Determination of Minimum Data Set to Evaluate Soil Quality in Piranshahr Region Wheat Fields

Evaluating and determining the minimum data set to evaluate soil quality is very important, valuable in terms of cost, and time save. The aims of this study were to assess the quality index of soils under successive, and long-term cultivation of wheat by a valid model (Integrated quality index= IQI), determine the minimum data set to evaluate the quality of soils in this region, and evaluate the relationship between soil quality index and wheat yield components. For these purposes, 18 physical, chemical, and fertility properties of the surface soil belonging to 40 soil profiles were determined in the croplands from Piranshahr region of West Azerbaijan province. The soils were classified in the three order of Mollisols, Inceptisols, and Vertisols. Total variables affecting soil quality (TDS) were determined, and minimum effective data (MDS) were estimated using principal component analysis (PCA). The soil quality index was divided into five classes according to the growth of the plant using the interpolation technique. Based on the results of PCA, five properties of organic carbon, clay, sodium adsorption ratio, calcium carbonate equivalent and silt had a specific value greater than one and were selected as MDS indicators. The highest values of IQITDS, and IQIMDS were observed in the Inceptisols, followed by Mollisols and Vertisols, respectively. A significant relationship (p <0.05) was found between wheat yield components (grain yield, and biological yield of wheat) with IQITDS and IQIMDS models, which showed a positive, and significant effect of soil quality index on wheat yield components. Moreover, the IQITDS model was more accurate than the IQIMDS model in predicting the performance of wheat components due to its higher R2. However, due to the positive, and significant correlation between IQITDS and IQIMDS (R2 =0.9(, the IQIMDS model is an economic and better model for evaluating the quality of soils in the region.