Revealing adulterated olive oils by triacylglycerol screening methods: Beyond the official method

Detection of Adulteration of Extra Virgin Olive Oil via Laser-Induced Breakdown Spectroscopy and Ultraviolet-Visible-Near-Infrared Absorption Spectroscopy: A Comparative Study

The fast detection of Extra Virgin Olive Oil (EVOO) adulteration with poorer quality and lower price vegetable oils is important for the protection of consumers and the market of olive oil from fraudulent activities, the latter exhibiting an increasing trend worldwide during the last few years. In this work, two optical spectroscopic techniques, namely, Laser-Induced Breakdown Spectroscopy (LIBS) and UV-Vis-NIR absorption spectroscopy, are employed and are assessed for EVOO adulteration detection, using the same set of olive oil samples. In total, 184 samples were studied, including 40 EVOOs and 144 binary mixtures with pomace, soybean, corn, and sunflower oils, at various concentrations (ranging from 10 to 90% w/w). The emission data from LIBS, related to the elemental composition of the samples, and the UV-Vis-NIR absorption spectra, related to the organic ingredients content, are analyzed, both separately and combined (i.e., fused), by Linear Discriminant Analysis (LDA), Support Vector Machines (SVMs), and Logistic Regression (LR). In all cases, very highly predictive accuracies were achieved, attaining, in some cases, 100%. The present results demonstrate the potential of both techniques for efficient and accurate olive oil authentication issues, with the LIBS technique being better suited as it can operate much faster.

Meeting the challenge of varietal and geographical authentication of hazelnuts through lipid metabolite fingerprinting

Hazelnuts are high-quality products with significant economic importance in many European countries. Their market price depends on their qualitative characteristics, which are driven by cultivar and geographical origin, making hazelnuts susceptible to fraud. This study systematically compared two lipidomic fingerprinting strategies for the simultaneous authentication of hazelnut cultivar and provenance, based on the analysis of the unsaponifiable fraction (UF) and triacylglycerol (TAG) profiles by gas chromatography-mass spectrometry coupled with chemometrics. PLS-DA classification models were developed using a large sample set with high natural variability (n = 309) to discriminate hazelnuts by cultivar and origin. External validation results demonstrated the suitability of the UF fingerprint as a hazelnut authentication tool, both tested models showing a high efficiency (>94 %). The correct classification rate of the TAG fingerprinting method was lower (>80 %), but due to its faster analysis time, it is recommended as a complementary screening tool to UF fingerprinting.

Advances in Vibrational Spectroscopic Techniques for the Detection of Bio-Active Compounds in Virgin Olive Oils: A Comprehensive Review

Vibrational spectroscopic techniques have gained significant attention in recent years for their potential in the rapid and efficient analysis of virgin olive oils, offering a distinct advantage over traditional methods. These techniques are particularly valuable for detecting and quantifying bio-active compounds that contribute to the nutritional and health benefits of virgin olive oils. This comprehensive review explores the latest advancements in vibrational spectroscopic techniques applied to virgin olive oils, focusing on the detection and measurement of key bio-active compounds such as unsaturated fatty acids, phenolic compounds, and other antioxidant compounds. The review highlights the improvements in vibrational spectroscopy, data processing, and chemometric techniques that have significantly enhanced the ability to accurately identify these compounds compared to conventional analytical methods. Additionally, it addresses current challenges, including the need for standardized methodologies and the potential for integrating vibrational spectroscopy with other analytical techniques to improve accuracy and reliability. Finally, findings over the last two decades, in which vibrational spectroscopy techniques were effectively used for the detailed characterization of bio-active compounds in virgin olive oils, are discussed.

Prospective exploration of hazelnut's unsaponifiable fraction for geographical and varietal authentication: A comparative study of advanced fingerprinting and untargeted profiling techniques

This study compares two data processing techniques (fingerprinting and untargeted profiling) to authenticate hazelnut cultivar and provenance based on its unsaponifiable fraction by GC-MS. PLS-DA classification models were developed on a selected sample set (n = 176). As test cases, cultivar models were developed for "Tonda di Giffoni" vs other cultivars, whereas provenance models were developed for three origins (Chile, Italy or Spain). Both fingerprinting and untargeted profiling successfully classified hazelnuts by cultivar or provenance, revealing the potential of the unsaponifiable fraction. External validation provided over 90 % correct classification, with fingerprinting slightly outperforming. Analysing PLS-DA models' regression coefficients and tentatively identifying compounds corresponding to highly relevant variables showed consistent agreement in key discriminant compounds across both approaches. However, fingerprinting in selected ion mode extracted slightly more information from chromatographic data, including minor discriminant species. Conversely, untargeted profiling acquired in full scan mode, provided pure spectra, facilitating chemical interpretability.

Direct analysis in real time of high-quality extra virgin olive oils for the rapid and automatic identification of origin trademark

BACKGROUND

Following our previous research on the differentiation of Italian extra virgin olive oils (EVOOs) by rapid evaporative ionization mass spectrometry coupled to a tandem high resolution mass analyser, the present study deals with the evaluation of another direct mass spectrometry (direct-MS) approach for the rapid and automatic discrimination of EVOOs. In particular, direct analysis in real time (DART-MS) was explored as an ambient MS (AMS) source for the building of a top-quality Italian EVOOs database and fast identification of unknown samples. A single quadrupole detector (QDa) was coupled with DART, taking advantage of a cost-saving, user-friendly and less sophisticated instrumental setup. Particularly, quickstrip cards, located on a moving rail holder, were employed, allowing for the direct analysis of 12 EVOO spots in a total analysis time of 6 min. The aim was to develop a reliable statistical model by applying principal component and linear discriminant analyses to clusterize and classify EVOOs according to geographical origin and cultivar, as main factors determining their nutritional and sensory profiles.

RESULTS

Satisfactory results were achieved in terms of identification reliability of unknown EVOOs, as well as false positive risk, thus confirming that the use of AMS combined with chemometrics is a powerful tool against fraudulent activities, without the need for mass accuracy data, which would increase the analysis cost.

CONCLUSION

A DART ionization source with a compact and reliable QDa MS analyser allowed for rapid fingerprinting analysis. Furthermore, MS spectra provided quali-quantitative information successfully related to EVOO differentiation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.