Quercetin (QU), a bioactive flavonoid with significant nutritional and antioxidant properties, plays a vital role in the quality and stability of wine. This study presents the development of a molecularly imprinted polymer (MIP)-based optical sensor for the selective and sensitive detection of quercetin in red and white wines. The sensor combines the selective molecular recognition capabilities of MIPs with the optical properties of nanostructured porous silica (PSiO2) scaffolds, which serve as the transducer. MIP synthesis was achieved through a novel room-temperature vapor-phase polymerization method using pyrrole as the functional monomer. Computational simulations were used to optimize pyrrole interactions with QU and at the polymer level, to explore the binding interactions of QU with the resulting polypyrrole (PPy) matrix. Comprehensive characterization including UV–vis reflectance spectroscopy and advanced surface analyses confirmed successful MIP formation. The sensor exhibited high sensitivity in a dual linear response range (2.5–80 μM and 80–200 μM), with a detection limit of 0.7 μM. Selectivity tests against structurally similar flavonoids and antioxidants demonstrated a significantly higher response to quercetin, with an imprinting factor of 3.6. The sensor was validated using real wine samples, demonstrating the ability to detect quercetin without prior sample preparation. Results showed strong agreement with high-performance liquid chromatography (HPLC), confirming the sensor reliability. Additionally, the sensor exhibited excellent reusability with minimal signal variation (RSD = 2.6%) and good stability over 60 days (RSD = 3%). This work highlights the potential of MIP-based optical sensors for the real-time monitoring of bioactive compounds in complex food matrices, such as wine, offering a robust and cost-effective alternative for quality control applications.

A Molecularly Imprinted Polymer-Based Porous Silicon Optical Sensor for Quercetin Detection in Wines

Ditaranto, Nicoletta
Investigation
;
2025-01-01

Abstract

Quercetin (QU), a bioactive flavonoid with significant nutritional and antioxidant properties, plays a vital role in the quality and stability of wine. This study presents the development of a molecularly imprinted polymer (MIP)-based optical sensor for the selective and sensitive detection of quercetin in red and white wines. The sensor combines the selective molecular recognition capabilities of MIPs with the optical properties of nanostructured porous silica (PSiO2) scaffolds, which serve as the transducer. MIP synthesis was achieved through a novel room-temperature vapor-phase polymerization method using pyrrole as the functional monomer. Computational simulations were used to optimize pyrrole interactions with QU and at the polymer level, to explore the binding interactions of QU with the resulting polypyrrole (PPy) matrix. Comprehensive characterization including UV–vis reflectance spectroscopy and advanced surface analyses confirmed successful MIP formation. The sensor exhibited high sensitivity in a dual linear response range (2.5–80 μM and 80–200 μM), with a detection limit of 0.7 μM. Selectivity tests against structurally similar flavonoids and antioxidants demonstrated a significantly higher response to quercetin, with an imprinting factor of 3.6. The sensor was validated using real wine samples, demonstrating the ability to detect quercetin without prior sample preparation. Results showed strong agreement with high-performance liquid chromatography (HPLC), confirming the sensor reliability. Additionally, the sensor exhibited excellent reusability with minimal signal variation (RSD = 2.6%) and good stability over 60 days (RSD = 3%). This work highlights the potential of MIP-based optical sensors for the real-time monitoring of bioactive compounds in complex food matrices, such as wine, offering a robust and cost-effective alternative for quality control applications.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/531860
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