The detection of crop-rows using algorithms generated in Aerobots has helped the Guatemalan sugar industry to adopt in a faster way the automation of agricultural processes such as mechanical harvesting. Within the adoption of precision agriculture, the generation of crop-rows (from infrared aerial photography, vegetation indices and artificial intelligence) is one of the first steps that must be taken in order to facilitate the operation of machinery such as variable rate fertilizers, herbicide applicators, etc. That is the reason why we have dedicated time to the development of our own algorithms that are based on Machine Learning, Computer Vision, among others.