Journal
MEAT SCIENCE
Volume 159, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.meatsci.2019.107915
Keywords
Visible-near infrared spectroscopy; Chemometrics; Beef quality; Trained sensory panel; Shear force
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Funding
- BreedQuality project - Irish Department of Agriculture, Food and the Marine (DAFM) under the National Development Plan 2007-2013 [11/SF/311]
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The aim of this study was to calibrate chemometric models to predict beef M. longissimus thoracis et lumborum (LTL) sensory and textural values using visible-near infrared (VISNIR) spectroscopy. Spectra were collected on the cut surface of LTL steaks both on-line and off-line. Cooked LTL steaks were analysed by a trained beef sensory panel as well as undergoing WBSF analysis. The best coefficients of determination of cross validation ((RCV)-C-2) in the current study were for textural traits (WBSF = 0.22; stringiness = 0.22; crumbly texture = 0.41: all 3 models calibrated using 48 h post-mortem spectra), and some sensory flavour traits (fatty mouthfeel = 0.23; fatty aftereffect = 0.28: both calibrated using 49 h post-mortem spectra). The results of this experiment indicate that VISNIR spectroscopy has potential to predict a range of sensory traits (particularly textural traits) with an acceptable level of accuracy at specific post-mortem times.
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