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

Abstract

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.

Keywords: Lamb; Meat quality; Supply chain; Visible and near-infrared spectroscopy.