Variability, Correlation and Path Coefficient Analysis: Principle Tools to Explore Genotypes of Brinjal (Solanum melongena L.)

Abstract

To lessen the pressure on staple crops and to combat hidden hunger, vegetable production is the key to success. Massive studies should be conducted regarding genotype selection to gain the desired yield to overcome these global problems. Brinjal is gaining popularity not only as a vegetable crop but also for its medicinal value. Despite this, the yield and nutritional potentials of brinjal genotypes remain underexploited in many parts of the world. In this study, brinjal genotypes were explored through genetic variability, correlation, and path coefficient analysis to combine yield along with yield contributing variables. Ten quantitative characters of twelve genotypes in a completely randomized design were investigated in this research work at Sher-e-Bangla Agricultural University, Dhaka, Bangladesh, from October 2013 to March 2014. In this study, PCV was found slightly higher than the GCV, which suggested the influence of the environment on the variability of these traits. Characters with a lower difference in GCV and PCV value could be improved by following phenotypic selection. Broad-sense heritability, coupled with moderate to low genetic advance was recorded in fruit length, average fruit weight, plant height and days to maturity. These traits were proposing the predominance of additive gene action. Days to first flowering, secondary branches per plant, fruit length and fruit diameter exhibited positive genotypic correlation with fruit yield per plant. In the case of path analysis, secondary branches per plant proposed maximum direct effect on the yield on both genotypic and phenotypic level followed by average fruit weight and fruit length. To explore interrelations among brinjal genotypes for gaining optimum yield variability, correlation and path coefficient analysis act as prime tools for which this study was conducted.