Prediction of tillage implement draught using cone penetrometer data

A novel approach to the prediction of tillage implement draught has previously been reported which involves a simple reference tine (standard tine) in relation to which tillage implements are rated in a reference soil in terms of their draught requirements. This prediction methodology makes use of the standard tine draught measured in situ to predict the draught required by any indexed tillage implement operating under the same soil condition. The standard tine draught in the reference soil is also described as the product of a soil strength factor S and a geometrical factor G(s). Results of an investigation conducted to assess the usefulness of cone penetrometer data when included in this prediction methodology are reported in this study. Specific cone penetration energy P-e significantly correlated with the soil strength factor S in two sandy-loam (r = 0.93) and two clay (r = 0.75) soils. Their relationship was quantified in a dimensionless parameter F, ratio of P-e over S, which was found to depend upon working depth, soil type and soil moisture content. Multiple regression equations for F with soil moisture content and working depth were defined empirically for clay and sandy soil categories. Using these equations, the draught of the standard;tine operating in three separate soil conditions was predicted over a working depth range (0.1-0.4 m) within a 15.5% error. The draughts of four multi-tool tillage implements operating at a typical working depth in three soil conditions were predicted using the measured standard tine draught data with a 17% error on an average. Using the standard tine draught values predicted from the cone penetrometer data, the average prediction error increased to 26%. The performance of the prediction models using the cone penetrometer data reflected a compromise between the improved practicality of the in situ data collection and the reduced prediction accuracy. Its usefulness, however, should be assessed in the light of the significant difficulties associated with using the current analytical methods for in situ predictions (requiring fundamental soil mechanical characteristics) and for complex tool shapes. (C) 1999 Silsoe Research Institute.