Uma plataforma para detecção de molhamento foliar utilizando processamento de imagens

Abstract

Plant disease management practices such as the forecast of infection risk by plant pathogenic organisms may help farmers and crop advisers to use pesticides in a rational manner. Many studies havebeen carried out involving plant disease forecast information based on meteorological variables. Leafwetness duration is a meteorological variable that plays an important role in disease forecast, especially those caused by fungi. This work proposes a system capable of detecting leaf wetness duration andquantify the presence of water leaf surface by capturing and processing digital images. In addition, the system also have sensors measuring temperature, relative humidity and rain. Dew point temperature isderived from temperature and relative humidity. The system is based on a network of wireless sensors.Indoor and field tests performed during the work showed that it is possible to use image processing to detect leaf wetness duration, but it is necessary to develop more complex algorithms to make thistechnology reliable to the point of becoming a product.