Correlation and Path Coefficient Analysis in Groundnut (Arachis hypogaea L.) Genotypes
Vadala Ram Reddy
Department of Genetics and Plant Breeding, College of Agriculture, PJTAU, Rajendranagar, Hyderabad, Telangana-500030, India.
Katti Sravanti *
Department of Genetics and Plant Breeding, Agricultural College, Palem, Nagarkurnool, Telangana-509215, India.
Nayaki Navatha
Department of Agronomy, Agricultural College, Palem, Nagarkurnool, Telangana-509215, India.
Satturu Vanisri
Department of Genetics and Plant Breeding, Institute of Biotechnology, PJTAU, Rajendranagar, Hyderabad, Telangana-500030, India.
Manthati Goverdhan
College of Agriculture, PJTAU, Rajendranagar, Hyderabad, Telangana-500030, India.
Meduri Malla Reddy
PJTAU, Rajendranagar, Hyderabad, Telangana-500030, India.
C. Sudhakar
PJTAU, India.
M. Sreedhar
RARS, Palem, Nagarkurnool, Telangana-509215, India.
*Author to whom correspondence should be addressed.
Abstract
Groundnut (Arachis hypogaea L.) is considered an unpredictable crop due to the subterranean development of its pods, which complicates the assessment of yield potential. Moreover, nut yield is a quantitatively inherited trait governed by multiple genes and significantly influenced by various yield-contributing components. As a result, direct selection for yield is often unreliable and may not lead to consistent genetic improvement. Therefore, understanding the extent of genetic variability, the interrelationships among yield-contributing traits, and their relative contributions to overall yield is crucial for the development of high-yielding groundnut genotypes. twenty two advanced breeding lines along with four checks (Girnar 4, Kadiri lepakshi, Vishihta and Kadir-6) were raised in a randomized block design with three replications and they were evaluated for 11 characters. Significant variations were observed among the genotypes for all the traits studied. The highest genotypic coefficient of variation was observed for kernel yield, dry pod yield and Dry haulm yield indicating the presence of wide range of variation for this trait. The dry pod yield per plot had significant positive association with kernel yield, dry haulm yield, hundred pod weight, hundred pod kernel weight and hundred kernel weight. Path coefficient analysis revealed that, kernel yield reported the highest positive direct effect on dry pod yield per plot followed by hundred kernel weight, hundred pod kernel weight, dry haulm yield and hundred pod weight indicating that the selection for these traits was likely to bring about an overall improvement in pod yield per plot directly.
Keywords: Groundnut, coefficient of variation, correlation, path analysis, phenotypic and genotypic, yield components