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Provedor de dados:  REA
País:  Brazil
Título:  PEDOFUNCTIONS APPLIED TO THE LEAST LIMITING WATER RANGE TO ESTIMATE SOIL WATER CONTENT AT SPECIFIC POTENTIALS
Autores:  Tavanti,Renan F. R.
Freddi,Onã da S.
Tavanti,Tauan R.
Rigotti,Adriel
Magalhães,Wellington de A.
Data:  2019-08-01
Ano:  2019
Palavras-chave:  Soil physics
Soil physical quality indicator
Available water
Pedotransfer functions
Artificial neural networks
Resumo:  ABSTRACT The least limiting water range (LLWR) is a soil physical quality indicator that receives much attention. It has been criticized and put to the test regarding mathematical models that compose it since they describe the behavior of soil physical attributes in a simplified way. This study aimed to assess the efficiency of some pedofunctions proposed in the literature and artificial neural networks on the accuracy in predicting soil water retention at potentials equivalent to field capacity (θFC) and permanent wilting point (θPWP). In other words, to apply the best models to LLWR of two soil types (Oxisol and Ultisol) and verify changes in their structure. The results indicated that pedofunctions using sand, silt, clay, bulk density, and soil organic matter contents are more efficient in estimating θFC and θPWP. However, the use of multiple linear regression models to predict θFC values below 0.20 m3 m−3 may present a slight tendency to overestimate it, which is not observed in the neural networks. As in R2, equations from neural networks were more efficient in estimating θFC and θPWP. Pedofunctions used to calculate LLWR differ in the establishment of the critical soil bulk density, exposing the limitations of the model.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000400444
Editor:  Associação Brasileira de Engenharia Agrícola
Relação:  10.1590/1809-4430-eng.agric.v39n4p444-456/2019
Formato:  text/html
Fonte:  Engenharia Agrícola v.39 n.4 2019
Direitos:  info:eu-repo/semantics/openAccess
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