Development of a digital image classification system to support technical assistance for Black Sigatoka detection

Abstract A large percentage of Colombia’s economic activity corresponds to the agricultural sector. In this sector, plantains rank second in production and planted area. However crop is affected by different diseases, among which The Black Sigatoka stands out, caused fungus Mycosphaerella fijiensis. disease highly reduces level although there are prevention measures that allow reducing incidence disease, there’s a lack support for small producers Colombia, who do not have technological tools detection processes. This article outlines development system black sigatoka using digital images. For this, characterization process user carried then, machine learning methodology implemented classify on mobile device. validated through laboratory tests, field tests feedback from user.