Illicit Drug Analysis in Blood Samples with Multivariate Analysis Using Surface-Enhanced Raman Spectroscopy

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dc.authoridAcikgoz, Gunes/0000-0001-9118-3153
dc.contributor.authorAcikgoz, Gunes
dc.contributor.authorColak, Abdullah
dc.date.accessioned2024-09-18T21:07:45Z
dc.date.available2024-09-18T21:07:45Z
dc.date.issued2023
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractThis study aims to discriminate different types of illicit drugs ( MDMA and THC) in blood samples using surface- enhanced Raman spectroscopy ( SERS) combined with chemometric techniques including principal components analysis (PCA) and par tial least squares discriminant analysis (PLS- DA). A PLS- DA classification model was built using a training data set containing Raman spectra from control and experimental groups (drug-detected blood). PLS- DA was performed for discrimination and classification among blood samples. The scores obtained in the PLS- DA model were used to evaluate the performance of the created model. The leave one out cross-validation (LOOCV) method was used for calibration and validation of the PLS-DA model. In the study, it was observed that the SERS method and chemometric techniques together could be used in drug analysis, even at low concentrations in complex body fluids such as blood. As a result, Raman spectroscopy with PCA and PLS- DA methods of data analysis could be used extensively to build similar or different classification models.en_US
dc.identifier.endpage27en_US
dc.identifier.issn0887-6703
dc.identifier.startpage20en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12483/13911
dc.identifier.volume38en_US
dc.identifier.wosWOS:001064160600003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherMjh Life Sciencesen_US
dc.relation.ispartofSpectroscopyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleIllicit Drug Analysis in Blood Samples with Multivariate Analysis Using Surface-Enhanced Raman Spectroscopyen_US
dc.typeArticleen_US

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