Calibration with virtual standards for monitoring biodiesel production using a miniature NIR spectrometer.

Abstract

This work describes the use of virtual standards as calibration samples in an innovative multivariate calibration approach for the on-line monitoring of alkyl-esters content during biodiesel production process using a miniature near infrared (NIR) spectrometer. For comparison purposes, a partial least squares (PLS) model was built using synthetic blends prepared in laboratory with different concentrations of oil, glycerol, biodiesel, and ethanol and resulted in a satisfactory predictive ability (root mean square error of prediction, RMSEP, of 1.51% w/w). When compared to conventional methods, calibration with synthetic blends has the advantage of simplifying the experimental procedure and reducing the need for reference analysis. Nevertheless, it still requires the preparation of a considerable number of blends in laboratory. To overcome this limitation, this study proposed an innovative approach where a PLS model was constructed based on virtual standards: representative calibration spectra were created by mathematically mixing spectra from pure components and performing an adjustment using the Piecewise Direct Standardization (PDS) method. This significantly reduced the need for calibration synthetic blends and led to similar results (RMSEP of 1.75% w/w), compared to the previous approach. This work also demonstrates the use of the constructed models to predict the concentration profiles of alkyl-esters during the batch transesterification process.