Data/hora: 21/05/2024 08:17:24

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	13/02/2019	
Data da última atualização: 	13/02/2019	
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.	
Título: 	Classification of soil respiration in areas of sugarcane renewal using decision tree.	
Ano de publicação: 	2018	
Fonte/Imprenta: 	Scientia Agricola, v. 75, n. 3, p. 216-224, May/June 2018.	
DOI: 	http://dx.doi.org/10.1590/1678-992X-2016-0473	
Idioma: 	Inglês	
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 (&#967;2) 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.	
Palavras-Chave: 	Árvore de decisão; Data mining; Decision tree; Emissão de gás carbônico no solo; Matéria orgânica no solo; Mineração de dados; Seleção de variável; Temperatura no solo; Variable selection.	
Thesagro: 	Respiração do Solo.	
Thesaurus Nal: 	Carbon dioxide; Soil organic matter; Soil temperature.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/192660/1/AP-Classification-soil-Farhate.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (20031-1) - UPC - AP - DD -  -  -  - DIS