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Heterosis for seed cotton yield and yield contributing traits cotton (Gossypium hirsutum L.)

International Journal of Chemical Studies · 2020 · Vol. 8(3) · pp. 2496–2500
Sudha RaniM Rani ChaparaY Satish

Abstract

Estimation of heterosis is very important to spot out the promising hybrid combinations for commercial exploitation of heterosis and to identify the best segregants to develop varieties. The objective of this study was to estimate the heterosis of all types i.e. mid parantal heterosis, heterobeltoisis and standard heterosis for yield contributing parameters. Nine genotypes and 20 F1 hybrids developed by crossing the parental genotypes in L x T design were sown in a randomized complete block design along with RCH 659 as standard check. It was observed that the line × tester interactions made greater contribution to the total variance for yield and its attributes. Proportional contribution of lines to total variance was very low for all the traits, while testers also followed similar pattern and contributed a minimum to the total variance. However, maximum variance was extended by line x tester interaction for all the yield contributing traits studied. Out of 20 hybrids, the cross combinations namely, TCH1716 × L 765, TCH1716 × L 766, GSHV179 × L 765 and F 2453 × L 766 were accompanied by significant and positive heterosis for number of bolls per plant, boll weight, number of sympodia per plant and lint index besides seed cotton yield per plant. It indicated larger scope for heterosis breeding for commercial exploitation of heterosis. The crosses that shown desirable heterosis over standard check can be advanced for isolation of improved lines for different yield contributing traits.

Research in Cotton CultivationSilkworms and Sericulture ResearchHeterosisLintHybridRandomized block designBiologyYield (engineering)AgronomyHorticultureBiotechnology
Citations
2
FWCI
0.46
field-weighted impact
References
13
Percentile
75%
vs. same field & year
Citations per year
References
Introduction to Quantitative Genetics.
Biometrics · 1982 · 21,753 citations
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