Analysis and prediction of the major fatty acids in vegetable oils using dielectric spectroscopy at 5-30 MHz

PLoS One. 2022 May 26;17(5):e0268827. doi: 10.1371/journal.pone.0268827. eCollection 2022.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Dielectric Spectroscopy
  • Fatty Acids* / analysis
  • Fatty Acids, Unsaturated / analysis
  • Least-Squares Analysis
  • Plant Oils* / chemistry

Substances

  • Fatty Acids
  • Fatty Acids, Unsaturated
  • Plant Oils

Grants and funding

Funding was provided by the Malaysian Ministry of Higher Education (www.mohe.gov.my) through the Fundamental Research Grant Scheme under the Grant No. [01-01-20-2247FR], awarded to FZR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.