Abstract.The adoption of apparent soil electrical conductivity (soil ECa) sensors has increased in precision agricultural systems, especially in systems pulled by vehicles. This work developed a portable soil sensor for measuring soil ECa that could be used without vehicles in mountainous areas and small farms. The developed system was based on the electrical resistivity method. The system measured the electrical conductivity by applying a square wave signal at frequencies defined by the user. The acquired data were georeferenced using a low-cost global navigation satellite system (GNSS) receiver. The sensor system was developed using a BeagleBone Black, a low-cost single-board computer. A user interface was developed in C++, and a touch screen with a resolution of 800×480 pixels was used to display the results. This interface performed statistical analysis, and the results were used to guide the user to identify more field locations to be sampled to increase mapping accuracy. The system was tested in a coffee plantation located in a mountainous area and in a sugarcane plantation in Minas Gerais, Brazil. The system worked well in mapping the soil ECa. The apparent soil electrical conductivities measured using frequencies of 10, 20, 30, and 40 Hz were highly correlated. In the sugarcane field that had more variation in soil texture, a greater number of soil properties presented a significant correlation with the soil ECa. Keywords: Electrical conductivity, Geostatistics, Precision agriculture, Soil properties, Soil sensing, Spatial variability.
Using Multivariate Geostatistics to Assess Patterns of Spatial Dependence of Apparent Soil Electrical Conductivity and Selected Soil Properties
