Fourier‐transform infrared spectroscopy, followed by multivariate treatment of the spectral data, was used to classify Tunisian extra virgin olive oils (EVOOs) according to their cultivar. Moreover, these data were also employed to establish the composition of binary mixtures of EVOOs from different cultivars. For this purpose, the spectra were divided in 20 regions, being the normalized peak areas within these regions used as predictors. Using linear discriminant analysis, an excellent resolution between EVOOs from different cultivar was obtained. Moreover, multiple linear regression models were used to predict the composition of binary mixtures of EVOOs, being in all cases capable of predicting the percentage of one of the oils with average validation errors below 6%. Thus, the FTIR method proposed in this work, followed by chemometric analysis, could be used in an industrial setting since no complicated laboratory facilities are required, which could save great deal of time and money. Practical applications: EVOO quality can be affected by different parameters, such as cultivar and maturity index, among others, consequently, it is necessary to develop analytical methods able to verify EVOO quality, and also to control its origin since olive oil producers have to include in their manufactured products the cultivar (monovarietal oils) from which the oil was obtained. Currently, almost all the research related to Tunisian EVOOs has been mainly focused on the improvement and characterization of the two main cultivars (Chétoui and Chemlali). Thus, to diversify Tunisian olive oil resources and improve the quality of olive oil produced in Tunisia, research on additional cultivars needs to be conducted. Thus, the present methodology (including the application of chemometric techniques) could be used as an authentication tool for olive oil industry to assess cultivar of EVOO. ATR‐FTIR data of Tunisian EVOOs are used to predict EVOO cultivar using LDA.

The usefulness of fatty acid profiles established by direct infusion mass spectrometry (DIMS) as a tool to discriminate between seven genetic varieties of Tunisian extra virgin olive oils (EVOOs) was evaluated in this work. Moreover, the discrimination of EVOOs from the genetic varieties Chemchali, Fouji, and Zarrazi, characterized with different maturity indices, was also studied. For DIMS, EVOO samples were diluted with an 85:15 propanol/methanol (v/v) mixture containing 40 mM ammonia and directly infused into the mass spectrometer using a syringe pump. The establishment of ratios of the peak abundances of the free fatty acids followed by linear discriminant analysis was employed to predict both genetic variety and maturity index. In all cases, an excellent resolution between all category pairs was achieved, which demonstrated that fatty acid profiles are a good marker of both genetic variety and maturity index of EVOOs.Practical applications: As EVOO quality can be affected by different parameters, such as cultivar and maturity index, among others, it is necessary to develop analytical methods able to verify EVOO quality, and also to control its origin as olive oil producers have to include in their manufactured products the cultivar (monovarietal oils) from which the oil was obtained. Currently, almost all the research related to Tunisian EVOOs has been mainly focused on the improvement and characterization of the two main cultivars (Ch etoui and Chemlali). Thus, to diversify Tunisian olive oil resources and improve the quality of olive oil produced in Tunisia, research on additional cultivars needs to be conducted. Thus, the present method could be used as an authentication tool for olive oil industry to asses both cultivar and maturity index of Tunisian EVOO, which could be extended to EVOO from all around the world.

Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR), followed by linear discriminant analysis (LDA) of spectral data, was used to discriminate olive fruits according to their cultivar. For this purpose, the spectral data of 136 olives coming from 17 cultivars, collected at different Spanish locations, were recorded. Up to 24 frequency regions were selected on the spectra, which corresponded to a peak or shoulder. The normalized absorbance peak areas within these regions were used as predictors. Although a good resolution was achieved among all categories, a second LDA model was also constructed to improve cultivar discrimination. With both models, evaluation set samples were correctly classified with assignment probabilities higher than 95%. Thus, it is demonstrated that FTIR followed by LDA of the spectral data presents a high potential to discriminate olives from a high number of different cultivars.Practical applications: Since virgin olive oil (VOO) quality can be affected by different parameters, such as the varietal and geographic origin, among others, the production of good-quality VOOs should start with raw materials that possess well-defined quality standards. Thus, it is necessary to develop analytical methods able to control raw material quality, and also to control its origin since olive oil producers have to include in their manufactured products both the genetic variety (monovarietal oils) and the geographical origin of the olives. In this work, a simple and quick ATR-FTIR method, capable of predicting the cultivar of several olive samples, after spectral data treatment with LDA, has been developed. With the proposed method, it could be possible to establish in a reliable way to perform cultivar prediction of unknown raw materials arising from VOO samples.