A COMPARATIVE STUDY BETWEEN MULTIVARIATE CALIBRATION AND ARTIFICIAL NEURAL NETWORK IN QUANTIFICATION OF SOYBEAN BIODIESEL

  • C.Z. Brusamarello
  • M. Di Domenico
  • C. Da Silva
  • F. de Castilhos

Abstract

Biodiesel is an alternative fuel and can be obtained by the transesterification of vegetable oils. Spectrophotometric methods can be used for the quantification of mixtures, associated with chemometric tools, enabling the analysis of overlapping signals. The aim of this work is to apply the multivariate calibration with PLS (partial least squares) and artificial neural network (ANN), to estimate the concentration of esters in the transesterification of soybean oil using molecular absorption spectrophotometry as analytical technique. Absorbance measurements were performed in a spectrophotometer UV/VIS. Synthetic solutions were prepared with standards of the five major compounds of soybean biodiesel and real samples were obtained by the reaction of transesterification of soybean oil with NaOH and enzymatic method was used Lipozyme® IM (Novozymes), as catalysts. Results shows that all components of this reaction medium absorb in the wavelength range of 190-280 nm. Reactions of basic catalysis reached conversions close to 100%, while enzymatic reactions reached lower conversions. For both methods, calibration and validation groups were composed, respectively, by synthetic and real samples. Results showed that the concentrations of esters estimated by ANN model in the real samples are more accurate (R2-0.93), showing the good ability to estimation of ANN.

Author Biographies

M. Di Domenico

Adjunct professor at the Federal Technological University of Paraná (UTFPR), with post-doctorate in Chemical Engineering (PNPD / CAPES, UFSC, 2015), PhD in Chemical Engineering (UFSC, 2013) with internship at Imperial College London ), Master's Degree in Chemical Engineering (UNICAMP, 2010) and a degree in Chemical Engineering (UFSC, 2006). Since the PhD it has been working in the area of energy utilization of mineral and biomass coals through the thermal conversion processes of pyrolysis, gasification and combustion.

C. Da Silva

PhD in Chemical Engineering from the State University of Maringá (2009). Associate Professor at the State University of Maringá - DTC (Department of Technology), Permanent Professor of the PEQ / UEM (Graduate Program in Chemical Engineering) and the PPB / UEM (Post-Graduate Program in Bioenergy). He has experience in Engineering, with emphasis in Chemical Engineering and Food Engineering, working mainly in the following subjects: processes in pressurized medium, processes assisted by ultrasound, biodiesel and extraction of vegetable oils.

F. de Castilhos

She holds a bachelor's degree in Chemical Engineering from the State University of Maringá (1999), a Master's degree in Chemical Engineering from the State University of Maringá (2001) and a PhD in Chemical Engineering from the State University of Maringá (2004). Adjunct Professor of the Federal University of Santa Maria, she Has experience in Chemical Engineering, with emphasis on Modeling Simulation and Process Control. Acting mainly on the following topics: optimal control, drying, state estimation, Virtual Sensors.

Published
2019-06-11
How to Cite
Brusamarello, C., Di Domenico, M., Da Silva, C., & de Castilhos, F. (2019). A COMPARATIVE STUDY BETWEEN MULTIVARIATE CALIBRATION AND ARTIFICIAL NEURAL NETWORK IN QUANTIFICATION OF SOYBEAN BIODIESEL. Revista Mexicana De Ingeniería Química, 19(1), 123-132. https://doi.org/10.24275/rmiq/Bio579
Section
Biotechnology