Date of Graduation

8-2025

Document Type

Thesis

Degree Name

Master of Science in Biological Engineering (MSBE)

Degree Level

Graduate

Department

Biological and Agricultural Engineering

Advisor/Mentor

Matlock, Marty

Committee Member

Thoma, Greg

Second Committee Member

Muenich, Rebecca

Keywords

APEX; Corn; Crop Modeling; Crop Production Data; Life Cycle Analysis; Maize

Abstract

Corn (Zea mays) is an important crop grown across the US for many uses such as grain for animal feed, bio-ethanol production, food products, and industrial products. Corn is produced in almost every state in the US, but most corn production is concentrated in the Corn Belt Region including Iowa, Illinois, Ohio, Indiana, Minnesota, and Nebraska. Although technologies and production practices are improving corn production efficiency primarily through increased yields (improved land use), corn production at this scale greatly impacts the environment through emissions from fertilizer and pesticide runoff and leaching, soil degradation due to improper field practices, as well as greenhouse gas (GHG) emissions associated with pumping large amounts of water for irrigation. Since the 1990’s, LCA has become a valuable tool for providing an overall framework for quantifying sustainability characteristics of agricultural production and consumption patterns. Crop production simulation models such as APEX have been increasingly used to analyze the impact of agricultural management at the field and watershed-level. Average regional and state-level corn production practices vary. Existing models of corn production in the United States do not account for differences in soil type and climate condition. Because production practices vary across the US, a framework for this project was developed to differentiate between production practices and include climate (precipitation, minimum and maximum temperature) and soil type. This framework included modeling county-level corn production using the APEX model and integrating results from APEX and other data into the LCA models to assess environmental impacts, such as global warming potential. When used in combination with LCA, the crop production model provides LCI across a variety of production practices and regions, allowing us to estimate potential regional environmental impacts of crop production more accurately. The body of work discussed in this article is an overview of the modeling process for a much broader research project performing a Life Cycle Assessment of the production of corn in the United States (Thoma et al., 2018). The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate 90% of the US corn production by using 73 different archetypical farm models from the top 15 corn producing states. We created lifecycle inventory data sets based on county-level survey data, state budgets, and model simulation data. We succeeded in calibrating 98% of our models to within our desired accuracy. During the calibration portion of this process, it was determined that the denitrification subprogram within APEX led to ammonia loss values that were higher than expected and nitrogen dioxide emissions that were lower than expected given the model inputs. The LCA developed from this modeling effort provides a basis for regional comparisons of corn production.

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