A Rapid Method to Predict Beer Shelf Life Using an MS-Based e-Nose

Abstract

A rapid and efficient technique was applied, which used an electronic nose based on a mass detector (MS-based e-nose) combined with headspace solid-phase microextraction sampling and chemometric tools to classify beer samples between fresh and aged and between samples contained in aluminium cans or glass bottles, and to predict the shelf life of beer. The mass spectra obtained from the MS-based e-nose contained details about volatile compounds and were recorded as the abundance of each ion at different mass-to-charge (m/z) ratios. The analysis was performed on 53 naturally aged samples for eleven months without light and with a controlled temperature of around 14 °C ± 0.5 °C. Principal component analysis (PCA) was performed on the data and showed a grouping of samples between fresh and aged. Partial least square discriminant analysis (PLS-DA) allowed the discrimination of fresh from aged beers but could not discriminate between the samples according to the type of packaging. Finally, partial least squares regression (PLSR) proved to be an effective method for predicting beer shelf life.