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Fourier transform infrared spectroscopy (FTIR) and multivariate analysis for identification of different vegetable oils used in biodiesel production.

Mueller D, Ferrão MF, Marder L, da Costa AB, Schneider Rde C - Sensors (Basel) (2013)

Bottom Line: For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used.The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis.It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.

View Article: PubMed Central - PubMed

Affiliation: Programa de Pós-Graduação em Sistemas e Processos Industriais, Universidade de Santa Cruz do Sul, Av. Independência, 2293, CEP 96815-900, Santa Cruz do Sul-RS, Brasil. danielamueller@hotmail.com

ABSTRACT
The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources--canola, cotton, corn, palm, sunflower and soybeans--were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.

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Related in: MedlinePlus

UATR-FTIR spectra of samples of biodiesel with the application of the first derivative and the SNV. The excluded regions of the spectra are highlighted.
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f2-sensors-13-04258: UATR-FTIR spectra of samples of biodiesel with the application of the first derivative and the SNV. The excluded regions of the spectra are highlighted.

Mentions: In the PCA and HCA, the 735–1,783 and 2,810–3,035 cm−1 regions were selected because the other regions contained no spectral information or were polluted by water vapor or carbon dioxide bands due to poor compensation. For obtaining the HCA dendrogram, the Euclidian distance and the incremental connection method were used. In Figure 2, one can observe the spectra of samples of biodiesel with the application of the first derivative and the SNV. The regions of the spectra that were excluded are highlighted.


Fourier transform infrared spectroscopy (FTIR) and multivariate analysis for identification of different vegetable oils used in biodiesel production.

Mueller D, Ferrão MF, Marder L, da Costa AB, Schneider Rde C - Sensors (Basel) (2013)

UATR-FTIR spectra of samples of biodiesel with the application of the first derivative and the SNV. The excluded regions of the spectra are highlighted.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3673082&req=5

f2-sensors-13-04258: UATR-FTIR spectra of samples of biodiesel with the application of the first derivative and the SNV. The excluded regions of the spectra are highlighted.
Mentions: In the PCA and HCA, the 735–1,783 and 2,810–3,035 cm−1 regions were selected because the other regions contained no spectral information or were polluted by water vapor or carbon dioxide bands due to poor compensation. For obtaining the HCA dendrogram, the Euclidian distance and the incremental connection method were used. In Figure 2, one can observe the spectra of samples of biodiesel with the application of the first derivative and the SNV. The regions of the spectra that were excluded are highlighted.

Bottom Line: For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used.The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis.It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.

View Article: PubMed Central - PubMed

Affiliation: Programa de Pós-Graduação em Sistemas e Processos Industriais, Universidade de Santa Cruz do Sul, Av. Independência, 2293, CEP 96815-900, Santa Cruz do Sul-RS, Brasil. danielamueller@hotmail.com

ABSTRACT
The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources--canola, cotton, corn, palm, sunflower and soybeans--were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.

Show MeSH
Related in: MedlinePlus