PENGELOMPOKAN KUDA SUMBAWA BERDASARKAN VARIASI FENOTIP MENGGUNAKAN METODE PCA (Principle Component Analysis)

Authors

  • Ahmad Ihrom Wijaya Program Studi Pendidikan Biologi, FSTT, Universitas Pendidikan Mandalika, Indonesia
  • Sri Nopita Primawati Program Studi Pendidikan Biologi, FSTT, Universitas Pendidikan Mandalika, Indonesia
  • Nofisulastri Nofisulastri Program Studi Pendidikan Biologi, FSTT, Universitas Pendidikan Mandalika, Indonesia

Keywords:

Equus caballus, Phenotypic Variation, Kinship, PCA (Principle Component Analysis) Method.

Abstract

The Sumbawa horse (Equus caballus) in the last 3 years has experienced a fluctuating population decline from 2019 to 2021, respectively 18,582, 14,378 and 14,364, this can cause the loss of one of the germplasm wealth on the island of Sumbawa. One of the efforts to prevent the loss of germplasm wealth on the island of Sumbawa is to do livestock breeding through kinship analysis based on their phenotypic characteristics. A total of 25 Sumbawa horses were obtained by purposive sampling in Lalar liang Village, Taliwang District, West Sumbawa Regency, West Nusa Tenggara Province. The research sample was 25 horses using purposive sampling technique. Morphological parameters observed were body length, body height, neck length, hip width, and head length. This type of research is exploratory descriptive, aims to describe the state of a phenomenon that occurs. Data were analyzed using the PCA method as primary data and cluster analysis using the UPGMA method as secondary data using PAST software. The results of the PCA analysis showed that the morphological distribution map of horses was divided into four quadrants, namely in quadrant I there were 4 individuals (KD4, KD17, KD18, KD22), in quadrant II there were 9 individuals (KD3, KD7, KD8, KD9, KD14, KD15, KD16 , KD18, KD20), quadrant III of 6 individuals (KD6, KD10, KD12, KD23, KD24, KD25), and quadrant IV of 6 individuals (KD1, KD2, KD5, KD11, KD13, KD21). The results of cluster analysis using the UPGMA method, where at a distance of 20 there are 2 clusters, namely Cluster 1 consisting of 24 individuals while 1 individual (KD13) is Cluster 2.

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Published

27-11-2023

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Articles