Principal component analysis of body measurements based morphological structure of Madgyal sheep
434 / 157
Keywords:
Body measurement, Madgyal sheep, Morphometric structure, Principal component analysisAbstract
The present study describes the morphometric structure of extensively managed Madgyal sheep of Maharashtra and predicts body weight from their body biometry traits using principal component analysis (PCA). The data on body weight and 13 body measurements were recorded on 200 randomly selected sheep. Phenotypic correlation among body weight and biometric traits were positive and highly significant except some of ear length related combinations. The PCA of morphometric traits extracted two components with a total variance 67.8% explained. The first factor had high loadings for variables related to body size, whereas second factor was loaded in favour of body shape. PCA was able to define the morphological structure of Madgyal sheep and identified traits with greater variability. The principal component based regression models were more appropriate than the use of original correlated variables in predicting the body weight. The findings could be useful in designing management, selection and breeding programmes of the Madgyal sheep.Downloads
References
Birteeb P T, Peters S O, Yakubu A, Adeleke M A and Ozoje M O. 2012. Multivariate characterisation of the phenotypic traits of Djallonke and Sahel sheep in Northern Ghana. Tropical Animal Health Production 45: 267–74. DOI: https://doi.org/10.1007/s11250-012-0211-4
JMP Version 9.0.1989–2007. SAS Institute Inc. Cary, NC.
Kunene N W, Bezuidenhout C C and Nsahlaii V. 2009. Determination of prediction equations for estimating body weight of Zulu (Nguni) sheep. Small Ruminant Research 84: 1–3. DOI: https://doi.org/10.1016/j.smallrumres.2009.05.003
Legaz E, Cervantes I, Pérez-Cabal M A, de la Fuente L F, Mártinez R, Goyache F and Gutiérrez J P. 2011. Multivariate characterisation of morphological traits in Assaf (Assaf.E) sheep. Small Ruminant Research 100:122–30. DOI: https://doi.org/10.1016/j.smallrumres.2011.06.005
Mavule B S, Muchenje V, Bezuidenhout C C and Kunene N W. 2013. Morphological structure of Zulu sheep based on principal component analysis of body measurements. Small Ruminant Research 111: 23–30. DOI: https://doi.org/10.1016/j.smallrumres.2012.09.008
Salako A E. 2006. Principal component factor analysis of the morph structure of immature Uda sheep. International Journal of Morphology 24 (4): 571–74. DOI: https://doi.org/10.4067/S0717-95022006000500009
Yadav D K and Bhar L M. 2008.Robust model fitting in Muzaffarnagri sheep growth data under field conditions. Indian Journal of Animal Sciences 78 (11):1285–87.
Yadav D K, Jain A, Kulkarni V S, Govindaiah M G, Aswathnarayan T and Sadana D K. 2013. Classification of four ovine breeds of southern peninsular zone of India: Morphometric study using classical discriminant function analysis. SpringerPlus 2: 29, doi: 10.1186/2193–1801–2–29. DOI: https://doi.org/10.1186/2193-1801-2-29
Yadav D K and Arora R. 2014. Genetic discrimination of Muzaffarnagri and Munjal sheep of north-western semi-arid zone of India based on microsatellite markers and morphological traits. Indian Journal of Animal Sciences 84 (5): 527–32.
Yadav D K, Arora R and Jain A. 2014. Exploring Deccani sheep ecotypes of Maharashtra: are these autonomous breeds? The Indian Journal of Small Ruminants 20 (1): 91–94.
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2016 The Indian Journal of Animal Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright of the articles published in The Indian Journal of Animal Sciences is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.