Masters Degrees (Food Science)
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Browsing Masters Degrees (Food Science) by browse.metadata.advisor "Allsopp, Mike"
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- ItemHoney authentication: effect of irradiation and ageing on near-infrared (NIR) spectroscopy classification models(Stellenbosch : Stellenbosch University, 2020-03) Rust, Alexandra Elizabeth; Manley, Marena; Williams, Paul James; Allsopp, Mike; Stellenbosch University. Faculty of AgriSciences. Dept. of Food Science.ENGLISH ABSTRACT: Near-infrared (NIR) spectroscopy was used to investigate the effects of syrup dilution, ageing, storage temperature and irradiation treatment on the NIR spectra of honey. Additionally, NIR spectroscopy and partial least squares discriminant analysis (PLS-DA) were employed to develop a classification model for the rapid screening of high-fructose corn syrup (HFCS) and invert cane sugar syrup (ICSS) diluted honey. Detection of irradiation treatment was also investigated, to assess NIR spectroscopy-based models as a potential screening tool for detecting mislabelled honey. Unfiltered and unheated honey samples (n = 17) obtained from South African beekeepers were uniformly strained and subjected to treatment combinations of 10 kGy gamma irradiation and dilution with 0, 10 or 20% (w/w) ICSS or HFCS to create sub-samples (n = 174) which were stored at 25°C. Another three undiluted subsets were stored at 4°C, 40°C and in uncontrolled ambient conditions (n = 51). A benchtop BÜCHI Fourier transform-near infrared (FT-NIR) spectrometer and a portable MicroNIR NIR spectrometer, with ranges of 1000–2500 nm and 908-1676 nm respectively, were used to acquire triplicate spectral measurements, over a period of 9 months. ANOVA-simultaneous component analysis (ASCA) indicated that honey type, diluent type, storage temperature and age had significant (p > 0.05) effects on the spectral dataset, while diluent level and irradiation treatment did not. Despite this, irradiation treatment was found to reduce the validation accuracy and efficacy of authentication models, by 5.82% and 7.19% respectively, when PLS-DA models based on only irradiated and only non-irradiated spectral data were compared, suggesting that authentication may be impeded by irradiation treatment to some degree. However, a PLS-DA model discriminating on the basis of irradiation treatment obtained an unsuccessful validation classification of 59.7%, suggesting that there is little or no utilisable effect of irradiation on the spectral data. The best-performing authentication solutions were individual two-class PLS-DA models for detecting ICSS (75.95% accuracy, 86.31% sensitivity) and HFCS (73.95% accuracy, 82.14% sensitivity) dilution, which demonstrated predictive power adequate for screening purposes. PLS-DA models based on spectral data acquired with the benchtop BÜCHI instrument performed best when compared with the portable MicroNIR instrument and its two sample presentation formats. Despite this, the MicroNIR with Teflon cup sample presentation was shown to be a feasible and cost-effective alternative, demonstrating similar accuracies (70.0-75.47%) and efficiencies (68.22-74.51%). In addition, quantification of the level of diluent with partial least squares regression (PLSR) was poor for both ICSS (R2 Pred = 0.118, RMSEP = 6.795%) and HFCS (R2 Pred = 0.147, RMSEP = 6.596%) dilutions. This was attributed to an inadequate range of dilution levels in the reference data, as well as the insignificant effect (p < 0.05) of diluent level on the overall variation in the spectral data. The findings of this study highlighted the potential shortcomings of NIR spectroscopy models in providing definite authentication, while demonstrating the capabilities of this technique for authenticity screening.
- ItemVinnige identifikasie van botaniese- en geografiese oorsprong van Suid-Afrikaanse heuning(Stellenbosch : Stellenbosch University, 2020-12) Vermeulen, Marguerite Antoinette; Manley, Marena; Williams, Paul James; Allsopp, Mike; Stellenbosch University. Faculty of AgriSciences. Dept. of Food Science.ENGLISH ABSTRACT: The botanical and geographic origin has the greatest influence on the properties of honey, and so it affects the price of honey as well. Therefore, it is important to determine the origin of the honey. Mellisopalionology analysis is the traditional method of determining the botanical and geographical origins of honey, but it is time consuming and requires an expert. This study aimed to develop a quick and easy method to determine the botanical and geographical origin of South African honey. NIR spectroscopy was used in conjunction with partial least squares discriminant analysis (PLSDA) for classification. Two different instruments were used for scanning honey, namely the benchtop instrument and the handheld instrument. The benchtop instrument in transflection and the handheld in diffusion reflection. The handheld instrument was used with two different presentation modes, a Teflon cup and a glass vial. The average spectra of the benchtop instrument indicated four main absorption bands at 1460 (sugar and moisture related), 1940 (moisture related), 2090 and 2280 nm (both sugar related) while the handheld intrument only indicated two main absorption bands for each presentation mode at 995 (aromatic related) ) and 1200 nm (sugar related), and 1200 and 1450 nm (sugar and moisture related) for the Teflon cup and glass vial respectively. The main component analysis (PCA) score plots for the botanical classification showed poor separation between the classes [fynbos (Sandveld and Strandveld) and ‘others’ (lucerne, macadamia, red river gum, saligna, citrus)]. This is due to the complexity of honey. For the geographic classification, the PCA score plots showed better separation especially for the Hopefield and Stanford classes. The Stellenbosch class overlapped with the other two classes. The reason for this was that Stellenbosch's vegetation is a mixture of mostly fynbos and Eucalyptus, while Hopefield has mostly fynbos and Stanford mostly has Eucalyptus. The hand model (Teflon cup) showed the best classification botanical classification with a prediction accuracy of 79.63%. This accuracy shows that fynbos could not be successfully distinguished from the ‘other’ honey, but does have the potential if a larger sample set can be collected. The geographical classification achieved an overall good predictive accuracy of 84.21% with the hand model (glass vial). This therefore appears to have been classified between the geographical origins, but by going back to the PCA score plots it can be seen that the classification is rather based on the botanical origin of the samples which is therefore a distinction between fynbos and Eucalyptus honey. With this finding, it shows that a distinction can be made between the botanical origin of South African honey, but a larger sample set is needed.