Use of near infrared spectroscopy for estimating meat chemical composition, quality traits and fatty acid content from cattle fed sunflower or flaxseed

• NIRS was tested to predict meat quality traits and fatty acid composition in beef.
• NIRS showed high predictability for crude protein, moisture and fat content.
• NIRS predictions were not reliable for meat quality attributes.
• NIRS successfully predicted main fatty acid group content (SFA, MUFA, BCFA, CLA).
• NIRS could be suitable for meat screening based on rumenic and vaccenic acid contents.

This study tested the ability of near infrared reflectance spectroscopy (NIRS) to predict meat chemical composition, quality traits and fatty acid (FA) composition from 63 steers fed sunflower or flaxseed in combination with high forage diets. NIRS calibrations, tested by cross-validation, were successful for predicting crude protein, moisture and fat content with coefficients of determination (R2) (RMSECV, g · 100 g− 1 wet matter) of 0.85 (0.48), 0.90 (0.60) and 0.86 (1.08), respectively, but were not reliable for meat quality attributes. This technology accurately predicted saturated, monounsaturated and branched FA and conjugated linoleic acid content (R2: 0.83–0.97; RMSECV: 0.04–1.15 mg · g− 1 tissue) and might be suitable for screening purposes in meat based on the content of FAs beneficial to human health such as rumenic and vaccenic acids. Further research applying NIRS to estimate meat quality attributes will require the use on-line of a fibre-optic probe on intact samples.