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Ruby Valdez-Ojeda, José Luis Hernández-Stefanoni, Margarita Aguilar-Espinosa, Renata Rivera-Madrid, Rodomiro Ortiz and Carlos F. Quiros

of morphological data. A cluster analysis was performed to group the individuals from both studied sites according to similar morphological traits based on different quantitative and qualitative descriptors of the capsule, flower, and seed. To form

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Alireza Talaie* and Rasoul Akrami

The objective of this study was the identification of existing olive trees in eight regions of Kermanshah province and investigation of their fruit, seed, and leaf characteristics in order to be used in the olive production industry of Iran. The germination ability of olive seed in field and nursery were also studied. In this research, 61 genotypes were identified and their characteristics were studied. It was found out that the present genotypes of Kermanshah showed different vegetative and reproductive growth based on the climatic and topographic conditions. This was verified by cluster analysis of the genotypes of different regions, which showed clearly their far and close relations. It was found out that some of the genotypes in the region spite of their appearance differences have same origin and most probably should be considered as the same genotype. The results also showed that favorable seed bed, planting depth and scarification of the seeds have positive effects on their germination while scarification of the seeds without other treatments had no significant effect on the seed germination.

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Benard Yada, Phinehas Tukamuhabwa, Bramwell Wanjala, Dong-Jin Kim, Robert A. Skilton, Agnes Alajo and Robert O.M. Mwanga

among all pairs of individuals were calculated using the Nei and Li coefficient ( Nei and Li, 1979 ). The distance matrix was then subjected to cluster analysis using the unweighted pair group method using arithmetic averages (UPGMA) algorithm of NTSYS

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Xinyi Zhang, Li Liao, Zhiyong Wang, Changjun Bai and Jianxiu Liu

fit between the cluster analysis and the original distance matrix for three data sets (ISSR, SRAP, and ISSR + SRAP). Results Polymorphism analysis. Twenty-five ISSR primers amplified 283 scorable bands, with an average of 11.32 amplified fragments per

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Joseph Monson and Denise Mainville

respect to farm characteristics, production techniques, marketing strategies, and producer socioeconomic characteristics. Groups of berry producers were characterized using cluster analysis of the survey data. Three types of producers were identified: the

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Zhiyi Bao, Bo Chen and Hua Zhang

autumn; 2) characterize phenotypic diversity among these accessions using cluster analysis; and 3) select some accessions with good characters to use in the landscape. Materials and Methods Seedlings were collected from Liuyang City, Hunan Province

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Ryan W. Dickson, Paul R. Fisher, Sonali R. Padhye and William R. Argo

height and yield to compare soybean ( Glycine max L.) cultivars grown in calcareous vs. noncalcareous soils. Gao and Shi (2007) used hierarchical cluster analysis to group peanut ( Arachis hypogaea L.) cultivars by sensitivity to iron chlorosis based

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Mostafa Farajpour, Mohsen Ebrahimi, Amin Baghizadeh and Mostafa Aalifar

chief components. The cluster analysis was performed using the seven identified main compounds. From this analysis, the Iranian A. millefolium accessions were categorized into five groups ( Fig. 1 ). The first group contained of ten accessions (Am25

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Eugene K. Blythe and Donald J. Merhaut

further examination and comparison of container substrates. Two such exploratory multivariate methods that require no distributional assumptions are principal components analysis (PCA) and cluster analysis (CLA). PCA, which reduces the dimensionality of

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Mengmeng Zhang, He Huang, Qing Wang and Silan Dai

., 2012 ). Compared with molecular markers and other methods, morphological markers are easier to observe and obtain. In chrysanthemum, previous studies that used the cluster analysis method based on morphological markers were considerably restricted to