Weka 3.8 - the decision tree J48 seem to have correct tree to predicate data but fail on the testing

Question

The decision tree J48 generated a tree structure as below.

J48 pruned tree

petalwidth <= 0.6: Iris-setosa (50.0)
petalwidth > 0.6
|   petalwidth <= 1.7
|   |   petallength <= 4.9: Iris-versicolor (48.0/1.0)
|   |   petallength > 4.9
|   |   |   petalwidth <= 1.5: Iris-virginica (3.0)
|   |   |   petalwidth > 1.5: Iris-versicolor (3.0/1.0)
|   petalwidth > 1.7: Iris-virginica (46.0/1.0)

But it fails to classify the data below. Do anyone knows what may go wrong?

Plot : weka.classifiers.trees.J48 (iris)
Instance: 98
      sepallength : 5.0
       sepalwidth : 3.5
      petallength : 1.6
       petalwidth : 0.6
prediction margin : -1.0
  predicted class : Iris-versicolor
            class : Iris-setosa

Answer 1

As @fracpete commented, I am using cross-validation. What Weka show in the classifier output is the Classifier model which experiences a full training set, not the predictive model.