Improving High-Latitude Rice Nitrogen Management with the CERES-Rice Crop Model

• Published in: Agronomy (Basel) Vol. 8; no. 11; p. 263
• Main Authors: Zhang, Jing, Miao, Yuxin, Batchelor, William, Lu, Junjun, Wang, Hongye, Kang, Shujiang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 15-11-2018
• Subjects: Agricultural production; Biomass; Calibration; Cereal crops; Climate change; Crop growth; crop model; Crop yield; Crops; Evaluation; Experiments; Farmers; Fertilizers; Field tests; Food security; Global warming; Growing season; Growth models; high latitude rice; Latitude; Leaf area; Leaf area index; Leaves; Management; Meteorological data; Nitrogen; nitrogen use efficiency; precision nitrogen management; Productivity; Rain; Rice; Seasons; Simulation; Sustainable development; variety-specific management; Weather; weather-specific management; China
• ISSN: 2073-4395; 2073-4395
• DOI: 10.3390/agronomy8110263

Efficient use of nitrogen (N) fertilizer is critically important for China’s food security and sustainable development. Crop models have been widely used to analyze yield variability, assist in N prescriptions, and determine optimum N rates. The objectives of this study were to use the CERES-Rice model to simulate the N response of different high-latitude, adapted flooded rice varieties to different types of weather seasons, and to explore different optimum rice N management strategies with the combinations of rice varieties and types of weather seasons. Field experiments conducted for five N rates and three varieties in Northeast China during 2011–2016 were used to calibrate and evaluate the CERES-Rice model. Historical weather data (1960–2014) were classified into three weather types (cool/normal/warm) based on cumulative growing degree days during the normal growing season for rice. After calibrating the CERES-Rice model for three varieties and five N rates, the model gave good simulations for evaluation seasons for top weight (R2 ≥ 0.96), leaf area index (R2 ≥ 0.64), yield (R2 ≥ 0.71), and plant N uptake (R2 ≥ 0.83). The simulated optimum N rates for the combinations of varieties and weather types ranged from 91 to 119 kg N ha−1 over 55 seasons of weather data and were in agreement with the reported values of the region. Five different N management strategies were evaluated based on farmer practice, regional optimum N rates, and optimum N rates simulated for different combinations of varieties and weather season types over 20 seasons of weather data. The simulated optimum N rate, marginal net return, and N partial factor productivity were sensitive to both variety and type of weather year. Based on the simulations, climate warming would favor the selection of the 12-leaf variety, Longjing 21, which would produce higher yield and marginal returns than the 11-leaf varieties under all the management strategies evaluated. The 12-leaf variety with a longer growing season and higher yield potential would require higher N rates than the 11-leaf varieties. In summary, under warm weather conditions, all the rice varieties would produce higher yield, and thus require higher rates of N fertilizers. Based on simulation results using the past 20 years of weather data, variety-specific N management was a practical strategy to improve N management and N partial factor productivity compared with farmer practice and regional optimum N management in the study region. The CERES-Rice crop growth model can be a useful tool to help farmers select suitable precision N management strategies to improve N-use efficiency and economic returns.