African and Asian origin pearl millet populations: Genetic diversity pattern and its association with yield heterosis

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a staple food crop of arid and semi-arid regions of Asia and Africa. Forty-five pearl millet populations of Asian and African origin were assessed for genetic diversity using 29 simple sequence repeat (SSR) markers. The SSR-based clustering and structure analyses showed that Asian origin–Asian bred (As-As) and African origin–African bred (Af-Af) populations were distributed across seven clusters, indicating no strong relationship among populations with their geographical origin. Most of the African origin–Asian bred (Af-As) populations had a higher average number of alleles per locus than As-As or Af-Af populations, and the majority of them clustered separately from As-As or Af-Af populations, indicating that introgression of African origin breeding materials led to the development of new gene pools adapted to the Asian region. Fourteen populations representing seven clusters were crossed according to a diallel mating design to generate 91 population hybrids (seeds of direct and reciprocal crossesweremixed) and evaluated at three locations in 2016. All the 91 hybrids when partitioned into three groups based on genetic distance (GD) between parental combinations (low,moderate, and high), revealed no correlation between GD and panmictic midparent heterosis in any of the groups, indicating that grain yield heterosis cannot be predicted based on GD. Two population hybrids (GB 8735 × ICMP 87307 and Sudan I × Ugandi) exhibited high levels of yield heterosis over standard checks and can be further utilized using different breeding schemes to develop high-yielding pearl millet cultivars

Genetic Variability, Genotype × Environment Interaction, Correlation, and GGE Biplot Analysis for Grain Iron and Zinc Concentration and Other Agronomic Traits in RIL Population of Sorghum (Sorghum bicolor L. Moench)

The low grain iron and zinc densities are well documented problems in food crops, affecting crop nutritional quality especially in cereals. Sorghum is a major source of energy and micronutrients for majority of population in Africa and central India. Understanding genetic variation, genotype × environment interaction and association between these traits is critical for development of improved cultivars with high iron and zinc. A total of 336 sorghum RILs (Recombinant Inbred Lines) were evaluated for grain iron and zinc concentration along with other agronomic traits for 2 years at three locations. The results showed that large variability exists in RIL population for both micronutrients (Iron = 10.8 to 76.4 mg kg−1 and Zinc = 10.2 to 58.7 mg kg−1, across environments) and agronomic traits. Genotype × environment interaction for both micronutrients (iron and zinc) was highly significant. GGE biplots comparison for grain iron and zinc showed greater variation across environments. The results also showed that G × E was substantial for grain iron and zinc, hence wider testing needed for taking care of G × E interaction to breed micronutrient rich sorghum lines. Iron and zinc concentration showed high significant positive correlation (across environment = 0.79; p 0.60, in individual environments) for Fe and Zn and other traits studied indicating its suitability to map QTL for iron and zinc

Genetic diversity analysis using shoot and root morphological markers in castor (Ricinus communis L.)

The morphological variation and genetic diversity in 15 root and shoot characters was studied in 27 castor accessions sown in an elevated temporary root study structure. Variation in characters accounted to 3.05 to 50.29%. Characters were subjected to Shannon Weaver diversity index (H`) to know the genetic diversity. Eleven traits recorded high H` indicating suitability in breeding programmes. Their regression coefficients indicated positive change for six traits in dependent variable seed yield. Phenotypic correlation studies revealed that seed yield was significantly correlated to root dry weight, root diameter, plant height, node number, effective spike length and 100 seed weight. Principal component analysis (PCA) revealed that PC1, 2 and 3 accounted for 44.52, 15.93 and 10.54% variation. High loadings in the first three PCs were recorded for nine traits viz., root dry weight, shoot dry weight, root length, total root length, root diameter at crown region, SCMR, effective spike length, node number to primary spike. Hence, present studies gains importance in understanding the root related traits and their role in quantifying the genotypes in terms of divergence