ArticlePloS one2019
Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Mixed-scale multivariate analysis reveals phenotypic structure in wood apple (Feronia limonia L.).Scientific reports · 2026Article
- Beyond efficiency: The multi-scale architecture of robust water transport in plants.Quantitative plant biology · 2026Review
- Patterns of Leaf and Fruit Morphological Variation in Marginal Populations ofPlants (Basel, Switzerland) · 2024Article
- Main Habitat Factors Driving the Phenotypic Diversity ofPlants (Basel, Switzerland) · 2023Article
- The Euscaphis japonica genome and the evolution of malvids.The Plant journal : for cell and molecular biology · 2021Article
- Genome-Wide Identification and Co-Expression Analysis ofFrontiers in genetics · 2021Article
- Genetic diversity and population structure ofPeerJ · 2021Article
- Phenotypic variation, functional traits repeatability and core collection inference in Synsepalum dulcificum (Schumach & Thonn.) Daniell reveals the Dahomey Gap as a centre of diversity.Scientific reports · 2020Article
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6 authors.
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Abstract
Fruit traits affect population genetic diversity by affecting seed protection and dispersal strategies, thereby comprising important components of phenotypic variation. Understanding of the phenotypic variation is an indispensable first step for developing breeding strategies. However, little information is known about the genetic variation in E. japonica-a monotypic species with abundant phenotypes that is mainly distributed in southern China. In this study, we evaluated the phenotypic diversity of 67 E. japonica using 23 phenotypic traits. Our results showed that the Shannon-Wiener (I) index of qualitative traits ranged from 0.55 to 1.26, and the color traits had a relatively high I. The average coefficient of variation of compound leaf traits (14.74%) was higher than that of fruit and seed traits (12.77% and 11.47%, respectively). Principal component analysis also showed that compound leaf and fruit traits were important components of total variation. Furthermore, correlation analysis revealed a significant difference in elevation and fruit color, irregular ribs, leaf margin and texture. The F value within populations was smaller than among populations, indicating the variation in phenotypic traits among populations was much greater than within populations. Dehua and Zunyi populations had the highest coefficients of variation, whereas Wenzhou population had the smallest-which may be attributed to habitat destruction. According to Q-type clustering, 67 samples clustered into four groups, with those having similar phenotypes clustering into the same group. In general, leaf and fruit traits had abundant phenotypic diversity, representing the main sources of phenotypic variation. Combined with clustering results and field surveys, this study suggests that the phenotypes of E. japonica are classified into two main categories: The deciduous E. japonica present at high altitudes; and the evergreen E. japonica present at low altitudes. Excavating E. japonica variations provides a theoretical reference for its classification and diversity, and is of great significance for planning genetic resources and establishing conservation strategies.
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