Estimating Soil Particle Density using Visible Near-infrared Spectroscopy and a Simple, Two-compartment Pedotransfer Function

The average particle density (rho(d)) is a fundamental soil property, used for calculating the total porosity. Traditional rho(d) measurement by pycnometer method is tedious and time-consuming. In this study, visible-near-infrared (vis-NIR) spectroscopy and a simple two-compartment linear and curvilinear pedotransfer function only requiring knowledge of soil organic matter content (OM) were tested and compared as alternative, indirect, rapid, and cost-effective methods. Soil rho(d) was measured by water pycnometer on 179 soils representing a wide range of OM (0.002-0.767 kg kg(-1)), whereas soil spectra were measured on air-dry samples by vis-NIR spectroscopy. The rho(d) models were developed using partial least squares regression with leave-one-out-cross-validation using vis-NIR spectral data, and a simple two-compartment pedotransfer function, rho(d) = A(OM) + B(1 - OM) using the OM content. Predictive abilities of these two methods were tested using three different datasets: (i) minerals soils (OM < 0.1 kg kg(-1)), (ii) organic soils (OM > 0.1 kg kg(-1)), and (iii) all soils. Calibrating the two-compartment pedotransfer function for the entire dataset gave expected values for the individual particle densities of OM (A = 1.244 g cm(-3)) and mineral particles (B = 2.615 g cm(-3)). The vis-NIR spectroscopy model successfully predicted soil p d for the entire dataset (R-2 = 0.87, RMSECV = 0.10 g cm(-3)), with a poorer performance than the two-compartment linear model (R-2 = 0.96, RMSE = 0.06 g cm(-3)). Using only the mineral soils data did not suffice to obtain realistic and accurate vis-NIR spectroscopy (R-2 = 0.62, RMSECV = 0.02 g cm(-3)) or OM based (R-2 = 0.80, RMSE = 0.02 g cm(-3)) models for pd, illustrating the importance of the wide range of OM content considered in the present study.