Abstract
This study was preformed to evaluate the biometric traits of 227 Yankasa sheep in northern Nigeria under a multivariate approach. The body measurements taken were: withers height, rump height, body length, heart girth, tail length, face length, shoulder width, head width, rump width, ear length, foreleg length, hind leg length and rump length. The animals were divided into two age groups: <15.5 and 15.5 - 28.3 months old, respectively. General linear model was used to study age group effect while principal component factor analysis was performed to define body shape upon the correlation matrix of the thirteen body measurements. Age group significantly (P<0.05) affected the morphological characters except ear length. Pearson?s coefficients of correlation were positive and significant in both age groups. In <15.5 months old sheep, four principal components (factors) were extracted (ratio of variance = 89.27). The first factor accounted for 73.03% of the total variance and was interpreted as a measure of general size. The second factor which explained 7.61% of the generalized variance tended to describe flesh dimensions (shoulder width and rump width), while the third factor had its loadings for tail length and ear length. The fourth factor was influenced by head width. In 15.5-28.3 months old sheep, three factors (ratio of variance=75.21) were identified. These seven extracted factors could be considered in breeding programmes to improve body conformation of sheep since variation in meat traits was not associated with body height.
Highlights
Body composition and growth performance are important to assess the potential of development in animals
The marked differences observed in the variables of the two age groups are not surprising since component parts of the animals are expected to increase differentially as the animal grows with age (Salhab et al, 2001; Yakubu, 2003)
Ear length, rump width, heart girth, shoulder width and body length were more variable in the former (CV= 21.84, 20.41, 16.79, 14.57, 14.37 and 14.03 respectively) while in the latter, variability was highest in tail length followed by ear length, head width, shoulder width, heart girth and rump width (CV = 19.36, 17.19, 15.90, 11.20 and 10.60 respectively)
Summary
Body composition and growth performance are important to assess the potential of development in animals. External body measurements of animals have been extensively used to assess the growth of skeletal parts; and to describe the changes in animal conformation with age (Ngere et al, 1984). Factor analysis is a multivariate methodology that can be employed when characteristics are correlated, thereby describing objectively the underlying dimension of size and shape. It permits the elimination of redundancies from sets of interdependent variables, extract and identify covariant variable sets that are statistically unrelated (Nugent and Notter, 1991; Shahin et al, 1995; Yakubu et al, 2011)
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