COMPARISON OF FUNCTIONS FOR CHARACTERIZING THE DRY AGGREGATE SIZE DISTRIBUTION OF TILLED SOIL

Functions to characterize the dry aggregate size distribution (DASD) a re needed for evaluating tillage implement performance. We compared th e log-normal, fractal and Rosin-Rammler functions as descriptors of th e DASD after tillage. These functions were fitted to data from flat an d rotary sieve analyses. Energy input was kept constant. Comparisons w ere made in terms of physical implications for aggregate fragmentation , goodness of fit and parameter sensitivity to soil properties. All th ree functions resulted in a more accurate description of seed bed cond itions than the use of individual size classes. However, the fractal a nd Rosin-Rammler functions were theoretically superior to the log-norm al function, which was unable to accommodate-scale dependent probabili ties of failure during aggregate fragmentation. In terms of goodness o f fit, the fractal function consistently gave the highest R(2) values (mean > 0.999 across a wide range of DASDs). The fractal parameter, D, showed the greatest sensitivity to inherent soil properties at a site with different soil types and a common cropping history. Clay content was the most important inherent property influencing D; cloddiness (d enoted by decreasing D) increased with increasing clay content. Despit e lower model R(2) values, the Rosin-Rammler parameter, alpha, showed a greater sensitivity to transient soil properties than D at a site wi th similar soil types and different crop rotations. Wet-aggregate stab ility at time of plowing was the most important transient property inf luencing alpha; cloddiness (denoted by increasing alpha) increased wit h decreasing wet-aggregate stability. We suggest the fractal parameter , D, be used for studies comparing seed bed conditions across a range of soils, and the Rosin-Rammler alpha parameter be used for studies co mparing management practices on a single soil.