We propose a printed 384-well microtiter paper-based fluorescent chemosensor array device (384-well microtiter PCAD) to simultaneously categorize and discriminate saccharides and sulfur-containing amino acids for food analysis. The 384-well microtiter PCAD requiring 1 μL/4 mm2 of each well can allow high-throughput sensing. The device embedded with self-assembled fluorescence chemosensors displayed a fingerprint-like response pattern for targets, the image of which was rapidly captured by a portable digital camera. Indeed, the paper-based chemosensor array system combined with imaging analysis and pattern recognition techniques not only successfully categorized saccharides and sulfur-containing amino acids but also classified mono- and disaccharide groups. Furthermore, the quantitative detectability of the printed device was revealed by a spike and recovery test for fructose and glutathione in a diluted freshly made tomato juice. We believe that the 384-well microtiter PCAD using the imaging analysis system will be a powerful sensor for multi-analytes at several categorized groups in real samples.
Keywords: food analysis; paper; pattern recognition; self-assembly; sensors.
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