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Data de publicació

2019-07-29

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cc-by (c) Campmajó, Guillem et al., 2019
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/139181

Classification of Hen Eggs by HPLC-UV Fingerprinting and Chemometric Methods

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Recurs relacionat

https://doi.org/10.3390/foods8080310

Resum

Hen eggs are classified into 4 groups according to their production method: organic, free-range, barn or caged. It is known that a fraudulent practice is the misrepresentation of a high quality egg with a lower one. In this work, high performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprints were proposed as a source of potential chemical descriptors to achieve the classification of hen eggs according to their labelled type. A reversed-phase separation was optimized to obtain discriminant enough chromatographic fingerprints, which were subsequently processed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Particular trends were observed for organic and caged hen eggs by PCA and, as expected, these groupings were improved by PLS-DA. The applicability of the method to distinguish egg manufacturer and size was also studied by PLS-DA, observing variations in the HPLC-UV fingerprints in both cases. Moreover, the classification of higher class eggs, in front of any other with one lower, and hence cheaper, was studied by building paired PLS-DA models, reaching a classification rate of at least 82.6% (100% for organic vs non-organic hen eggs) and demonstrating the suitability of the proposed method.

Matèries

Dactiloscòpia, Quimiometria, Cuina (Ous)

Matèries (anglès)

Fingerprints, Chemometrics, Cooking (Eggs)

Citació

Col·leccions

Articles publicats en revistes (Enginyeria Química i Química Analítica)

Citació

CAMPMAJÓ GALVÁN, Guillem, et al. Classification of Hen Eggs by HPLC-UV Fingerprinting and Chemometric Methods. Foods. 2019. Vol. 8, num. 8, pags. 310. ISSN 2304-8158. [consulted: 19 of August of 2026]. Available at: https://hdl.handle.net/2445/139181

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