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Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling

Kiah Edwards, Marena Manley, Louwrens C. Hoffman, Anel Beganović, Christian G. Kirchler, Christian W. Huck, Paul J. Williams

2020Molecules22 citationsDOIOpen Access PDF

Abstract

Near-infrared (NIR) spectroscopy, combined with multivariate data analysis techniques, was used to rapidly differentiate between South African game species, irrespective of the treatment (fresh or previously frozen) or the muscle type. These individual classes (fresh; previously frozen; muscle type) were also determined per species, using hierarchical modelling. Spectra were collected with a portable handheld spectrophotometer in the 908-1676-nm range. With partial least squares discriminant analysis models, we could differentiate between the species with accuracies ranging from 89.8%-93.2%. It was also possible to distinguish between fresh and previously frozen meat (90%-100% accuracy). In addition, it was possible to distinguish between ostrich muscles (100%), as well as the forequarters and hindquarters of the zebra (90.3%) and springbok (97.9%) muscles. The results confirm NIR spectroscopy's potential as a rapid and non-destructive method for species identification, fresh and previously frozen meat differentiation, and muscle type determination.

Topics & Concepts

Near-infrared spectroscopyLinear discriminant analysisSpectroscopyPartial least squares regressionChemistryMultivariate statisticsAnalytical Chemistry (journal)BiologyChromatographyMathematicsPhysicsStatisticsQuantum mechanicsNeuroscienceIdentification and Quantification in FoodMeat and Animal Product QualitySpectroscopy and Chemometric Analyses
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