Character Associations and Correlation Networks for Yield-Related and Vegetative Traits in Open-Pollinated and Hybrid Maize ( Zea Mays L.) Genotypes in Contrasting Savannah Ecologies
Abstract
Crop yield in maize (Zea mays L.) is a complex quantitative trait, making character associations crucial for developing indirect selection criteria. This study evaluated the phenotypic and genotypic associations among 22 growth, phenological, and yield traits across 10 elite maize genotypes. Field trials were conducted during the 2023 cropping season under contrasting environments in Gombe State, Nigeria: Dadin-Kowa (dry semi-arid, 350 mm annual rainfall) and Billiri (humid, 1,600 mm annual rainfall), using a Randomized Complete Block Design with three replications. Under dry semi-arid conditions at Dadin-Kowa, grain yield exhibited highly significant positive genotypic correlations with thousand-grain weight (rg = 0.865**) and field weight (rg = 0.931**). Conversely, under wet sub-humid conditions at Billiri, grain yield was strongly and positively correlated with vegetative traits, including number of leaves (rp = 0.890**; rg = 0.946**) and leaf area (rp = 0.925**; rg = 0.999**), indicating that canopy dimensions are primary yield drivers in high-moisture regimes. In the combined multi-environment analysis, grain yield was positively correlated with number of grains per row (rp = 0.790**; rg = 0.999**) and field weight (rp = 0.949**; rg = 0.999**). A notable physiological source-sink trade-off emerged, as harvest index was significantly negatively correlated with leaf area (rp = -0.795**) and above- ground biomass (rp = -0.814**). Maize selection must be environment-specific; breeders should prioritize thousand-grain weight for dry savannahs, leaf dimensions and ear diameter for humid zones, and grains per row for general regional cultivation.
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