NIR Monitoring and Modelling of Soybean Oil Methanolysis with Multivariate Curve Resolution-Alternating Least Squares with Correlation Constraint

Abstract

Near infrared spectroscopy in-line monitoring and modelling of soybean oil methanolysis has been done using multivariate curve resolution alternating least squares (MCR-ALS) with correlation constraint. This constraint allows for quantitation of the methyl ester formed with little calibration effort and the MCR model provides additionally a general description (qualitative and quantitative) of the rest of components in the process. Due to the complexity of this process, which shows components with severe kinetic and spectral overlap, suitably designed multiset analysis strategies were adopted to improve the recovery of concentration profiles of the methyl ester. To assess the temperature and catalyst concentration effects on the kinetic reaction, five batches with different temperatures (20, 44 and 55 °C) and catalyst concentrations (0.75 and 1 m/m%) were produced. The concentration profiles of methyl ester obtained by MCR-ALS for each batch was the starting information used to develop a simplified kinetic model and calculate the activation energy.