Use of Technologies of Image Recognition in Agriculture: Systematic Review of Literature

In the last decades, the mechanization of productive processes has focused on replacing the tasks performed by people with machines. However nowadays, the integration of software, robots and artificial intelligence point to the automation in agriculture. This is of great importance for the increase of productivity and the economic growth of the country solving in this way the lack of workforce and its associated high costs, offering great benefits to population. Currently, researchers are developing numerous fruit and vegetable classification algorithms, of which essential parameter is color; that allows the detection of nutrient deficiencies, diagnosis of diseases and fruit quality; the same ones that have proven to be accurate and require less time compared to traditional methods. The aim of this article is to provide a systematic review of classifying techniques through machine learning, its components and the utility for the agronomist.