Standardization of Soil Apparent Electrical Conductivity Using Multi-Temporal Surveys Across Multiple Production Fields.

Apparent soil electrical conductivity (EC_a) is an efficient technique for understanding within-field variability of physical and chemical soil characteristics. Commercial devices are readily available for collecting EC_a on whole fields and used broadly for crop management in precision agriculture; however, greater variations in the levels in EC_a occur when collected at different times due to changes in environmental factors such as soil moisture or management history. These differences result in inconsistent delineations of patterns in soil EC_a over time. Therefore, the objective of this research was to determine the feasibility of using soil-map information to adjust distributions of EC_a survey data to account for differences in conditions found within multiple fields. We obtained multi-year EC_a surveys from several crop fields in the claypan region of Missouri, USA under different antecedent moisture conditions. Distributions of EC_a were generated at the soil map-unit scale delineated from the NRCS Soil Survey Geographic (SSURGO) database. Possible normalizations of EC_a data collected over multiple surveys may be used to create a coherent dataset to predict regional-scale variability of soil properties.