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Adulteration of diesel/biodiesel blends by vegetable oil as determined by Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy
Authors:Oliveira Flavia C C  Brandão Christian R R  Ramalho Hugo F  da Costa Leonardo A F  Suarez Paulo A Z  Rubim Joel C
Affiliation:Laboratório de Materiais e Combustíveis (LMC), Instituto de Química da Universidade de Brasília, CP 04478, 70919-970, DF, Brazil
Abstract:
In this work it has been shown that the routine ASTM methods (ASTM 4052, ASTM D 445, ASTM D 4737, ASTM D 93, and ASTM D 86) recommended by the ANP (the Brazilian National Agency for Petroleum, Natural Gas and Biofuels) to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils. Considering the previous and actual problems with fuel adulterations in Brazil, we have investigated the application of vibrational spectroscopy (Fourier transform (FT) near infrared spectrometry and FT-Raman) to identify adulterations of B2 and B5 blends with vegetable oils. Partial least square regression (PLS), principal component regression (PCR), and artificial neural network (ANN) calibration models were designed and their relative performances were evaluated by external validation using the F-test. The PCR, PLS, and ANN calibration models based on the Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples. Other 62 samples were used in the validation and external validation, for a total of 182 samples. The results have shown that among the designed calibration models, the ANN/FT-Raman presented the best accuracy (0.028%, w/w) for samples used in the external validation.
Keywords:Fourier transform Raman spectrometry   Fourier transform (FT) near infrared spectrometry   Partial least squares regression   Principal component regression   Artificial neural network   Diesel/biodiesel blends
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