A multi sensor data fusion approach for creating variable depth tillage zones

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties, and the correct setting of the tillage implement. However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT) has been shown to reduce costs, labour, fuel consumption and energy requirements. To implement VDT it is necessary to determine and map soil physical properties, spatially and with depth through the soil profile. Up until now the measurement of soil compaction for VDT has been soil penetration resistance, expressed as Cone Index (CI). In this research a multi-sensor and data fusion approach was developed that allowed augmenting data collected with an electromagnetic sensor, a standard penetrometer, and conventional methods for the measurement of bulk density (BD) and moisture content (MC). Packing density values were recorded for eight soil layers of 0-5, 5-10, 10-15, 15-20, 20-25, 25-30 30-35 and 35-40 cm. From the results only 62% of the site required the deepest tillage at 38 cm, 16% required tillage at 33 cm and 22% required no tillage at all. The resultant maps of packing density were shown to be a useful tool to guide VDT operations. The results provided in this study indicate that the new multi0sensor and data fusion approach introduced is a useful approach to map layered soil compaction to guide VDT operations. The economic benefit analysis demonstrated fuel savings of 48% by implementing the proposed system. Further work is needed to implement the packing density map for VDT in larger numbers of field in order to generalise the approach.