Data of medicinal plants used to treat small ruminants diseases in Benin

Published: 19-04-2021| Version 1 | DOI: 10.17632/ywfkd494md.1
Esaïe Tchetan,
Abiodoun Pascal Olounlade,
Thierry Dehouegnon Houehanou,
Erick Virgile Bertrand Azando,
Josette Afiavi Kaneho,
Marcel Romuald Benjamin Houinato,
Sylvie Mawule Hounzangbe-Adote,
Joëlle Quetin-Leclercq,
Fernand Ahokonou Gbaguidi


The data presented in this database are related to ethnoveterinary medicine practices on traditional small ruminants farms in Benin (West Africa). They focus on the medicinal plants used and the socioeconomic and environmental factors that influence the level of ethnoveterinary knowledge on these farms. Table 1 provided a complete list of the 101 medicinal plants inventoried, their family, vernacular names, frequency of citation and the Cultural Importance Index (CI). In the other hand, details were provided in Table 2 on recipes used per disease category and how the recipes were prepared, the part of the plant to be used, the route of administration of the recipes, the clinical signs and their vernacular names. Gender, ethnicity, agro-ecological zone and flocks size were the socioeconomic and environmental factors that significantly influenced the level of ethnoveterinary knowledge. Researchers in ethnopharmacology can use the list of inventoried plants to assess the biological activity of less investigated plants and identify the active compounds.


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Ethnoveterinary survey was conducted in 8 municipalities. A semi-structured questionnaire was used and allow to collect data on respondents characteristics, the main plants used to treat small ruminants diseases, the parts used and recipe preparation. Voucher specimens of cited plants were obtained from interviewees and identified at the National Herbarium of Benin, University of Abomey-Calavi. Survey was conducted in 8 poorer municipality and allow to interview 506 respondents. Data were analyzed through calculation of the Cultural Importance Index (CI) and Frequency of Citation (FC). The symptoms cited by the respondents were categorized into 10 disease groups using the second version of International Classification of Primary Care. Socioeconomic and environmental factors affecting ethnoveterinary knowledge level were accessed using classification analysis based on a decision tree [1].