A stable isotope and chemometric framework for non-targeted detection of adulterations in milk

dc.contributor.authorFernando, B.R.
dc.contributor.authorKalpage, M.D.
dc.contributor.authorDissanayake, C.K.K.
dc.contributor.authorFrew, R.D.
dc.date.accessioned2026-06-15T08:19:53Z
dc.date.available2026-06-15T08:19:53Z
dc.date.issued2023-09-20
dc.description.abstractDairy is the most important subsector in the livestock industry in Sri Lanka due to the growing demand for fresh milk and its potential influence on the rural economy. Adulteration of milk reduces its quality and may introduce hazardous substances into the dairy supply chain jeopardizing consumers’ health. The present study used stable isotopes to identify adulterations in milk based on multivariate chemometric modelling techniques. Thirty-six authentic milk samples were collected throughout the year from the farm belonging to the Faculty of Veterinary Medicine and Animal Science, University of Peradeniya. A set of adulterated milk samples was prepared with possible adulterants including sodium bicarbonate, hydrogen peroxide, sodium chloride, sugar, urea, vegetable oil and water. The milk components such as fat, casein, and whey, were extracted from all the authentic samples and adulterated milk samples. Samples were analyzed using Isotope Ratio Mass Spectrometer (IRMS) for δ13C and δ15N. The results of isotope compositions of the samples were statistically evaluated using R-Studio version 4.2.0. A preliminary data analysis was carried out using descriptive statistics including box plots and scatter diagrams. Principle component analysis (PCA) was performed to check whether the combined isotopic parameters could be used to distinguish adulterated milk samples from authentic milk samples. A linear discriminant analysis (LDA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA) test was performed to discriminate adulterated milk samples. The results revealed that adulterated milk can be distinguished from authentic milk using stable isotope data combined with chemometrics with classification accuracies of more than 96%. The present study provides empirical evidence on the ability of IRMS in the detection of adulterated cow milk. Further, this study provides insight into non-targeted milk screening for adulterants using stable isotope information and a chemometric framework. Further investigations are required to confirm the promising results of this study.
dc.description.sponsorshipThis research was funded by the International Atomic Energy Agency, Vianna (IAEA), Coordinated Research Project (D52038).
dc.identifier.citationProceedings of the Peradeniya University International Research Sessions (iPURSE) – 2023, University of Peradeniya, P 197
dc.identifier.issn1391-4111
dc.identifier.urihttps://ir.lib.pdn.ac.lk/handle/20.500.14444/7803
dc.language.isoen_US
dc.publisherUniversity of Peradeniya, Sri Lanka
dc.subjectMilk
dc.subjectAuthenticity
dc.subjectIsotopes
dc.subjectChemometrics
dc.titleA stable isotope and chemometric framework for non-targeted detection of adulterations in milk
dc.typeArticle

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