Investigating the nature of GxE interaction under different management systems and yield levels using linear-bilinear models: The case of CIMMYT maize hybrids trials in Eastern Africa

Abstract

The International Center for Maize and Wheat Improvement(CIMMYT) conducts selection of stress-tolerant genotypes under managed stress conditions. Data sets for this study were from Intermediate to Late Hybrid Trials (ILHT) conducted in five Eastern and Central Africa (ECA) countries from 2008 to 2011. Several trials, which were categorized into four management systems and two yield levels were used for this study. Variance Components, broad sense heritability (H), Site Regression (SREG), Genotypic Regression (GREG) and Factor Analytic (FA) models were fitted. We argue that it is preferable to first fit the fixed effect models before proceeding to the mixed effect model, as the former shows the level of complexity of the GE component and the number of axes required to explain it. The fixed effect model, SREG2, is preferable for trials targeting comparison of hybrids with checks. From the GGE biplots it was noted that the first two principale components (PC) did not account for sufficient percentage of variation for all years. Nevertheless, since PC1 accounted for large percentage of variation than PC2, the plot gives some idea of which hybrids won where. Most importantly, location of genotypes along PC1 can serve for judging yielding potential of the genotypes to guide in selection decision. Equivalence between Finlay - Wilkinson and GREG was established. The few environmental covariables obtained for 2009 were used to fit Partial Least Square (PLS) regression. The result indicated complexity in the GE component, as PLS latent factors accounted for small percentage of variation. It was recommended to use information from SREG2, GREG2 and FA(1) models in order to identify stable genotypes.

Keywords: AMMI, Biplot, Factor Analytic Model, GREG, Mixed Effect Model, SREG, Stability.