Evaluation of geostatistical mapping strategies in monitoring of spatial distributions of iron and zinc on a calcareous barley field.

Geostatistical information on spatial distributions of chemical properties of agricultural soils is important for refining farm managements and precision farming. Site specific monitoring of field soils, that is one of the main steps of precision agriculture, provides more accurate information especially for balancing iron (Fe) and zinc (Zn) levels on the varied soil and plant conditions. In this study, spatial variability of Fe and Zn levels on a calcareous barley field under the barley plants were monitored by performing geostatistical mapping strategies. For this aim, soil samples were systematically taken from the study area at two depths (0-20 and 20-40 cm), on a grid system 10 m x 10 m intervals in the E-W and N-S directions. Descriptive statistics indicated that the coefficient of variation for Fe was low as compared for Zn in both subsoil layer samples. The CV values for Fe and Zn levels were 25% and 33% in topsoil and 23% and 29% in subsoil, respectively. Geostatistical analysis techniques were used in predicting the spatial structure of Fe and Zn levels of soil and plant. The spatial distribution maps were obtained by using Simple Kriging Method (SKM) with spherical semivariogram model for topsoil Fe, SKM with Gaussian semivariogram model for topsoil Zn. The Fe levels of topsoil and Zn levels of subsoil had moderate positional dependence, whereas Zn levels of topsoil and Fe levels of subsoil had weak dependence on the experimental field. The obtained range values were close to each other except for subsoil Fe and changed between 21 m and 15 m. The Fe and Zn levels of barley plants had moderate positional dependence. The results showed that site specific Fe and Zn levels of the field soil could be spatially varied within the small sampling points. The results have revealed that the data values of non-sampled points could be estimated by using SK method and suitable semivariogram model. Evaluation of geostatistical mapping strategies in monitoring of spatial distributions of Fe and Zn levels on a field will improve the decision support for field management practices in a more healthy and moderate way. It will also help to eliminate unequal micronutrient sources of the field soil, which is valuable for balanced crop nutrient consumption.