Masters Theses

Date of Award

5-2016

Degree Type

Thesis

Degree Name

Master of Science

Major

Agricultural Economics

Major Professor

Margarita Velandia

Committee Members

Dayton M. Lambert, James A. Larson, Chris N. Boyer

Abstract

Precision agriculture (PA) technologies allow producers to obtain information about their fields and use this knowledge to apply inputs and manage time more efficiently. PA technologies such as Automatic-Section Control (ASC) reduce inefficiencies such as overlapping application of inputs (e.g., seed, chemicals). Additionally, technologies such as Auto-Guidance (AG) systems complement ASC technologies and allow producers to work longer hours by reducing fatigue. Both ASC and AG technologies appear to be quickly adopted by producers because of their relatively low cost compared to other precision farming technologies.

The objective of this study is to determine the factors influencing the adoption of Automatic Section Control (ASC) technologies and GPS Auto-guidance (AG) systems among cotton producers. Using data from a survey of cotton producers in 14 states, this study evaluates the effect of age, education, farm size, use of information sources, and the use of specific production practices on the adoption decisions. Additionally, various field shape measures created using data from the NASS Crop Data Layer are included in the ASC equation to evaluate the influence of field shape on ASC adoption.

Results suggest that younger, more educated producers, managing larger farming operations, and consulting farm dealers for information about PA technologies are more likely to adopt ASC and AG technologies. The influence of field shape on the adoption of ASC technologies is inconclusive.

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