Cross-validation using linear discriminant analysis

The following code performs 10-fold cross-validation using linear discriminant analysis:

    load fisheriris
    indices = crossvalind('Kfold',species,10);
    cp = classperf(species); % initializes the CP object

    for i = 1:10
        test = (indices == i); train = ~test;
        class = classify(meas(test),meas(train),species(train));
        % updates the CP object with the current classification results
        classperf(cp,class,test)  
    end

    cp.CorrectRate

How can this be modified to use fitcdiscr instead of classify on line 7? When I try, I get an error (Wrong number of arguments). I do not know what arguments are needed or not.