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Biblioteca Using a Logistic Regression Model to Analyze Alley Farming Adoption Factors in Sierra Leone

Using a Logistic Regression Model to Analyze Alley Farming Adoption Factors in Sierra Leone

Using a Logistic Regression Model to Analyze Alley Farming Adoption Factors in Sierra Leone

Resource information

Date of publication
Dezembro 2016
Resource Language
ISBN / Resource ID
AGRIS:US201600102086
Pages
109-125

Slash-and-burn shifting cultivation is the conventional farming practice in Sierra Leone, where communal land tenure is by far the most common form of land use. Alley farming, the alternative agricultural system, has been introduced as a technical option to increase yield, reduce or eliminate fallow and conserve soil water. This study uses a logistic regression model to determine the factors influencing the adoption of alley farming in Sierra Leone. Data for the study were collected from a total of 160 farmers in 16 farming communities across 4 ecotones in the Freetown Peninsula through a survey, interactive discussion and personal observation. It is found that although most of these communities are aware of alley farming, female farmers are less likely than males to adopt this farming technology. Also membership of farmers’ associations and access to extension services positively influences adoption of alley farming, but limited land availability hinders adoption in the region. Most of the farmers practicing or trying out alley farming prefer this farming system over slash-and-burn shifting cultivation. High demand for fuelwood, short or no fallow periods and replenishment of soil fertility are among the attributes driving farmers to switch to alley farming. Despite its merits, alley farming is not perceived as a complete substitute for slash-and-burn shifting cultivation in the study area. For wider adoption, there is the need to develop demonstration farms to show the feasibility of incorporating farmer-specific biophysical, hydro-climatic and socio-economic conditions into alley farming system in the region.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Conteh, Alhaji M. H.
Moiwo, Juana P.
Yan, Xiangbin

Publisher(s)
Data Provider
Geographical focus