Use este identificador para citar ou linkar para este item:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1105884
Título: | Classification of soil respiration in areas of sugarcane renewal using decision tree. |
Autoria: | 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. ![]() ![]() |
Afiliação: | CAMILA VIANA VIEIRA FARHATE, Feagri/Unicamp; ZIGOMAR MENEZES DE SOUZA, Feagri/Unicamp; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA, Feagri/Unicamp; JOÃO LUÍS NUNES CARVALHO, CNPEM; NEWTON LA SCALA JÚNIOR, Unesp; ANA PAULA GUIMARÃES SANTOS, Feagri/Unicamp. |
Ano de publicação: | 2018 |
Referência: | Scientia Agricola, v. 75, n. 3, p. 216-224, May/June 2018. |
Conteúdo: | ABSTRACT: The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soil moisture > potential acidity. |
Thesagro: | Respiração do Solo |
NAL Thesaurus: | Carbon dioxide Soil temperature Soil organic matter |
Palavras-chave: | Mineração de dados Emissão de gás carbônico no solo Seleção de variável Temperatura no solo Matéria orgânica no solo Árvore de decisão Data mining Variable selection Decision tree |
Digital Object Identifier: | http://dx.doi.org/10.1590/1678-992X-2016-0473 |
Tipo do material: | Artigo de periódico |
Acesso: | openAccess |
Aparece nas coleções: | Artigo em periódico indexado (CNPTIA)![]() ![]() |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
---|---|---|---|---|
APClassificationsoilFarhate.pdf | 443.53 kB | Adobe PDF | ![]() Visualizar/Abrir |