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Journal of Pharmacognosy and Phytochemistry

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Journal of Pharmacognosy and Phytochemistry

Vol. 7, Special Issue 1 (2018)

Genetic variability, association study and identification of high yielding and water use efficient genotypes in the minicore collection of peanut (Arachis hypogaea L.)

Author(s): HC Sowmya, DL Savithramma, Vijayabharathi, Shivaleela S Kukanoor and HC Latha
Abstract: An experiment was conducted at UAS, GKVK, Bengaluru to study the genetic variability and character association for traits related to yield and water use efficiency in 225 genotypes consisting of 184 groundnut mini core accessions and 41 advanced breeding lines. High GCV, PCV, heritability and GAM was noticed for Pods/plant, Pod yield/plant, Kernel yield/plant, SMK and 100 kernel weight suggesting the presence of considerable variability for these traits in the material studied. Pod yield/plant exhibited significant correlation with all the traits except SMK. Path analysis revealed the maximum direct effect of kernel yield per plant on pod yield/plant. The accessions ICG 13942, ICG 12000, ICG 532, JL24, ICG 5745, ICG 5662, ICG 14482, GBFD5272, M282 and ICG 13099 exhibited higher SCMR value and the accessions ICG 13942, JL24, GKVK13, ICG 5745, ICG 2772, ICG 5016, ICG 10036, ICG 9777, ICG 875 and ICG 532 had lower SLA value. These accessions were identified as high water use efficient based on their high SCMR and low SLA values and need to be tested under both water stress and non stress condition in order to confirm their drought tolerance. High pod yield per plant was recorded by genotypes viz., ICG 13942, JL24, ICG 930121, GKVK13, ICG 6057, ICG 99003, ICG 10036, ICG 10556, ICG 11426 and ICG 10479
Pages: 1023-1027  |  541 Views  11 Downloads
How to cite this article:
HC Sowmya, DL Savithramma, Vijayabharathi, Shivaleela S Kukanoor and HC Latha. Genetic variability, association study and identification of high yielding and water use efficient genotypes in the minicore collection of peanut (Arachis hypogaea L.). 2018; 7(1S): 1023-1027.
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