Returning Cutoff Distance Using Cluster Function Given nClusters

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Hello all,
If you have used agglomerative clustering in MATLAB, you know there are two options for stopping the clustering.
The first option is to specify a "cutoff distance" (commonly 'epsilon' in literature). In this case, the clustering will stop once clusters are far enough apart, and return a vector of cluster labels for each point (e.g. [1 2 1 1 ...]).
The second option is to specify "maximum clusters" (commonly 'k' or 'c' in literature). In this case, the clustering will stop once the clusters have merged into a specified number of clusters and return a vector of clusters for each point. For example, if 2 is specified, the algorithm will continue to merge clusters until it hits 2.
My question is: Can I return the 'epsilon' value corresponding to the maximum clusters? For example, if max clusters is two, I want to know what the minimum distance to get to two clusters. This is a simple task, and I've written my own linkage clustering to do it. However, MATLAB's implementation is understandably much faster than what I wrote. Therefore, I'd like to have MATLAB do this for me.
Note: I don't want a dendrogram. I need a numeric value.
This is the code I wrote to call the MATLAB clustering.
function clusters=singleLinkMATLAB(dataset,clusterCutoffType,cutoffParameter,distanceType)
Z=linkage(dataset,'single',distanceType);
if clusterCutoffType==0
clusters=cluster(Z,'cutoff',cutoffParameter,'criterion','distance');
elseif clusterCutoffType==1
clusters=cluster(Z,'maxclusters',cutoffParameter);
end
end

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