Storage time of nut spreads using flash gas chromatography E-nose combined with multivariate data analysis

The quality assessment, in terms of lipid oxidative status, food products stored the long-term is great importance, especially those with a high content. Specifically, companies working this sector need feasible, simple, and fast techniques that are suitable for or process control. Herein, fingerprinting approach, based on headspace analysis carried out by flash gas chromatography electronic nose (FGC E-nose) multivariate data was applied to pistachio gianduja spreads. These samples, differently packaged, were climatic chambers at 40 °C 180 days their fraction analyzed periodically total 15 sampling times. Principal component showed clear separation according packaging type both samples. Partial least squares regression models developed predict storage time considering aggregated (R2 up 0.985, RMSEP = 6.16 days) separately 0.989, 5.71 days). Based obtained residual prediction deviation (RPD from 4.4 8.5 prediction), can be considered use control an industrial environment.