Effects of tillage on variability in soil penetration resistance in an olive orchard
Juan López de Herrera A B E , Tomás Herrero Tejedor B , Antonio Saa-Requejo A C and A. M. Tarquis A DA CEIGRAM, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, Madrid 28040, Spain.
B Departamento de Ingeniería Agroforestal, ETS Ingenieros Agrónomos, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, Madrid 28040, Spain.
C Departamento de Producción Agraria, ETS Ingenieros Agrónomos, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, Madrid 28040, Spain.
D Departamento MatemáticaAplicada, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, Madrid 28040, Spain.
E Corresponding author. Email: juan.lz.herrera@upm.es
Soil Research 54(2) 134-143 https://doi.org/10.1071/SR15046
Submitted: 11 February 2015 Accepted: 30 July 2015 Published: 4 March 2016
Abstract
Spatial variability of soil properties such as soil structure and soil penetrometer resistance (SPR) is relevant for identifying those zones with physical degradation. We used classical statistical and multifractal analyses for characterising the spatial patterns of SPR distributions and compared them at different soil depths to investigate the tillage effect in soil compaction. The study was conducted on an Ochrept dedicated to olive orchards for the last 70 years. Two parallel transects of 64 m were selected as different soil-management plots: conventional tillage and no tillage. Penetrometer resistance readings were carried out at 50-cm intervals within the first 20 cm of soil depth. Two-way analysis of variance (ANOVA) highlighted that tillage system, soil depth and their interaction were statistically significant to explain the variance of SPR data from 5 to 20 cm soil depth. The scaling properties of each SPR profile were characterised by τ(q) function, calculated in the range of moment orders (q) between −5 and +5 taken at 0.5 lag increments. Several parameters were calculated from this: the singularities of strength (α); the Hausdorff dimension (f(α)); entropy dimension (α1); and their multifractal spectrum, i.e. graph α v. f(α). Multifractal scaling was evident and added valuable information to describe the spatial arrangement of depth-dependent penetrometer datasets in all soil layers, which was complementary to the ANOVA results.
Additional keywords: ANOVA, multifractal analysis, olive orchard, soil degradation.
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