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Infrared Spectroscopy and Multivariate Calibration for Quantification of Soybean Oil as Adulterant in Biodiesel Fuels
Author(s) -
Guimarães Eloiza,
Mitsutake Hery,
Gontijo Lucas Caixeta,
de Santana Felipe Bachion,
Santos Douglas Queiroz,
Neto Waldomiro Borges
Publication year - 2015
Publication title -
journal of the american oil chemists' society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.512
H-Index - 117
eISSN - 1558-9331
pISSN - 0003-021X
DOI - 10.1007/s11746-015-2656-x
Subject(s) - adulterant , soybean oil , biodiesel , partial least squares regression , calibration , multivariate statistics , mathematics , chemistry , analytical chemistry (journal) , chromatography , statistics , organic chemistry , food science , catalysis
Abstract This work quantifies the adulteration of ethyl and methyl soybean biodiesels/diesel (B5) blended with soybean oil using mid‐infrared spectroscopy associated with multivariate calibration. The models constructed by the method of partial least squares (PLS) presented low values of root‐mean‐square error of prediction 0.22 % (w/w) and 0.26 % (w/w), respectively, for models containing ethyl and methyl soybean biodiesel. Along with the parameters of error, accuracy was evaluated by the use of an elliptical joint confidence region (EJCR). The EJCR for the both PLS models showed there was no significant difference between the prepared concentration values and PLS predicted concentration values, and that there was no evidence of bias within the 95 % confidence level. The PLS models showed excellent correlation in the prediction set ( R = 0.999) and did not present systematic errors according to the ASTM E1655 standard. Therefore, the models presented excellent performance in quantifying soybean oil as an adulterant in B5 blends, in concentrations within the range 1.00–30.00 % (w/w). The proposed methodology showed itself to be efficient for quality control of B5 contaminated with vegetable oil.