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Crop growth model: Optimal Application of Nitrogen Fertilizer in Corn for Economic Returns and Environmental Sustainability

Abstract. Even with the rapid advancement in environmental and crop sensing and transmission of data, crop growth models could fill the analytical gap to enable real-time decision-making for improved profitability and environmental sustainability. An example of a complex management situation needing improved predictions is nitrogen rate and timing for corn (Zea mays L.). Most of the existing decision support tools for N recommendation focus on yield response but fail to embrace biocomplexity and seek to predict systems with low predictability. Our approach seeks to manage the complexity by considering the effect of past and present weather and soil states, and the impact of the N application on the environment in a multi-year scale. To this end, the objective of this research is to compare N management strategies in corn fields using the crop growth model, Agricultural Production System sIMulator (APSIM), and shed light on yield and environmental footprint, using the genetic, environmental, and management information, to manage system complexity. Eleven different N management strategies were evaluated using the environmental and economic indicators. This study provides estimates of yield, N2O emissions, and N leaching based on the different rates and timings of N application. It was found that the amount of nitrogen applied with-in the season and its interaction with the rainfall had a significant impact on the corn yield, N2O emissions, and N leaching. But splitting the amount of N application at different timings did not have a significant impact on either the economic or the environmental variables. Furthermore, the amount of N leached or N2O emitted had a significant impact on corn yield. Although this study was simulated on a field-scale, it could be extrapolated to regional, state, or country-level to help policymakers and stakeholders select the best strategies for improving yield and reducing the negative footprint of fertilizer application.

Citation:  2023 ASABE Annual International Meeting  2300421.(doi:10.13031/aim.202300421)