Enzymatic Activity Prediction Using Time-Domain Nuclear Magnetic Resonance (TD-NMR) and Multivariate Analysis: A Case Study Using Cassava Roots

Abstract

Time-domain nuclear magnetic resonance (NMR) has been widely used in food science. In this work, we demonstrate that the NMR decay obtained with the Carr–Purcell–Meiboom–Gill (CPMG) sequence can be used to estimate the peroxidase activity (PA) in cassava roots. This enzyme has been involved in post-harvest physiological deterioration (PPD), which limits the storage of fresh cassava to a few days. Cassava is a staple food for almost one billion people in tropical areas in Americas, Africa and Asia. A multivariate method using CPMG data and reference values of PA from a standard biochemical assay was built with 216 measurements for non-refrigerated and refrigerated samples of cassava roots. The figures of merit of the global partial least squares model using both types of roots showed a 0.06 μmol min⁻¹ limit of detection (LOD) and a 0.2 μmol min⁻¹ limit of quantification (LOQ) for PA, with 0.4 [intensity (a.u.)/(μmol min⁻¹)] sensitivity and a standard error of cross-validation (SECV) of 0.7 μmol min⁻¹. All of the results demonstrated that TD-NMR has the potential to predict PA in cassava roots that is indicative of the PPD problem.