Spatial prediction of soil penetration resistance using functional geostatistics

Authors

  • Diego Leonardo Cortés-D National University of Colombia; Engineering Faculty; Dept. of Civil and Agricultural Engineering
  • Jesús Hernán Camacho-Tamayo National University of Colombia; Engineering Faculty; Dept. of Civil and Agricultural Engineering
  • Ramón Giraldo National University of Colombia; Science Faculty; Dept. of Statistics

DOI:

https://doi.org/10.1590/0103-9016-2015-0113

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 (R2 = 94 %). In addition, the results from descriptive analyses calculated from field data and FG models were similar for the observed and predicted values.

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Published

2016-10-01

How to Cite

Cortés-D, D. L., Camacho-Tamayo, J. H., & Giraldo, R. (2016). Spatial prediction of soil penetration resistance using functional geostatistics . Scientia Agricola, 73(5), 455-461. https://doi.org/10.1590/0103-9016-2015-0113

Issue

Section

Biometry, Modeling and Statistics