Using Multivariate Analysis to Evaluate Soil Quality in Agricultural Lands of Zanjan Province

Soil quality (SQ) index is used as a quantitative tool for assessing the impact of land use and management systems on soil condition. The aim of this study was to quantify SQ under agricultural ecosystems in Zanjan province using multivariate analyses. 154 soil samples were collected from 77 farms in Zanjan province (27 sites under irrigated and 50 sites under rain-fed land use) at 0-30 and 30-60 cm depths. 24 soil physical, chemical and biological properties were measured. Principal component analysis was used to identify minimum data set (MDS) for assessing SQ. Two groups of MDS were determined by considering physical, chemical and biological properties separately (MDS1), and by using all measured soil properties (MDS2). The capability of linear or non-linear approaches to develop SQ index was investigated. Four SQ indices were calculated using MDS1 and MDS2, linear and non-linear scoring methods. Total nitrogen, available phosphorus, sodium, zinc and copper, microbial biomass carbon, microbial quotient index, aggregate stability and bulk density were determined as the MDS1. Soil organic carbon, available phosphorus, sodium, zinc and copper, microbial quotient index, aggregate stability and sorptivity were identified as the MDS2. Both methods had enough efficiency to identify MDS for assessing SQ. The linear SQ indices (p˂0.001) showed higher capability than non-linear indices (p˂0.01) to differentiate SQ between rain-fed and irrigated land uses. The SQ index calculated using linear function and MDS1 indicated SQ of irrigated land use (0.524) had a better condition compared to rainfed land use (0.433). The SQ index calculated using MDS2 also indicated a similar trend between irrigated (0.551) and rainfed land use (0.433).