Analysis of Correlation and Path among 61 Genotypes of Groundnut (Arachis hypogaea L.)
Saurabh Arun Mudgalkar *
Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab, India.
Fadi Afandi
Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab, India.
Rajlakshami Nilesh Raut
Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab, India.
Kothavale Pruthviraj Rajgonda
Department of Agricultural Economics, Dr Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, India.
Harshal Avinashe *
Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab, India.
*Author to whom correspondence should be addressed.
Abstract
The present investigation was carried out to determine the interrelationship among yield and yield-contributing traits through correlation and path coefficient analysis in 61 groundnut (Arachis hypogaea L.) genotypes along with five check varieties during Kharif 2024 at the Agricultural Research Farm, Lovely Professional University, Punjab. Significant variability was observed among all genotypes, indicating the availability of substantial genetic diversity for selection. Genotypic and phenotypic correlation analyses revealed that kernel yield per plant exhibited strong and positive associations with 100-pod weight, 100-kernel weight, shelling percentage, pod yield per plant, days to maturity, and days to 50% flowering. These traits emerged as major contributors to kernel yield, suggesting their potential use as reliable selection indices in breeding programs. Negative or weak correlations were observed with traits such as sound mature kernel percentage and biological yield per plant, indicating limited influence on yield. Path coefficient analysis further clarified the direct and indirect contributions of various components toward dry pod yield. Kernel yield per plant expressed the highest positive direct effect, followed by pod yield per plant, harvest index, and biological yield. Traits such as 100-kernel weight, shelling percentage, days to maturity, and plant height displayed considerable indirect effects via kernel yield and related attributes. The study underscores that improvement in key traits, particularly kernel weight, pod weight, shelling efficiency, and maturity duration could effectively enhance overall productivity. The results provide insight into the complex yield structure and highlight essential traits that can be exploited for developing high-yielding groundnut cultivars suited to diverse environments.
Keywords: Correlation, path analysis, direct effect, yield, groundnut