Honey fraud detection based on sugar syrup adulterations by HPLC-UV fingerprinting and chemometrics
In recent years, honey-producing sector has faced the increasing presence of adulterated honeys, implying greateconomic losses and questioning the quality of this highly appreciated product by the society. Due to the highsugar content of honey, sugar syrups are among its most common adulterants, bei...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/206120 |
| Acceso en línea: | https://hdl.handle.net/2445/206120 |
| Access Level: | acceso abierto |
| Palabra clave: | Dactiloscòpia Quimiometria Mel d'abelles Sucres Fingerprints Chemometrics Honey Sugars |
| Sumario: | In recent years, honey-producing sector has faced the increasing presence of adulterated honeys, implying greateconomic losses and questioning the quality of this highly appreciated product by the society. Due to the highsugar content of honey, sugar syrups are among its most common adulterants, being also the most difficult todetect even with isotope ratio techniques depending on the origin of the sugar syrup plant source. In this work, ahoney authentication method based on HPLC-UV fingerprinting was developed, exhibiting a 100% classificationrate of honey samples against a great variety of sugar syrups (agave, corn, fiber, maple, rice, sugar cane andglucose) by partial least squares-discriminant analysis (PLS-DA). In addition, the detection and level quantitationof adulteration using syrups as adulterants (down to 15%) was accomplished by partial least squares (PLS)regression with low prediction errors by both internal and external validation (values below 12.8% and 19.7%,respectively) |
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