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Information Management, Provenance, Precision Agriculture, Mobile Devices, Wireless, Late Blight


Small farmers realize that the adoption of information systems and wireless communications in the field is more than a trend it becomes a necessity. Despite having access to mobile telephony, they do not usually use mobile applications to improve their operations. This work presents a novel computational approach focused on improving the quality of Brazilian tomato crops. We present a low cost and ubiquitous computing environment based on precision agriculture principles to support small farmers to inspect tomato crops and to help them to early detect late blight, one of major disease affecting tomato plants in Brazil. Our initial results have shown that the approach is capable of handling field observations, retrospective provenance descriptiors and process images with neural networks to assit small farmers in automated detection of the foliage disease.


This paper is in Portuguese (Manejo Tecnológico de Lavouras Através de Dispositivos Móveis e Agricultura de Precisão)