input: Write a function to develop a machine learning algorithm in Python that identifies apples from bananas using an SVM classifier with a linear kernel. The function should load pre-defined data, initialize the classifier, fit the data, and then make predictions on new data.
  
  assert identify_fruits(<X>, <y>, <x_test>)==<prediction>
  assert identify_fruits(np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]]), np.array([0, 0, 0, 1, 0, 1]), np.array([[2,2,2], [4,4,4]]))==[0, 1]
output: def identify_fruits(X, y, x_test):
      from sklearn.svm import SVC
      classifier = SVC(kernel='linear')
      classifier.fit(X, y)
      return classifier.predict(x_test).tolist()