Extra virgin Argan oils’ shelf-life monitoring and prediction based on chemical properties or FTIR fingerprints and chemometrics

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Output type: Journal article

UM6P affiliated Publication?: Yes

Author list: Kharbach M., Marmouzi I., Kamal R., Yu H., Barra I., Cherrah Y., Alaoui K., Heyden Y.V., Bouklouze A.

Publisher: Elsevier: 12 months

Publication year: 2021

Journal: Food Control (0956-7135)

Volume number: 121

ISSN: 0956-7135

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091371976&doi=10.1016%2fj.foodcont.2020.107607&partnerID=40&md5=02c675d7d5aef405b6c5dbdb59177e23

Languages: English (EN-GB)

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In order to achieve a better understanding of the shelf-life behavior of extra virgin Argan oils (EVAO) during storage, the influences of storage periods, roasting process and packaging materials were studied. Those oils were extracted from roasted and unroasted kernels. The EVAO shelf life assessment was made by determining chemical properties (acidity, peroxide value, specific absorbances K232 and K270, tocopherol content, fatty-acids and sterol composition, and oxidative stability index) and by FTIR spectra. Sixty EVAO samples (30 roasted and 30 unroasted) were evaluated after production and then were packed in two glass bottle types (dark and clear), which resulted in 120 samples. They were stored under realistic storage conditions (ambient temperature) for two successive years and analysed 6-monthly. Chemometric data analysis was applied to study the shelf-life influence. PCA and PLS-DA, on either the chemical data or the FTIR spectra, allowed the discrimination between fresh and oxidized oils. The oil shelf-life was predicted by means of PLS regression. Thus, the time of storage after which the oil loses its extra virgin quality could be predicted. Finally, the potential of FTIR fingerprinting to quantify four physicochemical properties (i.e. acidity, PV, K232 and K270) during EVAO storage was established using PLS regression. © 2020 Elsevier Ltd


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Last updated on 2021-24-11 at 23:16