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Discriminant analysis of biodiesel fuel blends based on combined data from Fourier Transform Infrared Spectroscopy and stable carbon isotope analysis
Pontificia Univ Catolica Rio Grande do Sul, Brazil.ORCID iD: 0000-0002-2565-4831
Pontificia Univ Catolica Rio Grande do Sul, Brazil.
Pontificia Univ Catolica Rio Grande do Sul, Brazil.
Pontificia Univ Catolica Rio Grande do Sul, Brazil.
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2017 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 161, p. 70-78Article in journal (Refereed) Published
Abstract [en]

A multivariate approach was used for classification of fuel blends using the combined information from Fourier Transform Infrared Spectroscopy (FTIR) and stable carbon isotopes analysis by Isotope Ratio Mass Spectrometry (IRMS). Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) were applied to the classification of biodiesel/diesel fuel blends containing 0-100% (v/v) of biodiesel. The LDA and PLS-DA methods were able to discriminate samples ranging from 10% to 100% biodiesel (v/v) using the combined information from FTIR and IRMS. Since the global trend is toward a gradual increase in the percentage of biodiesel in fuel blends, the technique presented in this paper could be an important development in improving the traceability and identification of different raw materials used in biodiesel production.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 161, p. 70-78
Keywords [en]
Infrared spectroscopy, Multivariate data analysis, Chemometrics, IRMS, Biodiesel, Stable isotope
National Category
Environmental Sciences
Research subject
Natural Science, Environmental Science
Identifiers
URN: urn:nbn:se:lnu:diva-75681DOI: 10.1016/j.chemolab.2016.12.004ISI: 000394066100009OAI: oai:DiVA.org:lnu-75681DiVA, id: diva2:1217048
Available from: 2018-06-12 Created: 2018-06-12 Last updated: 2018-06-12Bibliographically approved

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Ketzer, João Marcelo

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dos Santos, Victor Hugo J. M.Ketzer, João Marcelo
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