APPLICATION OF MULTIVARIATE ANALYSIS TO DIFFERENTIATE HARARGHE HIGHLAND GOAT POPULATIONS REARED IN THE WEST HARARGHE ZONE, ETHIOPIA

IF 0.3 Q4 AGRONOMY
A. Takele, A. Melesse, Mestawet Taye
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Abstract

Multivariate analysis of morphological variables has been successfully used to estimate genetic variation within and between local breeds. The objective of this study was to differentiate Hararghe highland goat populations based on their morphometric traits by applying multivariate analysis. Sixteen morphometric traits were collected from 450 goats reared in the three agroecological zones (highland, midland and lowland) of West Hararghe. Multivariate canonical discriminant analysis in combination with cluster and discriminant analysis was applied to identify the combination of variables that differentiate goats of the three agroecological zones. The results indicated that all the morphometric traits were significantly affected by age. The cluster analysis indicated that two main groups of midland goats were included in one group, while group two included highland and lowland goats under one sub-cluster. The canonical discriminant analysis identified two canonical variables (CAN) of which CAN1 and CAN2 accounted for 68.2 and 31.8% of the total variation, respectively. The quadratic discriminant analysis correctly assigned the respective 71.3, 77.3, and 81.3% of lowland, midland, and highland goat populations into their source populations, with an overall accuracy rate of 76.7%. The Mahalanobis distance verified that lowland and highland goats are the closest, while midland and highland goats were the furthest. However, the canonical discriminant analysis indicated a visible overlapping between goat populations of the three agroecological zones, indicating the existence of homogeneity among them. In conclusion, multivariate analysis identified 11 morphometric traits as the most imperative traits to differentiate Hararghe highland goat populations effectively. Genetic potentials of Hararghe highland goat populations can be improved through community-based breeding programs for their sustainable utilization and conservation.
应用多变量分析对埃塞俄比亚哈拉尔河西部地区饲养的哈拉尔河高原山羊种群进行区分
形态变量的多变量分析已成功用于估计当地品种内部和之间的遗传变异。本研究的目的是应用多元分析方法,根据哈拉尔河高原山羊种群的形态计量特征对其进行区分。从西哈拉尔吉三个农业生态区(高地、中部和低地)饲养的450只山羊身上采集了16个形态计量性状。将多元正则判别分析与聚类和判别分析相结合,确定了区分三个农业生态区山羊的变量组合。结果表明,所有形态计量性状都受到年龄的显著影响。聚类分析表明,一组包括两个主要的中部山羊群,而第二组包括一个子聚类下的高地和低地山羊。规范判别分析确定了两个规范变量(CAN),其中CAN1和CAN2分别占总变异的68.2%和31.8%。二次判别分析将71.3%、77.3%和81.3%的低地、中部和高地山羊种群正确地分配到其源种群中,总体准确率为76.7%。Mahalanobis距离验证了低地和高地山羊最接近,而中部和高原山羊最远。然而,典型判别分析表明,三个农业生态区的山羊种群之间存在明显的重叠,表明它们之间存在同质性。总之,多元分析确定11个形态计量性状是有效区分哈拉尔河高原山羊种群的最重要性状。哈拉尔河高原山羊种群的遗传潜力可以通过基于社区的育种计划来提高,以实现其可持续利用和保护。
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来源期刊
CiteScore
0.70
自引率
0.00%
发文量
23
期刊介绍: Revista Chile de Agricultura y Ciencias Veterinarias es una revista de acceso abierto (open access), que significa que su contenido está disponible en forma gratuita para los usuarios y sus instituciones. Los usuarios pueden leer, descargar, copiar, distribuir, imprimir, buscar, o establecer una conexión a los artículos sin necesidad de pedir autorización previa al editor o a los autores. Esto es de acuerdo con la definición de Budapest Open Access Initiative (BOAI). Los artículos se publican bajo una licencia de Creative Commons reconocimiento No Comercial 4.0 Internacional. Copyright: Se autoriza la reproducción y cita de los artículos publicados en Chilean Journal of Agricultural & Animal Sciences (ex Agro-Ciencia), siempre que se indique el nombre del autor(es), año, volumen, número y páginas. Las opiniones y afirmaciones expuestas en los trabajos representan exclusivamente los puntos de vista de los autores. La mención de productos o marcas comerciales en la revista no implica una recomendación por parte de la Universidad de Concepción.
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