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<p>An experiment using a randomized complete block design (RCBD) with three replications was conducted on 10 corn genotypes to evaluate the effect of genotype × trait interaction on grain yield. Analysis of variance revealed that all genotypes differed significantly (<i>p</i> &lt; 0.01) across all traits. Duncan’s multiple range test identified KSC704 and KSC706 as favorable genotypes, while SC540 and KSC260 were considered unfavorable. Correlation analysis showed a positive association between grain yield and chlorophyll a, chlorophyll b, phosphorus, carotenoids, sodium, catalase, and potassium. Principal component analysis indicated that the first five components accounted for over 79% of the total data variance. Based on the first two principal components, the genotypes were grouped into four distinct clusters, and the traits into three. A graphical assessment of genotype performance was also conducted. According to the polygon view, genotypes KSC705, KSC400, KSC706, DC370, SC540, and KSC260 were identified as favorable. Among them, KSC705 and KSC400 were selected as the most desirable genotypes based on trait-based and ideal-genotype ranking diagrams. The biplot analysis further confirmed the grouping of genotypes into four distinct clusters.</p>

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Physiological and biochemical pathway: understanding their influence on maize grain yield through genotype–trait interactions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月26日

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  • Pooria Mazloom,
  • Seyed Habib Shojaie,
  • Seyed Mohammad Nasir Mousavi

摘要

An experiment using a randomized complete block design (RCBD) with three replications was conducted on 10 corn genotypes to evaluate the effect of genotype × trait interaction on grain yield. Analysis of variance revealed that all genotypes differed significantly (p < 0.01) across all traits. Duncan’s multiple range test identified KSC704 and KSC706 as favorable genotypes, while SC540 and KSC260 were considered unfavorable. Correlation analysis showed a positive association between grain yield and chlorophyll a, chlorophyll b, phosphorus, carotenoids, sodium, catalase, and potassium. Principal component analysis indicated that the first five components accounted for over 79% of the total data variance. Based on the first two principal components, the genotypes were grouped into four distinct clusters, and the traits into three. A graphical assessment of genotype performance was also conducted. According to the polygon view, genotypes KSC705, KSC400, KSC706, DC370, SC540, and KSC260 were identified as favorable. Among them, KSC705 and KSC400 were selected as the most desirable genotypes based on trait-based and ideal-genotype ranking diagrams. The biplot analysis further confirmed the grouping of genotypes into four distinct clusters.