A web-based expert system for diagnosis of nutritional deficiency in sugarcane.
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This paper presents a web-based expert system for diagnosis of plant nutrient disorders in sugarcane. This system aims to provide a guide to identification of essential and functional plant nutrient disorders in sugarcane to avoid deficiency and to solve nutritional problems arising from the development of this culture. It is directed toward the sugarcane farmer, research scientist, extension specialist, student, and consultant. The first version of system was developed using the virtual diagnosis framework developed by Embrapa and CENA/USP. The adopted development methodology and the current status of the system for diagnosis of nutritional deficiency in sugarcane are discussed in this paper. The experience acquired in the development of this expert system and applications are also presented.
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Sistema especialista para internet, Deficiência nutricional em cana-de-açúcar, Inteligência artificial, Inferência dedutiva, Sugarcane, Expert systems, Artificial intelligence, Saccharum