Understanding Resilience of Agricultural Systems: A Systematic Literature Review
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Boahen, Samuel (1,2); Oviroh, Peter Ozaveshe (2,3); Austin-Breneman, Jesse (2); Miyingo, Emmanuel W. (2,4); Papalambros, Panos Y. (2)
Series: ICED
Institution: 1: Department of Mechanical Engineering, Kwame Nkrumah University of Science and Technology, PMB, Kumasi, Ghana;
2: Department of Mechanical Engineering, University of Michigan, Ann Arbor, USA;
3: Department of Mechanical Engineering Science, University of Johannesburg, South Africa;
4: Department of Electrical and Computer Engineering, Makerere University, Kampala, Uganda
Section: Design Methods
Page(s): 3701-3710
DOI number: https://doi.org/10.1017/pds.2023.371
ISBN: -
ISSN: -
Abstract
Resilience is a widely studied concept that is a key objective in the design and development of sustainable systems. This is especially true for the agricultural systems critical to food production, economic viability, and sustainability of our communities, as farmers seek to meet increasing demand in the face of shocks such as climate change and natural disasters. Although there is a rich body of work examining resilience, there is limited understanding of how the concept of resilience should be tailored for agricultural systems. This study seeks to address this gap by performing a systematic literature review of 50 papers selected from SCOPUS using the PRISMA protocol. A summary of research topics and characteristics by geographical region is presented. The paper also categorizes the types of shocks studied and the corresponding response methods. Results suggest that the focus of resilience research changes by region, which may indicate that design strategies and objectives should also differ by region. Furthermore, the work identifies a need for more simulation-based quantitative research into the impact of resilience.
Keywords: Resilience, Agricultural Systems, Sustainability, Robust design, Simulation