minimum data set

One of the important issues in the sustainable management of soils in order to optimize the agricultural production and preserve natural resources is the assessment of soil quality.  Soil quality is the capacity of a specific kind of soil to function to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation. It is also considered one of the most important factors investigated in the assessment of soil management. Knowledge of quality changes is necessary for sustainable soil management. Since soil quality cannot be measured directly, it must be obtained from the relevant characteristics. Soil quality characteristics are sets of measurable soil characteristics that are sensitive to land use change, management, or conservation operations. Using soil quality indicators is a useful tool to determine and compare soil quality. The purpose of this research is to quantify the soil quality index using multivariate analysis in different soil types in Urmia Plain.

In this research, according to the semi-detailed soil studies of Urmia plain, 24 soil profiles from different soil units of this area, which are mostly under garden and agricultural use, were excavated, described, sampled, and classified, and 96 samples were also collected from soil solum. 2 profiles in Typic Haploxerepts (TH1) soil type, 4 profiles in Fluvaquentic Endoaquepts (FE) soil type, 6 profiles in Typic Calcixerepts (TC) soil type, 2 profiles in Typic Endoaquepts (TE) soil type, 5 profiles in Fluventic soil type Haploxerepts (FH) and 2 profiles were located in Typic Halaquept (TH2) soil type. At a certain distance from the excavation site of the profiles, four soil samples were taken from four directions of the profile. Using principal component analysis (PCA), among 22 characteristics affecting soil quality (TDS), the minimum characteristics affecting soil quality (MDS) were determined. Then the soil quality in different soil types of region was evaluated using two cumulative soil quality indices (IQI) and Nemuro Quality Index (NQI) and each of them was evaluated in two sets of TDS and MDS in different soil types.

Among the measured parameters, pH had the lowest (2.5%) and salinity (EC) had the highest coefficient of variation (154.6%) in the region. Among the 22 measured soil properties, sodium absorption ratio (SAR) in the first component, nickel element (Ni) in the second component, cation exchange capacity (CEC) in the third component, sand percentage in the fourth component, active lime (ACCE) in the fifth component and absorbable phosphorus (PAW) in the sixth component were selected as MDS. The examination of the soil quality index showed that the soils of this region mainly have quality grade II (57%). The highest average value of selected soil quality index related to MDS mode in IQI model was calculated with a value of 0.79 in Fluventic Haploxerepts soil type and the lowest average value related to TDS mode in NQI model was calculated with 0.28 value in Typic Halaquepts soil type. The correlation coefficient between the soil quality index with the total category and minimum data in both IQI and NQI models was equal (R2=0.48).

The sequence order of both soil quality indices (IQIa, NQI) in both TDS and MDS conditions in the types of the studied area was as FE>TE>TH1>TC>FH>TH2. Therefore, the highest soil quality was observed in the Fluventic Endoaquepts type and the lowest soil quality was observed in the Typic Halaquepts type. Based on the results, both indicators were classified in three classes (good, medium and poor) in TDS and MDS sets. In the case of TDS, 57.83% of land (equivalent to 19731 hectares) had good class (II), 30.48% of land (equivalent to 10400 hectares) had medium class (III) and 11.69% of land (equivalent to 3990 hectares) they had poor class (IV); (very good (I) and very poor (V) class were not observed). In MDS mode, 18.56% of lands (equivalent to 6333 hectares) had very good class (I), 27.15% of lands (equivalent to 9264 hectares) had good class (II) and 54.29% of lands (equivalent to 18524 hectares) They had medium class (III); (weak class (IV) and very weak (V) were not observed). The degrees of IQIa and NQI indices were similar and were divided into three classes (good, medium and poor). As a result, 39.3% of land (equivalent to 13412 hectares) was in good class (II), 24.59% of land (equivalent to 8392 hectares) was in medium class (III) and 1.36% of land (equivalent to 12317 hectares) was placed in poor class (IV); (very good (I) and very poor (V) classes were not observed). In general, the soils of the region were limited in terms of the studied indicators in the parts leading to the lake, and there was a significant correlation between IQITDS and IQIMDS, and between NQITDS and NQIMDS. This shows that the determined MDS set can be a good representative of TDS in soil quality assessment in Urmia Plain.