Document Type
Article
Publication Date
7-2023
Abstract
Precision agriculture (PA) has been defined as a “management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” This definition suggests that because PA should simultaneously increase food production and reduce the environmental footprint, the barriers to adoption of PA should be explored. These barriers include: 1) the financial constraints associated with adopting DSS, 2) the hesitancy of farmers to change from their trusted advisor to a computer program often behaves as a black box, 3) questions about data ownership and privacy, and 4) the lack of a trained workforce to provide the necessary training to implement DSSs on individual farms. This paper also discusses the lessons learned from successful and unsuccessful efforts to implement DSSs, the importance of communication with end-users during DSS development, and potential career opportunities that DSSs are creating in PA.
Publication Title
Agronomy Journal
DOI of Published Version
10.1002/agj2.21432
Rights
Copyright © 2023 the Author(s)
Recommended Citation
Brugler, Skye; Gardezi, Maaz; Dadkhah, Ali; Rizzo, Donna M.; Zia, Asim; and Clay, Sharon A., "Improving Decision Support Systems with Machine Learning: Identifying Barriers to Adoption" (2023). Agronomy, Horticulture and Plant Science Faculty Publications. 406.
https://openprairie.sdstate.edu/plant_faculty_pubs/406
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.