Analysis and prediction of the major fatty acids in vegetable oils using dielectric spectroscopy at 5-30 MHz.
Masyitah Amat Sairin, Samsuzana Abd Aziz, Chan Yoke Mun and 2 more
PLoS ONE · 2022
doi:10.1371/journal.pone.0268827 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
A dielectric spectroscopy method was applied to determine major fatty acids composition in vegetable oils. Dielectric constants of vegetable oils were measured in the frequency range of 5-30 MHz. After data pre-treatment, prediction models were constructed using partial least squares (PLS) regression between dielectric spectral values and the fatty acids compositions measured by gas chromatography. Generally, the root means square error of validation (RMSECV) was less than 11.23% in the prediction of individual fatty acids. The determination coefficient (R2) between predicted and measured oleic, linoleic, mono-unsaturated, and poly-unsaturated fatty acids were 0.84, 0.77, 0.84, and 0.84, respectively. These results indicated that dielectric spectroscopy coupled with PLS regression could be a promising method for predicting major fatty acid composition in vegetable oils and has the potential to be used for in-situ monitoring systems of daily consumption of dietary fatty acids.
Abstract licence: CC BY
References45
40 more references, whose wording the paper’s licence keeps private.
All 45 referencesReads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.