Character Association Studies for Kernel Yield and Its Attributing Traits in Maize
D. Keerthana *
Agricultural College-Bapatla, Acharya N.G Ranga Agricultural University, Guntur-522101, India.
T. Haritha
Department of Genetics and Plant Breeding, Agricultural College Farm, Bapatla, Acharya N.G Ranga Agricultural University, Guntur-522101, India.
I. Sudhir Kumar
Department of Genetics and Plant Breeding, Agricultural Research Station (ARS), Peddapuram, East Godavari-533437, India.
D. Ramesh
Department of Statistics and Computer Application, Agricultural College-Bapatla, Acharya N.G Ranga Agricultural University, Guntur-522101, India.
*Author to whom correspondence should be addressed.
Abstract
Correlation coefficient measures the strength of the relationship between independent traits on the dependent trait like yield, that helps breeder in selection for yield enhancement. In this view, the present experiment was carried out to assess the correlation coefficient and path analysis using twelve quantitative traits. Eleven lines, four testers and their 44 crosses along with five checks were evaluated in simple lattice design during rabi 2021-22. Analysis of variance revealed significant differences among entries for all the characters under study, suggested the presence of substantial amount of genetic variability. Correlation studies specifies that plant height, ear placement height, ear length, ear girth, kernel rows per ear, number of kernels per row, 100-kernel weight exhibited significant positive association with kernel yield and among themselves at genotypic and phenotypic levels, signifying the importance of these traits during selection. Path analysis revealed that highest positive direct effects on kernel yield was exhibited by ear girth, number of kernels per row and days to 50% tasseling. As a result, the current study could aid in the reliable selection of parental lines based on these traits, as well as the development of high yielding varieties for future breeding programs.
Keywords: Correlation, path analysis, phenotypic, genotypic, traits