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In vivo prediction of goat body composition by computer tomography

Published online by Cambridge University Press:  02 September 2010

M. T. Sørensen
M. T. Sørensen
Affiliation:
National Institute of Animal Science, Research Center Foulum, PO Box 39, DK-8830 Tjele, Denmark
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Abstract

Computer tomography (CT) was evaluated as a method to predict body composition of live goats. Forty-one lactating goats were scanned. CT values (X-ray attenuation data) representing soft body tissues were summarized into 140 frequencies. By principal component analysis the 140 multicollinear frequencies were reduced to six orthogonal principal components at the loss of only 0·032 of the original variation.

Following scanning at four positions the goats were slaughtered, dissected and the data analysed. Seven compositional traits (water, protein and fat from the carcass and non-carcass parts, and total energy of the body) were regressed on live weight and the six principal components from each of five CT data sets (data from the four scan positions and pooled data) in a stepwise linear regression procedure. Models from the pooled data set were further evaluated in a cross-validation procedure. Compared with evaluation based on calibration only, a more simple and precise model was chosen as the best by this procedure.

After addition of CT variables in prediction equations already comprising live weight, cross-validation deviations were reduced by 0 for carcass water, 0 for carcass protein, 0·48 for carcass fat, 0·14 for non-carcass water, 0·23 for non-carcass protein, 0·73 for non-carcass fat, and 0·73 for total energy. These results show that CT is a valuable in vivo method for predicting body fat and energy, but less valuable for body water and protein.

Keywords

body compositiongoatstomography
Type
Research Article
Information
Animal Production , Volume 54 , Issue 1 , February 1992 , pp. 67 - 73
Copyright
Copyright © British Society of Animal Science 1992

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