Gum Arabic authentication and mixture quantification by near infrared spectroscopy

- Authentication of Gum Arabic samples by near infrared spectroscopy.
- Perfect classification separation between the major gum Arabic classes: Acacia Senegal and Acacia Seyal.
- Quantification of Acacia Senegal in a mixture with a prediction error of 2.8%.

A rapid and reliable method is developed for Gum Arabic authentication based on Near Infrared (NIR) spectroscopy and chemometric methods. On a large industrial collection of authentic gum Arabics, the two major Acacia gum species, Acacia senegal and Acacia seyal could be assigned perfectly by the NIR spectroscopic method. In addition, a partial least squares (PLS) regression model is calibrated to predict the blending percentage of the two pure gum types, producing an accuracy, root mean square error of cross validation (RMSECV) of 2.8%. Sampling of the Gum Arabic 'tears' is discussed, and it was determined that subsamples from three 'tears' is required for a representative result. It is concluded that NIR spectroscopy is a very powerful and reliable method for authenticity testing of Gum Arabic species.