Soil Quality Assessment: Integrated Study on Standard Scoring Functions and Geospatial Approach

Assessment of soil quality indices is highly influential in sustainable agriculture. A myriad of methods is currently used to select the most relevant soil quality indicators. However, information about the most accurate and precise methods for agricultural areas at the catchment scales is lacking. Therefore, the main aim of the present study was to assess ten soil quality indicators from a factor analysis (FA) to obtain the most suitable soil quality indicators in combination with an indicator selection method (standard scoring functions). The study was conducted in an irrigated agriculture area in the Mashhad Plain in Northeast Iran. Results of FA by maximum likelihood method showed that four factors were the most significant in explaining the system variance and collectively accounted for 78.9% of the total. The magnitude of the loadings, which explains a great part of the variance in each factor, was used for naming the factors. On the surface, nitrogen (0.12), electrical conductivity (0.11), exchangeable sodium percentage (0.11), and sodium adsorption rate (0.11) had the highest scores. In the subsoil, however, the scoring was sodium adsorption ratio (0.12), exchangeable sodium percentage (0.12), calcium carbonate equivalent (0.12), pH (0.11), and electrical conductivity (0.11). The lowest scores were obtained for soil nutrients Olsen-P and exchangeable K. Overall, higher soil quality was observed in the subsoil relative to the surface, which is a strong confirmation of the rapid land degradation processes developed in the area.