Genetic variability analyses considering multi-environment trials in maize breeding

Clustering techniques are widely adopted in genetic variability assessments. Aiming to understand the genotypes contrasting and complementarity, breeders have used those methodologies to guide them through crosses recommendation or heterotic group’s formation. In multi-environment trials (MET) studies, the clustering analyses are under influence of the genotype by environment interaction (GEI) effect. Thus, the goal of this study was to compare clustering analyses dealing with MET data. For this purpose, eight traits were assessed from 84 maize genotypes, whereas Tocher and Unweighted Pair Group Method with Arithmetic Mean clustering analyses were applied. The variance components were estimated through restricted maximum likelihood and genetic values were predicted by best linear unbiased prediction. The significance of the random effects of the statistical model was tested by the likelihood ratio test, attention was given to grain yield (GY) trait, that presented significant GEI effect. The variance components and genetic parameters varied among environments, considering the grain yield trait, for instance, the heritability varied from 21.51 to 47.65%, and in the joint analysis the heritability was 24.65%, evidencing the importance of joint analysis on MET studies. Finally, it was compared the number of clusters formed in the environments, individual and jointly, by both clustering methods. After these analyses, it was possible to conclude the importance of joint analysis in MET genetic variability study, recommending potential and complementary genetic materials, as the cross 11 × 65 indicated by both clustering methods.