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Xia Qiu, Haonan Zhang, Huiyi Zhang, Changwen Duan, Bo Xiong, and Zhihui Wang

cultivars and analyze the correlation between textural characteristics and basic physicochemical indicators. Furthermore, we used cluster analysis to classify different plum cultivars according to their textural characteristics and combined this with

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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

Open access

Ariana Torres

values on attributes for fresh produce. This study also contributes to the literature by providing the main factors driving young consumers to be part of each market segment. First, a two-stage cluster analysis process provided four distinct segments of

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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.

Open access

Xiuli Lv, Yuan Guan, Jian Wang, Yanwei Zhou, Qunlu Liu, and Zequn Yu

values of N e , H , and I are in bold type. Cluster analysis. The genetic similarity coefficient of the 28 accessions ranged from 0.4372 to 0.9765, with an average of 0.5767. The coefficient between most accessions was less than 0

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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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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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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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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

Open access

Catherine G. Campbell, Jorge Ruiz-Menjivar, and Alia DeLong

, NY) to calculate descriptive statistics. We performed a cluster analysis to identify salient groups (or clusters) of urban growers in Florida. In the absence of class labels, clustering is a useful machine learning tool that allows for the