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

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.

Automated summary

Farm typologies are frequently used in sub-Saharan Africa to simplify the classification of diverse farming systems. They can be utilized in various ways, such as designing efficient sampling schemes, targeting interventions to specific farm types, or providing contextual information. However, the process of constructing farm typologies involves subjective decisions that may not be immediately evident. A generalized framework has been developed to address this issue and quantify the impact of subjective decisions on the resulting typologies. The framework is accessible through the open-source RShiny App: TypologyGenerator, allowing users to focus on decision-making rather than implementation details.