Genetic variability studies for yield attributes and foliar disease resistance in groundnut (Arachis hypogaea L.)
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GENETIC VARIABILITY STUDIES FOR YIELD AND FOLIAR DISEASE RESISTANCE IN GROUNDNUT
Authors
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R DIVYADHARSINI
Department of Oilseeds, CPBG, Tamil Nadu Agricultural. University, Coimbatore-641 003, Tamil Nadu
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R PRABHU
Department of Oilseeds, CPBG, Tamil Nadu Agricultural. University, Coimbatore-641 003, Tamil Nadu
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N MANIVANNAN
Department of Oilseeds, CPBG, Tamil Nadu Agricultural. University, Coimbatore-641 003, Tamil Nadu
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P VINDHIYAVARMAN
Department of Oilseeds, CPBG, Tamil Nadu Agricultural. University, Coimbatore-641 003, Tamil Nadu
Keywords:
Genetic variability, Groundnut, Kernel yield, Late leaf spot, Pod yield, RustAbstract
In the present investigation, estimates of genetic variability, heritability and genetic advance were assessed for nine different characters in the F3 population derived from four groundnut crosses viz., CO 7 × GPBD 4, TMV 2 × GPBD 4, TMV Gn 13 × GPBD 4 and VRI 2 × GPBD 4. Considering the mean performance, the cross derivative CO 7 × GPBD 4 registered superiority for the characters viz., number of pods per plant, pod yield per plant (g), kernel yield per plant (g) and late leaf spot resistance. Apart from these characters, the cross VRI 2 × GPBD 4 and TMV 2 × GPBD 4 also showed superior mean performance for 100-pod weight (g) and rust score, respectively. High percentage of PCV, GCV, heritability coupled with high GAM values were recorded by number of pods per plant, 100-kernel weight (g), shelling (%), pod yield per plant (g), kernel yield per plant (g), late leaf spot score and rust score in various F3 cross derivatives. Selection would be effective for these traits in respective crosses to obtain promising progenies. Regarding the population distribution, negative skewness was observed in the cross CO 7 × GPBD 4 for 100-pod weight (g), 100-kernel weight (g), shelling (%) and sound mature kernel (%). Similarly, platykurtosis was observed for late leaf spot and rust disease scores in VRI 2 × GPBD 4. Directional selection will effectively improve the mean performance of these traits.
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References
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