A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements


Autoria(s): Ulson, Jose Alfredo Covolan; Boas, RLV; Godoy, LJG; de Souza, A. N.; Zazueta, F.; Xin, J.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/01/2001

Resumo

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Formato

29-35

Identificador

Proceedings of the World Congress of Computers In Agriculture and Natural Resources. St Joseph: Amer Soc Agr Engineers, p. 29-35, 2001.

http://hdl.handle.net/11449/8891

WOS:000185357400005

Idioma(s)

eng

Publicador

Amer Soc Agr Engineers

Relação

Proceedings of the World Congress of Computers In Agriculture and Natural Resources

Direitos

closedAccess

Palavras-Chave #Intelligent Systems #neural nets #SPAD index
Tipo

info:eu-repo/semantics/conferencePaper