Identification of Adapted and Stable Cultivars, Using the AMMI Model and Linear Regression Technique

Identify superior performing genotypes across a wide range of environmental conditions, is an important topic in genetics, plant breeding, and agronomy. This paper focus in the main properties of linear regression analysis (LR), and of the additive main effects and multiplicative interaction (AMMI) model. The study compares LR and AMMI with particular emphasis in determining yield stability of different genotypes across different environments. The application is made using a data set from a breeding program of durum wheat (Triticum aestivum L., Durum Group) conducted in Portugal. The results of the two models shows that the AMMI analysis had more stable results, being more efficient in describing the GE interaction than the LR.