Abstract
Towards assessment of variations within and between sheep; biometric and morphological data of the four breeds of sheep found in Nigeria were collected using multi-stage samplin method. A total of 46 Balami, 30 Uda, 36 Yankasa and 37 WAD were sampled. Stepwise multiple regression procedure was used to find the best linear combination of metric variables that best predict the body weight. Principal component analysis of biometric and morphological traits was carried out. Simple discriminant analysis procedure was used to classify the breeds. Cluster analysis was done using the model building specificationinterface. Head length (HL), chest girth (CG), leg length (LL), and tail length were the only linear body measurements that were significant (P<0.01) in predicting body weight of sheep in the overall prediction equation. Body weight and all the linear body measurements had their highest loadings on principal component 1 (PC1). Tassel was the only variable that had its highest loading on PC2. Tail type and state (location) were the variables that bestdescribes the third component (PC3). Sex and hair type were variables that best described the forth component (PC4). Discriminant analysis showed that 70.59% of sheep sampled as Balami were classified as pure breed. Sheep sampled as WAD and Yankasa had 100% conformation while Balami and Uda had 70.59% and 60%, respectively in conformation to the classifying features of their breed based on discriminant analysis. The farthest genetic distance (5.48) was observed between Balami and WAD while the shortest genetic distance (1.26) was observed between Balami and Uda. Improvement of growth traits of sheep breedsin Nigeria is recommended through the use of either Balami or Uda as sire and either WAD or Yankasa as dam.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.