Autor(es):
Fernandes, Mariele Monique Honorato [UNESP] ; Coelho, Anderson Prates [UNESP] ; Silva, Matheus Flavio da [UNESP] ; Bertonha, Rafael Scabello [UNESP] ; de Queiroz, Renata Fernandes [UNESP] ; Furlani, Carlos Eduardo Angeli [UNESP] ; Fernandes, Carolina [UNESP]
Data: 2020
Identificador Persistente: http://hdl.handle.net/11449/201518
Origem: Oasisbr
Assunto(s): Linear models; Models accuracy; Nonlinear models; Soil moisture; Linear models; Linear models; Models accuracy; Models accuracy; Nonlinear models; Nonlinear models; Soil moisture; Soil moisture
Descrição
Made available in DSpace on 2020-12-12T02:34:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-06-01
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
One of the most used evaluations to monitor soil compaction is based on soil penetration resistance (SPR). However, since SPR is influenced by soil moisture, this evaluation performed in the field may often lead to incorrect interpretations. This study aimed to evaluate the accuracy of models in the estimation of soil penetration resistance with standardized moisture (SPRlab) based on soil penetration resistance measured in the field (SPRfield) and on soil moisture (U) and indicate the best soil layer and best model for that. Samplings were carried out in the years 2016 (72 points – 24 in each layer) and 2017 (270 points – 90 in each layer) in three soil layers (0.00–0.10 m, 0.10–0.20 m and 0.20–0.30 m). Samples collected in 2017 were used to calibrate the models and samples collected in 2016 were used to validate them. The models used were obtained by multiple linear and nonlinear regressions and artificial neural networks (ANNs). Models were calibrated with all sampled layers and stratified per layer. In the latter case, the samples were separated into two parts, one with the surface layer (0.00–0.10 m) and another with subsurface layers (0.10–0.20 m and 0.20–0.30 m). SPRlab can be estimated with high accuracy from SPRfield and U measured in the field. We recommend the use of ANN models (MLP or RBF) and soil samples collected from the 0.10–0.30 m layer for the monitoring of soil penetration resistance.
São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences, Via de Acesso Prof. Paulo Donato Castellane s/n, 14884-900 Jaboticabal
São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences, Via de Acesso Prof. Paulo Donato Castellane s/n, 14884-900 Jaboticabal
