Genetic variability for yield and fiber related traits in genetically modified cotton

Abstract Background Cotton (Gossypium hirsutum L.) is grown for fiber and oil purposes in tropical and sub-tropical areas of the world. Pakistan is the 4th largest producer of cotton. It has a significant contribution in the GDP of Pakistan. Therefore, the present study was performed to assess the genetic variations and genetic diversity of yield and fiber quality traits in cotton and to analyze the associations present among them. Results Analysis of variance exhibited significant variation for all studied traits except total number of nodes and the height to node ratio. The phenotypic coefficient of variation was higher than the genotypic coefficient of variation for all studied traits. Plant height, monopodial branches, total number of bolls, lint index, seed index, and seed cotton yield displayed high heritabilities in a broad sense with maximum genetic advance. Correlation analysis revealed that seed cotton yield had a significant positive association with plant height, the number of monopodial branches, the number of sympodial branches, ginning outturn (GOT), the number of bolls, seed per boll, seed index, uniformity index, the number of sympodial branches, reflectance, and seed index at the genotypic level while a significant positive relationship was observed with plant height, the number of sympodial branches, boll number, and GOT. Plant height, monopodial branches, GOT, boll weight, seeds per boll, and short fiber index exerted direct positive effects on seed cotton yield. The first 6 principal component analysis (PCs) out of the total fourteen PCs displayed eigenvalues (> 1) and had maximum share to total variability (82.79%). The attributes that had maximum share to total divergence included plant height, uniformity index, the number of sympodial branches, seed per boll, GOT, seed cotton yield, and short fiber index. Conclusion The genotype AA-802, IUB-13, FH-159, FH-458, and CIM-595 were genetically diverse for most of the yield and fiber quality traits and could be utilized for the selection of better performing genotypes for further improvement.