Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks
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/11449/224199 |
Resumo: | The accurate identification of the nitrogen content in crop 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 involves a lot of nonlinear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator. |
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Repositório Institucional da UNESP |
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spelling |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networksThe accurate identification of the nitrogen content in crop 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 involves a lot of nonlinear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator.University of São Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-SPUniversity of São Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-SPUniversidade Estadual Paulista (UNESP)Covolan Ulson, J. A. [UNESP]Benez, S. H. [UNESP]Nunes Da Silva, I. [UNESP]Nunes De Souza, A. [UNESP]2022-04-28T19:55:06Z2022-04-28T19:55:06Z2001-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2088-2092Proceedings of the International Joint Conference on Neural Networks, v. 3, p. 2088-2092.http://hdl.handle.net/11449/2241992-s2.0-0034868966Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the International Joint Conference on Neural Networksinfo:eu-repo/semantics/openAccess2024-06-28T13:34:35Zoai:repositorio.unesp.br:11449/224199Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:05:55.599466Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
title |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
spellingShingle |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks Covolan Ulson, J. A. [UNESP] |
title_short |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
title_full |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
title_fullStr |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
title_full_unstemmed |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
title_sort |
Nitrogen content identification in crop plants using spectral reflectance and artificial neural networks |
author |
Covolan Ulson, J. A. [UNESP] |
author_facet |
Covolan Ulson, J. A. [UNESP] Benez, S. H. [UNESP] Nunes Da Silva, I. [UNESP] Nunes De Souza, A. [UNESP] |
author_role |
author |
author2 |
Benez, S. H. [UNESP] Nunes Da Silva, I. [UNESP] Nunes De Souza, A. [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Covolan Ulson, J. A. [UNESP] Benez, S. H. [UNESP] Nunes Da Silva, I. [UNESP] Nunes De Souza, A. [UNESP] |
description |
The accurate identification of the nitrogen content in crop 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 involves a lot of nonlinear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought spectral reflectance of plant leaves using artificial neural networks. The network acts as identifier of relationships among pH of soil, fertilizer treatment, spectral reflectance and nitrogen content in the plants. So, nitrogen content can be estimated and generalized from an input parameter set. This approach can be form the basis for development of an accurate real time nitrogen applicator. |
publishDate |
2001 |
dc.date.none.fl_str_mv |
2001-01-01 2022-04-28T19:55:06Z 2022-04-28T19:55:06Z |
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 International Joint Conference on Neural Networks, v. 3, p. 2088-2092. http://hdl.handle.net/11449/224199 2-s2.0-0034868966 |
identifier_str_mv |
Proceedings of the International Joint Conference on Neural Networks, v. 3, p. 2088-2092. 2-s2.0-0034868966 |
url |
http://hdl.handle.net/11449/224199 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the International Joint Conference on Neural Networks |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
2088-2092 |
dc.source.none.fl_str_mv |
Scopus 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_ |
1808128460395118592 |