Correlation and multivariate analysis across non-segregation and segregation generations in two cotton crosses [electronic resource]

By: Contributor(s): Language: English Summary language: Arabic Description: p. 380-390Other title:
  • الارتباطات والتحليل متعدد المتغيرات عبر الاجيال غير الإنعزالية والإنعزالية في هجينين من القطن [Added title page title]
Uniform titles:
  • Egyptian journal of agricultural research, 2021 v. 99 (4) [electronic resource]
Subject(s): Online resources: In: Egyptian Journal of Agricultural Research 2021.v.99(4)Summary: The present research uses Pearson’s correlation coefficient and multivariate analysis to assess the interrelationships, similarities, and dissimilarities among non-segregation (P1, P2 and F1) and segregation (F2, BC1 and BC2) generations for seed cotton yield and yield components in the two crosses, Giza 92 x Pima S6 and Giza 93 x C.B. 58. For all variables evaluated in the two crossings, the analysis of variance revealed significantly substantial genetic variability across six generations. For all of the tested features in the two crossings, the F1 performed better than the other generations. Across all six generations of the two crossings, there were positive and highly significant correlations between seed cotton yield/plant, lint cotton yield/plant, and no. of bolls/plant characteristics. Seed cotton yield and yield components in the two crosses showed some favourable connections over the six generations. The UPGMA hierarchical clustering revealed a greater degree of similarity coefficients between the six generations and the attributes investigated. The similarity coefficients for the six generations and the examined features, respectively, ranged from 0.96 to 0.99 and 0.65 to 0.96. In the principal component analysis (PCA), the PCA1 extracted had an Eigenvalue of greater than 1 across six generations for all studied traits in the two crosses. The PCA displayed a total variation of 91.84% among the six generations contributed by PCA1 (79.47%) and PCA2 (12.38%) and mainly distinguished the generations into different groups. The PCA1 and PCA2 were dominated by F1 and segregation generations in the two crosses, respectively, showing high correlations with the first two PCAs. All studied traits, as well as boll weight and lint percentage traits, contributed to positive significant component loadings for the PCA1 and PCA2, respectively. The biplot analysis of the relationship between the six generations revealed that the most appropriate generations for selecting yield traits were F1 in the two crosses and BC1 and BC2 in the cross Giza 93 x C.B. 58. As a result, we recommend considering backcrossing for 2–5 cycles (BC2–BC5) at the C.B. 58 parent in the future to improve Egyptian cotton yield. Keywords: Generations, Correlation, Multivariate Analysis, Cotton.
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The present research uses Pearson’s correlation coefficient and multivariate analysis to assess the interrelationships, similarities,
and dissimilarities among non-segregation (P1, P2 and F1) and segregation (F2, BC1 and BC2) generations for seed cotton yield and yield
components in the two crosses, Giza 92 x Pima S6 and Giza 93 x C.B. 58. For all variables evaluated in the two crossings, the analysis
of variance revealed significantly substantial genetic variability across six generations. For all of the tested features in the two crossings,
the F1 performed better than the other generations. Across all six generations of the two crossings, there were positive and highly significant
correlations between seed cotton yield/plant, lint cotton yield/plant, and no. of bolls/plant characteristics. Seed cotton yield and yield
components in the two crosses showed some favourable connections over the six generations. The UPGMA hierarchical clustering revealed a greater
degree of similarity coefficients between the six generations and the attributes investigated. The similarity coefficients for the six generations
and the examined features, respectively, ranged from 0.96 to 0.99 and 0.65 to 0.96. In the principal component analysis (PCA), the PCA1 extracted
had an Eigenvalue of greater than 1 across six generations for all studied traits in the two crosses. The PCA displayed a total variation of 91.84%
among the six generations contributed by PCA1 (79.47%) and PCA2 (12.38%) and mainly distinguished the generations into different groups.
The PCA1 and PCA2 were dominated by F1 and segregation generations in the two crosses, respectively, showing high correlations with the
first two PCAs. All studied traits, as well as boll weight and lint percentage traits, contributed to positive significant component loadings
for the PCA1 and PCA2, respectively. The biplot analysis of the relationship between the six generations revealed that the most appropriate
generations for selecting yield traits were F1 in the two crosses and BC1 and BC2 in the cross Giza 93 x C.B. 58. As a result,
we recommend considering backcrossing for 2–5 cycles (BC2–BC5) at the C.B. 58 parent in the future to improve Egyptian cotton yield.
Keywords: Generations, Correlation, Multivariate Analysis, Cotton.

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