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Advances in Biosensor Technologies for the Quality, Safety, and Traceability of Grape-Derived Products

Oct 2026 · Özgür Yayınları eBooks · 37 references
Electrochemical sensors and biosensors

Abstract

This chapter reviews recent advances in biosensor technologies for quality, safety, authenticity, and traceability assessment across the grape-derived product value chain, with emphasis on systems incorporating a biological recognition element in accordance with the IUPAC definition of a biosensor. The reviewed approaches span vineyard and grape ripening, must and juice processing, fermentation, finished wine, and other grape-derived products. Biosensor platforms based on enzymes, antibodies, aptamers and other nucleic-acid recognition elements, whole-cell systems, and nanostructured architectures have been investigated using electrochemical and optical transduction strategies. For quality and production monitoring, enzyme-based biosensors and bioelectronic tongue systems have been applied to sugars, organic acids, phenolic compounds, and fermentation-related metabolites, while electronic tongue approaches have demonstrated potential for monitoring grape ripening and compositional changes. Ochratoxin A (OTA) is the most extensively investigated safety-related analyte, with aptamer- and antibody-based platforms developed for grapes, grape juice, and wine. Reported detection capabilities range from the picogram-per-millilitre to attomolar levels. Biosensing applications have also been extended to microbial contaminants, fermentation-related biological events, Hardaliye, and grapevine varietal identification. Despite their potential for rapid, sensitive, selective, portable, and real-time analysis, practical implementation remains constrained by matrix effects, fouling, enzyme instability, calibration requirements, limited standardization, and insufficient real-matrix validation. Future developments should prioritize robust validation, stable biorecognition, portable multiplexed platforms, amplification-enhanced aptasensors, and integration with artificial intelligence, machine learning, IoT, edge computing, and digital traceability systems.

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