Genetic Association of Plant Physiological Parameters with Agronomically Important, Yield-Related Traits in American Cotton (Gossypium Hirsutum L.)

Muhammad  Younas; Muhammad  Zafar; Muhammad Kashif  Munir; Babar Hussain  Babar; Ali Hassan  Malik; Waseem  Sabir; Ghulam Mustfa  Siddiqui; Javed  Iqbal; Muhammad  Tauseef; Abdul Ghaffar  Khan; Musarrat  Shaheen; Muhammad Atif  Shabir; Iqra  Ibrar; Syed Waqar Hussain  Shah; Ghulam  Murtaza; Imran  Akram; Muhammad Rashid  Farooq; Salma  Kausar; Javid  Qamar; Natasha  Kanwal; Sabir  Hussain; Muhammad Irfan  Yousaf

doi:10.54112/bcsrj.v6i2.1628

Authors

Muhammad Younas Oilseed Research Institute, AARI Faisalabad, Pakistan
Muhammad Zafar Sugarcane Research Institute, AARI Faisalabad, Pakistan
Muhammad Kashif Munir Forage Crops Section, Faisalabad, Fodder Research Institute, Sargodha, Pakistan
Babar Hussain Babar Sugarcane Research Institute, AARI Faisalabad, Pakistan
Ali Hassan Malik Soil fertility Ayub Agricultural Research Institute, Faisalabad, Punjab, Pakistan
Waseem Sabir Agricultural Biotechnology Research Institute, AARI Faisalabad, Pakistan
Ghulam Mustfa Siddiqui Pulses Research Institute, AARI Faisalabad, Pakistan
Javed Iqbal Pulses Research Institute, AARI Faisalabad, Pakistan
Muhammad Tauseef Cotton Research Institute, Multan, Pakistan
Abdul Ghaffar Khan Soil Fertility (Field), Lahore, Pakistan
Musarrat Shaheen Cotton Research Institute, Khanpur, Pakistan
Muhammad Atif Shabir Cotton Research Sub-Station, Rajanpur, Pakistan
Iqra Ibrar Maize and Millets Research Institute, Yusafwala-Sahiwal, Pakistan
Syed Waqar Hussain Shah Entomological Research Sub-Station, Bahawalpur, Pakistan
Ghulam Murtaza Pesticide Quality Control Laboratory Bahawalpur, Pakistan
Imran Akram Regional Agricultural Research Institute, Bahawalpur, Pakistan
Muhammad Rashid Farooq Soil Fertility (Field), Bahawalpur, Pakistan
Salma Kausar Pesticide Quality Control Laboratory Bahawalpur, Pakistan
Javid Qamar Soil Fertility (Field), Bahawalpur, Pakistan
Natasha Kanwal Regional Agricultural Research Institute, Bahawalpur, Pakistan
Sabir Hussain Regional Agricultural Research Institute, Bahawalpur, Pakistan
Muhammad Irfan Yousaf Cotton Research Station, Bahawalpur, Pakistan

DOI:

https://doi.org/10.54112/bcsrj.v6i2.1628

Keywords:

Upland Cotton, Multivariate Analysis, Principal Component Analysis, Correlation

Abstract

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.

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