Lentil is an important food legume throughout the world and Pakistan stands at 18th 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.

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Sustainable production of food crops relies on germplasm improvement and genetic diversity. In the present study, seventy-four potato genotypes were evaluated for diversity analysis during autumn 2017-2018 and 2018-2019 at NARC, Islamabad. Our results showed significant diversity in qualitative traits with reference to skin color of five types (Red, yellowish, brown, light yellow, light brown skin color tubers=5), three types of flesh color (Yellow, cream and white flesh color tubers=3), three sizes of tubers (Medium, small and large size tubers=3) and four shape of tuber (Oval, round, oblong, elliptic= 4 shapes) and four different eyes color (Brown, light brown, dark red and yellow eyes color=4). Potato genotype under study had very high genetic variance for quantitative attributes including weight of tuber per plant and weight number of tubers per lane, leaf area and plant height. Significant positive correlation was observed between number of tubers per plant (TPP) with number of eyes on tubers (r = 0.241) and number of tubers per lane (TPL) (r = 0.349). Plant height was found significantly positive correlated with leaf area (r= 0.456), germination percentage (r = 0.255) and weight of tubers per plant (r = 0.307). Leaf area (LA) showed positive significant correlation with number of tubers per plant (r = 0.466) and weight of tubers per plant (r = 0.263), yield and harvest index (r = 0.798, 0.755, 0.255). Weight of tubers per lane (WTL) showed positive correlation with weight of tubers per plant (r = 0.387). Regarding the interrelation between the traits and genotypes, the first two principal component axes (PC1, 24.83% and PC2, 23.46%) accounted for about 48.29% of the total variability reflecting the complexity of the variation between the plotted traits of genotypes. The present study will be useful for the precise selection for effective breeding program.