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Construction of a generalised farm typology to aid selection, targeting and scaling of onfarm research.

Authors :
Hassall, Kirsty L.
Baudron, Frédéric
MacLaren, Chloe
Cairns, Jill E.
Ndhlela, Thokozile
McGrath, Steve P.
Nyagumbo, Isaiah
Haefele, Stephan M.
Source :
Computers & Electronics in Agriculture. Sep2023, Vol. 212, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• Defining typologies is an efficient way to capture diversity in farming systems. • Usually, such typologies only include equally weighted continuous variables. • Methods can be extended to include weighted and categorical variables. • Typologies defined in such a way show greater diversity in measured outcomes. • An R-shiny app has been developed to enable easy uptake of the proposed method. Farm typologies are often used to reduce the complexity in categorising diverse farming systems, particularly in sub-Saharan Africa. The resulting typologies can then be used in multiple ways including designing efficient sampling schemes that capture the diversity in smallholder farms, prescribing the selection of certain farm types to which interventions can be targeted or upscaled, or to give context into derived relationships. However, the construction of farm typologies consists of many subjective decisions that are not always obvious or evident to the end-user. By developing a generalized framework for constructing farm typologies, we clarify where these subjective decisions are and quantify the impact they have on the resulting typologies. Further, this framework has been encapsulated in the open source RShiny App: TypologyGenerator to enable users to focus on the decisions and not the underlying implementation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681699
Volume :
212
Database :
Academic Search Index
Journal :
Computers & Electronics in Agriculture
Publication Type :
Academic Journal
Accession number :
171365796
Full Text :
https://doi.org/10.1016/j.compag.2023.108074