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Combining ability for agronomic and quality traits in Indian mustard

International Journal of Chemical Studies · 2020 · Vol. 8(5) · pp. 720–724
Priyanka ChoudharyHemlata SharmaSanjay Kumar SanadyaN. S. DodiyaVimal Bishnoi

Abstract

The present study was carried out among forty-nine Indian mustard genotypes involving F1s, their parents and 2 checks developed through Line x Tester mating design and evaluated at Breeding Research Farm, MPUAT, Udaipur in Rabi-2018 in Randomized Block Design. Results revealed that contribution of General combining ability to total mean squares was higher than that of Specific combining ability for all the traits, providing that additive gene action was more important in their inheritance. The analysis of variance revealed that the mean squares due to genotypes, parents, crosses and parents v/s crosses were significant for all the traits. General combining ability mean squares for lines and testers and Specific combining ability mean squares were significant for most of the traits indicating that both additive and nonadditive gene action were involved in the inheritance of these traits. However, the contribution of General combining ability to total mean squares was higher than that of Specific combining ability for DOF, DOM, NSP, NPB, LMA, LS, SYP HI and OC traits, providing that additive gene action was more important, while non-additive gene action for resting traits. Lines PM-27 and SKM-1313 had positive General combining ability effects for seed yield per plant and negative General combining ability effects for oil content. These lines can be used as parents to create synthetic varieties or hybrids.

Nitrogen and Sulfur Effects on BrassicaAgricultural Practices and Plant GeneticsGenetics and Plant BreedingMating designRandomized block designHybridBiologyBiotechnologyHorticultureStatisticsMathematicsHeterosis
Citations
0
FWCI
0.00
field-weighted impact
References
11
Percentile
19%
vs. same field & year
References
International Journal of Applied Research
International Journal of Applied Research · 2018 · 933 citations
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