Prediction and classification of tenderness in beef from non-invasive diode array detected NIR spectra

NIR absorbance spectra of 48 beef samples were recorded 2, 9 and 21 days po st mortem in the wavelength range 950-1700 nm with a Zeiss MCS 511 instrume nt equipped with diode array detector. These spectra were used to predict t enderness of the meat samples when Warner-Bratzler (WB) shear force was use d as the reference method. Two types of prediction models were made. The mo dels were either based on NIR spectra alone or NIR spectra in combination w ith information about post slaughter treatments. Prediction models from NIR spectra alone gave correlation coefficients in the range 0.52-0.83, but wh en variables for post slaughter treatments were included in the models the correlation coefficients were in the range 0.71-0.85. The additional variab les had no effect on the prediction results when tenderness was predicted a t the same time as NIR spectra were acquired, but improvements were found w hen tenderness was forecast later than the spectral acquisition. Based on t hese prediction models the beef samples were classified into two or three t enderness groups. When the beef samples were classified into two groups, 73 -98% of the samples were correctly classified, while there were 63-75% corr ect classified samples when they were allocated into three groups.