STUDY OF THE UNCERTAINTY OF THE AMOUNT OF PRUNING IN THE OLIVE GROVE USING GEOSTATISTICAL ALGORITHMS

Abstract

Olive pruning mulch modifies the physical, chemical and biological properties of the soil. They are an efficient soil and water conservation system, while simultaneously improving the organic matter content of the soil. In any case, their effect on soil properties is a function of the densities provided. In any agricultural field, there can be significant variations in plant size, which can affect the amount of pruning obtained. In this research, a spatial sampling of pruning amount collected in olive trees (n=59) in a 13.1-ha traditional olive grove located in Cordoba (Spain), was conducted to estimate the mean pruning amount and assess its spatial uncertainty. In addition, the projected areas of all trees in the field (n=928) were determined. Tree projected area was found to be well correlated with the amount of pruning (Pearson correlation coefficient value of 0.74). The spatial continuity of the study variables was determined using isotropic variograms with nested spherical models. Direct sequential simulation and cosimulation algorithms were used to generate 125 realizations of each variable and map the spatial uncertainty of the amount of pruning in unsampled areas. The results indicate that pruning amounts exhibit spatial continuity. The projected area of the trees is a useful variable to improve estimates of total amount of pruning.