[R-sig-eco] proportion data with many zeros

[v_coudrain at voila.fr]

Dear all, I am trying to test how the proportion of pollen of different plants found in the brood cells of a wild bee changes over time. I conducted 4 sampling sessions 
(thus time is a factor with 4 levels) and collected several pollen samples for each time point (300 pollen grains counted for each sample). I thought about applying a 
quasi-binomial glm: 

y = cbind(total pollen - pollen of plant X, pollen of plant X)

glm(y~time, family=quasibinomial)

The problem is that I have a lot of zero value, because the pollen of some plants only occurred rarely or very clumped in time. I thought about applying a zero-inflated 
model, but I have never used it and I am not sure if it is suitable for proportion data. Additionally I wondered if I have to consider the fact that I don't have the same 
number of pollen sample for each date, which makes my design unbalanced. 
Thank you in advance for advice. 

Best wishes
Valérie
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