Breeds and muscle types modulate performance of near-infrared reflectance spectroscopy to predict the fatty acid composition of bovine meat

Meat Sci. 2015 Jan:99:104-12. doi: 10.1016/j.meatsci.2014.08.014. Epub 2014 Sep 6.

Abstract

This study aims to assess near-infrared reflectance spectroscopy feasibility for predicting beef fatty acid (FA) composition. Experimental scheme included four breeds (Angus, Blond d'Aquitaine, Charolais, Limousin) and three muscles, Longissimus thoracis (LT), Rectus abdominis (RA), Semitendinosus (ST). The results showed that 1) increasing FA content variability with several breeds increased calibration model reliability (R(2)CV>0.86) for the major individual and groups of FA unless polyunsaturated FAs, 2) Longissimus thoracis FAs were better predicted than RA FAs while no ST FAs were correctly predicted (R(2)CV<0.71). This difference could be explained by FA content, FA variability or specific muscle physico-chemical characteristics.

Keywords: Bovine; Fatty acid; Muscle; NIR spectroscopy.

Publication types

  • Evaluation Study

MeSH terms

  • Animals
  • Breeding*
  • Calibration
  • Cattle
  • Fatty Acids / analysis*
  • Fatty Acids / genetics
  • Humans
  • Meat / analysis*
  • Muscle, Skeletal*
  • Spectroscopy, Near-Infrared / methods*

Substances

  • Fatty Acids