A Comparison of Parametric and Non-Parametric Selection Indices for Selecting Corn Hybrids in the Brazilian Cerrado
Year: 2026
Type: article
Abstract: The selection of superior maize genotypes is complex due to the quantitative and intercorrelated nature of agronomic traits and their strong environmental influence, which limits the efficiency of direct selection and requires multivariate approaches. This study aimed to compare the efficiency of seven selection indices in identifying superior maize hybrids, quantify the genetic gains provided by each method, and evaluate the agreement among indices in genotype classification under Brazilian Cerrado conditions. Seventy-three maize genotypes were evaluated across multiple environments, considering grain yield and lodging resistance as primary traits and plant health, earliness, plant height, and ear height as secondary traits. The evaluated indices included direct and indirect selection, the Smith–Hazel classical index, the desired genetic gains of Pesek and Baker, the weight- and parameter-free index of Elston, the multiplicative index, the rank sum index of Mulamba and Mock, and the Genotype–Ideotype index. The results revealed differences in efficiency among methods for simultaneous trait selection. The Elston, Mulamba and Mock index and the Genotype–Ideotype index provided a better balance between productivity and other agronomic traits, resulting in more balanced genetic gains. In contrast, the Pesek and Baker and multiplicative indices were less efficient for joint selection, while direct selection and the Smith–Hazel index were more effective when applied to isolated traits. Overall, the combined use of indices improved selection reliability and enabled the identification of superior and more stable genotypes for the Cerrado.
Source: Agronomy
Language: English
Topic: Genetics and Plant Breeding
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,137
Awards: G4429332860, G7680315235, G8285809817
OpenAlex ID: W7128929110
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