Assessing and Mapping of Integrated and Nemero Soil Quality Indices and their Relationship with Rose Yield (A Case Study: Bardsir, Kerman Province)

The assessment of soil quality for agricultural land is essential for the economic successes and sustainability of the environment in developing countries. Currently, many types of methods with different factors are used to evaluate soil quality. Soil quality evaluation is an indicator of sustainable agriculture and optimized application of utilization of natural resources. Moreover, the Bardsir city is one of the most important regions of Rose (Rosa Damasceneea Mill) in Kerman province and Iran. In this research, soil quality were evaluated in a part of the cultivated land of Rose using integrated soil quality index (IQI) and Nemoro soil quality index (NQI) in combination with two of data sets, total data set (TDS) and minimum data set (MDS) for 0-25 and 25-50 cm depth.

In this research, a farm with an area of 30 hectares was selected in Bardsir city, Kerman province. Then, 100 locations were sampled to determine soil characteristics (0-25 and 25-50 cm), then in each location, the yield was determined. Among the total characteristics of soil quality, the most important of characteristics were determined Using principal component analysis (PCA). The results showed that in the topsoil and subsoil, minimum data set were organic matter, sand, Mn, calcium carbonate equivalent, Zn, Cu and sand, K, calcium carbonate equivalent, Zn, P, fragments and Mn, respectively.

The results showed that at the 0-25 cm, the correlation between IQITDS and IQIMDS and between NQITDS and NQIMDS were 0.85 and 0.79, respectively. Also, at the depth of 25-50 cm, the correlation between IQITDS and IQIMDS and between NQITDS and NQIMDS were 0.75 and 0.77, respectively. The geostatistical analysis of soil quality indices showed that all of the studied soil parameters and Rose yield have spherical model and strong to medium spatial structure. The range of variograms is varied from 119.33 m for IQITDS in the subsoil to 151.8 m for NQITDS in the topsoil. Besides, the range of variogram for Rose yield was 122.16 m. The correlation between kriging maps of Rose yield and soil quality indices showed that the highest correlation was found between the yield and the IQITDS index at both studied depths. The results of correlation between soil quality indices and Rose yield showed that the IQITDS index has a higher correlation with yield than other indices.

These results demonstrated that the IQI index, especially in the TDS set, has a better performance for assessing the soil quality in the study area. Because of the relatively good correlation between this set and MDS, the TDS set is better to determine soil quality indices; this result may be attributed to use MDS to determine the soil quality indices with proper accuracy. However, if the purpose of soil quality assessment is to achieve the optimal yield, the use of IQITDS index, due to its greater correlation with the Rose yield, has a better performance.