Remaining phosphorus estimated by pedotransfer function

Revista Brasileira de Ciência do Solo

Joice Cagliari²  Maurício Roberto Veronez¹  Marcelo Eduardo Alves¹ 

[1] ,Universidade de Caxias do Sul Centro de Ciências Exatas e Tecnologia Caxias do Sul RS

关键词: Artificial neural networks;    Modeling;    Multiple regression analysis;    regressão linear múltipla;    modelagem;    redes neurais artificiais;   

DOI  :  10.1590/S0100-06832011000100019

来源: SciELO

【 摘 要 】

Although the determination of remaining phosphorus (Prem) is simple, accurate values could also be estimated with a pedotransfer function (PTF) aiming at the additional use of soil analysis data and/or Prem replacement by an even simpler determination. The purpose of this paper was to develop a pedotransfer function to estimate Prem values of soils of the State of São Paulo based on properties with easier or routine laboratory determination. A pedotransfer function was developed by artificial neural networks (ANN) from a database of Prem values, pH values measured in 1 mol L-1 NaF solution (pH NaF) and soil chemical and physical properties of samples collected during soil classification activities carried out in the State of São Paulo by the Agronomic Institute of Campinas (IAC). Furthermore, a pedotransfer function was developed by regressing Prem values against the same predictor variables of the ANN-based PTF. Results showed that Prem values can be calculated more accurately with the ANN-based pedotransfer function with the input variables pH NaF values along with the sum of exchangeable bases (SB) and the exchangeable aluminum (Al3+) soil content. In addition, the accuracy of the Prem estimates by ANN-based PTF were more sensitive to increases in the experimental database size. Although the database used in this study was not comprehensive enough for the establishment of a definitive pedotrasnfer function for Prem estimation, results indicated the inclusion of Prem and pH NaF measurements among the soil testing evaluations as promising ind order to provide a greater database for the development of an ANN-based pedotransfer function for accurate Prem estimates from pH NaF, SB, and Al3+ values.

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