Mapping Soil Properties and Delineating Management Zones Based on Electrical Conductivity in a Hedgerow Olive Grove

Abstract

Abstract. Identifying spatial patterns of soil and plant properties can be an efficient method for site-specific management in areas with homogeneous characteristics (i.e., management zones, MZs). In this study, the use of soil apparent electrical conductivity (ECa) is proposed as the main information source for evaluating the spatial variability of soil and plant properties when using this variability to determine potential MZs. This study was conducted in a commercial hedgerow olive grove. Spatial distribution maps of the main soil properties and normalized difference vegetation index (NDVI) were generated by regression-kriging in which ECa was used as a secondary variable. According to the results obtained by the validation process, all maps were accurate. Soil and plant properties and ECa were subjected to principal component analysis (PCA). Two MZs were determined using a fuzzy cluster classification. The MZ map was validated using data related to soil samples, yield, and NDVI. Establishing different MZs was useful for adapting the irrigation strategies to the soil conditions of the plot, which resulted in increased productivity of the hedgerow olive grove. Keywords: Fuzzy c-means, Principal components analysis, Regression-kriging, Spatial prediction.