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Genetic Variability and Trait Association Analysis in Upland Cotton (Gossypium Hirsutum L) for Yield, Fiber Quality, and Physiological Attributes

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Cotton is a major cash crop globally, with both yield and the fiber quality parameters highly influenced by both genetic and environmental factors. The present study evaluated 30 cotton (Gossypium hirsutum L.) genotypes for morphological, physiological, and fiber quality traits to assess genetic variability, heritability, and trait associations under field conditions. The experiment was laid out in a randomized complete block design (RCBD) with three replications. Significant genotypic variation (p < 0.001) was observed across all studied traits, including plant height, boll weight, number of bolls, seed cotton yield per plant, ginning outturn, and fiber parameters such as span length, micronaire, and strength. Physiological traits such as photosynthetically active radiation, leaf temperature, net photosynthesis, and transpiration rate also showed considerable variation. High genotypic and phenotypic coefficients of variation (GCV and PCV) were recorded for yield per plant, number of bolls, and physiological traits, while fiber traits exhibited moderate to low variation. Broad-sense heritability measures were high (>80%) for maximum traits, with substantial genetic advance, indicating predominance of additive gene action and the potential for improvement through simple selection. Positive and significant correlations were observed between yield per plant and physiological traits, particularly photosynthesis (r = 0.91), stomatal conductance (r = 0.72), and transpiration rate (r = 0.60). Multiple regression analysis confirmed that photosynthesis, transpiration rate, plant height, and boll weight significantly contributed to yield variability. Principal component analysis (PCA) revealed that five principal components accounted for 78.5% of the total variation, with PC1 alone explaining 33.1%. Genotypes such as Bahar-7, CIM-599, FH-901, and CKC-28 were identified as genetically diverse and high-yielding, making them suitable candidates for future breeding programs.
Title: Genetic Variability and Trait Association Analysis in Upland Cotton (Gossypium Hirsutum L) for Yield, Fiber Quality, and Physiological Attributes
Description:
Cotton is a major cash crop globally, with both yield and the fiber quality parameters highly influenced by both genetic and environmental factors.
The present study evaluated 30 cotton (Gossypium hirsutum L.
) genotypes for morphological, physiological, and fiber quality traits to assess genetic variability, heritability, and trait associations under field conditions.
The experiment was laid out in a randomized complete block design (RCBD) with three replications.
Significant genotypic variation (p < 0.
001) was observed across all studied traits, including plant height, boll weight, number of bolls, seed cotton yield per plant, ginning outturn, and fiber parameters such as span length, micronaire, and strength.
Physiological traits such as photosynthetically active radiation, leaf temperature, net photosynthesis, and transpiration rate also showed considerable variation.
High genotypic and phenotypic coefficients of variation (GCV and PCV) were recorded for yield per plant, number of bolls, and physiological traits, while fiber traits exhibited moderate to low variation.
Broad-sense heritability measures were high (>80%) for maximum traits, with substantial genetic advance, indicating predominance of additive gene action and the potential for improvement through simple selection.
Positive and significant correlations were observed between yield per plant and physiological traits, particularly photosynthesis (r = 0.
91), stomatal conductance (r = 0.
72), and transpiration rate (r = 0.
60).
Multiple regression analysis confirmed that photosynthesis, transpiration rate, plant height, and boll weight significantly contributed to yield variability.
Principal component analysis (PCA) revealed that five principal components accounted for 78.
5% of the total variation, with PC1 alone explaining 33.
1%.
Genotypes such as Bahar-7, CIM-599, FH-901, and CKC-28 were identified as genetically diverse and high-yielding, making them suitable candidates for future breeding programs.

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