Evolving factor analysis-based method for correcting monitoring delay in different batch runs for use with PLS: On-line monitoring of a transesterification reaction by ATR-FTIR

In this work, the base-catalyzed transesterification of soybean oil with ethanol was monitored on-line using mid-infrared spectroscopy (MIRS) and the yield of fatty acid ethyl esters (biodiesel) was obtained by 1H NMR spectroscopy. The MIRS monitoring carried out for 12 min, was performed using a cylindrical internal reflectance cell of PbSe in the range of 3707–814 cm−1 with eight co-added scans. Two different data treatment strategies were used: in the first, the models were built using the raw data and in the other, evolving factor analysis (EFA) was used to overcome the sensor time delay due to the on-line analysis, producing significantly better results. In addition, models based on partial least squares (PLS) using three batches for calibration and another for validation were compared with models with just one batch for calibration and three for validation. The models were compared between each other using root mean square error of prediction (RMSEP) and root mean square prediction difference (RMSPD), obtaining relative errors under 3%.