Amb motiu del tancament d'estiu, la validació de documents es reprendrà a partir del 28 d'agost de 2026. Disculpeu les molèsties.
Con motivo del cierre de verano, la validación de documentos se reanudará a partir del 28 de agosto de 2026. Disculpad las molestias
Due to the summer closure, document validation will resume starting August 28, 2026. We apologize for any inconvenience.

Document type

Article

Version

Accepted version

Publication date

All rights reserved

Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/55253

Authentication of feeding fats: classification of animal fats, fish oils and recycled cooking oils

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

Classification of fats and oils involves the recognition of one/several markers typical of the product. The ideal marker(s) should be specific to the fat or oil. Not many chemical markers fulfill these criteria. Authenticity assessment is a difficult task, which in most cases requires the measurement of several markers and must take into account natural and technology-induced variation. The present study focuses on the identity prediction of three by-products of the fat industry (animal fats, fish oils, recycled cooking oils), which may be used for animal feeding. Their identities were predicted by their triacylglycerol fingerprints, their fatty acid fingerprints and their profiles of volatile organic compounds. Partial least square discriminant analysis allowed samples to be assigned successfully into their identity classes. Most successful were triacylglycerol and fatty acid fingerprints (both 96% correct classification). Proton transfer reaction mass spectra of the volatile compounds predicted the identity of the fats in 92% of the samples correctly.

Citation

Citation

RUTH, S. M. van, et al. Authentication of feeding fats: classification of animal fats, fish oils and recycled cooking oils. Animal Feed Science and Technology. 2010. Vol. 155, num. 1, pags. 65-73. ISSN 0377-8401. [consulted: 16 of August of 2026]. Available at: https://hdl.handle.net/2445/55253

Export metadata

JSON - METS

Share record