Estimation of Genetic Variability and Divergence in Some Selected Lines of Pearl Millet

Abstract

The objective of this study was to estimate the genetic variability , heritability , genotypic and phenotypic coefficients of variations , genetic advance , range , genotypic and phenotypic variances and to study the genetic divergence by using multivariate analysis for yield and yield components in forty selected lines of pearl millet during 2012 and 2013 summer seasons at Sakha Agriculture Research Station. Analysis of variance manifested highly significant differences among all selected lines for all the studied traits. The phenotypic coefficient of variation (PCV) was higher than the genotypic coefficient of variation (GCV). Heritability in broad sense ranged from 11.12%for fresh leaf/ stem ratio to 86.87% for stem diameter. High estimates of bread sense heritability were found in all the studied traits, except dry matter and fresh leaf/stem ratio which, were medium and low, respectably. The environmental variance ranged from 13.13% for stem diameter to 88.88% for fresh leaf / stem ratio. The results also cleared that the genetic advance ranged from 0.91% for fresh leaf / stem ratio to 24.72% for total fresh forage yield. The results cleared that the ascendant order of the importance of evaluated traits were, the first factor accounted 41.78% (number of tillers, plant height, total dry forage yield and total fresh forage yield) while, the second factor accounted 59.62% (dry matter, stem diameter and fresh leaf /stem ratio) of the multivariate variance. The forty selected lines were grouped into eight clusters based on dissimilarity coefficients. Thus, the pearl millet breeder would use these selected lines from divergent cluster for hybridization in order to isolate useful recombinants in the segregating generations.

Genetic Divergence for Grain Quality and Agromorphological Traits in Pearl Millet

“…Evaluation of genotypes from these clusters for per se performance and specific combining ability will identify the most promising lines and enable their utilisation as pollinators in developing of hybrids. Similar results were also provided by Drabo et al, 2013;Ghazy et al, 2015;Kiprotich et al, 2015;Nehra et al, 2016;Ton et al, 2022. Cluster III had the maximum mean grain yield per plant (26.48 g), dry fodder yield per plant (56.33 g),1000-seed weight (9.89 g), and plant height (162.88 cm). Cluster VI had the highest grain Mg content (2365.29 mg kg -1 ) and number of productive tillers per plant (2.90), and the lowest days to 50% flowering (60), panicle length (17.70 cm), plant height (126.50 cm), dry fodder yield per plant (18.12 g), 1000-seed weight (8.31 g), and grain yield per plant (8.31 g).…”

Multivariate analysis and role of direct–indirect effect for yield and its component traits in bread wheat (Triticum aestivum L.)

“…The knowledge of the nature and magnitude of genetic variability for a heritable trait is essential to exploit the yield contributing trait. Assessment of genetic diversity distance via D 2 analysis, between two genotypes, will help to choose better parents for hybridization (Ghazy et al, 2015;Kiprotich et al, 2015;Sharma et al, 2020). Intercrossing between genetically divergent genotypes is expected to produce superior hybrids and desirable recombinants.…”

Phenotypic Characterization and Genetic Divergence of some Pearl Millet Genotypes Based on Cluster and Principal Component Analysis

“…The degree and nature to which yield is related with other traits allows breeders to foresee the relative impact of different traits on yield improvement that allowing them to choose the traits that are desirable and crucial to achieving improvement. Berwal and Khairwal (1997) and Ghazy et al (2015) studied the genetic variation for forty genotypes of pearl millet and observed a significance difference in height of plant, no. of tillers, stem diameter, fresh, dry leaf/stem ratio and total fresh and dry forage yield across three cuts and over two seasons.…”