Support system in the detection of lesions of blackleg of oilseed rape, by means of image processing and artificial neural networks: Empirical case study preventive type for fungal alerts

This paper proposes a framework for detecting lesions of blackleg of oilseed Rape. The idea of the investigation is to develop an algorithm of automatic processing that allows to recognize symptoms of an illness in Rape leaves, so a precise diagnostic can be made and make an early alert of the presence of the illness in Raps cultures, a typical agricultural activity in Araucanía Region. The application of these technique is beneficial for the development of informatic engineering for support of agronomy and agricultures. The study in focused in investigate and experiment the identification of failures in Rape by using digital image processing and artificial neuronal nets technique