Unraveling the Genetic Framework Underlying Yield Dynamics in Maize (Zea mays L.): A Genetic Variability Perspective

Verma, Vishal and Biswal, Manoranjan and Gathiye, Gabu Singh (2023) Unraveling the Genetic Framework Underlying Yield Dynamics in Maize (Zea mays L.): A Genetic Variability Perspective. International Journal of Environment and Climate Change, 13 (11). pp. 4118-4126. ISSN 2581-8627

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Abstract

Aims: The improvement in crop yield depends upon the magnitude of genetic variability available in breeding material and the extent to which the yield component traits are heritable from generation to generation.

Study Design: Randomized Block Design.

Place and Duration of Study: Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, BU Campus, Jhansi (U.P.) between Kharif-2018 and June 2019.

Methodology: During the Kharif season of 2018, a thorough field investigation was conducted at the Horticulture Research Farm, Institute of Agricultural Sciences, BU Campus, Jhansi (U.P.) involving a total of 30 different maize inbred lines. The findings revealed a notable genetic diversity among the maize lines, as indicated by the considerable sum of squares attributed to genotypic variations across all observed characteristics. Notably, the variation in plant height was particularly prominent, followed by traits such as biological yield per plant, seed yield per cob, seed yield per plant, number of seeds per row and harvest index in maize. The significant values of PCV and GCV observed for characteristics like plant height, number of cobs per plant, and biological yield per plant suggest a substantial level of variability, thereby highlighting the potential for enhancing these traits through selective breeding. Furthermore, the combination of high heritability and significant genetic progress in traits such as plant height, harvest index, cob ear weight, rows per plant, seed yield per cob, biological yield per plant, days to 50 per cent germination, shelling per cent, days to 50 per cent silking suggests that these traits can be improved through direct selection.

Item Type: Article
Subjects: STM Open Academic > Geological Science
Depositing User: Unnamed user with email admin@eprint.stmopenacademic.com
Date Deposited: 02 Dec 2023 06:06
Last Modified: 02 Dec 2023 06:06
URI: http://publish.sub7journal.com/id/eprint/1779

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