Detection of the Adulteration of Extra Virgin Olive Oil by Near Infrared Spectroscopy and Chemometric Techniques

Abstract

The monetary value of extra virgin olive oil has led to adulteration in the industry and has created demand for quick and inexpensive fraud detection testing. A method using near infrared spectroscopy and chemometrics was developed to detect adulteration of extra virgin olive oil with other edible oil types that does not require sample preparation, can be completed in less than ten minutes, and has low operating costs. Principal component analysis on near infrared spectral data with soft independent modelling of class analogy was used for adulteration detection. The developed method could detect as low as 2.7% w/w adulteration if an unadulterated control sample was provided for comparison and 20%, 20%, 15%, and 10% w/w adulteration with corn, sunflower, soybean, and canola oils respectively if an unadulterated control sample was not provided. These results demonstrate that the developed method can be used to rapidly screen for adulterated olive oils.