Genotype plus genotype by-environment interaction biplot and genetic diversity analyses on multi-environment trials data of yield and technological traits of cotton cultivars

Abstract

Understanding the genetic diversity and overcoming genotype-by-environment interaction issues is an essential step in breeding programs that aims to improve the performance of desirable traits. This study estimated genetic diversity and applied genotype + genotype-by-environment (GGE) biplot analyses in cotton genotypes. Twelve genotypes were evaluated for fiber yield, fiber length, fiber strength, and micronaire. Estimation of variance components and genetic parameters was made through restricted maximum likelihood and the prediction of genotypic values was made through best linear unbiased prediction. The modified Tocher and principal component analysis (PCA) methods, were used to quantify genetic diversity among genotypes. GGE biplot was performed to find the best genotypes regarding adaptability and stability. The Tocher technique and PCA allowed for the formation of clusters of similar genotypes based on a multivariate framework. The GGE biplot indicated that the genotypes IMACV 690 and IMA08 WS were highly adaptable and stable for the main traits in cotton. The cross between the genotype IMACV 690 and IMA08 WS is the most recommended to increase the performance of the main traits in cotton crops.

First Report on the Genetic Diversity of Populations of Gossypium barbadense L. and Gossypium hirsutun L. in the Amazonian Native Communities, Cusco-Peru

“…The description provided by MINAM [ 2 ] did not report the presence of G. hirsutum L. in the region of Cusco; however, in the regions of Cajamarca, Lambayeque, and Pasco, these species can be found. On the other hand, it is known that G. hirsutum L. is an introduced and cultivated species [ 28 ]; its origin is Mexico [ 9 ], and its fiber is very important for the countries that cultivate it [ 10 , 21 ]. The accounts of the natives living in these localities confirmed the use of this species and showed the importance of these cotton species among indigenous communities.…”

“…Knowing the diversity of cotton is important, as Gossypium is a genus that easily hybridizes through genotype–environment interactions (G×E) [ 20 , 21 ]. Diversity studies are important and provide new knowledge that makes it possible to improve and recover native cottonwoods; they also deepen our understanding of how species have adapted to different environments [ 20 , 21 , 22 ]. In the case of Lower and Upper Urubamba in the province of La Convención-Cusco, hybridization is already occurring, as demonstrated in recent studies [ 22 ].…”

Comparative analysis of key fiber characteristics in white Pima cotton (Gossypium barbadense L.): Native accessions from the Peruvian Amazon

“…Multiple genes control fiber quality traits with a negative relationship with productive potential, which has often restricted advances in improving the fiber quality of new commercial varieties (Arriel et al., 2023; Hayat & Bardak, 2020; Ijaz et al., 2019; Li et al., 2022; Liu et al., 2020). Furthermore, some studies have reported that commercial upland cotton cultivars are losing some fiber quality characteristics, such as fiber strength (Hinze et al., 2016; Peixoto et al., 2022). In this context, the genetic breeding of fiber quality depends on exploring and efficiently using available plant genetic resources (He et al., 2021).…”

ESTIMATION GENOTYPIC ENVIRONMENTAL INTERACTION BY USING GGE BI-PLOT ANALYSIS OF COTTON GENOTYPES (Gossypium hersutum L)

“…High performance of genotype under different environmental conditions is a most important goal in breeding program, therefore the interaction must be consider through testing potential ability under different environmental conditions [5]. GGE biplot analysis use principal component analysis in explanations the differences among genotypes in terms of figures illustrate variability caused differences in traits in terms of stability parameters [6,7]. Seed cotton yield and it's components almost aren't congruent in their performance in different environments [8,9].…”