Prediction of carcass composition by impedance spectroscopy in lambs of similar weight

• Published in: Meat science Vol. 70; no. 2; pp. 319 - 327
• Main Authors: Altmann, M., Pliquett, U., Suess, R., Borell, E. von
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.06.2005; Elsevier
• Subjects: bioelectrical impedance; Biological and medical sciences; body composition; breed differences; Carcass composition; Food industries; Fundamental and applied biological sciences. Psychology; Impedance; Lamb; lamb carcasses; lambs; Meat and meat product industries; meat quality; prediction; slaughter weight; Impedance; Carcass composition; Lamb; Meat product; Chemical composition; Prediction
• ISSN: 0309-1740; 1873-4138
• DOI: 10.1016/j.meatsci.2005.01.018

Previous research on impedance measurements for the prediction of carcass composition was predominantly carried out on animals that varied widely in body weight, breed, or sex. The high accuracy for the estimated lean or fat mass was mainly obtained by including the body weight in the regression equations. The objective of this study was the prediction of carcass composition in lambs of similar weight. We used 70 male German Merino Mutton lambs and 70 male German Blackheaded Mutton lambs with 35 and 45 kg live weight each. Impedance measurements with different electrode placements were carried out in vivo and on carcasses 20 min and 24 h postmortem. The carcass composition was ascertained by dissection of the left carcass side into lean, fat, and bone. R 2-values for prediction of lean mass by impedance and body weight ranged between 0.11 and 0.71 within breeds and weight groups and between 0.84 and 0.89 in the total material. Lean percentage was estimated with R 2 = 0.18–0.48 within breeds and weight groups. The corresponding values for the total material varied from 0.23 to 0.37. We conclude that the impedance method is not suitable for the prediction of lean or fat percentage, neither in lambs of similar weight nor in heterogeneous animals.