Development of a methodology for in situ assessment of topsoil dry bulk density

A reliable, speedy and objective technique for in situ assessment of soil compaction in topsoil is needed. Penetrometer measurements to determine soil compaction are affected by several factors namely soil texture, moisture content (MC), organic matter content (OMC) and dry bulk density (BD), whereas core sampling method is laborious and time consuming. The aim of this study is to develop a methodology to predict BD as a function of MC, OMC, soil clay content (CLC) and penetration resistance (PR), aiming at the development of a reliable, cost, and time effective measurement system of field topsoil compaction indicated as BD. Laboratory and field tests were carried out using 570 soil samples collected from 20 fields in Czech Republic, Denmark, the Netherlands, and the UK to establish algorithms to predict BD as a function of PR, MC, OMC and CLC. These algorithms were created by means of multiple linear regression (MLR) and artificial neural network (ANN) methods.The results showed non-linear exponential relationships between PR, and all affecting independent parameters, e.g. BD, MC, OMC and CLC. Due to this non-linear relationship, MLR resulted in low prediction accuracy of BD with a determination coefficient (R2) value between predicted and measured BD of 0.51 and a root mean square error of prediction (RMSEP) of 0.13 Mg m−3. The ANN enabled the prediction of BD with high accuracy with a high R2 value of 0.81 and a low RMSEP of 0.11 Mg m−3. This ANN model can now be used to assess topsoil BD in agricultural fields with similar texture, pedology and geological conditions to those considered in this work, provided that data on PR, MC, OMC and CLC are available. Based on these results, a portable measurement device with multiple sensors is currently under development to enable the measurement of MC, OMC, CLC and PR, and thus derive BD values with the ANN algorithm developed. It is hoped that the proposed methodology will replace existing methods such as the core sampling method and provide a quick and easy solution for in situ assessment of topsoil BD.

► In situ measurement of bulk density in 17 fields across Europe and the UK.
► ANN algorithm developed to predict DB as functions of PR and other soil properties.
► Validation of ANN algorithm provided good correlation with core sampling method.
► The new ANN algorithm can be used to measure BD in fields with the same texture, soil type and origin.