Distinguishing Commercial Beers Using a Solution-Based Sensor Array Derived from Nanoscale Polydiacetylene Vesicles
Xiaomin Qian, Carina L. Gargalo, Krist V. Gernaey, Brigitte Städler
Abstract
The fast and effective discrimination of different liquid mixtures such as beers is a long-standing challenge in the food and beverage industry. We report the fabrication of a solution-based sensor array derived from nanoscale polydiacetylene (PDA) vesicles to distinguish different ethanol containing aqueous solutions supplemented with different model flavor compounds relevant in beers. The sensitivity of the sensors was significantly affected by the head group modification of the diacetylenes and the composition of the sensors. Finally, a selected set of sensors was utilized as a sensor array to distinguish different commercial beers in combination with statistical data analysis. This approach represents an effort toward the employment of low-cost sensors with an easy read-out for the fast discrimination of different beverages.