Model Selection and Cross Validation in Additive Main Effect and Multiplicative Interaction Models

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Genotype by environment interaction components underlying variations in root, sugar and white sugar yield in sugar beet (Beta vulgaris L.) (2018, background): “Two basic approaches, cross validation and test of hypothesis about the number of components, have evolved to identify the optimal number of multiplicative terms in dissection of GEI mean squares (Gauch and Zobel 1988; Cornelius 1993; Dias and Krzanowski 2003; Gauch 2013).”
Biplot Analysis of Genotype × Environment Interaction: Proceed with Caution (2009, background): “, 2005), and various schemes for cross validation and model choice (e.g., Gauch, 1988; Cornelius and Crossa, 1999; Dias and Krzanowski, 2003).”
Statistical analysis of yield trials by AMMI analysis of genotype × environment interaction (2014, methodology): “…in a unique model, additive components for the main effects of genotypes (gi), environments (ej) and multiplicative components for the interaction effect (ge)ij (Gauch, 1992; Dias and Krzanowski, 2003; Garćıa-Peña and Dias, 2009; Arciniegas-Alarcn et al., 2011; Gauch et al., 2011; Gauch, 2013).”