Seeking a Fast Screening Method of the Varietal Origin of Olive Oil: The Usefulness of an NMR-Based Approach

Application, challenges and future prospects of recent nondestructive techniques based on the electromagnetic spectrum in food quality and safety

Safety and quality aspects of food products have always been critical issues for the food production and processing industries. Since conventional quality measurements are laborious, time-consuming, and expensive, it is vital to develop new, fast, non-invasive, cost-effective, and direct techniques to eliminate those challenges. Recently, non-destructive techniques have been applied in the food sector to improve the quality and safety of foodstuffs. The aim of this review is an effort to list non-destructive techniques (X-ray, computer tomography, ultraviolet-visible spectroscopy, hyperspectral imaging, infrared, Raman, terahertz, nuclear magnetic resonance, magnetic resonance imaging, and ultrasound imaging) based on the electromagnetic spectrum and discuss their principle and application in the food sector. This review provides an in-depth assessment of the different non-destructive techniques used for the quality and safety analysis of foodstuffs. We also discussed comprehensively about advantages, disadvantages, challenges, and opportunities for the application of each technique and recommended some solutions and developments for future trends.

Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe)

Food authenticity regarding different varieties and geographical origins is increasingly becoming a concern for consumers. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) and fast gas chromatography electronic nose (fast GC e-nose) were used to successfully distinguish the varieties and geographical origins of dried gingers from seven major production areas in China. By chemometric analysis, a distinct separation between the two varieties of ginger was achieved based on HS-GC-MS. Furthermore, flavor information extracted by fast GC e-nose realized the discrimination of geographical origins, and some potential flavor components were selected as important factors for origin certification. Moreover, several pattern recognition algorithms were compared in varietal and regional identification, and random forest (RF) led to the highest accuracies for discrimination. Overall, a rapid and precise method combining multivariate chemometrics and algorithms was developed to determine varieties and geographical origins of ginger, and it could also be applied to other agricultural products.

Nuclear magnetic resonance spectroscopy in extra virgin olive oil authentication

Extra virgin olive oil (EVOO) is a high-quality product that has become one of the stars in the food fraud context in recent years. EVOO can encounter different types of fraud, from adulteration with cheaper oils to mislabeling, and for this reason, the assessment of its authenticity and traceability can be challenging. There are several officially recognized analytical methods for its authentication, but they are not able to unambiguously trace the geographical and botanical origin of EVOOs. The application of nuclear magnetic resonance (NMR) spectroscopy to EVOO is reviewed here as a reliable and rapid tool to verify different aspects of its adulteration, such as undeclared blends with cheaper oils and cultivar and geographical origin mislabeling. This technique makes it possible to use both targeted and untargeted approaches and to determine the olive oil metabolomic profile and the quantification of its constituents.

Chemometric Discrimination of the Varietal Origin of Extra Virgin Olive Oils: Usefulness of 13C Distortionless Enhancement by Polarization Transfer Pulse Sequence and 1H Nuclear Magnetic Resonance Data and Effectiveness of Fusion with Mid-Infrared Spectroscopy Data

The label authentication of monovarietal extra virgin olives is of great relevance from a socio-economical point of view. This work aims to gain insights into the prediction of the varietal origin of extra virgin olive oil (EVOO) samples obtained from single olive cultivars, French cultivars Olivière, Salonenque, and Tanche and Portuguese cultivars Blanqueta, Carrasquenha, and Galega Vulgar, collected in 2016-2017 and 2017-2018 harvest seasons. To pursue this study, spectroscopic approaches based on one-dimensional nuclear magnetic resonance (1D NMR) spectroscopy, namely, ¹H and ¹³C NMR distortionless enhancement by polarization transfer (DEPT) 45 pulse sequence, and Fourier transform mid-infrared spectroscopy (FT-MIR) are used in combination with partial least square discriminant analysis (PLS1-DA). The results obtained by PLS1-DA models using ¹H and ¹³C NMR DEPT 45 data are compared to those of PLS1-DA models using MIR data. The application of a control chart method allows for the optimization of the interpretation of the PLS1-DA results, and an efficient two-step strategy is proposed to improve the discrimination of the six studied cultivars. Then, NMR and MIR data are combined by either a mid- or high-level data fusion approach to further improve the discrimination. The models are also tested on samples from other cultivars to check their ability to reject varieties that were not considered in the calibration process.