Format

Send to

Choose Destination
Meat Sci. 2019 Aug 16;159:107915. doi: 10.1016/j.meatsci.2019.107915. [Epub ahead of print]

Investigating the use of visible and near infrared spectroscopy to predict sensory and texture attributes of beef M. longissimus thoracis et lumborum.

Author information

1
Department of Food Quality and Sensory Science, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland; School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
2
School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
3
Department of Food Quality and Sensory Science, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland.
4
Irish Cattle Breeding Federation, Shinagh House, Bandon, Co. Cork, Ireland.
5
Department of Food Quality and Sensory Science, Teagasc Food Research Centre, Ashtown, Dublin 15, Ireland. Electronic address: ruth.hamill@teagasc.ie.

Abstract

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 (R2CV) 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 after-effect = 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.

KEYWORDS:

Beef quality; Chemometrics; Shear force; Trained sensory panel; Visible-near infrared spectroscopy

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center