| |
|
|
| Registros recuperados : 37 | |
| 21. |  | FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; CARVALHO, J. L. N.; LA SCALA JÚNIOR, N.; SANTOS, A. P. G. Classification of soil respiration in areas of sugarcane renewal using decision tree. Scientia Agricola, v. 75, n. 3, p. 216-224, May/June 2018.| Biblioteca(s): Embrapa Agricultura Digital. |
|    |
| 22. | | ARAÚJO, F. S.; BARROSO, J. R.; FREITAS, L. de O.; TEODORO, M. S.; SOUZA, Z. M. de; TORRES, J. L. R. Chemical attributes and microbial activity of soil cultivated with cassava under different cover crops. Revista Brasileira de Engenharia Agrícola e Ambiental, v. 23, n. 8, p. 614-619, 2019.| Biblioteca(s): Embrapa Meio-Norte. |
| |
| 23. | | LÓPEZ-NORONHA, R.; SOUZA, Z. M. de; SOARES, M. D. R.; CAMPOS, M. C. C.; FARHATE, C. V. V.; OLIVEIRA, S. R. de M. Soil carbon stock in archaeological black earth under different land use systems in the Brazilian Amazon. Agronomy Journal, v. 112, n. 5, p. 4437-4450, Sept./Oct. 2020.| Biblioteca(s): Embrapa Agricultura Digital. |
|  |
| 24. | | NORONHA, R. L.; SOARES, M. D. R.; OLIVEIRA, I. N. de; FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M. Soil carbon stock predictive models on archaeological black lands - natural and transformed. In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. Não paginado. WCSS 2018.| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 25. | | OLIVEIRA, E. de; SILVA, F. M. da; SALVADOR, N.; SOUZA, Z. M. de; CHALFOUN, S. M.; FIGUEIREDO, C. A. P. de. Custos operacionais da colheita mecanizada do cafeeiro Pesquisa Agropecuária Brasileira, Brasília, DF, v. 42, n. 6, p. 827-831, jun. 2007 Título em inglês: Operational costs of mechanized harvest of coffee.| Biblioteca(s): Embrapa Unidades Centrais. |
| |
| 26. | | FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; LOVERA, L. H.; OLIVEIRA, I. N. de; GUIMARÃES, E. M. Data mining techniques for classification of soil CO2 emission. In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. Não paginado. WCSS 2018.| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 27. | | ARAÚJO, F. S.; LEITE, L. F. C.; SOUZA, Z. M. de; TORRES, J. L. R.; COSTA, A. S. H. B.; FERREIRA, A. H. C. Fertility and total organic carbon in oxisol under different management systems in Savannah of Piauí, Brazil. Tropical and Subtropical Agroecosystems, México, v. 20, p. 165-172, 2017. Título em espanhol: Fertilidad y el carbono orgánico total en oxisol bajo diferentes manejos en el Cerrado Piauiense, Brasil.| Biblioteca(s): Embrapa Meio-Norte. |
| |
| 29. | | TAVARES, R. L. M.; OLIVEIRA, S. R. de M.; BARROS, F. M. M. de; FARHATE, C. V. V.; SOUZA, Z. M. de; LA SCALA JUNIOR, N. Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach. Scientia Agricola, Piracicaba, v. 74, n. 4, p. 281-287, July/Aug. 2018.| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 30. | | SILVA, R. B. da; DIAS JUNIOR, M. de S.; IORI, P.; SILVA, F. A. de M.; FOLLE, S. M.; FRANZ, C. A. B.; SOUZA, Z. M. de. Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado. Pesquisa Agropecuária Brasileira, Brasília, v. 50, n. 1, p. 82-9, Janeiro 2015.| Biblioteca(s): Embrapa Cerrados. |
| |
| 31. | | MARÇAL, M. F. M.; SOUZA, Z. M. de; TAVARES, R. L. M.; FARHATE, C. V. V.; OLIVEIRA, S. R. de M.; GALINDO, F. S. Predictive models to estimate carbon stocks in agroforestry systems. Forests, v. 12, n. 9, p. 1-15, Sept. 2021. Article 1240. Na publicação: Stanley Robson Medeiros Oliveira.| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| 32. | | SILVA, R. B. da; DIAS JUNIOR, M. de S.; SILVA, F. A. de M.; FOLLE, S. M.; FRANZ, C. A. B.; SOUZA, Z. M. de. Predition of soil shear strength in agricultural and natural environments of the Brazilian Cerrado. PESQUISA AGROPECUÁRIA BRASILEIRA, Brasília, DF, v. 50, n. 1, p. 82-91, jan., 2015. Título em português: Predição da tensão de cisalhamento do solo em ambientes agrícola e natural do Cerrado brasileiro.| Biblioteca(s): Embrapa Unidades Centrais. |
