A preliminary study on the potential of FT-IR spectroscopy and chemometrics for tracing the geographical origin of Moroccan virgin olive oils

Abstract

Abstract Objective This study aims on the one hand to study the physicochemical data of olive oils collected from six regions of Morocco during two consecutive years 2020 and 2021. Methods Fourier transform infrared spectroscopy (FTIR) was used in this study as an emerging analytical technique to express a unique "fingerprint". A preliminary processing of the ATR-FTIR spectral data was performed by preprocessing algorithm in order to reduce the noise, the effect of signal variation and minimize the effects of light scattering to extract the maximum analytical information from the spectra. A multivariate statistical procedure based on principal component analysis (PCA) coupled with linear discriminant analysis (LDA) as well as partial least squares discriminant analysis (PLS-DA) were developed to provide a powerful classification approach. Results Based on principal component analysis (PCA), six clusters were identified. The application of PCA-LDA and PLS-DA procedures demonstrate a powerful capacity in predicting the geographic origin of olive oils, this capacity is showed by the high value of CCR varying between 84.09% and 100%. Conclusion The suggested procedure has given reliable results for the classification of olive oils according to their geographical origin, with advantages such as being fast, inexpensive and not requiring any prior separation process. Highlight The performance of this approach is significantly faster and possesses a higher degree of selectivity and sensitivity. The Implementation of this technique for routine analysis of olive oil would save significant time, resources and solvents.