Applied and Environmental Soil Science (Jan 2023)
Explaining the Soil Quality Using Different Assessment Techniques
Abstract
Soil quality serves as the basis for both food security and environmental sustainability. To optimize production and implement soil management interventions, understanding the state of the soil quality is fundamental. Thus, this study was conducted to assess the soil quality of arable lands situated in the Nitisols and Luvisols using different assessment techniques. A total of 57 georeferenced soil samples were taken at a depth of 20 cm (18 from Nitisols and 39 from Luvisols land). The soil samples were analyzed for particle size distribution (PSD), texture, pH, organic carbon (OC), total nitrogen (TN), available phosphorus (P), sulfur (S), exchangeable bases (calcium (Ca), magnesium (Mg), and potassium (K)), soil micronutrients (boron (B), copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn)), and cation exchange capacity (CEC). The techniques used to estimate soil quality includes principal component analysis (PCA), a normalized PCA, and common soil parameters (soil texture, pH, OC, N, P, and K). The results were expressed in terms of soil quality index (SQI). In addition, the soil fertility/nutrient/index (NI) approach was used. The result showed that the SQI values using the common parameters approach were 0.17 and 0.30 for the lands belonging to Nitisols and Luvisols and categorized as very poor (<0.2) and poor (0.2–0.4) quality soils, respectively. PCA-SQI and normalized PCA-SQI values for lands in the Nitisols were 0.36 and 0.42, while for Luvisols they were 0.38 and 0.40, respectively. The soil quality of lands in the Luvisols was rated low (0.38–0.44), while lands in the Nitisols qualified under very low (<0.38) and low soil quality, respectively. In addition, the value of 1.42 and 1.78 in their order for lands belonging to Nitisols and Luvisols were recorded using the NI method that indicated low and medium soil quality. In conclusion, PCA and common soil parameters techniques regardless of soil types offered consistently similar information and could be taken as useful techniques for aiding soil management interventions. Furthermore, the result also calls for the need for applying soil management practices.