Phenotypic Variation Analysis of Sweet Potato Germplasm Resources from Different Agro-climate Zones in the World
Journal Title: Journal of Experimental Agriculture International - Year 2016, Vol 13, Issue 6
Abstract
The objectives of this research were to study the phenotypic diversity of sweet potato germplasm collections using 16 agro-morphological traits. A field experiment was done with 123 cultivated varieties of sweet potato. The varieties were grown at the research farm of Hubei Academy of Agricultural Sciences, Jiangxia District, Wuhan, China in the year 2015. They were evaluated in a randomized complete-block design with three replications. Estimates of phenotypic variation found immature leaf color, mature leaf color, predominant color of vine and petiole pigmentation were in high similarity, whereas other traits demonstrated more genetic variation. The coefficient of variance in yield and dry matter content was 54.74% and 13.98%, respectively, this indicated that yield and dry matter content was liable to have environmental influences. Person correlation analysis was conducted to illustrate the interrelationships among the traits, the results showed that base of leaf vien pigmentation had highest correlation (r=0.848) with predominant color of leaf vien. Base of leaf vien pigmentation, base of petiole pigmentation and predominant color of leaf vien had significant positive correlations with yield. Number of central leaf lobes and immature leaf color had negative impacts on dry matter content. Principal component analysis extracted five principal components, contributed 66.05% of the total variability. The hierarchical cluster analysis based on five extracted principal components resulted in a dendrogram which was discordant with geographic origin. The sweet potato varieties in this study showed a high level of phenotypic diversity. This study could provide a reference for future research and have elucidated the phenotypic diversity that existed in sweet potato.
Authors and Affiliations
Wenjin Su, Yi Liu, Jian Lei, Lianjun Wang, Shasha Chai, Chunhai Jiao, Xinsun Yang
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