ArticlePloS one2026
Multivariate analysis for agro-morphological and quality traits in groundnut (Arachis hypogaea L.) genotypes in Eastern Ethiopia.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Multivariate analysis of yield, physiological, and biochemical traits in peanut (Frontiers in plant science · 2026Article
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Abstract
Groundnut is an important oil seed crop in Ethiopia, providing food, oil, and industrial products while contributing to soil fertility through nitrogen fixation. However, its production is limited by narrow genetic variability, low-yielding varieties, and environmental stresses, making it essential to assess genetic diversity among existing genotypes for effective breeding and improvement. The present study was carried out to assess the extent of genetic variability among groundnut genotypes for agro-morphological and quality traits. Thirty-six groundnut genotypes were evaluated in a 6 x 6 simple lattice design during 2023 post-rainy season under irrigation at Dire Dawa, the research station of Haramaya university, Ethiopia. Data were collected on kernel yield and other morphological traits, oil content and oil yield. The data on traits were subjected to principal component (PC) analysis, clustering and Euclidean distance. In this study, the first six Principal Components Analysis (PCA) found to be significant and accounted for 74.51% of the total variation in which the first principal component (PC1) and the second principal component (PC2) contributed more to the variation. PC1 and PC2, capturing most of the variation, identify the key traits contributing to genetic diversity, guiding the selection of distinct parents for effective groundnut breeding. Clustering of the genotypes resulted in six major clusters, and the dendrogram showed that cluster I, II, III, IV, V and VI included 6, 9, 8, 5, 7 and 1 genotypes, respectively. The result implies that, genotypes within the same cluster are genetically similar, while those in different clusters are more diverse, providing opportunities to select distinct parents for effective breeding. Euclidean distance ranged from 2.45 to 8.54 with the mean, standard deviation and coefficient of variation of 5.44, 1.17 and 21.56%, respectively. Based on the result of the current study, there were variations of genetic distances among genotypes, Gv17 and Gv28, Gv3 and Gv23, Gv3 and Gv30, Gv15 and Gv17, Gv22 and Gv28, and Gv3 and Gv34 which could be exploited through hybridization for cultivar development in groundnut breeding programs in Ethiopia. Therefore, the genetically divergent genotypes identified in this study provide valuable parental material for hybridization, offering strong potential for the development of improved groundnut varieties adapted to Ethiopian agro-ecologies.
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