Classification of the initial development of eucaliptus using data mining techniques.

Detalhes bibliográficos
Autor(a) principal: LIMA, E. de S.
Data de Publicação: 2017
Outros Autores: SOUZA, Z. M. de, OLIVEIRA, S. R. de M., LOVERA, L. H., FARHATE, C. V. V.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262
Resumo: Abstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature.
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spelling Classification of the initial development of eucaliptus using data mining techniques.Mineração de dadosEucaliptoEucalyptusTechnologyAbstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature.ELIZEU DE SOUZA LIMA, Unicamp; ZIGOMAR MENEZES DE SOUZA, USP, Jaboticabal; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LENON HENRIQUE LOVERA, Unicamp; CAMILA VIANA VIEIRA FARHATE, Unicamp.LIMA, E. de S.SOUZA, Z. M. deOLIVEIRA, S. R. de M.LOVERA, L. H.FARHATE, C. V. V.2017-07-07T11:11:11Z2017-07-07T11:11:11Z2017-07-0720172018-02-28T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCerne, v. 23, n. 2, p. 201-208, 2017.http://www.alice.cnptia.embrapa.br/alice/handle/doc/107226210.1590/01047760201723022296enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T04:35:11Zoai:www.alice.cnptia.embrapa.br:doc/1072262Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T04:35:11falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T04:35:11Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Classification of the initial development of eucaliptus using data mining techniques.
title Classification of the initial development of eucaliptus using data mining techniques.
spellingShingle Classification of the initial development of eucaliptus using data mining techniques.
LIMA, E. de S.
Mineração de dados
Eucalipto
Eucalyptus
Technology
title_short Classification of the initial development of eucaliptus using data mining techniques.
title_full Classification of the initial development of eucaliptus using data mining techniques.
title_fullStr Classification of the initial development of eucaliptus using data mining techniques.
title_full_unstemmed Classification of the initial development of eucaliptus using data mining techniques.
title_sort Classification of the initial development of eucaliptus using data mining techniques.
author LIMA, E. de S.
author_facet LIMA, E. de S.
SOUZA, Z. M. de
OLIVEIRA, S. R. de M.
LOVERA, L. H.
FARHATE, C. V. V.
author_role author
author2 SOUZA, Z. M. de
OLIVEIRA, S. R. de M.
LOVERA, L. H.
FARHATE, C. V. V.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv ELIZEU DE SOUZA LIMA, Unicamp; ZIGOMAR MENEZES DE SOUZA, USP, Jaboticabal; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; LENON HENRIQUE LOVERA, Unicamp; CAMILA VIANA VIEIRA FARHATE, Unicamp.
dc.contributor.author.fl_str_mv LIMA, E. de S.
SOUZA, Z. M. de
OLIVEIRA, S. R. de M.
LOVERA, L. H.
FARHATE, C. V. V.
dc.subject.por.fl_str_mv Mineração de dados
Eucalipto
Eucalyptus
Technology
topic Mineração de dados
Eucalipto
Eucalyptus
Technology
description Abstract - Eucalyptus plantation has expanded considerably in Brazil, especially in regions where soils have low fertility, such as in Brazilian Cerrados. To achieve greater productivity, it is essential to know the needs of the soil and the right moment to correct it. Mathematical and computational models have been used as a promising alternative to help in this decisionmaking process. The aim of this study was to model the influence of climate and physicochemical attributes in the development of Eucalyptus urograndis in Entisol quartzipsamment soil using the decision tree induction technique. To do so, we used 30 attributes, 29 of them are predictive and one is the target-attribute or response variable regarding the height of the eucalyptus. We defined four approaches to select these features: no selection, Correlationbased Feature Selection (CFS), Chi-square test (?2) and Wrapper. To classify the data, we used the decision tree induction technique available in the Weka software 3.6. This data mining technique allowed us to create a classification model for the initial development of eucalyptus. From this model, one can predict new cases in different production classes, in which the individual wood volume (IWV) and the diameter at breast height (DBH) are crucial features to predict the growth of Eucalyptus urograndis, in addition to the presence of chemical soil components such as: magnesium (Mg+2), phosphorus (P), aluminum (Al+3), potassium (K+), potential acidity (H + Al), hydrogen potential (pH), and physical attributes such as soil resistance to penetration and related to climate, such as minimum temperature.
publishDate 2017
dc.date.none.fl_str_mv 2017-07-07T11:11:11Z
2017-07-07T11:11:11Z
2017-07-07
2017
2018-02-28T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Cerne, v. 23, n. 2, p. 201-208, 2017.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262
10.1590/01047760201723022296
identifier_str_mv Cerne, v. 23, n. 2, p. 201-208, 2017.
10.1590/01047760201723022296
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072262
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
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institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
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