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Assessment of Various Variability Parameters and Correlation of Quantitative Characters in Maize (Zea mays L.) Inbred Lines

Srikanth Oruganti, Neelam Sunil, G. K. Chikkappa, M. V. Nagesh Kumar, S. Vanisri

International Journal of Environment and Climate Change · pp. 3049–3056 · Published 12 Sep 2023

10.9734/ijecc/2023/v13i102973

Abstract

The present research problem was carried out to assess the variability parameters, heritability, genetic advance and correlations among various quantitative traits in maize inbred lines. A total of 69 inbred lines were evaluated in alpha lattice design with 2 replications at Winter Nursery Centre, Hyderabad. ANOVA results displays genotypes were significantly different from each other. From the results it was depicted that Phenotypic Coefficient of Variation (PCV) was higher than Genotypic Coefficient of Variation (GCV) indicating the influence of environment. The traits, No. of kernels per row, Cob weight, Grain yield per cob showed high GCV and PCV values likewise Days to 50% tasseling, Days to 50% silking and Days to 75% dry husk showed low GCV and PCV values. Most of the characters showed high heritability and traits such as Plant height, Tassel length, Ear length, No. of kernels per row, Cob weight and Grain yield per cob showed high GAM and its values ranged from 21.5% to 101.30%. So, the traits such as No. of kernels per row, Cob weight and Grain yield per cob can be used for further crop improvement in the breeding programme. Of all the traits under study except, Days to 50% tasseling, Days to 50% silking and Days to 75% dry husk showed positive significant correlation with grain yield per cob indicating selection for the traits will enhance the grain yield whereas the excepted traits showed negative significant association with grain yield per cob indicating selection for these traits is also essential as it reduces duration of crop.

GCV PCV heritability genetic advance correlation

Cited by 2

Genetic analysis of quality protein maize (QPM): a review

Rajendra Vidadala, Vinay Kumar, Sanghamitra Rout · Cereal Research Communications · 2024

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