Estimating of Stability Parameters among some Extra Long Staple Cotton Genotypes under Different Environments

Abstract

Understanding the implication of genotype x environment interaction (GEI) structure is an important consideration in plant breeding programs. A significant GE interaction for a quantitative trait such as yield can seriously limit efforts in selecting superior genotypes for both new crop introduction and cultivar improving. In order to, select the best lines in Egyptian cotton breeding programme two trials must be done, the first one is preliminary trial (HA) which has sown in one location and the second one is the advanced trial or regional trial (HB) sown in the production area of Egyptian extra-long staple cotton varieties. The experimental design for the two trials was a randomized complete block design with six replications in each location and each entry was grown in plot of five rows. Forty two cotton genotypes showed highly significant differences in trial A. twenty four selected genotypes from trial A was evaluated in the regional trial (HB) and the combined analysis of variance showed highly significant differences for the genotypes, environments and G x E interaction indicating the possibility to select the most stable genotypes in trial HB across five locations. two genotypes No. 11 and 18 are stable for the three studied traits and No. 14 for seed cotton yield and lint yield are good adapted for the most important cotton production locations for extra-long staple cotton varieties using Eberhart and Russell model. The results of AMMI analysis indicated that the first two AMMI (IPCA1 and IPCA2) were highly significant. The first two multiplicative components of the interaction accounted for 58.77, 68.20 and 77.13 % of the sum of squares for boll weight, seed cotton yield and lint yield, respectively. AMMI stability value (ASV) and yield stability index (YSI) are suitable stability indices in discriminating stable genotypes with high mean yield performance. Four genotypes No. 6, 12, 14 and 17) are stable under the two phenotypic models.

Parametric Stability and Principal Components Analysis of some Egyptian Cotton Cultivars under Different Environments

“…These results were in harmony with Dewdar (2013), Abd El-Aziz (2014), Gibely et al (2015), Ali (2017) and Abro et al (2020). Gibely and Hassan (2018) indicated highly significant differences for the genotypes, environments and G x E interaction indicating the possibility to select the most stable genotypes for quantitative traits across different environments.…”

“…Meanwhile, cultivar G 86 and G 88 performed consistently better in favorable environments (bi>1), one of them (cultivar G 86) showed a high mean when compared with the mean overall cultivars (Table 9). Similar conclusion was reported by Abd El-Aziz (2014), Gibely et al (2015), Ali (2017) and Gibely and Hassan (2018). Dewdar (2013) indicated that the two cultivars Giza 90 Giza 80 met the two criteria (bi did not differ significantly from one and S 2 d close significantly from zero or equal zero) for lint yield trait.…”

“…Dewdar (2013) found Giza 90 and Giza 80 cultivars were stable across the studied environments with high seed cotton yield. Gibely and Hassan (2018) found genotype No. 14 for seed cotton yield was good adapted for the most important cotton production locations for extra-long staple cotton varieties using Eberhart and Russell model.…”

Stability Analyses of Early Segregating Egyptian Cotton Populations and Their Parents Across different Irrigation Intervals and Sowing Dates.

“…The rank-sum (Rs) and simultaneous selection for yield and stability (YSi) were widely used as selection criteria due to both considered both yield and stability and enables the identification of high-yielding and stable genotypes. Recently cotton breeders used different stability methods to estimate GEI through multilocation trials for Egyptian cotton genotypes under different environments (Khalifa et al, 2010;Dewdar, 2013;Said, 2016;Gibely and Hassan, 2018;Shaker et al, 2020 as well as Said and Hefny, 2021).The capability of various parametric and nonparametric stability concepts for identification the extent stability and their interrelationships may be violated due to lacking data normality and or homogeneity of error terms (Kang,1988).…”