Research endeavors focused on examining genetic diversity play a pivotal role in advancing agricultural practices, as they furnish valuable insights for breeding programs and the preservation of germplasm. Wheat holds significant global importance as a cereal crop, serving as a primary source of sustenance for almost one-third of the global human population. In the current study, a total of 80 bread wheat genotypes were characterized using the start codon targeted (SCoT) marker system. A set of 14 polymorphic primers yielded a cumulative count of 399 bands with an average of 28.05 bands per primer. The range of diversity markers, such as polymorphism information content (0.26–0.59), effective numbers of alleles (1.27–1.59), Shannon’s information index (0.30–0.51), and gene diversity (0.18–0.34), provided evidence of elevated genetic differences within the examined germplasm. According to the findings of the molecular variance analysis, greater genetic variations are found within populations (92%). The model-based structural approach partitioned the 80 bread wheat genotypes into two distinct populations (Population A and B). The diversity indices based on the structures of the populations revealed that population A had greater diversity compared to population B. Both the principal coordinate analysis and the neighbor-joining analysis also differentiated the 80 different bread wheat genotypes based on their respective collection points. The present crop diversity offers great opportunities for enhancing crop quality and increasing tolerance to environmental challenges, both of which will lead to a reduction in the problem of food insecurity.

Lentil is an important food legume throughout the world and Pakistan stands at 18^th position with 8,610 tons production from 17,457 hectares. It is rich in protein, carbohydrates, fat, fiber, and minerals that can potentially meet food security and malnutrition issues, particularly in South Asia. Two hundred and twenty lentil genotypes representing Pakistan (178), Syria (14), and the USA (22) including 6 from unknown origins were studied for yield, yield contributing traits, and cooking time (CT). Genotype 6122 (Pakistan) performed the best during both years with seed yield per plant (SY) 68±1.7 g, biological yield per plant (BY) 264±2.8 g, pod size (PS) 0.61±0.01 cm, number of seeds per pod (NSP) 2, cooking time (CT) 11 minutes, with no hard seed (HS). The genotypes 6122 (Pakistan) and 6042 (Syria) produced the highest BY, hence these have the potential to be an efficient source of fodder, particularly during extreme winter months. The genotypes 5698 (Pakistan) and 6015 (USA) were late in maturity during 2018–19 while 24783 and 5561 matured early in 2019. A minimum CT of 10 minutes was taken by the genotypes 6074 and 5745 of Pakistani origin. The lowest CT saves energy, time, and resources, keeps flavor, texture, and improves protein digestibility, hence the genotypes with minimum CT are recommended for developing better lentil cultivars. Pearson correlation matrix revealed significant association among several traits, especially SY with BY, PS, and NSP which suggests their use for the future crop improvement program. The PCA revealed a considerable reduction in components for the selection of suitable genotypes with desired traits that could be utilized for future lentil breeding. Structural Equational Model (SEM) for SY based on covariance studies indicated the perfect relationship among variables. Further, hierarchical cluster analysis establishes four clusters for 2017–18, whereas seven clusters for 2018–19. Cluster 4 of 2017–18 and cluster 5 of 2018–19 exhibited the genotypes with the best performance for most of the traits (SY, BY, PS, NSP, CT, and HS). Based on heritability; HSW, SY, BY, NSP were highly heritable, hence these traits are expected for selecting genotypes with genes of interest and for future lentil cultivars. In conclusion, 10 genotypes (5664, 5687, 6084, 6062, 6122, 6058, 6087, 5689, 6042 and 6074) have been suggested to evaluate under multi-location environments for selection of the best one/s or could be utilized in hybridization in future lentil breeding programs.

A high density genetic map was constructed using F₂ population derived from an interspecific cross of G. hirsutum × G. tomentosum. The map consisted of 3093 marker loci distributed across all the 26 chromosomes and covered 4365.3 cM of cotton genome with an average inter-marker distance of 1.48 cM. The maximum length of chromosome was 218.38 cM and the minimum was 122.09 cM with an average length of 167.90 cM. A sub-genome covers more genetic distance (2189.01 cM) with an average inter loci distance of 1.53 cM than D sub-genome which covers a length of 2176.29 cM with an average distance of 1.43 cM. There were 716 distorted loci in the map accounting for 23.14% and most distorted loci were distributed on D sub-genome (25.06%), which were more than on A sub-genome (21.23%). In our map 49 segregation hotspots (SDR) were distributed across the genome with more on D sub-genome as compared to A genome. Two post-polyploidization reciprocal translocations of “A2/A3 and A4/A5” were suggested by seven pairs of duplicate loci. The map constructed through these studies is one of the three densest genetic maps in cotton however; this is the first dense genome wide SSR interspecific genetic map between G. hirsutum and G. tomentosum.

DNA fingerprinting and genetic diversity analysis of 79 early-maturing upland cotton (Gossypium hirsutum L.) cultivars were performed using Simple Sequence Repeat (SSR) molecular markers. Out of 126 pairs of SSR primers, we selected 71 pairs that gave good polymorphisms and clear bands, had good stability, and showed even distribution on the cotton chromosomes, and 142 polymorphic genotypes were amplified. The average number of alleles amplified with the SSR primers was 2.01. The polymorphism information content (PIC) of the markers ranged from 0.1841 to 0.9043, with an average of 0.6494. The results of fingerprint analysis showed that nine varieties had characteristic bands, and at least six primer pairs could be used to completely distinguish all 79 cotton accessions. Using NTSYS-pc 2.11 cluster analysis, the genetic similarity coefficients between the cotton genotypes ranged from 0.3310 to 0.8705, with an average of 0.5861. All cotton accessions were grouped into five categories at a similarity coefficient of 0.57, which was consistent with the pedigree sources. At the same time, the average genetic similarity coefficients of early-maturing upland cotton varieties in China showed a low-high-low pattern of variation over time, revealing the development history of early-maturing upland cotton varieties from the 1980s to the present. This also indirectly reflects that in recent years, China’s cotton breeders have focused on innovation and have continuously broadened the genetic resources for early-maturing upland cotton.