Genotypic Path Coefficient Analysis of Cotton Derived through Introgression

Abstract

Present investigation was carried out with 38 cotton genotypes including both the species G. arboreum and G. hirsutum in randomized complete block design with three replications. The observations were reported form three randomly selected plant from each treatment and replication on 17 characters viz., Plant height (cm), number of nodes per plant, length of internodes (cm), number of monopodia per plant, number of sympodia per plant, number of bolls per plant. Boll weight (g), seed cotton yield per plant (g), ginning out turn (%), lint index (g), seed index (g), fibre quality traits including 2.5% span length, fineness (MIC), bundle strength. Fibre elongation, uniformity ratio (UR) and short fibre index (SFI). Path coefficient analysis revealed positive direct genotypic effect on seed cotton yield per plant through boll weight, number of bolls per plant, seed index, ginning out turn, number of sympodia per plant, 2.5% span length, length of internodes, short fibre index, fibre elongation and number of monopodia per plant while negative direct effect was observed with lint index, plant height, bundle strength, number of nodes per plant and micronaire value except lint index that had positive direct phenotypic effect on seed cotton yield per plant. The positive direct effect on seed cotton yield per plant through boll weight, number of bolls per plant, seed index, ginning out turn, number of sympodia per plant, 2.5% span length, length of internodes, short fibre index, fibre elongation and number of monopodia per plant reveals that these traits can be directly manipulated for increased yield and fibre quality.

Authors and Affiliations

Ashish Gulhane, M. S. Wadikar

Keywords

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  • EP ID EP568244
  • DOI 10.20546/ijcmas.2017.602.007
  • Views 59
  • Downloads 0

How To Cite

Ashish Gulhane, M. S. Wadikar (2017). Genotypic Path Coefficient Analysis of Cotton Derived through Introgression. International Journal of Current Microbiology and Applied Sciences (IJCMAS), 6(2), 49-55. https://europub.co.uk/articles/-A-568244