Evaluating the Effects of A Five-year Irrigation Experiment on Soil Quality and Crop Yield using Soil Quality Indexes

Soil quality on irrigated farmland is declining due to intensive agricultural activities and inappropriate agricultural inputs. This study aimed to analyze the effects of agricultural inputs (fertilizer and irrigation input) on soil quality and quantify the relationship between soil quality and resource use and yield formation under two irrigation patterns [border irrigation (BI) and drip irrigation (DI)] in the Hetao Irrigation District of China. We identified nine soil indexes [clay, sand, bulk density, pH, soil organic matter (SOM), electrical conductivity of saturated extract, structural stability index (SSI), soil water content, NH4+-N] as the minimum dataset (MDS) in topsoil (0–30 cm) and subsoil (30–60 cm). The results showed that the soil quality indicator (SQI) calculated using multi-linear regression (SQI-M) qualified the relationship between soil quality and crop yield better than the SQI calculated using factor analysis (SQI-F), especially for subsoil. The variation in soil quality was related to soil depth, with the SQIs in topsoil decreasing and subsoil increasing with increasing soil depth. The SQI variation was due to decreased SOM and SSI in topsoil and increased sand content in subsoil. The ANOVA and linear mixed-effects model (LMM) had high predictive performance, the LMM method quantified management, environment and SQIs factors to accurately estimate yield. In addition, the reduction in soil quality decreased the crop water and fertilizer use capacities and soil carbon sequestration capacity. Our study provides a quantitative tool for assessing soil quality in farmland and develops an LMM model to estimate yield considering soul quality. Overall, our findings suggest that continuous irrigation agricultural practices decrease soil quality, limit crop resource use and yield formation, and decrease agricultural sustainability.