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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/230759
Development of High-Throughput Screening Methods for Honey Classification based on UV-Vis and FIA-UV Spectroscopic Fingerprints
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This project focuses on the development, validation, and comprehensive comparison of two rapid, reliable, and high-throughput non-targeted screening methodologies based on UV-Vis and FIA-UV spectroscopic fingerprints combined with chemometrics for honey classification and authentication. To address the issue of food fraud, these optical strategies are proposed as efficient screening systems to perform a preliminary evaluation of honey samples according to both their botanical origin (Spanish honeys from different regions) and geographical origin (international samples from different countries). This approach acts as a first-line filter, avoiding the immediate use of classic confirmatory techniques that are more expensive, time-consuming, and frequently less environmentally friendly. Chemometric analysis consisting in Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) provide acceptable sensitivity, specificity and low classification error rates, confirming that non-targeted spectral fingerprints successfully capture key chemical markers, such as polyphenolic and floral absorption descriptors, required for robust differentiation. Regarding method suitability, the automated FIA-UV method proved to be more efficient for the classification of botanical varieties, demonstrating a great capacity to handle high sample volumes due to its high-throughput capability of analysing 30 samples per hour. Conversely, conventional UV-Vis spectroscopy proved to be highly effective for discriminating geographical origins, demonstrating a remarkable capacity to handle the wider chemical variability of international samples through a simpler, budget-friendly setup with lower operational complexity. Both methodologies demonstrate that rapid analytical speed does not imply a sacrifice in classification accuracy. Their highly favourable environmental and operational performances are confirmed by sustainability and operational practicality metrics. Both systems achieved an identical AGREE score of 0.71 by avoiding the use of hazardous organic solvents, while the practical BAGI index yielded scores of 70.0 and 77.5 out of 100 for UV-Vis and FIA-UV, respectively. Therefore, this research provides the beekeeper sector with two valid, eco-friendly, and practical screening alternatives that successfully strengthen honey fraud prevention while ensuring low operational costs and a minimal ecological footprint.
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Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2026, Tutor: Oscar Nuñez Burcio
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LUJÁN TEIXIDÓ, Gerard. Development of High-Throughput Screening Methods for Honey Classification based on UV-Vis and FIA-UV Spectroscopic Fingerprints. [consulted: 9 of September of 2026]. Available at: https://hdl.handle.net/2445/230759