Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/281163 
Year of Publication: 
2024
Citation: 
[Journal:] NJAS: Impact in Agricultural and Life Sciences [ISSN:] 2768-5241 [Volume:] 96 [Issue:] 1 [Article No.:] 2287476 [Publisher:] Taylor & Francis [Place:] London [Year:] 2024
Publisher: 
Taylor & Francis, London
Abstract: 
This study aims to contribute to the understanding of diversity within the context of banana farming and its implications for the management of banana Xanthomonas wilt (BXW) disease in Rwanda. We used a structured questionnaire to collect data from 690 banana farmers in eight districts, representing various agroecological zones, across Rwanda. We implemented principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the data leading to the delineation of three distinct groups of banana farmers, namely: 1) Beer banana farmers (39.1%), 2) Livestock-based farmers (31.7%), and 3) Cooking banana farmers (29.1%). These farm types exhibit apparent differences in their main farming objectives and adoption of BXW management practices. Cooking banana farmers prioritize BXW prevention over control, whereas beer banana farmers exhibit the opposite trend. Livestock-based farmers show no significant difference in practices in comparison to cooking banana farmers. Beer banana farmers predominantly adopt the officially recommended complete mat uprooting (CMU) approach for disease control, while cooking banana farmers adopt the single diseased stem removal (SDSR) method. These findings provide insights for designing customized and targeted interventions to address BXW management effectively, based on farmer typology.
Subjects: 
agricultural innovation systems
farm types
crop disease management
principal component analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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