Improving decision support systems with machine learning: Identifying barriers to adoption

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外文摘要: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 decision support system (DSS); (2) the hesitancy of farmers to change from their trusted advisor to a computer program that 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.
作者:Gardezi, Maaz;Brugler, Skye;Dadkhah, Ali;Rizzo, Donna M M;Zia, Asim;Clay, Sharon A A
作者单位:Virginia Tech;Univ Vermont;South Dakota State Univ
期刊名称:AGRONOMY JOURNAL
期刊影响因子:0.0
出版年份:2024
出版刊次:116(3)
原文传递申请:江苏省科技资源(工程技术文献)统筹服务平台

  1. 编译服务:智慧农业
  2. 编译者:虞德容
  3. 编译时间:2025-01-20