The importance of objective, on-line evaluation of the nutritional and sensory characteristics of fresh meat is increasing for both selective and commercial purposes. NIRS (Near-Infra-Red Spectroscopy) may allow to reach these objectives. The aim of this study was to evaluate the possibility to predict by NIRS the chemical composition and physical properties of beef. The spectra were collected by using NIRFLex N-500 (Büchi, Switzerland) on samples of Longissimus dorsi m. dissected at slaughter from 280 young bulls. The spectral acquisition was obtained in a range from 4,000 to 10,000 cm-1 on entire fresh meat, kept at 4 °C for 48 h. The proximate and fatty acids (FA) analysis, color, cooking loss, Warner Bratzler shear force (WBSF) were carried out on the same samples. The chemometric analyses were performed using Buchi NIRCal 5.5. The PLS models predicted humidity with a coefficient of determination of calibration (R2 c) of 0.682 (standard error of calibration, SEC, 1.09%, n=173) and a coefficient of determination of validation (R2 p) of 0.479 (standard error of validation, SEP, 1.11%, n=85), ether extract (R2 c=0.594; SEC=0.59%, n=110; R2 p=0.550; SEP=0.54%, n=47), ash (R2 c=0.760; SEC=0.06%, n=205; R2 p=0.787; SEP=0.05%, n=73), lightness (R2 c=0.555; SEC=1.90, n=122; R2 p=0.557; SEP=1.89, n=58), WBSF (R2 c=0.781; SEC=5.09N, n=134; R2 p=0.740; SEP=5.15N, n=57), cooking loss (R2 c=0.693; SEC=2.84%, n=96; R2 p=0.714; SEP=2.80%, n=45), monounsaturated FA (R2 c=0.756; SEC=1.83%, n=119; R2 p=0.738; SEP=1.82%, n=49), polyunsaturated FA (R2 c=0.854; SEC=2.25%, n=115; R2 p=0.869; SEP=2.21%, n=56). In conclusion, NIRS was able to reliably predict proximate and FA composition, color, cooking loss, and WBSF of entire fresh meat. Consequently, it may be a useful technology for an on-line application. This project was funded by CRITA of FVG Autonomous Region.
Beef characteristics predicted by NIRS / Corazzin, M.; Saccà, E.; Bozzi, Riccardo; Ferrari, G.; Negrini, R.; Piasentier, E.. - ELETTRONICO. - (2017), pp. 330-330. (Intervento presentato al convegno 68th Annual Meeting of the European Federation of Animal Science tenutosi a Tallin (Estonia) nel 28 August - 1 September, 2017) [10.3920/978-90-8686-859-9].
Beef characteristics predicted by NIRS
R. Bozzi;
2017
Abstract
The importance of objective, on-line evaluation of the nutritional and sensory characteristics of fresh meat is increasing for both selective and commercial purposes. NIRS (Near-Infra-Red Spectroscopy) may allow to reach these objectives. The aim of this study was to evaluate the possibility to predict by NIRS the chemical composition and physical properties of beef. The spectra were collected by using NIRFLex N-500 (Büchi, Switzerland) on samples of Longissimus dorsi m. dissected at slaughter from 280 young bulls. The spectral acquisition was obtained in a range from 4,000 to 10,000 cm-1 on entire fresh meat, kept at 4 °C for 48 h. The proximate and fatty acids (FA) analysis, color, cooking loss, Warner Bratzler shear force (WBSF) were carried out on the same samples. The chemometric analyses were performed using Buchi NIRCal 5.5. The PLS models predicted humidity with a coefficient of determination of calibration (R2 c) of 0.682 (standard error of calibration, SEC, 1.09%, n=173) and a coefficient of determination of validation (R2 p) of 0.479 (standard error of validation, SEP, 1.11%, n=85), ether extract (R2 c=0.594; SEC=0.59%, n=110; R2 p=0.550; SEP=0.54%, n=47), ash (R2 c=0.760; SEC=0.06%, n=205; R2 p=0.787; SEP=0.05%, n=73), lightness (R2 c=0.555; SEC=1.90, n=122; R2 p=0.557; SEP=1.89, n=58), WBSF (R2 c=0.781; SEC=5.09N, n=134; R2 p=0.740; SEP=5.15N, n=57), cooking loss (R2 c=0.693; SEC=2.84%, n=96; R2 p=0.714; SEP=2.80%, n=45), monounsaturated FA (R2 c=0.756; SEC=1.83%, n=119; R2 p=0.738; SEP=1.82%, n=49), polyunsaturated FA (R2 c=0.854; SEC=2.25%, n=115; R2 p=0.869; SEP=2.21%, n=56). In conclusion, NIRS was able to reliably predict proximate and FA composition, color, cooking loss, and WBSF of entire fresh meat. Consequently, it may be a useful technology for an on-line application. This project was funded by CRITA of FVG Autonomous Region.File | Dimensione | Formato | |
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