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Morphological Structure of South African Non-Descript Does Raised in Syferkuil Farm, Capricorn District of Limpopo Province Using Factor Analysis

机译:南非非描述的形态学结构在Syferkuil Farm,林蛙省山顶省山顶省的山楂区使用因子分析

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Goat is one of important livestock in Africa for meat and milk productions. This research was aimed to characterize the morphological structure in South African non-descript does (1-2 years of age). Two body parameters including body measurements (14 variables) and body indices (11 variables) were used in this study and taken from fifty (n = 50) does. The data of two body parameters were used to characterize the animal’s morphological structure. Factor analysis including Pearson’s correlations, Principal Component Analysis (PCA) and multiple regression analysis were used for evaluations. Results of Pearson’s correlation analysis of body measurements indicated that body weight had a positive and highly statistical association with body length (r = 0.84, P0.01). While in body indices the body weight had a positive and highly statistical correlation with area index (r = 0.83, P0.01). PCA results showed that two body parameters in this study were explained about 80% of total variance in animal’s morphological structure. Despite, three PC’s of body indices in does have very high correlation with body weight (R2 = 0.82). Meanwhile, four PC’s of body measurements in does have moderate correlation with body weight (R2 = 0.59). It can be concluded that six body measurements (bicostal diameter, ear length, head width, head length, heart girth, cannon circumference) and six body indices (length index, depth index, conformation index, proportionality, thoracic development, cannon thickness index) were classified into first component that explain about 30.06% in body measurements and 48.88% in body indices. The results revealed that the first component in the body indices can be used as the criteria for South African non-descript goat because it represents the animal’s morphological structure and body weight.
机译:山羊是非洲的重要牲畜之一,用于肉和牛奶制作。该研究旨在表征南非非描述性的形态结构(1-2岁)。在本研究中使用了两个身体参数,包括身体测量(14个变量)和身体指标(11个变量),并从五十(n = 50)中取出。两个体参数的数据用于表征动物的形态结构。因子分析包括Pearson的相关性,主成分分析(PCA)和多元回归分析用于评估。 Pearson对体测量相关分析的结果表明体重具有阳性和高度统计关联的体长(R = 0.84,P <0.01)。虽然在身体指数中,体重与区域指数具有正且高度统计相关性(R = 0.83,P <0.01)。 PCA结果表明,本研究中的两个体参数占动物形态结构总方差的约80%。尽管如此,三个PC的身体指数确实与体重非常高(R2 = 0.82)。同时,四个PC的身体测量确实与体重(R2 = 0.59)具有中等的相关性。可以得出结论,六个身体测量(面部直径,耳长,头部宽度,头长,心周长,炮圆周)和六个身体指数(长度指数,深度指数,构象指数,比例,胸廓开发,炮灰厚度指数)分为第一个组成部分,可以在身体测量中解释约30.06%,身体指标中的48.88%。结果表明,身体指数中的第一个组成部分可用作南非非描述山羊的标准,因为它代表了动物的形态结构和体重。

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