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

Scientia Agricola

Paulo Canas Rodrigues²  Dulce Gamito Santinhos Pereira¹  João Tiago Mexia² 

[1] ,Universidade Nova de Lisboa Faculdade de Ciências e Tecnologia CMA- Depto. de MatemáticaCaparica,Portugal

关键词: AMMI models;    genotype by environment interaction;    joint regression analysis;    missing values;    durum wheat;   

DOI  :  10.1590/S0103-90162011000600012

来源: SciELO

【 摘 要 】

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 of randomly 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 dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.

【 授权许可】

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