Using H-1 and C-13 NMR techniques and artificial neural networks to detect the adulteration of olive oil with hazelnut oil

摘要

The lack of any official analytical method to detect the adulteration of olive oil with a low percentage of hazelnut oil is explained by the similarities in the chemical compositions of both kinds of oils. To counter this problem, an artificial neural network based on H-1-NMR and C-13-NMR data has been developed to detect olive oil adulteration, and the results from this ANN are presented here. A training set consisting of hazelnut oils, pure olive oils, and olive oils blended with 2-20% hazelnut oils was used to design and train a multilayer perceptron with 100% correct classifications. This mathematical model was also validated using an external validation set of blend samples (3-15%) and genuine samples. The detection limit of the model was around 8%.