WATFWashington Assistive Technology Foundation (Seattle)
WATFWater Availability Task Force (Colorado)
WATFWeb Application Testing Framework
WATFWell and Truly Freaked (polite form)
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The WATF comprises traffic forecasts for more than 110 countries and presents detailed metrics which include total passengers (broken down into international and domestic traffic), total air cargo, and total aircraft movements up to 2040.
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 [2]) 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.