August 14, 2025SensorsOpen Access

Capillary Flow Profile Analysis on Paper-Based Microfluidic Chips for Classifying Astringency Intensity

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Classifying astringency intensity can be achieved by measuring capillary flow rates on paper-based chips, enhancing portable assessments.
In experiments with tannic acid solutions, higher concentrations resulted in greater mucin aggregation and lower capillary flow rates.
Machine learning models, particularly support vector machines, accurately classified astringency levels with a 95.2% accuracy rate.
The approach shows promise for field analysis of various liquid samples, ensuring cost-effectiveness and simplicity.

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Analysis using capillary flow measures astringency levels in solutions, indicating potential for field use.

Son et al. (2025) studied this question.

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