2018•Journal of Pharmacognosy and PhytochemistryOpen access

Genetic variability and diversity analysis for identification of most divergent parents in relation to grain yield and its component traits in wheat (Triticum aestivum L. Em. Thell.)

Anurag Kumar, Lokendra Singh, Kanhaiya Lal, Vaibhav Pratap Singh, Ashvani Kumar, Kuladeep Yadav

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Abstract

An experiment was made to evaluate fifty wheat genotypes of different eco-geographic origin. Data on eight quantitative characters viz; Plant height, reproductive tillers/plant, length of spike, spikelets/spike, days to maturity, grains/spike, test weight and grain yield/plant were recorded. Analysis of variance (ANOVA) revealed significant differences among all the genotypes for almost all the traits under study. The genotypes showed moderate to high level of genotypic coefficients of variance (GCV) and phenotypic coefficients of variance (PCV). In general phenotypic coefficient of variance was found to be higher than their genotypic coefficient of variance but the extent was quite small, indicating very less environmental influence on the expression of the characters. Higher estimate of GCV (15.55) was recorded for Length of spike followed by grain yield per plant (14.91). Divergence analysis is a tool to identify the divergent genotype for hybridization purpose. All the 50 genetically diverse genotypes were grouped into 8 clusters according to their closeness relationship values. Cluster I, II, III and VIII each had 7 genotypes, cluster IV and VI each had 4 genotypes, cluster V had 12 genotypes and cluster VII had 2 genotypes. Cluster V had maximum 12 genotypes, indicated that the genotypes involved in particular cluster are less divergent than genotype of other cluster. The maximum value of inter cluster distance was recorded between cluster I and VII (1755.86) followed by cluster IV and VII (1144.22). Inter cluster distance between cluster I and VII indicated that superior strains of cluster I may be used as parents for hybridization with superior genotypes selected from cluster IV in order to develop genetic variability in population for selection of the desirable recombinants.

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An experiment was made to evaluate fifty wheat genotypes of different eco-geographic origin. Data on eight quantitative characters viz; Plant height, reproductive tillers/plant, length of spike, spikelets/spike, days to maturity, grains/spike, test weight and grain yield/plant were recorded. Analysis of variance (ANOVA) revealed significant differences among all the genotypes for almost all the traits under study. The genotypes showed moderate to high level of genotypic coefficients of variance (GCV) and phenotypic coefficients of variance (PCV). In general phenotypic coefficient of variance was found to be higher than their genotypic coefficient of variance but the extent was quite small, indicating very less environmental influence on the expression of the characters. Higher estimate of GCV (15.55) was recorded for Length of spike followed by grain yield per plant (14.91). Divergence analysis is a tool to identify the divergent genotype for hybridization purpose. All the 50 genetically diverse genotypes were grouped into 8 clusters according to their closeness relationship values. Cluster I, II, III and VIII each had 7 genotypes, cluster IV and VI each had 4 genotypes, cluster V had 12 genotypes and cluster VII had 2 genotypes. Cluster V had maximum 12 genotypes, indicated that the genotypes involved in particular cluster are less divergent than genotype of other cluster. The maximum value of inter cluster distance was recorded between cluster I and VII (1755.86) followed by cluster IV and VII (1144.22). Inter cluster distance between cluster I and VII indicated that superior strains of cluster I may be used as parents for hybridization with superior genotypes selected from cluster IV in order to develop genetic variability in population for selection of the desirable recombinants.

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Available abstract

An experiment was made to evaluate fifty wheat genotypes of different eco-geographic origin. Data on eight quantitative characters viz; Plant height, reproductive tillers/plant, length of spike, spikelets/spike, days to maturity, grains/spike, test weight and grain yield/plant were recorded. Analysis of variance (ANOVA) revealed significant differences among all the genotypes for almost all the traits under study. The genotypes showed moderate to high level of genotypic coefficients of variance (GCV) and phenotypic coefficients of variance (PCV). In general phenotypic coefficient of variance was found to be higher than their genotypic coefficient of variance but the extent was quite small, indicating very less environmental influence on the expression of the characters. Higher estimate of GCV (15.55) was recorded for Length of spike followed by grain yield per plant (14.91). Divergence analysis is a tool to identify the divergent genotype for hybridization purpose. All the 50 genetically diverse genotypes were grouped into 8 clusters according to their closeness relationship values. Cluster I, II, III and VIII each had 7 genotypes, cluster IV and VI each had 4 genotypes, cluster V had 12 genotypes and cluster VII had 2 genotypes. Cluster V had maximum 12 genotypes, indicated that the genotypes involved in particular cluster are less divergent than genotype of other cluster. The maximum value of inter cluster distance was recorded between cluster I and VII (1755.86) followed by cluster IV and VII (1144.22). Inter cluster distance between cluster I and VII indicated that superior strains of cluster I may be used as parents for hybridization with superior genotypes selected from cluster IV in order to develop genetic variability in population for selection of the desirable recombinants.

Key concepts: Genotype, Biology, Cluster (spacecraft), Grain yield, Genetic divergence, Genetic diversity, Horticulture, Veterinary medicine

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Genetic variability and diversity analysis for identification of most divergent parents in relation to grain yield and its component traits in wheat (Triticum aestivum L. Em. Thell.) — Research Paper | ScholarLens