Abstract
Aim of study: Our main objective was to take advantage of the ECa information that the EM38-MK2 sensor records simultaneously at two relative depths for modeling using spatial regression and the subsequent blocking of the conductivity estimate values, incorporating elevation. Area of study: A 23.1-ha field located in the municipality of Puerto López (Meta, Colombia). Material and methods: A series of georeferenced data (15438) was collected from the EM38-MK2 sensor, through which the ECa was obtained at two depths, a spatial aggregation was performed using a grid of 40 m ´ 40 m (167 grid cells), to provide data in Lattice form, the centroid of the cells was determined as the new representative spatial coordinates, to adjust a Spatial Autoregression Model (SAC), and then define the blocks from the predictions of the adjusted model. Main results: The adjusted model has a comparative purpose with the usual proposals for delimiting management zones separately, so it was convenient to incorporate in the model a 3D weighting matrix relating the two relative depths recorded by the EM38MK2 sensor. By mapping the surface layer with the predictions of the SAC model, two distinguishable blocks were delimited in its ECa and management zone analyst (MZA), which can be suitable for experimentation or agricultural management. Research highlights: These results can be adopted to define the shape and dimension of the blocks in the context of experimental design so that with adequate blocking, the effect of spatial dependence associated with the physicochemical properties of soils related to ECa can be mitigated or suppressed.
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