The recognition of beer with flow-through sensor array based on miniaturized solid-state electrodes

Area of Science:

• Analytical Chemistry
• Sensor Technology
• Food Science

Background:

• Development of advanced analytical tools for food and beverage quality control.
• Need for rapid and reliable methods for distinguishing between similar products like different beer brands.
• Limitations of traditional methods in terms of speed and complexity.

Purpose of the Study:

• To develop and evaluate a flow-through electronic tongue for the qualitative analysis of beer.
• To assess the sensor array's ability to discriminate between different beer brands and batches.
• To validate the performance of potentiometric sensors in a complex liquid matrix.

Main Methods:

• Fabrication of miniaturized solid-state potentiometric sensors using membrane solution casting on gold transducers.
• Integration of ion-selective and partially selective microelectrodes into a flow-through sensor array.
• Application of Partial Least Squares (PLS) and Artificial Neural Network (ANN) techniques for data analysis and classification.

Main Results:

• Successful development of a flow-through electronic tongue system.
• Demonstrated ability to discriminate between different brands of beer.
• Achieved 83% correct classification of beer samples, including those from different manufacture dates and lots.

Conclusions:

• The developed electronic tongue is a promising tool for the qualitative analysis and differentiation of beer.
• The combination of potentiometric sensors and chemometric methods (PLS, ANN) offers effective pattern recognition capabilities.
• This technology has potential applications in quality control and authentication within the beverage industry.