Genetic analysis of grain yield and its contributing traits for their implications in improvement of bread wheat cultivars

Journal Title: Journal of Applied and Natural Science - Year 2016, Vol 8, Issue 1

Abstract

Genetic analysis was carried out in 55 genotypes (10 parents and 45 F1s) through diallel mating design excluding reciprocals in bread wheat. Analysis of variance showed appreciable variability among the breeding material for almost all the traits under study. The highest value of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) was found for flag leaf area (PCV=18.82, GCV=17.74), biological yield (PCV=12.98, GCV=11.70), grain yield (PCV=11.90, GCV=10.39) and harvest index (PCV=10.39, GCV=10.05). Highest heritability with highest genetic advance was estimated for flag leaf area (h2=52.24, GA=34.64), biological yield (h2=15.04, GA=21.71), harvest index (h2=18.19, GA=20.01), peduncle length (h2=31.72, GA=15.96) and spikelets per spike (h2=34.92, GA=12.96), therefore selection will be effective based on these traits. Grain yield was found significantly correlated (at <1% level of significance) with productive tillers (gr=0.3283**, pr=0.4347**), spike length (gr=0.1959**, pr=0.2203**), spikelets per spike (gr=0.4342**, pr=0.3813**), grains per spike (gr=0.7188**, pr=0.4918**), biological yield (gr=0.6101**, pr=0.6616**), harvest index (gr=0.3518**, pr=0.3227**) and thousand grain weight (gr=0.5232**, pr=0.3673**). Similarly path coefficient analysis estimates for biological yield (g=1.0524, p=1.0554), harvesting index (g=0.8862, p=0.8291), thousand grain weight (g=0.0588, p=0.0269), grains per spike (g=0.0496, p=0.0074), spike length (g=0.0209, p=0.0289), days to maturity (g=0.0142, p=0.0127), productive tillers (g=0.0186, p=0.0147), peduncle length (g=0.0123, p=0.0157), days to 50% flowering (g=0.0093, p=0.0072) and plant height (g=0.0042, p=0.0020) showed high positive direct effects on grain yield indicating that due importance should be given to these traits during selection for high yield.

Authors and Affiliations

Pradeep Kumar, Gyanendra Singh, Sarvan Kumar, Anuj Kumar, Ashish Ojha

Keywords

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  • EP ID EP284437
  • DOI -
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How To Cite

Pradeep Kumar, Gyanendra Singh, Sarvan Kumar, Anuj Kumar, Ashish Ojha (2016). Genetic analysis of grain yield and its contributing traits for their implications in improvement of bread wheat cultivars. Journal of Applied and Natural Science, 8(1), 350-357. https://europub.co.uk/articles/-A-284437