Journal
GENETIC RESOURCES AND CROP EVOLUTION
Volume 59, Issue 5, Pages 909-926Publisher
SPRINGER
DOI: 10.1007/s10722-011-9733-2
Keywords
Cerasus; Correlation coefficients; Genetic resources; Native population; Principal component analysis; Prunus; Wild species
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Knowledge of relationships among the cultivated and wild species of a subgenus of L., is important for recognizing gene pools, identifying pitfalls in germplasm collections and developing effective conservation and management strategies. In this study, morphological characterization of wild subgenus species naturally growing in Iran, including L. (mazzard), L., Boiss., Pall., Mozaff., Boiss. subsp. , Boiss. subsp. and Pojark. and three commercial species, sweet cherry ( L.), sour cherry ( L.) and duke cherry ( x Rehd.) was investigated. Twenty-nine variables were recorded in 95 accessions of these species to detect similarities among them. All studied characteristics were showing a high degree of variability, but it was highly pronounced for plant height, leaf characters especially for dimensions and pubescence as well as for petiole and peduncle length. The majority of significant correlation coefficients were found in the characteristics representing plant size and growth habit 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 growth habit, height, compactness, trunk diameter, leaf dimensions, petiole length, leaf tip and serration, flower color, peduncle length, fruit shape and stone shape. Based on the cluster analysis, species included in two main clusters, first those with large structure (sweet, sour and duke cherries, mazzard and mahaleb), second the other species with small structure which might be potentially suitable for rootstock breeding programs. Scatter plot using two first factors also confirmed the grouping by cluster analysis. The conservation of the highly diverse native populations of Iranian wild species is recommended.
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