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Differentiation of edible fats from selected sources after heating treatments using fourier transform infrared spectroscopy (FTIR) and multivariate analysis

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dc.Conferencecode137127
dc.Conferencedate7 November 2017 through 8 November 2017
dc.ConferencenameInternational Conference on Recent Advancements in Science and Technology 2017, ICoRAST 2017
dc.FundingDetailsMinistry of Higher Education and Scientific Research
dc.FundingDetailsThe research financial was fully supported by Ministry of Higher Education under Fundamental Research
dc.citedby1
dc.contributor.affiliationsInstitute of Halal Research and Management (IHRAM)
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.affiliationsUniversiti Teknologi MARA (UiTM)
dc.contributor.authorSalleh N.A.M.en_US
dc.contributor.authorHassan M.S.en_US
dc.contributor.authorJumal J.en_US
dc.contributor.authorHarun F.W.en_US
dc.contributor.authorJaafar M.Z.en_US
dc.date.accessioned2024-05-28T08:28:18Z
dc.date.available2024-05-28T08:28:18Z
dc.date.issued2018
dc.description.abstractLard consumption is forbidden for Muslim people and researches have been done to differentiate lard from other fats for Halal authentication. Therefore, this study was conducted to differentiate lard from other edible fats after heating treatments using Fourier transformed infrared spectroscopy (FTIR) and multivariate data analysis techniques. Five samples of fats from different sources; lard, chicken, mutton, tallow and palm based shortening were heated at different temperature (120, 180 and 240°C) and time (30, 60, 120 and 180 min). The spectra in the form of multivariate data were acquired using FTIR spectroscopy. Principal components analysis (PCA), k-mean cluster analysis (k-mean CA) and linear discriminant analysis (LDA) were used to compare the ability of each technique to differentiate the fats after the heating treatments. It was found that the combination of PCA with k-mean CA was able to differentiate heated fats according to its origin. LDA method was successfully used to classify 80.5 % of samples in its group. Thus, PCA, CA and LDA can be used as multivariate data analysis to differentiate the heated edible fats.en_US
dc.description.natureFinalen_US
dc.editorAli E.S.Yatim N.M.Harun F.W.en_US
dc.identifier.doi10.1063/1.5041236
dc.identifier.isbn9780740000000
dc.identifier.issn0094243X
dc.identifier.scopus2-s2.0-85048860046
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85048860046&doi=10.1063%2f1.5041236&partnerID=40&md5=9d4c2b5cc7cb4b1b9c3981f6f27b11ac
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/8848
dc.identifier.volume1972
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherAmerican Institute of Physics Inc.en_US
dc.relation.ispartofOpen Accessen_US
dc.relation.ispartofAIP Conference Proceedings
dc.sourceScopus
dc.titleDifferentiation of edible fats from selected sources after heating treatments using fourier transform infrared spectroscopy (FTIR) and multivariate analysisen_US
dc.title.alternativeAIP Conf. Proc.en_US
dc.typeConference Paperen_US
dspace.entity.typePublication

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