Predicting bulk density of Ohio soils from morphology, genetic principles, and laboratory characterization data

A 937-horizon data set composed of site characteristics, morphology, and laboratory characterization data for soils of Ohio was used to develop soil bulk density (D-b) prediction models. We tested the hypothesis that using a combination of continuous variables (laboratory data) and nominal variables (site/state factor and morphological class descriptors) would enable the development of improved Pedo-Transfer Functions (PTFs) for D-b Three primary models were developed. The Lab Model, composed entirely of continuous variables, accounted for 56% of the variability in D-b Using only state factors and morphology as nominal variables, the Field Model explained 69%, A combined Field + Lab Model accounted for 72%, Restricting the data set to samples derived from loess and glacial till generated a Field + Lab Model that explained nearly 80% of the variability in D-b For a subset of 402 horizons.