic traits unless the heritable part of the trait was determined [54]. The efficiency of selection depends upon the heritable (genetic) percentage of variability, therefore high heritability (80%<) connected by high genetic (20%<) advance for the characters studied determination additive gene action and selection might be effective for these characters. Based on the above, additive gene effects were controlled in all studied traits, as shown in Fig. 3 [27, 55]. The correlation results in Table 7 are consistent with previous results, because all the studied traits recorded a significant positive correlation with GY. Therefore, a selection index that contained all the studied traits will be effective in isolating promising mutant lines of wheat [56, 57].
The current study used ten SSR markers to identify salt-tolerant wheat genotypes and identified 43 alleles, with a mean of 4.3 alleles per locus and a range of two to seven alleles per locus. These findings are supported by Hasanuzzaman [58] who found 45 alleles produced by eleven SSR markers and ranged from two to seven, the average alleles per locus were 4.09. However, the average of alleles per locus was more than the 2.5 and 2.71 which was reported by Islam [59] and Sundeep Kumar [60], respectively. It was less than those reported by Mardi [61], who discovered two to ten alleles per locus, with a mean of 5.5 alleles, in 122 genotypes of durum wheat using 19 SSR markers. Salehi [62] found 180 alleles in 21 genotypes, with an average of nine alleles per locus. Using 18 SSR markers, Mehta [63] found around 49 alleles among the 54 genotypes of wheat. The cause of the variety in the number of alleles per locus may be different locus-specific mutations [64] or may be due to differences in the genotypes or SSR markers employed [65]. The allele frequency of each locus ranged from 0.43 to 0.79 with a mean of 0.58. This average was higher than the 0.098, 0.41, and 0.5558 observed by Soriano [66], Eid [65] and Hasanuzzaman [58].
In this study, the majority of SSR markers showed a high level of polymorphism between wheat genotypes with a mean of 83%. These results are similar to those observed by El-Rawy and Hassan [67] who found 84.35% polymorphism. However, it was higher than Malik [68] who reported a 65.48% polymorphism rate in Indian bread wheat cultivars and Kumar et al. (2016) found a high degree of genetic polymorphism (70%) among seven wheat genotypes.
The PIC value and gene diversity (Expected heterozygosity) are the fundamental indicators of genetic diversity [65, 69]. PIC value is a measure of the polymorphism of the markers and indicates the ability of the markers to distinguish between different genotypes [70], while gene diversity (He or GD) describes the expected proportion of heterozygous genotypes under Hardy-Weinberg equilibrium [71]. The heterozygous condition occurs as a result of mutations in any one of the alleles [72]. The average PIC (0.36) was moderately informative because the PIC ≥ 0.25 [73, 74]. It was discovered to be less than the mean of 0.51 [65], 0.53 [33], and 0.4967[58]. However, it was discovered to be more than the meaning of 0.1393 [31], 0.315 [75], and 0.19 [76]. Whereas, this study found moderate levels of gene diversity (0.4574) in wheat genotypes, it was found to be lower than 0.59 [65], 0.56 [58], and 0.67 [77], but is higher than 0.336 [75]. On the other hand, Shannon diversity Index (H) revealed that genetic diversity ranged from 0.04 to 1.15 with an average of value 0.65. It was lower than 0.95 [65] and 1.005 [78]. In this study the mean discrimination power (Dp) was determined as 0.660, this value was greater than 0.042 [31], 0.114 [79], 0.040 [75] but lower than 0.71 [65] using SSR markers in wheat. when high PIC is coupled with Dp this indicates that this marker can discriminate between two genotypes and detect allelic variation this was clear in the XcweM54 marker in our study [80].
The genetic similarity ranged from 0.48 to 0.95 with an average of 0.72, which means that the 17 wheat genotypes share on average 72% of their marker alleles at the examined SSR loci. This means that the genetic variation among genotypes was fairly low. It may be the result of using SSR markers specific to salinity tolerance rather than random selection. This finding was also noted in wheat by Mir [81] and Shafi [82] as well as in sesame by Samaha [83]. The cluster analysis utilizing data from 10 SSR primers distinguished 17 wheat genotypes into two clusters based on their salt tolerance. According to Elshafei [31], the cluster analysis grouped the 11 wheat genotypes into two main clusters with similarity coefficients ranging from 0.086 to 0.88.
