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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/07/2017 |
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Data da última atualização: |
28/02/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LIMA, E. de S.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; LOVERA, L. H.; FARHATE, C. V. V. |
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Afiliação: |
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. |
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Título: |
Classification of the initial development of eucaliptus using data mining techniques. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Cerne, v. 23, n. 2, p. 201-208, 2017. |
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DOI: |
10.1590/01047760201723022296 |
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Idioma: |
Inglês |
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Conteúdo: |
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. MenosAbstract - 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... Mostrar Tudo |
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Palavras-Chave: |
Mineração de dados. |
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Thesagro: |
Eucalipto. |
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Thesaurus Nal: |
Eucalyptus; Technology. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161528/1/classificacao-desenv.pdf
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Marc: |
LEADER 02313naa a2200229 a 4500
001 2072262
005 2018-02-28
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1590/01047760201723022296$2DOI
100 1 $aLIMA, E. de S.
245 $aClassification of the initial development of eucaliptus using data mining techniques.$h[electronic resource]
260 $c2017
520 $aAbstract - 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.
650 $aEucalyptus
650 $aTechnology
650 $aEucalipto
653 $aMineração de dados
700 1 $aSOUZA, Z. M. de
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aLOVERA, L. H.
700 1 $aFARHATE, C. V. V.
773 $tCerne$gv. 23, n. 2, p. 201-208, 2017.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
08/03/2010 |
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Data da última atualização: |
16/11/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 3 |
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Autoria: |
POTTER, C.; KLOOSTER, S.; HUETE, A.; GENOVESE, V.; BUSTAMANTE, M.; FERREIRA, L. G.; OLIVEIRA JUNIOR, R. C. de; ZEPP, R. |
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Afiliação: |
NASA; CALIFORNIA STATE UNIVERSITY MONTEREY BAY; UNIVERSITY OF ARIZONA; CALIFORNIA STATE UNIVERSITY MONTEREY BAY; UNB; UNIVERSIDADE FEDERAL DE GOIAS; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; US ENVIRONMENTAL PROTECTION AGENCY. |
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Título: |
Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
Biogeosciences discussions, v. 6, n. 1, p. 947-969, Jan./Feb. 2009. |
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Idioma: |
Inglês |
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Conteúdo: |
A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000?2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002?2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong. |
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Thesagro: |
Carbono; Ecossistema. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/43169/1/bgd-6-947-2009-print.pdf
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Marc: |
LEADER 02014naa a2200229 a 4500
001 1660205
005 2022-11-16
008 2009 bl uuuu u00u1 u #d
100 1 $aPOTTER, C.
245 $aTerrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling.$h[electronic resource]
260 $c2009
520 $aA simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000?2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002?2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.
650 $aCarbono
650 $aEcossistema
700 1 $aKLOOSTER, S.
700 1 $aHUETE, A.
700 1 $aGENOVESE, V.
700 1 $aBUSTAMANTE, M.
700 1 $aFERREIRA, L. G.
700 1 $aOLIVEIRA JUNIOR, R. C. de
700 1 $aZEPP, R.
773 $tBiogeosciences discussions$gv. 6, n. 1, p. 947-969, Jan./Feb. 2009.
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Embrapa Amazônia Oriental (CPATU) |
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