The purpose of this study is to provide an introduction to cloud-based decision support systems for crop management. In recent years, cloud computing, the Internet of Things (IoT), and machine learning have seen significant advancements, which has contributed to the rise in popularity of these kinds of systems. These technologies make it possible for farmers to gather, process, and analyse data in real time, which provides them with invaluable insights about the growth, yield, and overall health of their crops. This, in turn, assists farmers in making decisions that are better informed on the timing of when to sow, irrigate, and fertilise their crops, as well as when to harvest their produce. In this work, we draw on current research conducted in both the academic and industrial spheres to describe the many methods and uses of cloud-based decision support systems for crop management. In conclusion, we will discuss the many advantages and disadvantages of these systems, as well as the possible directions that future study may go.