Precision farming overcomes the paradigm of uniform field treatment by site-specific data acquisition and treatment to cope with within-field variability. Precision farming heavily relies on spatially dense information about soil and crop status. While it is often difficult and expensive to obtain precise soil information by traditional soil sampling and laboratory analysis some geophysical methods offer means to obtain subsidiary data in an efficient way. In particular, geoelectrical soil mapping has become widely accepted in precision farming. At present it is the most successful geophysical method providing the spatial distribution of relevant agronomic information that enables us to determine management zones for precision farming. Much work has been done to test the applicability of existing geoelectrical methods and to develop measurement systems applicable in the context of precision farming. Therefore, the aim of this paper was to introduce the basic ideas of precision farming, to discuss current precision farming applied geoelectrical methods and instruments and to give an overview about our corresponding activities during recent years. Different experiments were performed both in the laboratory and in the field to estimate first, electrical conductivity affecting factors, second, relationships between direct push and surface measurements, third, the seasonal stability of electrical conductivity patterns and fourth, the relationship between plant yield and electrical conductivity. From the results of these experiments, we concluded that soil texture is a very dominant factor in electrical conductivity mapping. Soil moisture affects both the level and the dynamic range of electrical conductivity readings. Nevertheless, electrical conductivity measurements can be principally performed independent of season. However, electrical conductivity field mapping does not produce reliable maps of spatial particle size distribution of soils, e.g., necessary to generate input parameters for water and nutrient transport models. The missing step to achieve this aim may be to develop multi-sensor systems that allow adjusting the electrical conductivity measurement from the influence of different soil water contents.
