Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/139181
Title: Classification of Hen Eggs by HPLC-UV Fingerprinting and Chemometric Methods
Author: Campmajó, Guillem
Cayero, Laura
Saurina, Javier
Núñez Burcio, Oscar
Keywords: Dactiloscòpia
Quimiometria
Cuina (Ous)
Fingerprints
Chemometrics
Cooking (Eggs)
Issue Date: 29-Jul-2019
Publisher: MDPI
Abstract: 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.
Note: Reproducció del document publicat a: https://doi.org/10.3390/foods8080310
It is part of: Foods, 2019, vol. 8, num. 8, p. 310
URI: http://hdl.handle.net/2445/139181
Related resource: https://doi.org/10.3390/foods8080310
ISSN: 2304-8158
Appears in Collections:Articles publicats en revistes (Enginyeria Química i Química Analítica)

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