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Detection of addition of fats non-dairy origin into milk products

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dc.contributor.author CHIRA, Nicoleta
dc.contributor.author TOCIU, Mihaela
dc.contributor.author POPESCU, Liliana
dc.contributor.author IVANOVA, Mihaela
dc.contributor.author BRATU, Aurelia
dc.contributor.author MIHALACHE, Mihaela
dc.contributor.author DELEANU, Calin
dc.date.accessioned 2021-10-13T10:25:57Z
dc.date.available 2021-10-13T10:25:57Z
dc.date.issued 2021
dc.identifier.citation CHIRA, Nicoleta, TOCIU, Mihaela, POPESCU, Liliana ș. a. Detection of addition of fats non-dairy origin into milk products. In: Intelligent Valorisation of Agro-Food Industrial Wastes. Book of abstracts. International Conference, 7-8 October 2021. Chișinău, 2021, p. 22. ISBN 978-9975-3464-2-9. en_US
dc.identifier.isbn 978-9975-3464-2-9
dc.identifier.uri http://repository.utm.md/handle/5014/17707
dc.description Abstract. en_US
dc.description.abstract This work deals with the detection of adulteration of dairy products, which in some countries (especially the developing countries) is seen as a serious issue. Possible adulterants for milk fat (MF) are waste oils from both vegetal (sunflower, soybean, rapeseed) and animal (lard, beef/sheep tallow, chicken fat) origin. MF contrasts with other fats and oils by its short (C4-C6) and medium (C8-C12) chain fatty acids composition. The standard method to accurately determine of the fatty acids profile (FAP) of milk and dairy products is gas-chromatography (GC), which requires the methylation of the fatty acids to the corresponding methyl esters, prior to their chromatographic separation. As a result, the GC method is laborious and time-consuming, given the chromatographic separation step is also long (approximately 1 hour). Consequently, faster alternative methods are welcome. Materials and methods: Three descriptors of conformity/adulteration were determined for each sample, based on the 1H-NMR data (in particular, based on the integral values of resonances associated with chain length, unsaturation, and butyric moiety). Each fat sample was consequently characterized by three numerical values, corresponding to the descriptors. Results: Cartesian 3D representation of samples revealed their clustering according to fat type, leading to good classification. Adulterated samples placed outside the groups, as outliers. Conclusions: The classification model according to the H-NMR based descriptors allows visualization of adulterated samples. en_US
dc.language.iso en en_US
dc.publisher Universitatea Tehnică a Moldovei en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject butyric acid en_US
dc.subject adulteration en_US
dc.subject milk fat en_US
dc.subject H-NMR descriptors en_US
dc.subject 3D data visualization en_US
dc.title Detection of addition of fats non-dairy origin into milk products en_US
dc.type Article en_US


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