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<p>Climate change has intensified the frequency of simultaneous drought and heat stress, posing a major threat to cotton productivity. This study aimed to evaluate the morpho-physiological and biochemical responses of 40 upland cotton genotypes at the seedling stage, an efficient phase for early stress screening. The experiment was conducted in a controlled environment, with stress treatments (control, drought, heat, combined) replicated thrice. Twenty traits, including shoot/root length, biomass, relative water content (RWC), chlorophyll pigments, proline, total soluble proteins, antioxidant enzymes (SOD, POD, CAT, APX), and oxidative markers, were measured. Drought primarily reduced root traits and osmolytes; heat caused pigment and protein degradation. Combined stress (DHS) triggered compounded suppression in RWC, APX, Chl.a, and biomass, indicating synergistic cellular injury. Antioxidant activities were non-monotonic at peak stress, supporting the ROS-threshold ‘oxidative window’ model, stating that antioxidant activities did not increase monotonically at the highest stress intensity. Mean squares and standard deviations revealed significant genotype × stress interactions. Cluster analysis and dendrograms grouped genotypes into three distinct tolerance categories. Discriminant Function Analysis effectively separated genotypes based on multi-trait performance. Principal Component Analysis (PCA) identified RWC, Chl.a, APX, and root dry weight as key discriminators of tolerance. These discriminators are consistent with genotypes that maintain ROS within an optimal signaling window, sustaining detox capacity (e.g., APX) and water/pigment status under DHS. Genotypes G2 (MNH-886), G10 (NIAB-545), and G14 (MNH-988) emerged as the most tolerant. Seedling-stage screening, coupled with a targeted multivariate panel, enables early selection of climate-resilient cotton under combined stress.</p>

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Oxidative-window homeostasis in cotton under drought and heat defines climate resilience and guides genotype selection via the ROS-threshold model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月3日

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  • Zafran Khan,
  • Nimra Gul,
  • Maria Riaz,
  • Bakhtawar Zubair,
  • Mazhar Tariq,
  • Azeem Iqbal Khan,
  • Amir Shakeel,
  • Daniel K. Y. Tan

摘要

Climate change has intensified the frequency of simultaneous drought and heat stress, posing a major threat to cotton productivity. This study aimed to evaluate the morpho-physiological and biochemical responses of 40 upland cotton genotypes at the seedling stage, an efficient phase for early stress screening. The experiment was conducted in a controlled environment, with stress treatments (control, drought, heat, combined) replicated thrice. Twenty traits, including shoot/root length, biomass, relative water content (RWC), chlorophyll pigments, proline, total soluble proteins, antioxidant enzymes (SOD, POD, CAT, APX), and oxidative markers, were measured. Drought primarily reduced root traits and osmolytes; heat caused pigment and protein degradation. Combined stress (DHS) triggered compounded suppression in RWC, APX, Chl.a, and biomass, indicating synergistic cellular injury. Antioxidant activities were non-monotonic at peak stress, supporting the ROS-threshold ‘oxidative window’ model, stating that antioxidant activities did not increase monotonically at the highest stress intensity. Mean squares and standard deviations revealed significant genotype × stress interactions. Cluster analysis and dendrograms grouped genotypes into three distinct tolerance categories. Discriminant Function Analysis effectively separated genotypes based on multi-trait performance. Principal Component Analysis (PCA) identified RWC, Chl.a, APX, and root dry weight as key discriminators of tolerance. These discriminators are consistent with genotypes that maintain ROS within an optimal signaling window, sustaining detox capacity (e.g., APX) and water/pigment status under DHS. Genotypes G2 (MNH-886), G10 (NIAB-545), and G14 (MNH-988) emerged as the most tolerant. Seedling-stage screening, coupled with a targeted multivariate panel, enables early selection of climate-resilient cotton under combined stress.