Variation and Cluster Analysis for Segregating Populations of Egyptian Cotton (Gossypium barbadense L.) for Yield and Fiber Quality Traits under Different Environmental Conditions

Taha, Eman M.; Darwish, D. S.; El-Karamity, A. El.; Asaad, Mohamed Reda

doi:ء10.21608/jpp.2022.157809.1158

Variation and Cluster Analysis for Segregating Populations of Egyptian Cotton (Gossypium barbadense L.) for Yield and Fiber Quality Traits under Different Environmental Conditions

Document Type : Original Article

Authors

¹ Agronomy Department, Faculty of Agriculture, Minia University, El-Minia, 61517, Egypt.

² Agronomy Department, Faculty of Agriculture, Cairo University, 12613 Giza, Egypt.

³ Agronomy Department, Faculty of Agriculture, Minia University, El-Minia, Egypt

ء10.21608/jpp.2022.157809.1158

Abstract

The sufficient magnitudes of genetic variation and multivariate analysis of Egyptian cotton segregating populations for yield and quality traits under variable environmental conditions are required for effective selection of promising varieties that may be resilient to climatic changes. The current study will accomplish the obtained view of the first part of these investigations concerning the extent of stability accompanied of yield potentiality of these populations. The environmental conditions either early or late sown, irrigated each two weeks or four ones are highly significant sources of variation for all studied traits except seed index (of late sowing), boll weight (under all environments). Fiber quality traits seemed to be less sensitive to the differences that occurred due to sowing dates and/or irrigation intervals. The studied cotton genotypes had pronounced variations for all traits. The studied germplasm varied differently among different environments for all traits except boll weight. Segregating populations (C) exhibited lower magnitudes of variations than corresponding parents (P). The significance of variances due P vs C was more frequent under late sowing or water saving conditions than recommended planting dates or irrigation intervals. The obtained variation parameters and relative expected gains varied from environment to another and due to studied attributes. Cluster analysis proved to be beneficial for cotton selection program by sorting the singleton promising segregating populations rather than grouping similar ones. Thus, four F₂ungrouped populations: G90xAustralian (P1xP6), G90xG94(P1xP2), G94xG90CB(P2xP5) and G95xG90CB (P3xP5) exhibited superior performance under different investigated conditions and could be considered for generating promising cotton selections.

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