Vitenskapelig artikkel

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

Rødbotten, Rune; Mevik, Bjørn-Helge; Hildrum, Kjell Ivar

Publikasjonsdetaljer

Tidsskrift: Journal of Near Infrared Spectroscopy, vol. 9, p. 199–210, 2001

Utgave: 3

Internasjonale standardnumre:
Trykt: 0967-0335
Elektronisk: 1751-6552

Open Access: none

Lenker:
DOI

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