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Description and analysis of genetic diversity among squash accessions

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dc.contributor.author Tsivelikas, AL en
dc.contributor.author Koutita, O en
dc.contributor.author Anastasiadou, A en
dc.contributor.author Skaracis, GN en
dc.contributor.author Traka-Mavrona, E en
dc.contributor.author Koutsika-Sotiriou, M en
dc.date.accessioned 2014-06-06T06:49:39Z
dc.date.available 2014-06-06T06:49:39Z
dc.date.issued 2009 en
dc.identifier.issn 15168913 en
dc.identifier.uri http://dx.doi.org/10.1590/S1516-89132009000200003 en
dc.identifier.uri http://62.217.125.90/xmlui/handle/123456789/4701
dc.subject Cluster analysis en
dc.subject Gower's distance en
dc.subject Morphophysiological characteristics en
dc.subject Principal component analysis en
dc.subject RAPD markers en
dc.subject Winter squash en
dc.subject.other Cucurbita maxima en
dc.subject.other Fusarium oxysporum en
dc.title Description and analysis of genetic diversity among squash accessions en
heal.type journalArticle en
heal.identifier.primary 10.1590/S1516-89132009000200003 en
heal.publicationDate 2009 en
heal.abstract In this work, the part of the squash core collection, maintained in the Greek Gene Bank, was assessed using the morphological and molecular data. Sixteen incompletely classified accessions of the squash were characterized along with an evaluation of their resistance against two isolates of Fusarium oxysporum. A molecular analysis using Random Amplified Polymorphic DNA (RAPD) markers was also performed, revealing high level of polymorphism. To study the genetic diversity among the squash accessions, a clustering procedure using Unweighed Pair Group Method and Arithmetic Average (UPGMA) algorithm was also adopted. Two independent dendrograms, one for the morphophysiological and one for molecular data were obtained, classifying the accessions into two and three main clusters, respectively. Despite the different number of the clusters there were many similarities between these two dendrograms, and a third dendrogram resulting from their combination was also produced, based on Gower's distance and UPGMA clustering algorithm. In order to determine the optimal number of clusters, the upper tail approach was applied. The more reliable clustering of the accessions was accomplished using RAPD markers as well as the combination of the two different data sets, classifying the accessions into three significantly different groups. These groups corresponded to the three different cultivated species of C. maxima Duch., C. moschata Duch., and C. pepo L. The same results were also obtained using Principal Component Analysis. © 2009 Tecpar. en
heal.journalName Brazilian Archives of Biology and Technology en
dc.identifier.issue 2 en
dc.identifier.volume 52 en
dc.identifier.doi 10.1590/S1516-89132009000200003 en
dc.identifier.spage 271 en
dc.identifier.epage 283 en


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