SUSTAINABLE GOAT BREEDING AND GOAT FARMING IN CENTRAL AND EASTERN EUROPEAN COUNTRIES
Date Issued
2014
Author(s)
Vladimir Dzabirski, Koco Porcu, Dragoslav Kocevski, Mirjana Jankulovska and Goran Trajkovski
Abstract
Principal component analysis (PCA) and cluster analysis were performed to describe and
understand the extent of genetic variability in domestic Balkan goat ecotypes from The
former Yugoslav Republic of Macedonia. In this study, goat ecotypes from ten different
farms/locations were analysed to determine the uniqueness of the domestic Balkan
goat breed and evaluate the level of diversity among ecotypes. A total of 1 129 animals
of both sexes were characterized according to 18 qualitative traits. The frequencies
of each analysed trait for each ecotype were determined and used in PCA and cluster
analysis. The first two principal components explained 94 percent of the total variance
in this data set. All ecotypes except ecotypes 5 and 6 were significantly correlated with
principal component 1 (PC1). These findings were confirmed by cluster analysis. Based
on the obtained results, two main clusters were identified. The first cluster comprised
ecotypes 5 and 6 while ecotypes in the second cluster were classified into two subclusters.
This study provided initial information on the extent of genetic variability in Balkan
goat ecotypes from the country. However, for better characterization and assessment of
genetic diversity in the analysed goat population, further evaluation is recommended,
based on both morphological and molecular markers.
understand the extent of genetic variability in domestic Balkan goat ecotypes from The
former Yugoslav Republic of Macedonia. In this study, goat ecotypes from ten different
farms/locations were analysed to determine the uniqueness of the domestic Balkan
goat breed and evaluate the level of diversity among ecotypes. A total of 1 129 animals
of both sexes were characterized according to 18 qualitative traits. The frequencies
of each analysed trait for each ecotype were determined and used in PCA and cluster
analysis. The first two principal components explained 94 percent of the total variance
in this data set. All ecotypes except ecotypes 5 and 6 were significantly correlated with
principal component 1 (PC1). These findings were confirmed by cluster analysis. Based
on the obtained results, two main clusters were identified. The first cluster comprised
ecotypes 5 and 6 while ecotypes in the second cluster were classified into two subclusters.
This study provided initial information on the extent of genetic variability in Balkan
goat ecotypes from the country. However, for better characterization and assessment of
genetic diversity in the analysed goat population, further evaluation is recommended,
based on both morphological and molecular markers.
Subjects
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