عنوان مقاله [English]
Knowledge of the soils capacity to utilize them in the form of different major uses in agricultural ecosystems and natural resources requires the accurate recognition of the physico-chemical and biological properties of the soil, ensuring the sustainable use of the lands. Therefore, this research was conducted to evaluate the soil quality using quantitative models in the Kane Sorkh lands of Mehran as a part of arid and semi-arid lands of Ilam province (Iran). Soil samples were taken from the depth of 0-30 cm and weighted average for the depths of 30-100 cm of the soil profile. Physicochemical properties were measured based on the standard methods. Using principal component analysis (PCA), among a total 16 soil characteristics (TDS), eight properties were selected based on the eigen values and the correlation coefficient as the least properties affecting soil quality (MDS). Then, soil quality assessment was performed using two models of integrated quality index (IQI), Nemoro Quality Index (NQI), and each in two sets of TDS and MDS. The results showed that the top layer (0-30 cm) have a moderate quality class and the sub layer (30-100 cm of the profiles) have poor quality with severe constraints. According to the results, the most important factors limiting soil quality were organic matter deficiency, high percentage of calcium carbonate, gypsum, gravel and soil salinity. Determination coefficients (R2) for the top and sub-layer samples between the two TDS and MDS sets in both IQI and NQI models were 0.79 and 0.79, 0.95 and 0.94, respectively, indicating the reliability of using MDS set instead of TDS in both models. Therefore, the use of most effective soil properties in the soil quality assessment studies is not only time consuming but also it is cost-effective for sustainable monitoring of agricultural land use.
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