year 11, Issue 3 (Autumn 2021)                   E.E.R. 2021, 11(3): 123-139 | Back to browse issues page

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karimzadeh Z, shahab arkhazloo H, soltani toolarood A A, asghari S. Determining of most important characteristics for soil health indices in Khaneghah Namin area. E.E.R.. 2021; 11 (3) :123-139
Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili ,
Abstract:   (180 Views)
Extended abstract
1- Introduction
The ability of soil to provide products in the ecosystem, protect soil and water and perform its environmental functions reflects the quality and health of the soil. Soil health is an index for assessing soil functions such as crop production and growth of microorganisms. Soil health is affected by soil's physical, chemical, and biological properties, and its integrated evaluation needs to consider the collective effect of these characteristics. In this study, to present the cumulative soil health index, an integrated quality index (IQI) and Nemero quality index (NQI) were used. These indices are designed initially to assess soil quality, but they are used to assess soil health in this study. To determine these Indices, the most important characteristics affecting soil health were determined by the PCA method.
2- Methodology
In this study, 72 soil samples were taken from 208 hectares in the Khaneghah Namin area of Ardabil province, which included 19 samples of agricultural lands and 53 samples of rangelands. In each soil sample, 16 physical, chemical, and biological properties of soil (pH, EC, organic carbon, percentage of lime, percentage of sand, silt and clay, porosity, bulk density, the population of soil microorganisms, basic microbial respiration, microbial respiration Substrate stimulated, microbial biomass carbon, microbial biomass nitrogen, biomass carbon to organic carbon ratio and metabolic fraction) were determined as total data set (TDS). Among these properties, five factors were obtained as minimum data set (MDS) using PCA. Then, soil health indices were calculated based on the two methods of the integrated quality index (IQI) and Nemero quality index (NQI), and using two TDS and MDS data sets. The significant correlation of indices calculated by TDS with MDS (Correlation of IQITDS with IQIMDS and NQITDS with NQIMDS) confirmed the efficiency of selected MDS to determine the soil health indices. Also, the difference of soil health indices between agricultural and rangelands was compared by a non-paired t-test. 
3- Results 
Based on PCA results, five biological and physical soil properties were selected as the minimum data set. These properties include basal soil respiration, soil biomass carbon, soil biomass nitrogen, bulk density, and total soil porosity as the most important characteristics affecting soil health. In IQI index for a combination of soil properties as an integrated index, weighted scores of properties calculated. For scoring the soil properties used from fuzzy membership functions that scoring between 0-1. The commonality of properties is divided by the sum of commonalities in a data set to weighting the properties. The results showed that IQITDS and IQIMDS soil health indices rated the region's soils as grade II, while NQITDS and NQIMDS indices ranked the soils as grade IV. A significant correlation was obtained between the indicators calculated with TDS and MDS in the region and rangeland and agricultural land use. The average IQITDS, IQIMDS, NQITDS, and NQIMDS indices in the rangeland were 0.71, 0.67, 0.03, and 0.082, respectively. The indices in agricultural fields were 0.66, 0.66, 0.027, and 0.08, respectively. The mean comparison between two land-use shows that IQITDS and NQITDS have a significant difference, and IQIMDS and NQIMDS do not have a significant difference. These results show that rangelands have significantly more soil health in comparison to agricultural lands. Also, these results show that the integrated quality index (IQI) is more suitable for evaluating soil health in comparison to nemero quality index (NQI). 
4- Discussion & Conclusions
This study shows that the PCA method had efficient in selecting the most important characteristics that affect soil health. Qi et al. (2009) and Shahab et al. (2018) confirmed the PCA efficiency in MDS selection. It was also observed that the use of soil biological properties in determining the cumulative indices of IQI and NQI could lead to better modeling of soil quality and health so that most of the characteristics selected as MDS by PCA are the biological characteristics. Zhou et al. (2020) reported that the use of soil biological properties as indicators of soil health could be used to detect soil degradation. Comparison of soil health between agricultural and rangeland showed that cumulative indicators with TDS data could provide a better index for evaluating land use impact on soil health. 
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Received: 2021/05/26 | Published: 2021/09/23

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