Prediction of lean meat proportion of lambs carcasses
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abstract
The objectives of this study were to identify a reduced pertinent set of variables from an
original data set of 18 carcass measurements in order to avoid redundancy and collinearity
problems or to simplify data analysis and the development of the linear regression models to
predict lean meat yield of lamb carcasses. Forty-six (46) male lambs, 26 of Churro Galego
Bragançano Portuguese local breed and 20 of Sufolk c breed were used. Lambs were
slaughtered and carcasses weighed approximately 30 min after in order to obtain hot carcass
weight (HCW). After cooling at 4 o C for 24-h a set of seventeen carcass and tissues
measurements were recorded. The data interrelationships were analysed following the common
factor analysis procedure. HCW was lowly correlated with leg length (r = 0.17) and
moderately correlated with measurements that characterize carcass lengths and perimeters (r =
-0.39 to 0.56). Four common factors (factor I = HCW; factor II = breast bone tissue thickness;
factor III = subcutaneous fat thickness; and factor IV = carcass conformation) were retained,
account for 81.9% of the variation in the eighteen original variables. This study shows that
common factors analysis can be used to condense the information given by large sets of
variables, by selecting a reduced number of variables, which avoids collinearity problems and simplifies the development of carcass composition estimation models.
