Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/119284
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dc.titleAuthentication of Edible Bird's Nest using Advanced Analytical Techniques and Multivariate Data Analysis
dc.contributor.authorCHUA YONG GUAN, PETER
dc.date.accessioned2015-03-31T18:01:57Z
dc.date.available2015-03-31T18:01:57Z
dc.date.issued2014-07-22
dc.identifier.citationCHUA YONG GUAN, PETER (2014-07-22). Authentication of Edible Bird's Nest using Advanced Analytical Techniques and Multivariate Data Analysis. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/119284
dc.description.abstractThe authenticity issue involving edible bird?s nest (EBN) has affected the consumer?s confidence. Instead of relying on current techniques, new analytical methods are developed and applied in combination with multivariate data analysis to tackle the problem of authenticity. Hotelling T2 range plot illustrated that it is feasible to identify EBN as well as, to differentiate matries similar to EBN, thereby resolving the issues of quality control and species of origin of EBN. Classification of EBN according to its coloration, country of origin and production site could be done with metabolite fingerprinting and supervised score plots. Moreover, score plots based on the data from gas chromatography mass spectrometer demonstrated better prediction abilities. In qualitative discrimination, principal component analysis is able to discriminate EBN from spiked samples at the level of 0.5 %. In quantitative analysis, accurate prediction of spiked sample was shown to detect as low as 1 % of adulterants.
dc.language.isoen
dc.subjectedible bird's nest, authentication, multivariate analysis
dc.typeThesis
dc.contributor.departmentCHEMISTRY
dc.contributor.supervisorLI FONG YAU, SAM
dc.contributor.supervisorLEONG LAI PENG
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Ph.D Theses (Open)

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