The results discuss the multifaceted roles of ten SSR markers in wheat. These markers were initially identified for their association with salt tolerance in wheat [11, 31]. However, subsequent research has revealed their potential involvement in other important agronomic traits.
The Barc124 marker in wheat has garnered attention for its potential role in multiple agronomically important traits. While Elshafei [31] primarily focused on its association with salt tolerance, subsequent research has revealed its broader significance in wheat breeding. Kumar [84] and Khaled [11] suggest that the Barc124 marker might be linked to quantitative trait loci (QTLs) on chromosomes 2B, 5B, 2A, and 2D. This indicates that the marker could influence a range of traits beyond salt tolerance, potentially including yield, disease resistance, and other agronomic characteristics. On the other hand, Kumar [84] specifically highlighted the proximity of Barc124 to a QTL associated with leaf rust resistance (LrH2) on chromosome 2DS. Leaf rust is a significant disease affecting wheat production, and the identification of markers linked to resistance genes is crucial for developing resistant cultivars. Khaled [11] further revealed a connection between Barc124, and QTLs related to plant height and wilting time on chromosome 5B. Plant height is an important consideration for lodging resistance, while wilting time is a component of drought tolerance. The association of Barc124 with these traits suggests its potential utility in breeding for improved adaptation to environmental stresses.
The diverse associations of the Barc124 marker with various agronomically important traits underscore its potential as a valuable tool in wheat breeding programs. By utilizing marker-assisted selection, breeders can expedite the development of wheat cultivars with enhanced salt tolerance, leaf rust resistance, desirable plant height, and improved drought tolerance.
Barc125 is located on chromosomes 7D, 3D, 4B, and 5A. While primarily linked to salt tolerance, it has also been found to be associated with Septoria tritici blotch (STB) resistance on chromosome 3DL [85]. STB is a major fungal disease affecting wheat production worldwide, causing significant yield losses. The identification of Barc125 as a marker linked to STB resistance opens up possibilities for developing wheat cultivars with enhanced resistance to this devastating disease. Barc144 is located on chromosomes 5D and 5A and is associated with salt stress tolerance. Additionally, it has been found to be flanked by a QTL related to grain protein content (GPC) on chromosome 5D [86]. GPC is a critical quality trait in wheat, influencing its nutritional value and end-use properties. The association of Barc144 with GPC suggests its potential utility in breeding programs aimed at improving grain quality. The discovery of these multiple roles for Barc125 and Barc144 highlights the potential of SSR markers as valuable tools in wheat breeding. By utilizing marker-assisted selection, breeders can expedite the development of wheat cultivars with improved salt tolerance, disease resistance, and enhanced grain quality. cfd60, previously recognized for its potential in marker-assisted selection for salt tolerance [31], may also be linked to QTLs related to grain filling rate and traits influenced by heat stress [87]. This connection suggests its possible role in improving wheat resilience to multiple environmental stresses. Xcwem9 Located on chromosomes 1D, 1A, and 3A, this marker is associated with salt tolerance and appears to be linked to QTLs related to sedimentation volume, a key indicator of wheat quality [42]. This finding indicates that Xcwem9 could be instrumental in breeding wheat varieties with improved quality traits along with salt tolerance. xgwm291 Identified as a salt tolerance marker, this marker is also flanked by a QTL related to kernel number per spike and spike length on chromosome 5A. This association suggests its potential in influencing yield-related traits in wheat. These findings collectively demonstrate the versatility of SSR markers in identifying loci that govern various agronomic traits in wheat. These markers can play significant roles in improving multiple traits, including salt tolerance, heat stress resilience, grain quality, and yield components. This multifaceted nature makes them valuable tools for developing wheat varieties that can thrive in diverse and challenging environments. This knowledge can be leveraged in marker-assisted breeding programs to develop wheat cultivars with improved salt tolerance, disease resistance, grain quality, and yield-related traits.
In general, SSR markers showed moderate genetic diversity in the wheat genotypes studied, sufficient to develop salt-tolerant wheat cultivars. It was also able to classify the genotypes as tolerant or sensitive based on specific alleles revealed by five SSR loci (Barc63, Barc124, Barc125, XWmc18, and XcweM54) that were associated with salinity and might be applied in breeding programs using marker-assisted selection (MAS).