A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements
Autor(a) principal: | |
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Data de Publicação: | 2001 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/8891 |
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. |
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Repositório Institucional da UNESP |
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A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurementsIntelligent Systemsneural netsSPAD indexThe 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.UNESP, Univ São Paulo, FE, Dept Elect Engn, Bauru, BrazilUNESP, Univ São Paulo, FE, Dept Elect Engn, Bauru, BrazilAmer Soc Agr EngineersUniversidade Estadual Paulista (Unesp)Ulson, Jose Alfredo Covolan [UNESP]Boas, RLVGodoy, LJGde Souza, A. N.2014-05-20T13:27:12Z2014-05-20T13:27:12Z2001-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject29-35Proceedings 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/11449/8891WOS:00018535740000545170571214622588212775960494686Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the World Congress of Computers In Agriculture and Natural Resourcesinfo:eu-repo/semantics/openAccess2024-06-28T13:34:35Zoai:repositorio.unesp.br:11449/8891Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:00:10.707887Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
title |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
spellingShingle |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements Ulson, Jose Alfredo Covolan [UNESP] Intelligent Systems neural nets SPAD index |
title_short |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
title_full |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
title_fullStr |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
title_full_unstemmed |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
title_sort |
A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements |
author |
Ulson, Jose Alfredo Covolan [UNESP] |
author_facet |
Ulson, Jose Alfredo Covolan [UNESP] Boas, RLV Godoy, LJG de Souza, A. N. |
author_role |
author |
author2 |
Boas, RLV Godoy, LJG de Souza, A. N. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Ulson, Jose Alfredo Covolan [UNESP] Boas, RLV Godoy, LJG de Souza, A. N. |
dc.subject.por.fl_str_mv |
Intelligent Systems neural nets SPAD index |
topic |
Intelligent Systems neural nets SPAD index |
description |
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. |
publishDate |
2001 |
dc.date.none.fl_str_mv |
2001-01-01 2014-05-20T13:27:12Z 2014-05-20T13:27:12Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
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 4517057121462258 8212775960494686 |
identifier_str_mv |
Proceedings of the World Congress of Computers In Agriculture and Natural Resources. St Joseph: Amer Soc Agr Engineers, p. 29-35, 2001. WOS:000185357400005 4517057121462258 8212775960494686 |
url |
http://hdl.handle.net/11449/8891 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the World Congress of Computers In Agriculture and Natural Resources |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
29-35 |
dc.publisher.none.fl_str_mv |
Amer Soc Agr Engineers |
publisher.none.fl_str_mv |
Amer Soc Agr Engineers |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128735622201344 |