Biplot analysis of phenotypic stability in upland cotton genotypes in Mato Grosso

Seed cotton yield is a trait governed by multiple genes that cause changes in the performance of genotypes depending on the cultivation environment. Breeding programs examine the genotype x environment interaction (GE) using precise statistical methods, such as AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction). The AMMI method combines the analysis of variance and principal components, to adjust the main effects (genotypes and environments) and the effects of GE interaction, respectively. The GGE biplot groups the genotype additive effect together with the multiplicative effect of the GE interaction, and submits both of these to the principal components analysis. The aim of this study was to investigate the association between the AMMI and GGE biplot methods and select cotton genotypes that simultaneously showed high productivity of seed cotton and stability in Mato Grosso environments. Trials were conducted with cotton cultivars in eight environments across Mato Grosso State in the 2008/2009 crop season. The experiment used a randomized block design with 16 genotypes and four replicates per genotype x environment combination. Data for seeds cotton productivity were analyzed by AMMI and GGE biplot methods. Both methods were concordant in the discrimination of environments and genotypes for phenotypic stability. The genotypes BRS ARAÇÁ and LD 05 CV had high seed cotton productivity and phenotypic stability, and could be grown in all environments across Mato Grosso State

Usefulness of the HMRPGV method for simultaneous selection of upland cotton genotypes with greater fiber length and high yield stability

The harmonic mean of the relative performance of genotypic predicted value (HMRPGV) method has been used to measure the genotypic stability and adaptability of various crops. However, its use in cotton is still restricted. This study aimed to use mixed models to select cotton genotypes that simultaneously result in longer fiber length, higher fiber yield, and phenotypic stability in both of these traits. Eight trials with 16 cotton genotypes were conducted in the 2008/2009 harvest in Mato Grosso State. The experimental design was randomized complete blocks with four replicates of each of the 16 genotypes. In each trial, we evaluated fiber yield and fiber length. The genetic parameters were estimated using the restricted maximum likelihood/best linear unbiased predictor method. Joint selection considering, simultaneously, fiber length, fiber yield, stability, and adaptability is possible with the HMRPGV method. Our results suggested that genotypes CNPA MT 04 2080 and BRS CEDRO may be grown in environments similar to those tested here and may be predicted to result in greater fiber length, fiber yield, adaptability, and phenotypic stability. These genotypes may constitute a promising population base in breeding programs aimed at increasing these trait values