Discriminant analysis of biodiesel fuel blends based on combined data from Fourier Transform Infrared Spectroscopy and stable carbon isotope analysis

• Published in: Chemometrics and intelligent laboratory systems 2017-02, Vol.161, p.70-78
• Main Authors: dos Santos, Victor Hugo J.M., Ramos, Alessandro S., Pires, Jéssica P., Engelmann, Pamela de M., Lourega, Rogério V., Ketzer, João M.M., Rodrigues, Luiz F.
• Format: Article
• Language: English
• Subjects: Biodiesel; Chemometrics; Environmental Science; Infrared spectroscopy; IRMS; Miljövetenskap; Multivariate data analysis; Stable isotope
• ISSN: 0169-7439; 1873-3239; 1873-3239
• DOI: 10.1016/j.chemolab.2016.12.004

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. •Discriminant analysis of biodiesel fuel blends through chemometrics are possible.•The combination of the data from Mid-FTIR and IRMS are possible and advantageous.•δ13C data improve the discriminant capability of the multivariate models.•LDA and PLS-DA are suitable to perform the classification of the fuel blends.•The methods present potential to be applied for fuel blends quality control.