Discrimination of diesel fuels marketed in Morocco using FTIR, GC-MS analysis and chemometrics methods

The purpose of this study was to perform a discrimination and classification of diesel samples from the four major suppliers of petroleum products in Morocco using Fourier Transform Infrared Spectroscopy (FTIR), Gas Chromatography coupled with Mass Spectrometry (GC-MS) and chemometrics tools. Eighty...

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Bibliographic Details
Published in:Talanta (Oxford) 2020-03, Vol.209, p.120543-120543, Article 120543
Main Authors: Barra, Issam, Kharbach, Mourad, Bousrabat, Mohamed, Cherrah, Yahia, Hanafi, Mohamed, Qannari, El Mostafa, Bouklouze, Abdelaziz
Format: Article
Language:English
Subjects:
Analytical chemistry
Chemical Sciences
Cheminformatics
Chemometrics
Diesel
FTIR
GC-MS
PLS discriminant analysis
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Summary:The purpose of this study was to perform a discrimination and classification of diesel samples from the four major suppliers of petroleum products in Morocco using Fourier Transform Infrared Spectroscopy (FTIR), Gas Chromatography coupled with Mass Spectrometry (GC-MS) and chemometrics tools. Eighty diesel samples were collected from different gas stations owned by the four biggest brands in the Moroccan market. Principal Component Analysis (PCA) was performed to depict the similarities between the samples and check the presence of outliers. Partial Least Squares Discriminant Analysis (PLS-DA) models were set up for the discrimination and the classification of the four groups of samples (i.e., diesel suppliers). The models proposed in this study, were characterized by good prediction abilities, especially the FTIR-PLSDA model that was characterized by 100% of accurate discrimination of the four groups. The approach of analysis showed that the FTIR spectra can provide a cheap and rapid means for the determination of the diesel origin and to ensure the traceability of diesel products marketed in Morocco with respect for the rules of the green chemistry. [Display omitted] •The first comprehensive classification of diesel fuels by suppliers.•GC-MS and FTIR fingerprints of 80 diesel samples were plotted.•A comparison of the classification ability between two PLS-DA models set up on the FTIR and GC-MS data was done.•The FTIR-PLS-DA model gave the best results for diesel fuels classification by suppliers.
ISSN:0039-9140
1873-3573
DOI:10.1016/j.talanta.2019.120543