However, in a minority of cases NO 3 РІв‚¬вЂ™ leaching was greater at the economic optimum, indicating that managing to maximize ROI rather than yield may not always reduce environmental impacts.

A site-specific application of the framework comparing economic optimum seeding density and N-fertilizer rates with agronomic optimum values estimated an average ROI benefit of 7.2% as well as an average NO 3 РІв‚¬вЂ™ leaching and N 2O emissions reductions of 2.5 and 7.6 kg ha РІв‚¬вЂ™1, respectively. Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field and had an r 2 = 0.65 and a root mean square error of 1645.0 kg ha РІв‚¬вЂ™1. Framework performance was evaluated using multiple years of precision yield monitor data obtained from a conventionally managed continuous maize ( Zea mays L.) cropping system field located in north central Iowa on which varying N-fertilizer rates were applied.

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 РІв‚¬вЂ™ 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 РІв‚¬вЂ™) 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 StatesР”Р„ 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 *

Apsim input files