| |
| 33. | | CARVALHO, T. M. R. de; MOURA, D. J. de; SOUZA, Z. M. de; SOUZA, G. S. de; BUENO, L. G. de F. Qualidade da cama e do ar em diferentes condições de alojamento de frangos de corte. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 46, n. 4, p. 351-361, abril 2011 Título em inglês: Litter and air quality in different broiler housing conditions.| Biblioteca(s): Embrapa Unidades Centrais. |
| |
| 34. | | LEMOS, J. M.; TRENTIN, G.; PEREZ, N. B.; VOLK, L. B. da S.; AMARAL, G. A. do; SOUZA, Z. M. de. Radiação fotossintética ativa disponível para a pastagem em sistema silvipastoril. In: JORNADA DE PÓS-GRADUAÇÃO E PESQUISA, 11.; MOSTRA DE INICIAÇÃO CIENTÍFICA, 11.; MOSTRA DE INICIAÇÃO CIENTÍFICA JÚNIOR, 9., 2013, Sant'Ana do Livramento. Anais... Bagé: Ediurcamp, 2013. 1 pen drive. CONGREGA 2013.| Biblioteca(s): Embrapa Pecuária Sul. |
| |
| 36. | | VISCHI FILHO, O. J.; SOUZA, Z. M. de; SILVA, R. B. da; LIMA, C. C. de; PEREIRA, D. de M. G.; LIMA, M. E. de; SOUSA, A. C. M. de; SOUZA, G. S. de. Capacidade de suporte de carga de Latossolo Vermelho cultivado com cana-de-açúcar e efeitos da mecanização no solo. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 50, n. 4, p. 322-332, abr. 2015. Título em ingles: Load support capacity of an Oxisol cultivated with sugarcane and mechanization effects on the soil.| Biblioteca(s): Embrapa Solos / UEP-Recife; Embrapa Unidades Centrais. |
| |
| 37. | | ROSSI NETO, J.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M.; KÖLLN, O. T.; FERREIRA, D. A.; CARVALHO, J. L. N.; BRAUNBECK, O. A.; FRANCO, H. C. J. Use of the decision tree technique to estimate sugarcane productivity under edaphoclimatic conditions. Sugar Tech, v. 19, n. 6, p. 662-668, Nov./Dec. 2017.| Biblioteca(s): Embrapa Agricultura Digital. |
| |
| Registros recuperados : 37 | |
|
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
07/12/2018 |
|
Data da última atualização: |
07/01/2020 |
|
Tipo da produção científica: |
Resumo em Anais de Congresso |
|
Autoria: |
NORONHA, R. L.; SOARES, M. D. R.; OLIVEIRA, I. N. de; FARHATE, C. V. V.; SOUZA, Z. M. de; OLIVEIRA, S. R. de M. |
|
Afiliação: |
RENATO LÓPEZ NORONHA, Unicamp; MARCELO DAYRON RODRIGUES SOARES, Unicamp; INGRID NEHMI DE OLIVEIRA, Unicamp; CAMILA VIANA VIEIRA FARHATE, Unicamp; ZIGOMAR MENEZES DE SOUZA, Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA. |
|
Título: |
Soil carbon stock predictive models on archaeological black lands - natural and transformed. |
|
Ano de publicação: |
2018 |
|
Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS, 2018. |
|
Páginas: |
Não paginado. |
|
Idioma: |
Inglês |
|
Notas: |
WCSS 2018. |
|
Conteúdo: |
In the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was determined using the Wrapper method for attribute selection. In the depth of 0.00-0.05 m, we generated a model of 79% accuracy containing only six rules, including, as the most important classification attribute was soil use. For the depth of 0.05-0.10 m, we generated an eight-rule decision tree of 74% accuracy including sand as the most important attribute. In this context, we highlight the Wrapper method efficiency to select subsets of predictive attributes, capable to generate more understandable decision trees, using a smaller number of attributes in the classification process, making it faster and with a lower computational cost. In addition, data mining techniques were efficient at providing predictive models capable to assist the decision-making process on possible management practices with the potential to conserve or increase soil carbon stock in archeological black lands. MenosIn the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was d... Mostrar Tudo |
