Assessment of total glycerol core aldehyde and monomer content based on NIR and PLS

Abstract

Glycerol core aldehydes (GCAs) are non-volatile aldehydes residing in frying oil. In this study, near-infrared spectrum (NIR) was used in conjunction with partial least squares (PLS) to create a model for quantifying the total and monomeric content of GCAs. The total and monomer GCAs content in high oleic sunflower oil determined by the GC-MS method was used to assess the model's prediction accuracy. After comparison, the optimal spectrum ranges for both total GCAs and GCAs (9-oxo, 10-oxo-8, and 11-oxo-9) were 8800–6600 cm−1, and the optimal spectrum range for GCAs (8-oxo) was 7420–6600 cm−1. The optimal preprocessing for total GCAs and GCAs (8-oxo, 9-oxo, 10-oxo-8, and 11-oxo-9) were first derivative spectrum, first derivative, original spectrum, first derivative spectrum + NDF smoothing, and first - derivative spectrum + S-G smoothing, respectively. The results demonstrated that the NIR-PLS model had good predictive ability, and the coefficients of determination (R2) for total GCAs and four monomers in the proposed quantitative analysis models were 0.9772, 0.9383, 0.9688, 0.9674, and 0.9745, respectively, and the relative root means square errors of prediction (RMSEP) were 0.0362, 0.0071, 0.0300, 0.0034, 0.0043, and can be predicted quickly and nondestructively, non-toxic, and easy to operate and use.