Genetic Diversity and Multivariate Analysis of Yield-Attributing Traits in Groundnut (Arachis hypogea L.)
R. Narasimhulu *
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
C. Kiran Kumar Reddy
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
M. Vanipraveena
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
N. Ramesh Naik
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
E. Priyankabai
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
B. V. Bhaskar Reddy
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
O. Venkateswarlu
Agricultural Research Station, Acharya N.G Ranga Agricultural University, AICRP on Groundnut, Kadiri - 515 591, Andhra Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
Groundnut yield improvement depends on the availability of genetically diverse genotypes possessing desirable yield and quality traits. Evaluating genetic variability, trait associations and multivariate diversity among genotypes helps breeders identify superior parents for developing high-yielding and quality cultivars. This study evaluated genetic variability, trait associations and selection efficiency in twenty-three groundnut genotypes. Kernel traits varied widely, with 100-kernel weight (25-38 g), sound mature kernel (SMK) weight (23-35 g) and SMK percentage (86-95%). Pod yield (3314-4970 kg ha-1) and kernel yield (2156-2967 kg ha-1) also showed considerable variability. Kernel yield exhibited a strong positive association and high direct effect on pod yield, indicating its usefulness as a selection criterion, although negative correlations with quality traits suggested a trade-off between yield and quality traits. Principal component analysis showed that the first three components explained 80.83% of total variation with PC1 alone contributing 46.41%. Cluster analysis grouped genotypes into four clusters, with Cluster IV showing superior yield performance. The genotypes K-9, K 2658, K 2660 and K 2659 grouped in Cluster II, showed moderate yield, desirable quality traits and early flowering. Therefore, the genotypes in Cluster IV and II, can be used as parents for developing high-quality and high-yielding groundnut cultivars.
Keywords: Clustering, diversity, association studies, selection index, yield