Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/188064
Title: Using fluorescence excitation-emission matrices to predict bitterness and pungency of virgin olive oil: A feasibility study
Author: Quintanilla-Casas, B.
Rinnan, Åsmund
Romero, Agustí
Guardiola Ibarz, Francesc
Tres Oliver, Alba
Vichi, S. (Stefania)
Bro, Rasmus
Keywords: Oli d'oliva
Antropometria
Espectrometria de masses
Olive oil
Anthropometry
Mass spectrometry
Issue Date: 29-Jun-2022
Publisher: Elsevier B.V.
Abstract: Unlike other food products, virgin olive oil must undergo an organoleptic assessment that is currently based on a trained human panel, which presents drawbacks that might affect the efficiency and robustness. Therefore, disposing of instrumental methods that could serve as screening tools to support sensory panels is of paramount importance. The present work aimed to explore excitation-emission fluorescence spectroscopy (EEFS) to predict bitterness and pungency, since both attributes are related with fluorophore compounds, such as polar phenols. Bitterness and pungency intensities of 250 samples were provided by an official sensory panel and used to build and compare partial least squares regressions (PLSR) with the excitation-emission matrix. Both PARAFAC scores and two-way unfolded data led to successful PLSR. The most relevant PARAFAC scores agreed with virgin olive oil phenolic spectra, evidencing that EEFS would be the fit-for-purpose screening tool to support the sensory panel.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.foodchem.2022.133602
It is part of: Food Chemistry, 2022, vol. 395, p. 133602
URI: http://hdl.handle.net/2445/188064
Related resource: https://doi.org/10.1016/j.foodchem.2022.133602
ISSN: 0308-8146
Appears in Collections:Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)

Files in This Item:
File Description SizeFormat 
724171.pdf2.6 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons