AMMI analysis of the adaptability and yield stability of yellow passion fruit varieties

Abstract

High yield stability and adaptability of yellow passion fruit varieties (Passifl ora edulis Sims. f. fl avicarpa Deg.) are highly desirable attributes when exploring different environments.This study aimed to evaluate the adaptability and yield stability of yellow passion fruit varieties using AMMI (additive main effects and multiplicative interaction) and other ancillary statistics.Twelve varieties were evaluated in eight environments. Analysis of variance showed effects attributable to the varieties (G), environment (E) and their interaction (G×E). The fi rst two multiplicative components of the interaction accounted for 69% of the sum of squares. The scores of the principal interaction components showed high variability for the environments relative to the variety effects. High varietal phenotypic stability was observed in three environments; which can be used in yellow passion fruit breeding programs for initial selection trials. A biplot-AMMI analysis and yield stability index incorporating the AMMI stability value and yield capacity in a single non-parametric index were useful for discriminating genotypes with superior and stable fruit yield. AMMI analysis also allowed for the identifi cation of more productive varieties in specifi c environments, leading to signifi cant increase in passion fruit productivity.

Phenotypic stability in cassava estimated by the AMMI analysis with supplementary genotypes

“…Comparison of AMMI analysis applied to several different cultures indicates that this analysis typically explains 60% of the total variation by the SSGE interaction (Carbonell et al 2004, Kvitschal et al 2007, Gonçalves et al 2010, Barros et al 2013, Costa et al 2013, Mattos et al 2013, Oliveira et al 2014). …”

“…Therefore, the study on both adaptability and stability of genotypes is desirable in order to identify those with the most predictable responses to diverse environments. Among the several methodologies to analyze adaptability and stability (Eberhart and Russel 1966, Lin and Binns 1988, Gauch and Zobel 1996, Toler and Burrows 1998, the multivariate AMMI or Additive Main Effects and Multiplicative Interaction Analysis is the most widely used in Brazil (Carbonell et al 2004, Pacheco et al 2005, Kvitschal et al 2007, Kvitschal et al 2009, Gonçalves et al 2010, Oliveira et al 2010, Mattos et al 2013, Barros et al 2013, Oliveira et al 2014. This method combines analysis of variance and principal components to adjust the main effects (genotypes and environments) and the effects of G×E interactions Vencovsky 2001, Zobel et al 1988).…”

Genotype-by-environment interaction and yield stability analysis in sorghum (Sorghum bicolor (L.) Moench) genotypes in North Shewa, Ethiopia

“…De Oliveira et al (2014) pointed out that the stability information that is drawn using AMMI2 biplot is more precise than AMMI1 biplot because AMMI2 model contains information from IPCA1 and IPCA2 [19]. In AMMI2 model, those genotypes which are close to the nearby environment will perform better in that specific environments than those genotype which are far away [19]. AMMI2 also quantifies stability using AMMI stability value (ASV).…”

AMMI model to analyse GxE for dual purpose barley in multi-environment trials

“…On the other hand, same sign or near zero scores represent a non-crossover interaction or a proportionate genotype response (Silveira et al, 2013). The genotypes with lower IPCA1 scores would produce a lower absolute G×E interaction effect than those with higher absolute IPCA1 scores and have less variable yields (more stable) across genotypes (Oliveira et al, 2014). Genotypes G5(RD 2715) and G7(BH 971) with yields greater than the overall mean and low IPCA1 scores had a combination of high yield and stability performances (Table 3a).…”

“…The discriminating ability of the environments can be judged by calculating the distance of each environment from the biplot origin (Oliveira et al, 2014). In this regard, the environments Banswara, Jalore and Hisar are most discriminating as indicated by long distance from the biplot origin.…”