JOURNAL ARTICLE
Mozambican Languages and their Role in Indigenous Ecological Knowledge Preservation: The Case of Medicinal Plants in Anyungwe Community.
Published In: Journal of Humanities & Social Sciences (JHSS), 2025, v. 14, n. 2. P. 100 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: da Câmara, Crisófia Langa; Lusekelo, Amani 3 of 3
Abstract
Since language is accredited for the preservation and transference of indigenous ecological knowledge (IEK) across generations, this paper presents the findings about the correlation between languages and indigenous knowledge system of the Anyungwe community. Specifically, the paper presents the outcome of the investigation of medicinal plants used by the Anyungwe in Tete Province in Mozambique. The data comes from the Marara area in the Cinyungwe speaking village in Tete Province. Images of medicinal plants were photographed in Tete Province by a research assistant, and their uses were explained by three elders living in Kachembe. Our findings illustrate that IEK studies must consider the language factor because both language and IEK are culturally bound. The paper follows the hypothesis that, similar to what happens in other Bantu languages, the Anyungwe employs both linguistic resources and the physical and natural environment in assigning plant names. Plants like mulambe [Adansonia digitata], mulengera [Moringa oleifera], and musawu [Zizyphus mauritiana], for instance, have always been used as a cure for diseases like blood pressure, diabetes and anaemia. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Humanities & Social Sciences (JHSS). 2025/07, Vol. 14, Issue 2, p100
- Document Type:Article
- Subject Area:Anthropology
- Publication Date:2025
- ISSN:1821-7427
- Accession Number:191126684
- Copyright Statement:Copyright of Journal of Humanities & Social Sciences (JHSS) is the property of Dar es Salaam University College of Education (DUCE) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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