Spatial prediction of soil penetration resistance using functional geostatistics

Abstract

Knowledge of agricultural soils is a relevant factor for the sustainable development of farming activities. Studies on agricultural soils usually begin with the analysis of data obtained from sampling a finite number of sites in a particular region of interest. The variables measured at each site can be scalar (chemical properties) or functional (infiltration water or penetration resistance). The use of functional geostatistics (FG) allows to perform spatial curve interpolation to generate prediction curves (instead of single variables) at sites that lack information. This study analyzed soil penetration resistance (PR) data measured between 0 and 35 cm depth at 75 sites within a 37 ha plot dedicated to livestock. The data from each site were converted to curves using non-parametric smoothing techniques. In this study, a B-splines basis of 18 functions was used to estimate PR curves for each of the 75 sites. The applicability of FG as a spatial prediction tool for PR curves was then evaluated using cross-validation, and the results were compared with classical spatial prediction methods (univariate geostatistics) that are generally used for studying this type of information. We concluded that FG is a reliable tool for analyzing PR because a high correlation was obtained between the observed and predicted curves (R 2 = 94 %). In addition, the results from descriptive analyses calculated from field data and FG models were similar for the observed and predicted values.

Establishment of homogeneous zones in a soil of alluvial origin

“…According to Cambardella et al (1994), the variables with strong spatial dependence are more influenced by soil formation factors ( Table 2). The evaluation of UK interpolation was intermediate, with a range of cross-validation coefficients between 0.53 and 0.73, i.e., lower than those found by Varón-Ramírez, Camacho-Tamayo and González, (2018), and similar to those found by Cortés, Camacho-Tamayo and Giraldo (2016). The pH interpolation range fluctuated between 3.5 and 7.4, with a mean of 5.49 and a standard deviation of 0.98.…”

“…To establish the goodness of the predictions made by different methods, cross-validations were made, and the best model was selected by the highest cross-validation coefficient (CVC), the smallest root of the mean square error (RMSE), the reduced error (RE) value closer to zero, the value of the standard deviation of the reduced errors (SDRE) closer to one (Faraco et al, 2008;Johann et al, 2010;Cortés;Giraldo, 2016) and the best degree of spatial dependence (DSD) of each of the chemical soil properties, according to the classification proposed by Cambardella et al (1994). These authors consider the degree of spatial dependence as strong when DSD ≤ 25%, moderate when 25 < DSD ≤ 75%, and weak when DSD > 75%.…”

Determining Attribute—Response Relationships of Soils under Different Land Uses: A Case Study

“…Descriptive statistics were calculated for each physical property of the soils for the three systems and subsystems (Table 1). The skewness coefficient empirically verified changes in the mean of the indicator (or process) in the studied area, and values close to zero indicated a stationary process whose mean did not change [38]. Several skewness values greater than 0.5 indicated spatial variability in certain properties (e.g., BD and θv) that were influenced by agrotechnics or soil type properties in the case of the forest (Table 1).…”

Investigations of bioinspired soil penetration strategies via a numerical model: Does radial expansion improve soil intruder performances?

“…For example, the soil is often assumed to be a continuum medium, and parameters such as temperature, soil pH, soil aeration, the incidence of light, or nutrient status are kept at adequate and constant levels [6]. Besides plant roots, radial expansion is employed by other burrowing organisms (e.g., polychaetes, clams, and earthworms), and penetration performances of their different modalities of actuation have been investigated [10,12,20,25,30]. In [10], the authors analyzed numerically the penetration in granular soil of a bioinspired probe, which penetrates through a three-phase process: The probe is first pushed into the soil until reaching a target depth, then a region located behind the tip (named anchor) expands radially, and finally, the tip is displaced downward whereas the anchor is moved upward.…”

“…The results showed that the actuation through radial expansion outperforms bidirectional bending since it implies a lower drag force. In [12], an earthworminspired probe penetrating in homogeneous clear mud analog was experimentally investigated. Specifically, this probe includes a region located behind the tip implementing radial expansion with a balloon mechanism.…”