Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)

Department / School

Agronomy, Horticulture, and Plant Science

First Advisor

Ali Mirzakhani Nafchi


This study conducted in 2023 aimed to enhance nitrogen use efficiency (NUE) in wheat and corn grown in South Dakota. Based on dynamic weather conditions and other factor interactions, conventional nitrogen (N) recommendations need to be improved. Soil properties information, including electrical conductivity, was used to create management zones. In each zone, three N-rich spots were established as biosensors. Drones and satellites collected imagery data, and an AI-driven approach assessed the crop response to applied N. A dynamic N application approach, integrating aerial data with historical records, was developed and evaluated. Our methodology, at a 95% confidence level, resulted in a 12.4% higher yield in wheat and a potential 4.77% increase in corn yield compared to conventional approaches, with a 16.2% and 10% reduction in N application in wheat and corn fields, respectively. This led to cost savings and environmental benefits. The financial outcomes revealed cost savings of $7.87 per acre in wheat and $3.62 per acre in corn. The wheat yield increased to 75.09 bu/ac compared to 66.61 bu/ac in control plots, generating an additional revenue of $57.82 per acre. The corn yield increased to 173.75 bu/ac compared to 165.84 bu/ac, indicating a potential increase of 6.89 bu/ac and additional revenue of approximately $34.11 per acre. Moreover, there was a 16.2% increase in NUE in wheat and a 4.3% improvement in corn compared to traditional methods. The findings from this study will be applicable for farmers as a decision-making tool, providing a straightforward approach to enhance NUE while increasing their farm profit.

Library of Congress Subject Headings

Nitrogen in agriculture.
Nitrogen in agriculture -- Remote sensing.
Crops and nitrogen.
Nitrogen fertilizers.
Wheat -- Yields -- South Dakota.
Corn -- Yields -- South Dakota.
Plants -- Effect of nitrogen on.
Artificial intelligence -- Agricultural applications.



Rights Statement

In Copyright