Confusion about variance components

[BaxW]

Hi,

I'm running BGGE using the maizefiles.RData and copying the code in box 5 of the BGGE paper. The only difference from box 5 is i'm using a GBLUP kernel ie:

library(BGGE)

### Load the maize dataset from supplementary material

load(“maizefiles.Rdata”)

ne <- as.vector(table(pheno_geno$env))

K2 <- getK(Y = pheno_geno, X=geno, kernel = “GB”, bandwidth = 1, model = “MDe”)

fit <- BGGE(y = pheno_geno$GY, K = K2, ne = ne)

fit$yHat[pheno_geno$env == “AN_LN”] #predicted values for environment 2

fit$K$G$varu #main genetic variance

fit$varE #residual variance

fit$K$AN_LN$varu #specific genetic variance

fit$varE #residual variance

plot(fit$yHat, pheno_geno$GY)

What I don't understand is how to reconcile these results with the variance components listed in table 2 of the BGGE paper. The code above gives me values around 1.8 for fit$varE and around 3.3 for fit$K$G$varu, but table 2 seems to suggest there should be more residual variance than variance explained by genetic effects. Is the data used to make table 2 in the BGGE paper the same as maizefiles.Rdata? How can I properly extract the variance components from the fit like was done to produce table 2?

Thanks!