Spectroscopic fingerprinting and Multivariate Data Analysis of Light Beer Towards Informed Tailored Food Consumption

There is increasing awareness of consumer and society in general towards all aspects, which concern food consumption encompassing ethics, sustainability, health, safety, quality, tradition, communication, marketing, etc. Research in food chemistry area has mainly focused on chemical analysis and characterization to contribute to fundamental issues such as food safety and quality, nutritional and health requirements. Aim of this work is to go a step beyond the aforementioned approach. Could our analytical chemistry expertise be of use and ease in the cultural and gastronomic aspect linked to food consumption? In particular, could we think of developing new tools to aid consumers when choosing foodstuff (to have proper knowledge of it) and producers to meet consumer expectations while using food quality as a driver? To this aim the proposal is to use analytical spectroscopy to capture salient features of foodstuff (fingerprint) and build a reference database that can be efficiently searched through multivariate data analysis tools and, likely in the near future, linked to apps for mobile smart devices implemented for consumers inquires. At the same time consumer’s choice may be oriented by showing how products of similar categories cluster according to different criteria. As a first benchmark to develop these ideas a survey on beer is presented. Beer is one of the most consumed alcoholic beverages with a highly relevant economic impact associated. However, our interest is mainly due to the fact that recently the consumers favor more and more artisanal product coming from local and micro-breweries weighting much more the cultural and quality aspects linked to its consumption. This may be a very positive trend in order to prevent alcoholic disorders especially among young people. One-hundred samples of light beer (i.e. no stout or dark beers have been considered) differing by brewery, alcohol content, yeast, brew type, etc, have been collected. Visible-NIR (Near-Infra Red), NMR (Nuclear Magnetic Resonance), GCMS (Gas-Chromatography and Mass Spectroscopy) and fluorescence fingerprinting together with sensory attribute and economic parameters have been acquired. Multivariate explorative and clustering tools are employed to group beer according to several search criteria.