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The estimation of pig carcass composition from different measurements with special reference to classification and grading

Published online by Cambridge University Press:  02 September 2010

A. Diestre  and
A. J. Kempster
A. Diestre
Affiliation:
Institut Catala de la Carn, Granja Camps i Armet, Monells, Girona, Spain
A. J. Kempster
Affiliation:
Meat and Livestock Commission, PO Box 44, Queensway House, Queensway, Bletchley, Milton Keynes MK2 2EF
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Abstract

Data for 1002 pigs slaughtered between 1979 and 1982 from the Meat and Livestock Commission's Commercial Pig Evaluation scheme were used to examine the relative precision of different measurements for predicting carcass lean concentration. The sample covered the main market weights in Britain and comprised gilts and barrows. The overall means of carcass weight and lean concentration were 66·1 (s.d. 20·00) kg and 499 (s.d. 44·2) g/kg. Predictors were examined when used in addition to carcass weight.

Of the measurements taken on the intact or centre-split carcass, fat thickness measured by optical probe 65 mm from the dorsal mid line over the m. longissimus at the last rib was the most precise predictor of lean concentration (residual s.d. = 24·6 g/kg). The precision was improved significantly when a mid-line loin fat thickness measurement was added (residual s.d. = 23·7). The stability of the selected regression equations was examined by applying them to data for three other sets of carcasses (totalling 489 carcasses) sampled from commercial abattoirs between 1975 and 1983. Biases (predicted minus actual lean concentrations) ranged from +13 to −25 g/kg.

Among the measurements taken on the cut surface at the last rib, fat thickness 8 cm from the dorsal mid line was the most precise predictor (residual s.d. = 22·4 g/kg). The precision was improved significantly when m. longissimus depth was added (residual s.d. = 20·3 g/kg). Prediction bias with these measurements was similar to that recorded with the intact or split-carcass measurements. In both cases, bias tended to increase with the number of independent variables in the prediction equations.

Type
Research Article
Information
Animal Production , Volume 41 , Issue 3 , December 1985 , pp. 383 - 391
Copyright
Copyright © British Society of Animal Science 1985

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References

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