Apparent electrical conductivity and multivariate analysis of soil properties to assess soil constraints in orchards affected by previous parcelling

Abstract

Fruit production is relevant to the European agricultural sector. However, orchards in semi-arid areas of southern Europe may contain soils with constraints for tree development. This is the case of soils with high CaCO⁠3 content or limiting layers at variable depth. To assess spatial and in-depth variation of these soil constraints, an apparent electrical conductivity (ECa) survey was conducted in an orchard by using a galvanic contact soil sensor (Veris 3100). Different soil properties were randomly sampled at two depths (topsoil and subsoil) in 20 different sampling points within the plot. ECa raster maps were obtained for shallow (0-30cm) and deep (0-90cm) soil profile depths. In addition, an inversion modelling software was used to obtain horizontal ECa slices corresponding to 10cm thick soil layers from 0-10cm to 80-90cm in depth. Concordance analysis of ECa slices allowed the soil profile to be segmented into four homogeneous horizons with different spatial conductivity pattern. Then, a multivariate analysis of variance (MANOVA) was key, i) to better interpret the specific soil properties that mainly contributed to the spatial variation of ECa (CaCO⁠3 and organic matter (OM) contents), and ii) to delimit the soil layer and the specific spatial pattern of ECa that allows potential management areas to be delineated by presenting the same trend in CaCO⁠3 and OM for topsoil and subsoil simultaneously. Moreover, assessing 3D variation of ECa made it possible to identify different soil areas that, linked to previous earthworks to optimize the parcelling of the farm, are the main cause of spatial variability within the orchard.

This work was funded by the Spanish Ministry of Economy and Competitiveness through the project AgVANCE (AGL2013-48297-C2-2-R). We are also grateful to the University of Lleida for funding PhD scholarship for the first author.