Soil quality evaluation is a tool to improve soil management and land use system. A large number of different physical, chemical and biological properties of soil, known as soil quality indicators, are used to soil quality assessment. These properties, that are sensitive to stress or disturbance, are synthesized using numerical quality indices obtained by several different types of methods. The aim of this study was to compare two different methods for soil quality index calculation in agricultural lands of Qazvin Province, Iran. In particular, the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI) models were applied using the indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS). Ten soil quality indicators were included in TDS: pH, Electrical Conductivity (EC), Organic Matter (OM), Cation Exchange Capacity (CEC), percentage of equivalent CaCO3 (TNV), heavy metal content of cadmium (Cd), cobalt (Co), lead (Pb), chromium (Cr) and soil erodibility factor (K), while Principal Components Analysis (PCA) was used to select the indicators to include in MDS. The tested soil quality indices were appropriate to evaluate the effects of land management practices on soil quality. The results of the linear relationship as well as of the match analysis, among the approaches studied, identified better estimation of soil quality applying IQI index when compared to NQI index and higher values of agreement of TSD than MSD. However, also IQIMSD approach resulted in suitable evaluation of the effects of land management practices on soil quality. This latter result was particularly relevant in the area studied because the use of a limited number of indicators could allow to reduce the cost of the analysis and to increase the sampling density in order to obtain a more detailed evaluation of soil quality through a geostatistical approach. © 2013 Elsevier Ltd. All rights reserved.
Assessment of soil quality indices in agricultural lands of Qazvin Province, Iran
Rossana Marzaioli;
2014
Abstract
Soil quality evaluation is a tool to improve soil management and land use system. A large number of different physical, chemical and biological properties of soil, known as soil quality indicators, are used to soil quality assessment. These properties, that are sensitive to stress or disturbance, are synthesized using numerical quality indices obtained by several different types of methods. The aim of this study was to compare two different methods for soil quality index calculation in agricultural lands of Qazvin Province, Iran. In particular, the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI) models were applied using the indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS). Ten soil quality indicators were included in TDS: pH, Electrical Conductivity (EC), Organic Matter (OM), Cation Exchange Capacity (CEC), percentage of equivalent CaCO3 (TNV), heavy metal content of cadmium (Cd), cobalt (Co), lead (Pb), chromium (Cr) and soil erodibility factor (K), while Principal Components Analysis (PCA) was used to select the indicators to include in MDS. The tested soil quality indices were appropriate to evaluate the effects of land management practices on soil quality. The results of the linear relationship as well as of the match analysis, among the approaches studied, identified better estimation of soil quality applying IQI index when compared to NQI index and higher values of agreement of TSD than MSD. However, also IQIMSD approach resulted in suitable evaluation of the effects of land management practices on soil quality. This latter result was particularly relevant in the area studied because the use of a limited number of indicators could allow to reduce the cost of the analysis and to increase the sampling density in order to obtain a more detailed evaluation of soil quality through a geostatistical approach. © 2013 Elsevier Ltd. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
