The framework couples the process-based APSIM cropping system model with the SSURGO soils database, Daymet weather data service, land grant university estimates of crop production costs and commodity price estimates, and the R statistics software. The framework is used estimate differences in yield, ROI, NO 3 − leaching, and N 2O emissions corresponding with economic optimum (maximum ROI) and agronomic optimum (maximum yield) inputs. Here a cropping system model framework is used to predict site-specific subfield optimum seeding density and (N) fertilizer application rates based on publicly available data sources. Seeding density and nitrogen (N) fertilizer application rates are two of the most important inputs influencing agronomic, economic and environmental outcomes in cropping systems including yield, return on investment (ROI), and nitrate (NO 3 −) leaching. The challenge for precision agriculture is that these factors interact with one another on a subfield scale. Department of Agronomy, Iowa State University, Ames, IA, United StatesĪ key goal of precision agriculture is to achieve the maximum crop yield while minimizing inputs and loses from cropping systems.
Gabriel McNunn, Emily Heaton, Sotirios Archontoulis, Mark Licht and Andy VanLoocke *
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