Publication | Open Access
Prediction of pH and color in pork meat using VIS-NIR Near-infrared Spectroscopy (NIRS)
24
Citations
36
References
2018
Year
Food AnalysisPork MeatMeat QualityPartial Least SquaresFood ChemistryVis-nir Near-infrared SpectroscopyFood AuthenticationBioanalysisAnalytical ChemistryBiostatisticsBiophysicsHealth SciencesAnimal PhysiologyPorcine Ld MuscleInfrared SpectroscopyFeed EvaluationMeat Quality AnalysisNear-infrared SpectroscopyFood QualityMeat PackagingSpectroscopyPhysiologyMedicine
The potential of near-infrared spectroscopy (NIRS) to predict the physicochemical characteristics of the porcine longissimus dorsi (LD) muscle was evaluated in comparison to the standard methods of pH and color for meat quality analysis compared to the pH results with Colorimeter and pH meter. Spectral information from each sample (n = 77) was obtained as the average of 32 successive scans acquired over a spectral range from 400 - 2498 nm with a 2 - nm gap for calibration and validation models. Partial least squares (PLS) regression was used for each individual model. An R2 and a residual predictive deviation (RPD) of 0.67/1.7, 0.86/2, and 0.76/1.9 were estimated for color parameters L*, a *, and b*, respectively. Final pH had an R2 of 0.67 and a RPD of 1.6. NIRS showed great potential to predict color parameter a * of porcine LD muscle. Further studies with larger samples should help improve model quality.
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