Citrus is an important fruit crops worldwide, and diseases are one of the major constraints affecting their production and quality. An early stage detection and precise classification of citrus diseases are very important for the disease management, effectively. Diseases can affect Leaves, Fruits and stem of citrus plant. Traditional methods for disease detection and classification are time-consuming and expensive. Various techniques are proposed for the classification and detection of citrus crop diseases. Use of Machine Learning algorithms like SVM, ANN, Fuzzy C-Means Classifier, KNN, and CNN classifier are proposed by many researchers worldwide after the investigation and validation of results. This work includes the study of various citrus crop diseases and the review of literature on automatic detection and identification of the diseases using machine learning and Deep learning approaches. It also includes the brief overview of the techniques in order to improve the detection accuracy using Data Augmentation and Transfer Learning. Keywords— Citrus diseases, Deep learnings(DL), Data Augmentation, Machine Learning(ML) , Timely detection, Transfer Learning.