Genetic Association of Plant Physiological Parameters with Agronomically Important, Yield-Related Traits in American Cotton (Gossypium Hirsutum L.) - Younas, Muhammad; Zafar, Muhammad; Munir, Muhammad Kashif; Babar, Babar Hussain; Malik, Ali Hassan; Sabir, Waseem; Siddiqui, Ghulam Mustfa; Iqbal, Javed; Tauseef, Muhammad; Khan, Abdul Ghaffar; Shaheen, Musarrat; Shabir, Muhammad Atif; et al. (Biological and Clinical Sciences Research Journal, 2025)
Cotton (Gossypium hirsutum L.) productivity in semi-arid regions like Pakistan is severely constrained by water scarcity and heat stress. With an average yield of 570.99 kg/ha, Pakistan lags behind major cotton-producing countries such as China (1,992 kg/ha), emphasizing the urgent need for identifying climate-resilient, high-yielding genotypes. Objective: To evaluate the physiological and yield-related performance of ten elite cotton genotypes under semi-arid conditions, and to identify superior candidates for breeding programs to improve cotton yield. Methods: A field trial was conducted at the Cotton Research Station, Bahawalpur, using a Randomized Complete Block Design (RCBD) with three replications. Ten cotton genotypes (BH-188, BH-226, BH-291, BH-403, BH-407, BH-410, BH-423, BH-563, BH-184, and CIM-600) were assessed for physiological traits including photosynthetic rate, stomatal conductance, and transpiration rate, as well as yield-related parameters such as boll weight, number of sympodial branches, and seed cotton yield. Statistical analyses included ANOVA, Pearson correlation, Principal Component Analysis (PCA), and cluster analysis to determine genotypic variation and trait associations. Results: ANOVA revealed highly significant genotypic differences (p ≤ 0.01) for most traits: seed cotton yield (F = 2.89245), photosynthetic rate (F = 15.793), and sympodial branches (F = 7.4963). Correlation analysis demonstrated strong positive relationships between yield and sympodial branches (r = 0.75*) and boll weight (r = 0.25). PCA showed that the first two principal components (PC1 = 33%, PC2 = 21.6%) explained 54.6% of the total variation, primarily influenced by yield and physiological traits. Cluster analysis grouped genotypes into three distinct clusters, with Cluster 1 (BH-188, BH-226, BH-410) exhibiting the highest yield (4.56 t/ha), driven by superior photosynthetic rate (30.33 µmol m⁻² s⁻¹) and sympodial branching (21.66). Conclusion: This study highlights BH-226 and BH-410 as promising candidates for breeding programs to enhance cotton yield under semi-arid conditions. Their superior physiological efficiency and yield-related traits present viable solutions to overcoming productivity challenges in water-stressed environments. These genotypes can be pivotal in developing climate-resilient cotton varieties tailored to Pakistan’s agro-climatic conditions.