Multivariate near infrared spectroscopy models for predicting the methyl esters content in biodiesel.


Biodiesel is the main alternative to fossil diesel. The key advantages of its use are the fact that it is a non-toxic renewable resource, which leads to lower emissions of polluting gases. European governments are targeting the incorporation of 20% of biofuels in the general fuels until 2020. Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils/fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties. This work reports the use of near infrared (NIR) spectroscopy to determine the esters content in biodiesel as well as the content in linolenic acid methyl esters (C18:3) in industrial and laboratory-scale biodiesel samples. Furthermore, calibration models for myristic (C14:0), palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2) acid methyl esters were also obtained. Principal component analysis was used for the qualitative analysis of the spectra, while partial least squares regression was used to develop the calibration models between analytical and spectral data. The results confirm that NIR spectroscopy, in combination with multivariate calibration, is a promising technique to assess the biodiesel quality control in both laboratory-scale and industrial scale samples.

DOI: 10.1016/j.aca.2007.11.044

Cite this paper

@article{Baptista2008MultivariateNI, title={Multivariate near infrared spectroscopy models for predicting the methyl esters content in biodiesel.}, author={Patricia Baptista and Pedro M Felizardo and Jos{\'e} Cardoso Menezes and M Joana Neiva Correia}, journal={Analytica chimica acta}, year={2008}, volume={607 2}, pages={153-9} }