In the quest to enhance agricultural productivity and sustainability, researchers have been honing the capabilities of crop simulation models to better predict how different management practices and environmental conditions affect crop growth and yield. A recent study published in *Frontiers in Agronomy* has evaluated the performance of the Agricultural Production Systems sIMulator Next Generation (APSIM-NG) in simulating winter wheat growth, yield response to nitrogen (N), and nitrogen dynamics. The findings offer promising insights for farmers and agronomists looking to optimize nitrogen management and adapt to climate variability.
The study, led by Jose G. C. P. Pinto from the Department of Agronomy and Horticulture at the University of Nebraska-Lincoln, focused on calibrating and validating APSIM-NG using field experiments conducted over two growing seasons (2020/21 and 2021/22) in Nebraska. The experiments involved two winter wheat cultivars, LCS and WB, subjected to four different nitrogen rates (0, 56, 112, and 168 kg N ha⁻¹). The researchers collected a comprehensive set of data, including phenology, grain yield, protein content, shoot biomass, carbon-to-nitrogen ratio, soil nitrate and ammonium levels, soil moisture, and weather variables.
The calibration process targeted cultivar-specific phenology, biomass, yield, and protein content, which significantly improved the model’s performance. “Calibration improved model performance, with well to moderate accuracy for phenology, grain yield, protein content, and grain N uptake,” Pinto explained. The model demonstrated good to moderate accuracy in simulating phenology (RRMSE = 2.1–2.2%; RMSE = 3–5 days), grain yield (15–24%), protein content (8–11%), and grain N uptake (11–13%).
Validation of the model was conducted using grain yield data from 29 site-year combinations across five Nebraska counties spanning six growing seasons (2017–2022). The results showed good performance for grain yield in both cultivars (RRMSE = 14% for LCS and 19% for WB). The model also effectively simulated the yield response to nitrogen for LCS (RRMSE = 18% at the economic optimum N rate) and moderately for WB (32%).
The implications of this research are significant for the agriculture sector. Accurate simulation of crop growth and yield response to nitrogen can help farmers make informed decisions about nitrogen application rates, optimizing nitrogen use efficiency and reducing environmental impacts. “These results highlight the model’s utility for evaluating N management strategies and supporting climate-smart decision-making aimed at improving nitrogen use efficiency and adaptation to climate variability in wheat systems,” Pinto noted.
The study also underscores the importance of accurate calibration and validation in ensuring the reliability of crop simulation models. As climate variability and the need for sustainable agriculture practices continue to challenge farmers, tools like APSIM-NG can play a crucial role in developing climate-smart agronomy strategies. By providing reliable predictions of crop growth and yield under diverse environmental and management conditions, these models can support farmers in enhancing productivity and resilience.
The research published in *Frontiers in Agronomy* by Pinto and colleagues represents a step forward in the application of crop simulation models for improving nitrogen management in winter wheat production. As the agricultural sector continues to evolve, the integration of advanced modeling techniques with field data will be essential in shaping the future of sustainable and productive farming practices.