Optimization of total polar compounds quantification in frying oils by low-field nuclear magnetic resonance

Abstract

To improve the accuracy of total polar compounds (TPC) quantification in frying oils by low-field nuclear magnetic resonance (LF-NMR), an optimized statistical method was proposed. The method uses a specially designed sequence to detect the NMR signal in frying oils, and establishes the TPC prediction model by partial least squares (PLS) regression on relaxation properties extracted from the NMR signal. Compared with inversion recovery (IR) and Carr-Purcell-Meiboom-Gill (CPMG) sequences, the designed sequence provides more relaxation information. The experimental result shows that the proposed method is more accurate than reported methods that are based on longitudinal and transverse relaxation times in the TPC quantification of frying oils.