After standardization, covariates were always introduced in the following same order: GDDs_f, GDDf_m for the genotypic covariates and WATf, TM121_e, TMs_121, SRf for the environmental covariates.
In the 1-yr analyses, the mean temperature in the second part of the cycle (TM121_e) and water balance around flowering (WATf) were the most important (each explaining about 10.5%, on average), followed by mean temperature in the first part of the cycle (TMs_121; 7% on average) and radiation around flowering (SRf; about 5% on average).
Factorial regression analysis (Model ) for individual years, including four environmental covariates: WATf, TM12l_e, TMs_12l, SRf and two genotypic covariates: GDDs_f and GDDf_m.
The most meaningful cross-products were GDDs_f x WATf (0.86, 0.72 and 0.61% on average of interaction SS in the 1-, 2-, and 12-yr analyses) and GDDf_m x TMs_121 (1.03, 0.38, and 0.25% on average of interaction SS in the 1-, 2-, and 12-yr analyses).
From the interaction of the genotypic (respectively environment) covariate with the residual environmental (respectively genotypic) variation, it appears from Tables 2 and 3, that earliness of flowering (GDDs_f x env), water balance (WATf x var), and mean temperature in the second part of the cycle (TM121_e x var) were the most explicative of the GE interaction for early hybrids in the trial network of AGPM.
The most explicative cross-product was GDDs_f x WATf (Table 5), thus confirming a major contribution of flowering earliness and water supply to the interaction effect.