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Online Prediction of Physico-Chemical Quality Attributes of Beef Using Visible—Near-Infrared Spectroscopy and Chemometrics
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2019-10-23
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Sahar, A.; Allen, P.; Sweeney, T.; Cafferky, J.; Downey, G.; Cromie, A.; Hamill , R.M. Online Prediction of Physico-Chemical Quality Attributes of Beef Using Visible—Near-Infrared Spectroscopy and Chemometrics. Foods 2019, 8, 525. https://doi.org/10.3390/foods8110525
Abstract
The potential of visible–near-infrared (Vis–NIR) spectroscopy to predict physico-chemical
quality traits in 368 samples of bovine musculus longissimus thoracis et lumborum (LTL) was evaluated.
A fibre-optic probe was applied on the exposed surface of the bovine carcass for the collection of
spectra, including the neck and rump (1 h and 2 h post-mortem and after quartering, i.e., 24 h and 25 h
post-mortem) and the boned-out LTL muscle (48 h and 49 h post-mortem). In parallel, reference
analysis for physico-chemical parameters of beef quality including ultimate pH, colour (L, a*, b*),
cook loss and drip loss was conducted using standard laboratory methods. Partial least-squares (PLS)
regression models were used to correlate the spectral information with reference quality parameters
of beef muscle. Different mathematical pre-treatments and their combinations were applied to
improve the model accuracy, which was evaluated on the basis of the coefficient of determination of
calibration (R2C) and cross-validation (R2CV) and root-mean-square error of calibration (RMSEC)
and cross-validation (RMSECV). Reliable cross-validation models were achieved for ultimate pH
(R2CV: 0.91 (quartering, 24 h) and R2CV: 0.96 (LTL muscle, 48 h)) and drip loss (R2CV: 0.82 (quartering,
24 h) and R2CV: 0.99 (LTL muscle, 48 h)) with lower RMSECV values. The results show the potential
of Vis–NIR spectroscopy for online prediction of certain quality parameters of beef over different
time periods.