Estimation of soil organic matter, as a function of soil chemical-physical attributes, in tropical sugarcane areas Paulo Alexandre da Silva, Alan Rodrigo Panosso, Maria Elisa Vicentini, Nelson José Peruzzi, Glauco de Souza Rolim

Abstract

 This study aims to quantify soil organic matter in commercial sugarcane fields in Brazil using the multiple linear regression technique with soil attribute variables. The experiment was carried out in a sugarcane field in the municipality of Motuca, Guariba, Pradópolis and Aparecida do Taboado. The technique used was multiple linear regression and the dependent variable was soil organic matter (MOS) and the independent variables were available phosphorus (P), cation exchange capacity (CTC), air temperature (Tair), air temperature. soil (Ts), particle density (Dp) and soil moisture (Us). The multiple linear regression learning technique estimated the MOS as a function of the variables P, CTC, Tair, Ts, Dp and Us, in areas of raw sugarcane, showing the existence of a high relationship between independent and dependent variables. Studies like this one, related to the determination of soil parameters are important for farmers, as the information generated can be used in the management and decision-making of the productive and financial process, being an alternative for the characterization not only of MOS, but also of other soil attributes.