Genetic variability and diversity analysis for yield and its components in wheat (Triticum aestivum L.)

Abstract

Forty nine genotypes of wheat were studied for generating scientific information on nature and magnitude of genetic variability and diversity for designing breeding programme. The experiment was conducted in randomized complete block design in three replications. The data were recorded on days to 50% flowering, plant height, peduncle length, number of productive tillers per plant, days to maturity, spike length, number of spikelets per spike, number of grains per spike, 1000-grain weight, biological yield per plant, grain yield per plant, harvest index and gluten content. Analysis of variance revealed significant differences among the genotypes for all the characters under study. The highest estimates of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed for grain yield per plant. High heritability coupled with high genetic advance was observed for grain yield per plant. Based on D 2 -Statistics, 49 genotypes were grouped into eight clusters. The highest inter-cluster distance was found between cluster VII and VIII followed by III and VII. This indicates that genotypes included in these clusters possess wide genetic diversity. Grain yield per plant (31.46%) showed highest contribution towards genetic divergence; therefore, this character was major determinant of genetic diversity. On the basis of divergence and cluster mean it may be suggested that maximum heterosis and good recombinants could be obtained in crosses between genotypes of cluster VIII, VII and III in varietal improvement programme. Thus, crosses between the genetically diverse genotypes of cluster VIII with genotypes HUW 655, HP 1937, DBW 88 and HD 3058 and cluster VII with genotypes like HP 1938, HUW 656, K1006, DBW83, DBW 84, K1004, UP2822 and NW5050 are expected to exhibit high heterosis and are also likely to produce new recombinants with desired traits.

Study of Genetic Variability, Path Analysis and Diversity of Selected Germplasm Lines of Wheat (Triticum aestivum L.), Under Very Late Sown Condition

“…The results obtained showed the highest GCV and PCV for grain yield plant -1 (12.57%, 17.95%) followed by Days to heading (10.86%, 10.92%). Similar results has been reported by Bhushan et al, 2013;Kumar et al, 2013;Arya et al, 2017 respectively. Biological yield per plot, however, showed a wide difference between GCV and PCV (4.90%, 10.80%) with respect to other traits under study hence, indicating the high environmental effect on expression of the biological yield.…”

Genetic divergence analysis in chickpea germplasm

“…As the D 2 values represent the index of genetic diversity among the cluster, it would be more appropriate to make cross between genotypes separated by high estimates of statistical distance (Parhe et al, 2014). Selecting parents from the maximum et al, 2002;Kumar et al,2017). Similar result has been reported by Dwevedi and Lal, (2009); Syed et al, (2012) in chickpea; Arya et al, (2017) in wheat, Gowsalya et al, (2017) in black gram, Wankhade et al,2017 in clusterbean.…”

“…Selecting parents from the maximum et al, 2002;Kumar et al,2017). Similar result has been reported by Dwevedi and Lal, (2009); Syed et al, (2012) in chickpea; Arya et al, (2017) in wheat, Gowsalya et al, (2017) in black gram, Wankhade et al,2017 in clusterbean. According to Temesgen et al, (2015) increasing parental distance implies a great number of contrasting alleles at the desired loci and then to the extent that these loci recombine in the F 2 and F 3 generation following a cross of distantly related parents, the greater will be the opportunities for the effective selection for yield factors.…”

Charcterization of Agronomic Traits and Grain Quality of Some Wheat Landraces

“…This shows the presence of additive gene effect and selection may be made for the improvement of these traits. Although low heritability exhibited that the characters were highly influenced by environmental effect and genetic improvement through selection will be difficult due to effect of environment (Arya et al, 2017).…”