Molecular characterization of Vietnamese cocoa genotypes (Theobroma cacao L.) using microsatellite markers

Molecular characterization of Vietnamese cocoa genotypes (Theobroma cacao L.) using... Vietnam has the appropriate climate, soil, and humidity for cocoa cultivation and is growing as a cocoa-producing country. To supply the international cocoa market, trees have been planted in Southern Vietnam. Cocoa quality depends on various factors, such as the genotype/cultivar, environment, and post-harvest processing. Until now, little research has been done on the genetic background of Vietnamese cocoa. Therefore, this study focused on the genetic relationships of 75 cocoa cultivars, sampled in Vietnam. Fourteen microsatellite markers were used to assay the genetic diversity and to genotype and differentiate the accessions. Descriptive statistics showed that most of the used microsatellite markers were sufficient to be used in further analysis, of which mTcCIR 15, 33, and 37 were the most polymorphic. The principal coordinate analysis (PCoA) and Bayesian clustering approach divided the samples in two groups, which were linked to the Trinitario and Forastero varieties. The Vietnamese Can Tho (CT) cultivars showed little variation, while the Thu Duc (TD) cultivars showed a continuous variation between the different reference cultivars. This indicates that the CT cultivars were Trinitario and that the TD cultivars were hybrids of Forastero or Forastero and Trinitario. The molecular characterization is an important step towards developing a strong genetic basis for the Vietnamese cocoa industry. It can be used to conserve valuable genetic material and to select promising cocoa cultivars which are disease resistant, high yielding, and fine flavored. In this way, the high-quality Vietnamese cocoa production can be improved and maintained. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Tree Genetics & Genomes Springer Journals

Molecular characterization of Vietnamese cocoa genotypes (Theobroma cacao L.) using microsatellite markers

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany
Subject
Life Sciences; Forestry; Plant Genetics and Genomics; Plant Breeding/Biotechnology; Tree Biology; Biotechnology
ISSN
1614-2942
eISSN
1614-2950
D.O.I.
10.1007/s11295-017-1180-6
Publisher site
See Article on Publisher Site

Abstract

Vietnam has the appropriate climate, soil, and humidity for cocoa cultivation and is growing as a cocoa-producing country. To supply the international cocoa market, trees have been planted in Southern Vietnam. Cocoa quality depends on various factors, such as the genotype/cultivar, environment, and post-harvest processing. Until now, little research has been done on the genetic background of Vietnamese cocoa. Therefore, this study focused on the genetic relationships of 75 cocoa cultivars, sampled in Vietnam. Fourteen microsatellite markers were used to assay the genetic diversity and to genotype and differentiate the accessions. Descriptive statistics showed that most of the used microsatellite markers were sufficient to be used in further analysis, of which mTcCIR 15, 33, and 37 were the most polymorphic. The principal coordinate analysis (PCoA) and Bayesian clustering approach divided the samples in two groups, which were linked to the Trinitario and Forastero varieties. The Vietnamese Can Tho (CT) cultivars showed little variation, while the Thu Duc (TD) cultivars showed a continuous variation between the different reference cultivars. This indicates that the CT cultivars were Trinitario and that the TD cultivars were hybrids of Forastero or Forastero and Trinitario. The molecular characterization is an important step towards developing a strong genetic basis for the Vietnamese cocoa industry. It can be used to conserve valuable genetic material and to select promising cocoa cultivars which are disease resistant, high yielding, and fine flavored. In this way, the high-quality Vietnamese cocoa production can be improved and maintained.

Journal

Tree Genetics & GenomesSpringer Journals

Published: Aug 21, 2017

References

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