Using a Crop Modeling Framework for Precision Cost-Benefit Analysis of Variable Seeding and Nitrogen Application Rates

Thumbnail Image
Date
2019-12-01
Authors
McNunn, Gabriel
Archontoulis, Sotirios
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Person
Licht, Mark
Associate Professor
Person
Heaton, Emily
Affiliate Professor
Person
VanLoocke, Andy
Associate Professor
Research Projects
Organizational Units
Organizational Unit
Agronomy

The Department of Agronomy seeks to teach the study of the farm-field, its crops, and its science and management. It originally consisted of three sub-departments to do this: Soils, Farm-Crops, and Agricultural Engineering (which became its own department in 1907). Today, the department teaches crop sciences and breeding, soil sciences, meteorology, agroecology, and biotechnology.

History
The Department of Agronomy was formed in 1902. From 1917 to 1935 it was known as the Department of Farm Crops and Soils.

Dates of Existence
1902–present

Historical Names

  • Department of Farm Crops and Soils (1917–1935)

Related Units

Journal Issue
Is Version Of
Versions
Series
Department
Abstract

A key goal of precision agriculture is to achieve the maximum crop yield while minimizing inputs and loses from cropping systems. The challenge for precision agriculture is that these factors interact with one another on a subfield scale. 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 (NO3−) leaching. 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. The framework is used estimate differences in yield, ROI, NO3− leaching, and N2O emissions corresponding with economic optimum (maximum ROI) and agronomic optimum (maximum yield) inputs. 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. 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. Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field and had an r2 = 0.65 and a root mean square error of 1645.0 kg ha−1. 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 NO3− leaching and N2O emissions reductions of 2.5 and 7.6 kg ha−1, respectively. However, in a minority of cases NO3− leaching was greater at the economic optimum, indicating that managing to maximize ROI rather than yield may not always reduce environmental impacts. Our results suggest that managing cropping systems for the economic optimum is plausible using publicly available data with our framework and will likely lead to improved environmental outcomes.

Comments

This article is published as McNunn G, Heaton E, Archontoulis S, Licht M and VanLoocke A (2019) Using a Crop Modeling Framework for Precision Cost-Benefit Analysis of Variable Seeding and Nitrogen Application Rates. Front. Sustain. Food Syst. 3:108. doi: 10.3389/fsufs.2019.00108.

Description
Keywords
Citation
DOI
Copyright
Tue Jan 01 00:00:00 UTC 2019
Collections