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One of the most important issues in the field of quality assurance of olive oils is the detection of the freshness of olive oil. In this study, 400 nm laser-induced fluorescence spectroscopy was used with supervised and unsupervised multivariate analysis methods to develop a rapid method able to discriminate between freshly produced olive oils and oil that has been stored for a period of time ranging from 12 to 24 months. The fluorescence spectral data were firstly processed by the PCA. This method shows strong discrimination of the three oil classes using the first three components which present 96% of the total variability of the initial data, and then supervised classification models were constructed using the discriminant partial least square regression PLS-DA, support vector machine SVM, and linear discriminant analysis LDA. These methods show a high capacity in the classification of the three classes of olive oil. The validation of these classification models by external samples shows a high capacity of classification of the samples in their class with an accuracy of 100%. This study demonstrated the feasibility of the fluorescence spectroscopy fingerprint (routine technique) for the classification of olive oils according to their freshness and storage time.

The aim of this study is to prove the effectiveness of IR spectroscopy as an identification test able to discriminate between mineral compounds in mixtures. This work is concerned with the physical characterisation of purified bentonite, bentonite in organic mixtures and organic excipients, and mineralized organic mixture containing bentonite using FT-IR spectroscopy. The different spectra were compared with each other in order to determine fingerprints of bentonite represented by bands located at 3632 cm−1 and 3437 cm−1. The analysis of the spectra of the nonmineralized mixture demonstrates the presence of two bands at 1454 and 2928 cm−1, superimposed on those of the excipients and which disappear after 2 hours of mineralization at 500°C. Finally, we notice a displacement of the stretching band of H2O to the right with increasing the proportion of the excipients.

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One of the most important challenges in the authentication of olive oil is the determination of the geographical origin of virgin olive oil. In this work, we evaluated the capacity of two spectroscopic techniques, UV-Visible and ATR-FTMIR, coupled with chemometric tools to determine the geographical origin of olive oils. These analytical approaches have been applied to samples that have been collected during the period of olive oil production, in the Moroccan region of Beni Mellal-Khenifra. To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. The application of the PCA-LDA method on the spectral data of UV-Visible and ATR-FTMIR shows a good ability to classify olive oils according to their geographical origin with a percentage of correct classification that represents 90.24% and 85.87%, respectively, and the processing of the spectral data of UV-Visible and ATR-FTMIR by PCA-SVM allows differentiating correctly between five olive oils with a correct classification rate of 100% and 97.56, respectively. This study demonstrated the feasibility of UV-Visible and ATR-FTMIR fingerprinting (routine technique) for the geographical classification of olive oils in the Moroccan region of Beni Mellal-Khenifra. Such developed methods can be proposed as alternative and complementary methods to authenticate the geographical origin of virgin olive oil.

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This work targets mainly the quality control of electronic cigarette liquids. It relies on an analytical control of a “32-product” sample made of several types of e-cigarette liquids taken from various supermarkets and tobacconist’s offices in Morocco. All along this study, we made sure to check both the conformity of the nicotine level indicated in the packaging of each product and the existence of any other components inside the product, especially toxic or unknown impurities. The method used for this study is known under the name of high-performance liquid chromatography. For statistical analysis, we used Student’s t-test for a single sample in order to analyze the relative differences between nicotine quantity reported in the product and the one measured during our experiment. Finally, we used linear regression test to determine the relationship between the nicotine level accuracy on the packaging and the level of toxic impurities in the products. The differences between the nicotine concentrations reported in the packages and the measured ones varied from −100% to +3.3%. The study showed that 31% of analyzed products have an accurate indication of the level of nicotine on the packaging. However, 47% of the studied products showed more than 20% difference between measure and packaging indication. In all analyzed samples, the level of impurities altered from 0 to 32.6%. Furthermore, the level of the nicotine breakdown products did not exceed 2% of the nicotine content in pretty much all of the samples. The actual nicotine content of electronic cigarette refill liquids is not always as precise as what is stated on the packaging; in addition to the level of impurities detected in several brands and that exceeds the European Pharmacopoeia standards, some may even present a risk of causing toxicological damage.