Document Type : Research Paper
Authors
1
Ph.D. Student, Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
2
Professor, Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
3
Associate Professor, Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
10.22124/cr.2026.33190.1895
Abstract
In this study, 86 maize genotypes sourced from multiple research centers (Razi University of Kermanshah, Agricultural Research Center of Mashhad, and Institute of Plant Breeding and Seedling Preparation of Karaj) were evaluated under four environmental conditions: non-salinity (SN), salinity stress (SS), optimal phosphorus (PN), and phosphorus deficiency stress (PS) to assess the stability of grain yield (GY) and biological yield (BY). The experiment was conducted in an open field at the College of Agriculture, Urmia University, using a completely randomized design with three replications during the 2017-2018 cropping season (1396 in the Persian calendar). The Multi-Trait Genotype Ideotype Distance Index (MGIDI) was employed as a multivariate tool for selecting stable genotypes by integrating traits such as grain yield and biological yield alongside parametric and non-parametric stability indices. Composite analysis of variance revealed that the grain yield and biological yield of the studied maize lines were significantly influenced (at P ≤ 0.01) by environment, genotype, and genotype × environment interaction. The MGIDI index for grain yield and biological yield facilitated the selection of lines that maximized selection differential and genetic gain. Heritability estimates across environments for these two traits were high, approaching 90%. Based on the results of this index, lines No. 9, 22, and 27 were desirable for grain yield, while lines No. 1, 9, 11, 13, and 27 excelled in biological yield and stability for both traits. Line No. 9 (P14L1Kahriz) and Line No. 27 (P16L12Kahriz) were present in selections for both traits and are recommended as the superior lines. Overall, the findings of the present study demonstrated that the MGIDI index can successfully select desirable maize genotypes across the four environments for the two key traits of grain yield and biological yield. Therefore, combining the MGIDI index with stability statistics provides a simple, comprehensive, and reliable approach for selecting high-yielding and stable maize lines, which can serve as a model for future studies.
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