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The aim of this study was to investigate the potential use of near infrared (NIR) reflectance spectroscopy to predict chemical composition in both sunflower whole plant (WPSun) and sunflower silage (SunS). Samples of both WPSun (n= 73) and SunS (n= 50) were analysed by reference method and scanned in reflectance using a NIR monochromator instrument (400–2500 nm). Calibration models were developed between NIR data and reference values for dry matter (DM), crude protein (CP), ash, acid detergent fibre (ADFom), neutral detergent fibre (aNDFom), in vitroorganic matter digestibility (OMD), ether extract (EE) and pH using partial least squares regression (PLS). Due to the limited number of samples full cross-validation was used to test the calibration models. The best correlations (R2cal) and lowest standard errors in cross-validation (SECV)were obtained for DM (R2cal>0.82, SECV: 27.0 and 35.8 g kg−1), CP (R2cal> 0.85, SECV: 9.9 and 10.1 g kg−1) and ash (R2cal> 0.85, SECV11.2 and 8.2 g kg−1) in both WPSun and SunS samples, respectively. For ADFom, aNDFom and OMD the calibrations were considered to be poor (R2cal<0.85). In SunS samples a good correlation was found for EE (R2cal= 0.94, SECV: 15.3 g kg−1).

Near infrared (NIR) reflectance spectroscopy was used as a tool to classify beef muscle samples according to their feeding regime. Seventy-eight beef longissimus dorsimuscle samples both intact and minced were scanned in a NIRS 6500 instrument (NIRSystems, MD, USA) in reflectance. A dummy regression technique was developed to differentiate beef muscle samples, which originated from beef feed exclusively on pasture or/and mainly on corn silage feeding regimes. Ninety percent of the pasture-fed beef muscle samples were correctly classified using principal component regression (PCR) and 86% of beef fed on corn silage were correctly classified. Both muscle chemical composition and physical characteristics explained the classification results. The results in the present study showed the potential of muscle optical properties for classification and traceability of meat muscles in the food chain.