A comparison between Joint Regression Analysis and the Additive Main and Multiplicative interaction model: the robustness with increasing amounts of missing data

This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction(AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts ofrandomly selected missing data. The application is made using a data set from a breeding program of durum wheat(Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominantcultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had morestable results with the increase in the incidence rates of missing values.