Author(s):
Cadavez, Vasco 
Date: 2009
Persistent ID: http://hdl.handle.net/10198/2898
Origin: Biblioteca Digital do IPB
Subject(s): Lambs; Carcass; Tissue; Measurements; Common factors
Document details
Prediction of lean meat proportion of lamb carcasses
Description
The objectives of this study were to identify a reduced pertinent set of variables from an original set of 18 carcass measurements and the development of linear regression models to predict lean meat yield of lamb carcasses. Forty- six male lambs, 26 of Churro Galego Bragançano Portuguese local breed and 20 of Suffolk breed were used. Lambs were slaughtered and carcasses were weighed approximately 30 min after slaughter in order to obtain hot carcass weight (HCW). After cooling at 4°C for 24-h a set of 17 carcass 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 thickness; factor III = subcutaneous fat thickness; and factor IV = carcass conformation) were retained, accounting for 81.9% of the variation in the 18 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.
The objectives of this study were to identify a reduced pertinent set of variables from an original set of 18 carcass measurements and the development of linear regression models to predict lean meat yield of lamb carcasses. Forty- six male lambs, 26 of Churro Galego Bragançano Portuguese local breed and 20 of Suffolk breed were used. Lambs were slaughtered and carcasses were weighed approximately 30 min after slaughter in order to obtain hot carcass weight (HCW). After cooling at 4°C for 24-h a set of 17 carcass 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 thickness; factor III = subcutaneous fat thickness; and factor IV = carcass conformation) were retained, accounting for 81.9% of the variation in the 18 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.
Document Type
Article
Language English
Language English
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