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conducted by using module DCENTER and EIGEN of NTSYSpc ( Gower, 1996 ). This multivariate approach was chosen to complement the cluster analysis information; because cluster analysis is more sensitive to closely related individuals, the PCO is more

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

variables in hierarchical cluster analysis, we classified the fragrance patterns of herbaceous peony cultivars for the first time by combining these results with the identification of the main aromatic compounds and the results of sensory evaluation. This

Windows, v 9.4; SAS Institute Inc., Cary, NC). Last, investigators performed a k-means cluster analysis using the FASTCLUS procedure of SAS software. Cluster analysis has been widely used to define consumer segments based on their preferences and attitudes

overall and by cluster derived from responses by participants to a conjoint analysis of floral characteristics and price of Ratibida columnifera. z There were some differences among the clusters with regard to preference. All clusters ranked petal

Pine and Gilmore (2011) . We conducted an agglomerative cluster analysis in SPSS (Version 25; Chicago, IL) k -means clustering procedure, saving cluster membership for comparisons and mean testing using the demographic characteristics and the other

Jaccard (1908) . This data set was used as input for cluster analysis using the UPGMA to generate a dendrogram using PAST Version 1.92 software ( Hammer et al., 2001 ). Correlation coefficients between the combined data with morphological data and between

with a weak signal or blurred appearance were not considered. Data analysis. Genetic population structure was investigated using the Bayesian clustering model implemented in STRUCTURE 2.3.3 ( Pritchard et al., 2000 ). The software was run without a

Univ., Clemson, S.C.) for assistance with the cluster analysis. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations, this paper therefore must be hereby marked advertisement solely to

. Consumers were then clustered according to Ward’s Method ( Qannari et al., 1997 ). A two-way ANOVA was performed and a significant cluster by product interaction validated the clusters. Consumer preferences were modeled with the descriptive analysis