Derivative FTIR spectroscopy for cluster analysis and classification of morocco olive oils

Fourier transform infrared (FTIR) spectra were employed for differentiation and classification of olive oilsfrom several producing regions of Morocco. A preliminary treatment of the FTIR data was done by a derivativeelaboration based on the Savitzky–Golay algorithm to reduce the noise and extract a largest number ofanalytical information from the spectra. A multivariate statistical procedure based on cluster analysis (CA)coupled to partial least squares-discriminant analysis (PLS-DA), was elaborated, providing an effective classificationmethod. On the basis of a hierarchical agglomerative CA and principal component analysis (PCA),four distinctive clusters were recognised. The PLS-DA procedure was then applied to classify samples fromthe same regions, picked in different times, or unknown olive oil samples. The model was optimised byapplying the Martens’ Uncertainty Test that provided to select the wavelength zones giving the most usefulanalytical information. The proposed method furnished results reliable in classifying olive oils from differentlands with the advantages of being rapid, inexpensive and requiring no prior separation procedure.