A fluorescence-based multivariate method for biodiesel quantification in undiluted diesel-biodiesel blends without sample preparation

Fernando R Conceição; Flávio S Michels; Evaristo A Falcão; Gustavo Nicolodelli; Samuel L Oliveira; Anderson R L Caires

doi:10.1016/j.saa.2023.123773

A fluorescence-based multivariate method for biodiesel quantification in undiluted diesel-biodiesel blends without sample preparation

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Mar 5:308:123773. doi: 10.1016/j.saa.2023.123773. Epub 2023 Dec 17.

Authors

Fernando R Conceição¹, Flávio S Michels², Evaristo A Falcão³, Gustavo Nicolodelli⁴, Samuel L Oliveira², Anderson R L Caires⁵

Affiliations

¹ Optics and Photonics Group, Institute of Physics, Federal University of Mato Grosso do Sul, PO Box 549, 79070-900 Campo Grande, MS, Brazil; Federal Institute of Mato Grosso do Sul, 79750-000 Nova Andradina, SP, Brazil.
² Optics and Photonics Group, Institute of Physics, Federal University of Mato Grosso do Sul, PO Box 549, 79070-900 Campo Grande, MS, Brazil.
³ Faculty of Exact Sciences and Technology, Federal University of Grande Dourados, PO Box 364, 79804-970 Dourados, MS, Brazil.
⁴ Department of Physics, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil.
⁵ Optics and Photonics Group, Institute of Physics, Federal University of Mato Grosso do Sul, PO Box 549, 79070-900 Campo Grande, MS, Brazil. Electronic address: anderson.caires@ufms.br.

PMID: 38142492
DOI: 10.1016/j.saa.2023.123773

Abstract

In this work, excitation-emission matrices (EEMs) were used in association with parallel factor analysis (PARAFAC) to assess biodiesel content in undiluted diesel-biodiesel blends (DBBs) without pre-sample preparation. EEMs were decomposed using the PARAFAC (EEMs-PARAFAC), and the loading values of the PARAFAC component as a function of biodiesel content in the blends were used to build an analytical model to quantify the biodiesel content in DBBs. The proposed model presenting a limit of detection (LOD) and a limit of quantification (LOQ) of 2.5% and 11% w/w, respectively, successfully predicted the biodiesel content in the validation samples. The robustness of the model was confirmed by a close analysis of the root mean square error of prediction, standard error of prediction, relative standard deviation of prediction, and Bias. Therefore, an accurate and robust analytical model based on EEMs-PARAFAC was developed to quantify the biodiesel content in undiluted DBBs without sample preparation.

Keywords: Biodiesel; Diesel; EEM; Fluorescence; PARAFAC; Quantification.

MeSH terms

Biofuels* / analysis
Factor Analysis, Statistical
Spectrometry, Fluorescence / methods

Substances

Biofuels