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Morphological characterization of Prunus scoparia using multivariate analysis

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Abstract

In this research, morphological characterization of wild Prunus scoparia species, naturally growing in Iran, was investigated. Twenty-one variables along flowering and ripening date were recorded in 150 accessions of this species to detect their phenotypic variation. All studied characteristics were showing a high degree of variability, but it was highly pronounced for secondary shoot number, leaf area and shape, growth habit, fruit exocarp color, nut shape, pubescence on fruit, canopy size and trunk diameter. The majority of significant correlation coefficients were found in the characteristics representing tree and nut sizes with leaf size. Principal component analysis was performed for phenotypical diversity determination and grouping of species. Characters with high discriminating values were those related to tree height, growth habit, canopy size and kernel weight. Based on the UPGMA cluster analysis, accessions were placed in two main clusters. The first main cluster was divided into five subclusters with high variability within and between populations, while the second cluster contained 11 accessions of Estahban region. Current findings supported these opportunities since the phenotypic variability in Iranian wild P. scoparia species has been found to be very high, suggesting an extensive genetic diversity available to almond cultivar and rootstock development programs. The wide adaptation of this species indicates its potential as resources for resistance to abiotic and biotic stresses such as drought and spring frost. The conservation of the highly diverse native populations of Iranian wild P. scoparia species is recommended.

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  1. Department of Horticultural Sciences, Faculty of Agriculture and Natural Resources, Arak University, 38156-8-8349, Arāk, Iran

    Abdollah Khadivi-Khub & Karim Anjam

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  1. Abdollah Khadivi-Khub
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  2. Karim Anjam
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Correspondence to Abdollah Khadivi-Khub.

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Khadivi-Khub, A., Anjam, K. Morphological characterization of Prunus scoparia using multivariate analysis. Plant Syst Evol 300, 1361–1372 (2014). https://doi.org/10.1007/s00606-013-0967-7

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