DSSAT-CERES-Wheat model to optimize plant density and nitrogen best management practices

Abstract

Intensive use of groundwater and chemical fertilizer has led to serious negative impacts on environmental conditions in the North China Plain. The main objective of this study was to evaluate the best management production strategies for winter wheat that increase yield and reduce environmental impacts. This study combined field data with model analysis using the CERES-Wheat model to evaluate long-term winter wheat productivity and nitrogen use in response to plant density and nitrogen rate under limiting irrigation conditions. The CERES-Wheat model was calibrated and evaluated with 3 years of data which consisted of plant density, nitrogen rates and irrigation treatments. The simulated results using historical weather data showed that grain yield and nitrogen use were sensitive to different management practices including plant density, nitrogen rate and amount of irrigation applications. Nitrogen application of 180 kg ha−1 with 300 plants m−2 improved long-term nitrogen use, stabilized grain yield, produced the highest net return, and decreased soil residual nitrogen to reduce environment risk. There was a positive correlation between canopy nitrogen and grain yield. Compared with current nitrogen recommendations (240 kg ha−1), N rate of 180 kg ha−1 increased partial factor productivity and agronomic efficiency by about 32% and 33% due to increase in nitrogen uptake efficiency and reduced soil residual nitrogen. In conclusion, results of this study indicated that the CERES-Wheat model was a useful tool to evaluate alternative management practices in order to optimize yield and nitrogen use under limited irrigation conditions.