Rapid differentiation of South African game meat using portable near-infrared (NIR) spectroscopy

[摘要] ENGLISH ABSTRACT: The South African game meat industry operates as a free-market enterprise; however, this can create certain problems for producers and consumers. For example, in South Africa no standardised meat cuts exist and there are no quality standards in place for game. Therefore, allowing the legal sale of inferior quality game meat. Due to a general lack of regulations as well as varying carcass dressings, the chance that a species may be mislabelled or substituted is greatly increased.In recent years, meat authenticity awareness has increased, as there have been incidences where meat has been fraudulently mislabelled. Typical cases involve the intentional substitution of high value raw ingredients with inferior species or materials, the addition of non-declared proteins from several origins, or the marketing of frozen-thawed meat as fresh. This type of food fraud concerns consumers in terms of economic loss, food allergies, religious compliance, and food safety. This study aimed to investigate a feasible alternative to the manual, tedious and time-consuming conventional analytical methods used for meat differentiation and authentication that could provide the meat industry with a rapid, non-destructive, accurate and reliable solution in the near future.Near-infrared (NIR) spectroscopy combined with multivariate data analysis (MDA) techniques were used to rapidly differentiate between South African game species, irrespective of the treatment (fresh or previously frozen) or the muscle type as well as determine these individual classes (fresh; previously frozen; frozen period; muscle type) per species. Meat samples of four game species [black wildebeest (Connochaetes gnou), zebra (Equus quagga burchelli), springbok (Antidorcas marsupialis), ostrich (Struthio camelus)] were scanned at ca. 23° C. Spectra were collected with a portable MicroNIR OnSite spectrophotometer (Viavi Solutions Inc., Milpitas, USA), in the range of 908 – 1676 nm, after which the data was analysed using MDA.It was possible to differentiate between game species, irrespective of the treatment (fresh or previously frozen), the frozen period or the muscle type. The partial least squares discriminant analysis (PLS-DA) model was successful and achieved accuracies ranging 89.8 – 93.2%. It was also possible to distinguish between fresh and previously frozen meat, and with low accuracies determine the frozen period. The principal component analysis (PCA) score plots illustrated good separation between the fresh and frozen-thawed samples, however, the frozen-thawed samples exhibited an overlap between the individual frozen periods. Therefore, lacking separation and distinct clustering for the different frozen periods. Thus, the MDA models were not effective when trying to classify the different frozen periods. The PLS-DA models could however discriminate between the fresh and previously frozen meat, irrespective of the frozen period or muscle type. The black wildebeest (99.2%), zebra (94.4 and 99.3%), springbok (100%) and ostrich (90 and 98.3%) models achieved good overall accuracies.Lastly, this study found that the ostrich muscles could be distinguished from each other with a 100% accuracy. Furthermore, the results suggested that discrimination of the different muscle types for both zebra and springbok was less sufficient due to the lack of separation between the different muscles.Misclassification mostly occurred between muscles that are anatomically located near to one another. Therefore, the samples with spectral similarities were grouped to form a two-group class discrimination model. The PLS-DA results showed that it was possible to differentiate between the forequarters and hindquarters of the zebra (90.3%) and springbok (97.9%) muscles.The results showed NIR spectroscopy's potential as a rapid and non-destructive method for species identification, fresh and previously frozen meat differentiation as well as muscle type determination. Furthermore, this technique has the potential of providing the South African game meat industry with an alternative technique to the current manual, destructive and time-consuming authentication methods.

[发布机构] Stellenbosch University