Prediction of tillage implement draught using cone penetrometer data

A novel approach to the prediction of tillage implement draught has previou sly been reported which involves a simple reference tine (standard tine) in relation to which tillage implements are rated in a reference soil in term s of their draught requirements. This prediction methodology makes use of t he standard tine draught measured in situ to predict the draught required b y any indexed tillage implement operating under the same soil condition. Th e standard tine draught in the reference soil is also described as the prod uct of a soil strength factor S and a geometrical factor G(s). Results of a n investigation conducted to assess the usefulness of cone penetrometer dat a 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) soi ls. 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 moist ure content and working depth were defined empirically for clay and sandy s oil categories. Using these equations, the draught of the standard;tine ope rating 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 w orking depth in three soil conditions were predicted using the measured sta ndard 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 improv ed practicality of the in situ data collection and the reduced prediction a ccuracy. Its usefulness, however, should be assessed in the light of the si gnificant difficulties associated with using the current analytical methods for in situ predictions (requiring fundamental soil mechanical characteris tics) and for complex tool shapes. (C) 1999 Silsoe Research Institute.