Classification of game meat species Springbok (Antidorcas marsupialis) and Blesbok (Damaliscus pygargus phillipsi) with NIR hyperspectral imaging

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dc.contributor.advisorWilliams, Paul Jamesen_ZA
dc.contributor.advisorManley, Marenaen_ZA
dc.contributor.advisorHoffman, Louwrens C.en_ZA
dc.contributor.authorMakhubo, Qhakazile Angelen_ZA
dc.contributor.otherStellenbosch University. Faculty of AgriSciences. Dept. of Food Science.en_ZA
dc.date.accessioned2020-02-21T13:33:18Z
dc.date.accessioned2020-04-28T15:13:41Z
dc.date.available2020-02-21T13:33:18Z
dc.date.available2020-04-28T15:13:41Z
dc.date.issued2020-12
dc.descriptionThesis (MScFoodSc)--Stellenbosch University, 2020.en_ZA
dc.description.abstractENGLISH ABSTRACT: Game meat is a lucrative alternative to domesticated meat. It is lower in fat and is an organic product, as it complies with organic agricultural enterprises. However, the game meat industry operates as a free-market in South Africa and is a high value product, making it a vulnerable target to food fraud. The development of methods to assess the authenticity of game meat would be a favourable investment for both the consumer and producers. Thus, this investigation aimed to classify different game meat species, namely Springbok (Antidorcas marsupialis) and Blesbok (Damaliscus pygargus phillipsi) using NIR hyperspectral imaging. Additionally, classification of the different muscles, namely the longissimus thoracis et lumborum (LTL), biceps femoris (BF), semimembranosus (SM), semitendinosus (ST), infraspinatus (IS) and supraspinatus (SS), and classification the species irrespective of the muscle was investigated. NIR hyperspectral imaging offers rapid measurement of data, and provide both spatial and spectral information. Two analytical approaches, namely pixel and object wise were investigated. Multivariate analysis techniques, namely principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied for exploratory and classification purposes, respectively. Object-wise analysis performed better in comparison to pixel-wise, with the classification accuracies of 95.90 and 71.49 % respectively. Additionally, the species could successfully be classified when using one muscle and when any muscle of the six muscles was used. Classification of the muscles was successful, however, grouping into hindquarter (containing the BF, ST, SM), forequarter (containing the IS and SS) and LTL had to be done to achieve this. Moreover, despite the successful classification, the other statistical parameters used to assess models were unsatisfactory.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Geen opsomming beskikbaar.af_ZA
dc.description.versionMastersen_ZA
dc.format.extent143 : illustrations (some color)en_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/108433
dc.language.isoen_ZAen_ZA
dc.language.isoen_ZAen_ZA
dc.subjectGame meat -- Classification -- South Africaen_ZA
dc.subjectBlesbok -- Carcassesen_ZA
dc.subjectSpringbok -- Carcassesen_ZA
dc.subjectNIR hyperspectral imagingen_ZA
dc.subjectVariable importance in projection (VIP)en_ZA
dc.subjectWildlife as fooden_ZA
dc.subjectChemometricsen_ZA
dc.subjectPrincipal components analysisen_ZA
dc.subjectUCTDen_ZA
dc.titleClassification of game meat species Springbok (Antidorcas marsupialis) and Blesbok (Damaliscus pygargus phillipsi) with NIR hyperspectral imagingen_ZA
dc.typeThesisen_ZA
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