Estimating the Particle Density of Clayrich Soils with Diverse Mineralogy.

This study examined the utility of nonlinear regression as a means of developing a statistically-based function for the estimation of particle density (Dp) of clay-rich mineral soils where the <0.002 mm fraction was mineralogically diverse. Physical and chemical soil property data (including semi-quantitative clay mineralogy) were analyzed for 54 mineral soil horizons sampled from 18 soil profiles at seven different locations across North America. Plausible estimates of particle density for the mineral component (2.72 Mg m-3), and particularly for the humic component (1.48 Mg m-3), were obtained (r² = 0.856, root mean square error [RMSE] = 0.035 Mg m-3 P < 0.0001) even though the calibration data set had a limited range of soil organic matter content (<23%). Particle density was shown to vary with clay content (P < 0.05), and Dp of different mineral particle-size fractions could also he distinguished statistically. The convenient and traditional assumption of Dp = 2.65 Mg m-3 for silicate-based soils in the absence of Dp measurements is challenged, given the considerable observed variability in Dp with changes in soil organic matter content and texture. [ABSTRACT FROM AUTHOR]