Mean Performance and Stability in Multi‐Environment Trials I: Combining Features of AMMI and BLUP Techniques

Additive main effect and multiplicative interaction (AMMI) and best linear unbiased prediction (BLUP) are popular methods for analyzing multi‐environment trials (MET). The AMMI has nice graphical tools for modeling genotype‐vs.‐environment interaction (GEI) but fails in some aspects, such as accommodating a linear mixed‐effect model (LMM) structure. The BLUP provides reliable estimates but new insights to deal graphically with a random GEI structure are needed. This article compares the predictive success of BLUP and AMMI, shows how to generate biplots for modeling GEI in MET analysis using LMM, and proposes a new quantitative genotypic stability measure called WAASB, which is the W eighted A verage of A…

• CD
  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
• CN
  Conselho Nacional de Desenvolvimento Científico e Tecnológico