Soil quality assessment in the Araban plain across various land use types

Soil is an important resource for improving the quality of human well-being and creating sustainable environmental awareness. Therefore, it is imperative to protect the soil health. This study determined quality of the soils in the Araban plain, Türkiye using three different methods, i.e., principal component analysis (PCA), analytic hierarchy process (AHP), and expert opinion (EO). The major aim was to determine the most appropriate method for determining soil quality and recommending soil protection practices for improving quality. This study was conducted on an area of approximately 25,000 ha. A total of 230 soil samples (7 pasture areas, 56 orchards, and 167 arable crops) were analyzed to determine key soil quality indicators. A minimum dataset consisting of parameters that best represent the soils of the region was created. Subsequently, PCA was used to predict soil quality with the optimal accuracy using the least amount of data. The EO was incorporated to validate the PCA results. The AHP was used to assign weights to the parameters. Indicators at all sampling points were converted to unitless scorers. These scores were then formulated as soil quality index (SQI) using the weighted summation method. Organic matter (OM) exerted the highest impact on soil quality. Significant variations in SQI values were observed among arable land, orchards land and pastureland (P < 0.01). Significant variations were recorded in SQI values of the assessment methods employed in this study. The lowest (0.552) and highest (0.829) SQI values were recorded for AHP and EO, respectively. Overall, streamlining indicators through PCA gave the most accurate result for SQI value. Subsequently, SQI determination should involve weighing with AHP, particularly towards EO. The AHP was found to be the most appropriate method for evaluating soil quality in Araban. This integrated approach ensures a robust evaluation of soil quality, facilitating more accurate and nuanced insights for informed land management decisions. Overall, 92.61 % of the region's soil had poor and medium soil quality. Therefore, increasing OM content and aggregate stability are suggested to improve soil quality in the study region.