Journal
MEAT SCIENCE
Volume 171, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.meatsci.2020.108286
Keywords
Lamb; Meat quality; Visible and near-infrared spectroscopy; Supply chain
Categories
Funding
- Innovate UK through an Agri-Tech Catalyst Industrial Research Award [101917]
- Scottish Government's Strategic Research Programme
- BBSRC [BB/P005098/1] Funding Source: UKRI
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The study used Vis-NIR spectroscopy to collect IMF data of UK lamb meat, showing potential for sorting cuts based on quality and improving overall meat quality.
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 (R-2 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 (R-2 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.
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