Abstract

Introduction: Phenotypic characterization contributes to the knowledge of breeds and their sustainable use. The present study assessed the possibility of using factorial analysis of mixed data (FAMD) combined with hierarchical clusters on principal components to manage goat characteristics. Materials and methods: A total of 1644 adult male and female indigenous goats were randomly sampled across different climate zones (Guinean, Sudanian-Guinean, and Sudanian zone) of Benin. The samples were investigated in terms of 20 body measurements (head length, right and left horn length, right and left ear length, neck girth, neck length, cannon length, cannon bone circumference, body length, heart girth, tail length, body weight, Rump width, withers height, chest depth, back height, rump height, rump depth, and age) and 12 qualitative traits sex, coat color, color pattern, horn presence, horn shape, horn orientation, ear orientation, head profile, beard presence, wattles presence, back profile, and rump profile). Data analysis was performed using FAMD and hierarchical clusters on principal components. Results: The findings indicated three types of goats with distinct characteristics. The first goat type had a small size (35.65 cm in withers and 38.29 cm in back height), while the third type had a large size (57.02 cm in withers and 59.08 in back height ). The second genetic type had a medium size (47.31 cm and 50.01 cm for withers and back height, respectively) resulting from the previous types of genetic crosses. Conclusion: The results indicate the efficiency of FAMD-based cluster analysis in handling phenotypic data.

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