In agriculture science, automated and computerized methods increase the country's growth, economy and productivity as it is highly dependent on the export of fruits and vegetables. Nowadays, it is impossible to check the quality of fruits and vegetables with bare hands as they are exported in a batch. In this world of technology, artificial intelligence plays an essential role by introducing many algorithms to detect diseases that hamper quality. This paper presents a detailed review of which algorithm best detects diseases in fruits and vegetables. The paper also includes details about pre-processing, segmentation, different algorithms for detection, and image enhancement. An analysis of different algorithms proposed by researchers for disease detection within fruits and vegetables was conducted. From contemporary research works, we have come to know that there is not one perfect method for detecting diseases of all fruits and vegetables. By careful analysis, we have recommended which machine learning method might be suitable for specific types of fruits and vegetables.