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Farmers’ indigenous knowledge in the management of coffee berry disease caused by Colletotrichum kahawae and its status assessment

Bibliographic Data

ID19226445
AuthorsGerema Amente (0000-0001-6076-2291, Addis Ababa Science and Technology University, corresponding author), Diriba Muleta (0000-0003-1977-245X, Addis Ababa Science and Technology University), Fekadu Gadissa (0000-0002-8666-6086, Madda Walabu University), Dagmawit Chombe (0000-0003-4872-0069, Addis Ababa Science and Technology University), Kibrom B Abreha (0000-0001-8084-8340, Swedish University of Agricultural Sciences), Cecilia Hammenhag (0000-0003-1354-1909, Swedish University of Agricultural Sciences), Kassahun Tesfaye (0000-0002-4046-4657, Addis Ababa Science and Technology University), Mulatu Geleta (0000-0002-2293-1178, Swedish University of Agricultural Sciences, corresponding author)
Year2026
Volume22
Issue1
Publication date2026-05-31
Open AccessYes
TypeARTICLE
VenueJournal of Ethnobiology and Ethnomedicine (JOURNAL)
Journal identifiersISSN: 1746-4269 • E-ISSN: 1746-4269
PublisherBioMed Central (PUBLISHER • GB)
DOI10.1186/s13002-026-00911-7
PMID42219505
OpenAlexW7162957875
LanguageEN
References cited28

BACKGROUND: Coffee berry disease (CBD), caused by Colletotrichum kahawae, is a major constraint to Coffea arabica production in Ethiopia, where coffee is crucial for livelihoods and national income. However, farmers' indigenous knowledge and local disease management practices remain underexplored. This study aimed to document farmers' knowledge of CBD detection and control and to assess disease incidence and severity across forest and semi-forest coffee systems along altitudinal gradients. METHODS: A mixed-methods design was used, including structured household surveys of 90 experienced farmers across nine sites, focus group discussions (FGDs), key informant interviews (KIIs), and field assessments using berry count and visual scoring. Qualitative data were analysed thematically, while quantitative data on CBD incidence and severity were analysed using one-way ANOVA with Tukey's HSD test (p < 0.05) in R (v4.5.3). Boxplots were used to compare variation across systems. RESULTS: Nearly all farmers accurately identified early CBD symptoms through visual observation and relied heavily on indigenous knowledge for management. Common practices included pruning, sanitation (removal of infected parts), and selection of locally preferred coffee types. Farmers also reported selecting genotypes perceived as resistant based on berry traits, indicating informal farmer-led selection. However, these practices showed limited effectiveness in controlling disease spread. FGDs identified climate variability, dense canopy management, and weak institutional support as key drivers of CBD intensification. KIIs revealed gaps in access to resistant varieties, weak extension services, and limited integration of farmer selection criteria into formal breeding. Significant differences in CBD incidence and severity were observed across sites and production systems (p < 0.05), with forest systems showing higher severity and variability than semi-forest systems. CONCLUSIONS: Indigenous knowledge plays a vital role in early CBD detection and local adaptation strategies. However, current farmer practices alone are insufficient for effective control. Integrated approaches combining local knowledge, resistant varieties, improved agronomic practices, and strengthened extension services are essential for sustainable CBD management and conservation of Ethiopia's Arabica coffee genetic resources

Berry · Biodiversity · Coffea arabica · Focus group · Incidence (geometry) · Indigenous · Sanitation · Traditional knowledge · Cocoa and Sweet Potato Agronomy · Coffee research and impacts · Plant Pathogens and Fungal Diseases

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