Scholarlink

<p>Heavy metal contamination, particularly cadmium (Cd) and nickel (Ni), poses severe threats to agricultural productivity and environmental sustainability. This study aimed to evaluate the response of 20 maize genotypes under Cd, Ni, and combined (Cd + Ni) stress to identify resilient genotypes for breeding programs. A greenhouse experiment was conducted with four treatments: control, Cd (5 mM), Ni (5 mM), and Cd + Ni (2.5 + 2.5 mM). Morphological (plant height, root and shoot length, biomass) and physiological (chlorophyll content, moisture content, stomatal traits) traits were measured. Principal component analysis (PCA), the multi-trait genotype ideotype distance index (MGIDI), and decision tree algorithms were used to analyze genotype performance and identify key stress tolerance traits. Heavy metal stress significantly reduced germination, plant height, biomass, and chlorophyll content, with the most severe reductions observed under Cd + Ni stress. Correlation analysis revealed strong associations (e.g., root moisture and fresh root weight, <i>r</i> = 0.86***). MGIDI suggested that genotypes 53P4 and F-206-1 consistently outperformed others. Decision tree analysis highlighted fresh shoot length (FSL) as a key predictor of stress tolerance. This study highlights the superior resilience of maize genotypes 53P4 and F-206-1 under heavy metal stress, providing a valuable foundation for breeding tolerant varieties to enhance productivity and support sustainable agriculture in contaminated soils.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Harnessing Multivariate and Machine Learning Tools for Morpho-Physiological Traits to Reveal Maize Genotype Performance Against Heavy Metals Stress

  • 期刊论文

  • 发表日期：

    2025年6月16日

查看全文
  • Saba Akram,
  • Benish Iltaf,
  • Asma Shabbir,
  • Jamshaid Ali Junaid

摘要

Heavy metal contamination, particularly cadmium (Cd) and nickel (Ni), poses severe threats to agricultural productivity and environmental sustainability. This study aimed to evaluate the response of 20 maize genotypes under Cd, Ni, and combined (Cd + Ni) stress to identify resilient genotypes for breeding programs. A greenhouse experiment was conducted with four treatments: control, Cd (5 mM), Ni (5 mM), and Cd + Ni (2.5 + 2.5 mM). Morphological (plant height, root and shoot length, biomass) and physiological (chlorophyll content, moisture content, stomatal traits) traits were measured. Principal component analysis (PCA), the multi-trait genotype ideotype distance index (MGIDI), and decision tree algorithms were used to analyze genotype performance and identify key stress tolerance traits. Heavy metal stress significantly reduced germination, plant height, biomass, and chlorophyll content, with the most severe reductions observed under Cd + Ni stress. Correlation analysis revealed strong associations (e.g., root moisture and fresh root weight, r = 0.86***). MGIDI suggested that genotypes 53P4 and F-206-1 consistently outperformed others. Decision tree analysis highlighted fresh shoot length (FSL) as a key predictor of stress tolerance. This study highlights the superior resilience of maize genotypes 53P4 and F-206-1 under heavy metal stress, providing a valuable foundation for breeding tolerant varieties to enhance productivity and support sustainable agriculture in contaminated soils.