Prediction of intramuscular fat in lamb by visible and near-infrared spectroscopy in an abattoir environment

• Published in: Meat science Vol. 171; p. 108286
• Main Authors: Lambe, N.R., Clelland, N., Draper, J., Smith, E.M., Yates, J., Bunger, L.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.01.2021
• Subjects: Abattoirs; Adipose Tissue; Animals; Food Quality; Lamb; Meat quality; Muscle, Skeletal; Red Meat - analysis; Sheep, Domestic; Spectroscopy, Near-Infrared - veterinary; Spectrum Analysis - veterinary; Supply chain; Visible and near-infrared spectroscopy; Supply chain; Visible and near-infrared spectroscopy; Lamb; Meat quality
• ISSN: 0309-1740; 1873-4138
• DOI: 10.1016/j.meatsci.2020.108286

The study used visible and near-infrared spectroscopy (Vis-NIR) in a large commercial processing plant, to test a system for meat quality (intramuscular fat; IMF) data collection within a supply chain for UK lamb meat. Crossbred Texel x Scotch Mule lambs (n = 220), finished on grass on 4 farms and slaughtered across 2 months, were processed through the abattoir and cutting plant and recorded using electronic identification. Vis-NIR scanning of the cut surface of the M. longissimus lumborum produced spectral data that predicted laboratory-measured IMF% with moderate accuracy (R2 0.38–0.48). Validation of the Vis-NIR prediction equations on an independent sample of 30 lambs slaughtered later in the season, provided similar accuracy of IMF prediction (R2 0.54). Values of IMF from four different laboratory tests were highly correlated with each other (r 0.82–0.95) and with Vis-NIR predicted IMF (r 0.66–0.75). Results suggest scope to collect lamb loin IMF data from a commercial UK abattoir, to sort cuts for different customers or to feed back to breeding programmes to improve meat quality. •Visible and near-infrared spectroscopy can predict intramuscular fat in lamb loins.•Spectroscopic predictions can be taken in an abattoir on intact meat cuts.•Meat quality predictions could feed back in the supply chain to inform breeding.