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.
Ramulosis is one of the most aggressive diseases in cotton, and understanding the genetic control of its resistance is imperative for selecting superior cotton genotypes in breeding programs. This study analyzed the inheritance pattern of this resistance using chi-square goodness-of-fit tests to determine the phenotypic proportions of the F2 generation, and a mixed inheritance approach to jointly model major gene and polygenes effects.
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.