|
Palavras-Chave: |
Anthropic soils; Árvore de decisão; Data mining techniques; Decision tree; Mineração de dados; Soil management system. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 03289nam a2200265 a 4500
001 2100986
005 2020-01-07
008 2018 bl uuuu u00u1 u #d
100 1 $aNORONHA, R. L.
245 $aSoil carbon stock predictive models on archaeological black lands - natural and transformed.$h[electronic resource]
260 $aIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: abstracts. Viçosa, MG: SBCS$c2018
300 $aNão paginado.
500 $aWCSS 2018.
520 $aIn the Amazon region, types of soil known as Archaeological Black Lands (ABL) present anthropic horizon A and are associated with prolonged human occupation by indigenous societies from the pre-Columbian period, where chemical and physical attributes have better quality than other types of soil in the Amazon, setting a large organic carbon reservoir. However, the conversion of these natural ecosystems into cultivated environments make emerge changes in soil carbon dynamics, often leading to a decline in soil organic carbon content. Therefore, our aim was to use data mining techniques to generate predictive models for the effect of soil use on carbon stock in natural and transformed areas of Archaeological Black Lands. We carried out our experiment in Manicoré and Apuí, Amazonas State, Brazil. After field data collection and laboratory analysis, we obtained a set of data consisting of 21 attributes, 20 predictive attributes consisting of 13 soil physical attributes, 6 soil chemical attributes, 1 soil use related attribute, and 1 response variable, referring to soil carbon stock (SCS), which is the classification target. Due to the large number of attributes, we performed a selection procedure to eliminate attributes of low correlation to the response variable. For data classification, we used the binary induction technique of the decision tree through software Weka 3.8. The results obtained showed that for the depth of 0.00-0.05 and 0.05-0.10 m, the best selected subset was determined using the Wrapper method for attribute selection. In the depth of 0.00-0.05 m, we generated a model of 79% accuracy containing only six rules, including, as the most important classification attribute was soil use. For the depth of 0.05-0.10 m, we generated an eight-rule decision tree of 74% accuracy including sand as the most important attribute. In this context, we highlight the Wrapper method efficiency to select subsets of predictive attributes, capable to generate more understandable decision trees, using a smaller number of attributes in the classification process, making it faster and with a lower computational cost. In addition, data mining techniques were efficient at providing predictive models capable to assist the decision-making process on possible management practices with the potential to conserve or increase soil carbon stock in archeological black lands.
653 $aAnthropic soils
653 $aÁrvore de decisão
653 $aData mining techniques
653 $aDecision tree
653 $aMineração de dados
653 $aSoil management system
700 1 $aSOARES, M. D. R.
700 1 $aOLIVEIRA, I. N. de
700 1 $aFARHATE, C. V. V.
700 1 $aSOUZA, Z. M. de
700 1 $aOLIVEIRA, S. R. de M.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
