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Title: Chemical profiling of honey produced in the Maltese Islands
Authors: Formosa, Jean Paul (2017)
Keywords: Honey -- Malta
Bee products -- Malta
Honey -- Malta -- Gozo
Issue Date: 2017
Citation: Formosa, J. P. (2017). Chemical profiling of honey produced in the Maltese Islands (Master’s dissertation).
Abstract: Maltese honey has been produced, marketed and sold as an exclusive local gourmet food product for countless years. Yet thus far no study has evaluated the individuality of this local food product, even though the evaluation of the parameters and properties which characterise the provenance and floral source of honey have been the subject of various studies worldwide, owing to the price and potential beneficial properties of this food product. The HMF content, sugar composition, phenolic profile and trace element content of thirteen Maltese and eight Gozitan samples directly collected from beekeepers were analysed. Phenolic profiling showed that the local honey studied can be characterised into three main groups of; carob and eucalyptus honey, Maltese honey and Gozitan honey. Possible chemical markers for local carob and eucalyptus honey were also highlighted. A distinction between Maltese and Gozitan honey was also observed in the sugar composition with Gozitan honey generally having a significantly lower amount of fructose and significantly higher amounts of sucrose, turanose, melezitose and two other oligosaccharides. Models analysing the potential of ATR-FT-MIR and fluorescence spectroscopy in discriminating and classifying local honey from that of foreign origin were investigated using the aforementioned honey samples and 49 foreign honey samples. These included samples from Sicily, Greece, Sweden, Italy, France and other samples of mixed geographical origin. Through a combination of spectroscopic techniques, spectral transformations, variable selection and PLS-DA, chemometric models which successfully classified the provenance of local and non-local honey were developed, with some models showing 100% accuracy. The results of these models were also corroborated with other classification and pattern recognition techniques such as LDA, SVM, and FF-AAN, and also with results from phenolic profiling. Furthermore eight "off the shelf' samples claiming to be local were also tested and characterised in order to further asses model consistency and also to assess the quality and authenticity of honey being sold at local markets.
Description: M.SC.CHEMISTRY
Appears in Collections:Dissertations - FacSci - 2017
Dissertations - FacSciChe - 2017

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