variance structure

Hello,

I'm running a model where the response is normally distributed and has an excess 
of zeros. Because I was familiar with the lmer package I used it to run a GLMM 
on this response, and addressed the problem of the excess of zeros by running 
two models: one with the response as a binary one, using the complete data set, 
and another excluding all the zeros and using the remaining response values in a 
Gaussian model. This seemed to work fine. However, a reviewer suggested using 
the whole data set and a zero-inflated poisson error structure in the MCMCglmm 
package. I don???t know if this is appropriate as my response are rates (grams of 
meat consumed per hr of observation) and not discrete values.