The most essential concept in generating food for people, and the backbone of our country, is agriculture. The production of agricultural land decreases year after year as a result of various disease affections. Our daily lives involve the usage of turmeric plant materials for preparing meals, treating illnesses, and other things. A variety of expanding factors affect both the quantity and quality of turmeric output. In addition to field trials, crop simulation models are commonly used as research tools to analyze the effects of various technologies. A viable substitute for artificial intelligence and an additional tool to the widely utilized crop production models are machine learning (ML) techniques. Automatic plant disease diagnosis is aided by machine learning techniques like Random Forest, Bayesian Network, Decision Tree, Support Vector Machine, etc. In this study, we will investigate many machine learning methods to create the turmeric grow and diseases detection.