AI Article Synopsis

  • Fat-spread products are water and vegetable oil emulsions with fat content varying from 10 to 90%, and their composition differs by country, necessitating methods to identify their geographical origin.
  • The study developed and optimized multivariate classification methods to differentiate fat-spread products from Spain and Morocco using instrumental fingerprints from HPLC-DAD analysis, requiring no sample treatment other than dissolution in n-hexane.
  • The results showed that 100% of samples were accurately classified using partial least squares-discriminant analysis (PLS-DA) with data collected in reverse phase, demonstrating the effectiveness of the classification methods employed.

Article Abstract

Fat-spread products are a stabilized emulsion of water and vegetable oils. The whole fat content can vary from 10 to 90% (/). There are different kinds, which are differently named, and their composition depends on the country in which they are produced or marketed. Thus, having analytical solutions to determine geographical origin is required. In this study, some multivariate classification methods are developed and optimised to differentiate fat-spread-related products from different geographical origins (Spain and Morocco), using as an analytical informative signal the instrumental fingerprints, acquired by liquid chromatography coupled with a diode array detector (HPLC-DAD) in both normal and reverse phase modes. No sample treatment was applied, and, prior to chromatographic analysis, only the samples were dissolved in n‑hexane. Soft independent modelling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA) were used as classification methods. In addition, several classification strategies were applied, and performance of the classifications was evaluated applying proper classification metrics. Finally, 100% of samples were correctly classified applying PLS-DA with data collected in reverse phase.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6915439PMC
http://dx.doi.org/10.3390/foods8110588DOI Listing

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