Abstract

BOSCH MAYOL, Matías; COSTA, José Luís; CABRIA, Fabián Néstor  and  APARICIO, Virginia Carolina. Relationship between spatial variability of electrical conductivity and soil sodium content. Cienc. suelo [online]. 2012, vol.30, n.2, pp.95-105. ISSN 1850-2067.

Precision agriculture utilizes modern tools in order to obtain and analyze georreferenced data. Direct measuring sensors of soil apparent electrical conductivity (EC_a) are part of these modern tools and are widely used to quantify EC_a spatial variability. This variable is correlated with other soil properties (water holding capacity, organic matter content, salinity, drainage, topography, tillage managing and soil texture). Plants are negatively affected by elevated salts amount and elevated exchangeable sodium content, which causes physical and chemical damage of soils, affecting crop's grown and production. In order to determinate sodium spatial content and distribution, three fields about 80 Has average were selected. All fields are under central pivot irrigation system and are located in the southeast of Buenos Aires province, Argentina. In these fields EC_a was measured and georreferenced whit a direct measure sensor. Obtained data was used to create EC_a maps in every field using spatial interpolation methods (Kriging). All fields were divided into four different zones, based on its EC_a value, where soil samples were taken. Soil samples were laboratory processed in order to determinate gravimetric humidity (θ_g),, electrical conductivity of soil saturation paste extract (EC_e) and soluble cations (Na+, Ca+2 and Mg+2), and sodium adsorption ratio (SAR) was calculated. Experimental data was statistically analyzed using SAS PROC MIXED procedure. We observed CE_a spatial variability, and associations between EC_a and SAR. Significantly relationships between EC_a, EC_e and soil sodium content were found. Sodium content was statistically differenced between different EC_a zones in every field. The EC_a direct measuring sensors are accurately tools to estimate soil sodium spatial content.

Keywords : Georeferencing; Irrigation; Sensor; Precision Agriculture; Sodicity.

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