Abstract

The aim of this study was to compare the genetic diversity of 12 populations of goats in Brazil and Morocco (n = 796) through the use of physical measurements and different multivariate techniques. Traits measured included wither height (WH), distance from the brisket to the ground (BH) and ear length (EL). The standardized Euclidean distance (D) was adopted. The D values were submitted to clustering analysis using hierarchical methods (from nearest neighbor and UPGMA - Unweighted Pair Group Method with Arithmetic Mean) and the numbers of clusters were analyzed using the Tocher optimization method. The population clustering was different depending on the method of analysis used. Among the hierarchical methods, UPGMA showed the best fit (CCC = 0.82). The Tocher method enabled the formation of four different clusters. Although the hierarchical and Tocher methods resulted in different cluster formations, both contributed to the interpretation of the genetic cluster divergence. The results obtained through UPGMA and Tocher optimization enable their use for future studies that may include a larger number of biometric variables on greater numbers of individuals and additional populations.

Highlights

  • Goats can be classified according to type, use and geographical distribution

  • The aim of this study was to compare the genetic diversity of 12 populations of goats in Brazil and Morocco (n = 796) through the use of physical measurements and different multivariate techniques

  • The D values were submitted to clustering analysis using hierarchical methods and the numbers of clusters were analyzed using the Tocher optimization method

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Summary

Introduction

Goats can be classified according to type, use (milk, meat or dual-purpose) and geographical distribution. The physical measurements are important in studies of genetic diversity for considering the variation existing among various breed groups and allowing for breed identification (Epstein, 1953; Mason, 1988). This methodology has been enhanced using the simultaneous measurement of several characteristics and the establishment of index between two physical measurements (Bourzat et al., 1993; Bouchel et al, 1997). Among the most used methods in genetic divergence are the hierarchical and optimization methods (Cruz & Carneiro, 2006)

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