Spatial variability assessment of essential soil and plant variables to sitespecific crop management in olive orchards

Application of new techniques in precision farming for the determination of soil and plant spatial variability in such matters as soil nutrients, soil physical and chemical properties have received great attention. This study was carried out in order to map the spatial variability of essential plant and soil variables associated with olive yield, through generating maps that can be used in site-specific crop management (SSCM). For this purpose, two orchards with optimum and low yields were selected in the Tarom region of Zanjan province and 65 soil and plant samples were taken during 2014-2015 on a 49-m systematic sampling grid corresponding to a density of four soil samples per ha. All the samples were analyzed using appropriate laboratory methods. In addition, the percentage of fruit set in both years was calculated by counting the number of flowers and fruits. An interpolation map of each variable was created by the inverse distance weighted (IDW) method using ArcGIS. The results showed that nitrogen and potassium accounted for 94.6% of fruit set variations and silt accounted for 93.9%, according to the fitted models using the stepwise regression method. In addition, nitrogen and potassium accounted for 94.6% and silt for 93.9% of the fruit set variations. In aggregate, the main reasons for the differences in fruit set in the olive orchards were including nitrogen and potassium deficiency, high silt, deficiency in available phosphorous, high SAR, TNV and EC. Interpolation maps showed that the spatial distribution of fruit set in both orchards was inversely related to yield limiting variables.