Abstract

In this study, a new screening technique for the detection of two types of oil adulterants in cold pressed rapeseed oil is investigated. The calibration models built with four different multivariate classifiers (SIMCA, PLS‐DA, LDA‐KNN, and LDA‐SVM) are based on spectral fingerprints from either FT‐IR and Raman instruments from authentic pure oils and in‐house admixtures of the oils involved. When refined sunflower oil is the adulterant, both FT‐IR and Raman produce effective models with high sensitivity of 86% and 93% respectively. When refined rapeseed oil is the adulterant the sensitivity decreases. This is explained by the chemical differences of the two adulterants. PLS‐R quantification analysis estimates minimum detection levels of 15% (Raman) and 9% (FT‐IR) when refined sunflower oil is the adulterant, and 22% (Raman) and 64% (FT‐IR) when refined rapeseed oil is the adulterant. This initial study shows the potential of Raman spectroscopy to be utilized for the screening of cold pressed rapeseed oil authenticity.Practical Applications: It has been well documented in the past that high‐value edible oils can be easily adulterated with lower cost oils for economic gain. Although the cold pressed rapeseed oil industry has not experienced such fraud, it would be prudent to have analytical techniques available to authenticate genuine oils quickly. This would further strengthen cold pressed rapeseed oil's reputation as a product free from substitutional fraud. These calibration models can tool the industry and regulatory bodies with a screening method to detect authenticity in realistic levels.A feasibility study regarding cold pressed rapeseed oil adulteration is investigated. Cold pressed rapeseed oil is adulterated with either refined rapeseed oil or refined sunflower oil and spectra is acquired using either Raman or FT‐IR spectroscopy. A library of spectra is gathered which includes pure cold pressed rapeseed oil and cold pressed rapeseed oil admixtures of varying concentrations. Chemometric analysis is carried out on the dataset with both classification and quantification techniques. The optimum instrument‐chemometric pairings for cold pressed rapeseed oil authentication are discussed.

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